S.O.S Planet - Special simulation issue (2016)

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3464 Supplement . april 14 2016 . not to be Sold Separately

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S.o.S. planet special simulation issue

CEA at the heart of innovation for extreme computing and Big Data CEA and Bull are co-designing exascale technologies

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Harnessing exascale computing and data processing will open unexplored perspectives for the numerical simulation of complex physical phenomena and industrial objects, by 2020 and beyond. In order to tackle this challenge, CEA, in partnership with Atos, is co-designing technologies to: Reduce energy consumption Process and manage massive flows of data Increase performance, efficiency and modularity of supercomputer architectures Design fault-tolerant architectures 1 - At the scale of a billion of billions of operations per second (exaFlops) and memory bytes (exaBytes).

TERA 1000, developed in partnership with Atos/Bull according to CEA requirements and installed in 2016, is foreshadowing exascale supercomputers.

CEA boosts industrial innovation Located at CEA Bruyèresle-Châtel site, TGCC (CEA Very Large Computing Centre) hosts CCRT (Computing Centre for Research and Technology), a shared infrastructure optimized for HPC. CCRT partners receive 1.4 Pflops of computing power, as well as services and expertise supported by CEA HPC team skills – an essential asset for their numerical simulations.

Numerical simulation of combusion in an helicopter turbo-engine - TURBOMECA

Aero-acoustic numerical simulation of a car interior air conditioning system - VALEO

CCRT partners as of March 2016 Airbus D&S, Areva, Cerfacs, EDF, Herakles, Ineris, L’Oréal, SafranTech, Snecma, Techspace Aero, Turbomeca, Thales, Thales Alenia Space, Valeo, CEA as well as FranceGénomique consortium (supported by French government PIA).

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To know more www-ccrt.cea.fr Contact christine.menache@cea.fr

Simulation of surface currents on an aircraft nose radome - THALES

SIMUlatIon

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Supplément du 3464 . 14 avril 2016 . ne peut être vendu Séparément

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S.o.S. planète spécial simulation

Representation of the magnetic field in the earth’s core.

9 Billion Humans, onE planEt

Sommaire ESSENTIALS

a year of simulation

p. 4

INTERVIEW

antoine petit, Ceo of Inria

W

p. 6

DOSSIER

We need to simulate the planet now a French savoir faire p. 10 Keepers of the planet p. 16

p. 8

INTERVIEW

olivier Gupta, Météo France’s deputy director general p. 18 MARKETS

SMeS, natural element experts

p. 20

A REAL STAR

Cybeletech, numerical farming p. 26 DIGITAL TRANSFORMATION

the new agricultural revolution

p. 28

PORTFOLIO

nature revealed p. 34 VIRTUAL REALITY

affordable immersion for everyone

p. 38

DESIGN OFFICE

the quest for fully autonomous vehicles

p. 42

INNOVATION

networks of connected objects, it’s a challenge p. 44 AERONAUTICS

Solar Impulse 100% calculated

p. 46

Président-directeur général : Christophe Czajka Directeur général délégué : Julien Elmaleh Directeur du pôle industrie : Pierre-Dominique Lucas Directrice de la rédaction : Christine Kerdellant Directrice adjointe de la rédaction : Anne Debray Coordinatrice éditoriale : Aurélie Barbaux Chef d’édition : Guillaume Dessaix Direction artistique : Eudes Bulard Ont participé à ce numéro : Claire Laborde et Rebecca Lecauchois (secrétariat de rédaction) ; Laurent Pennec (maquette) Supplément de « L’Usine Nouvelle » n° 3464 du 14 avril 2016 (commission paritaire n° 0712T81903) Ne peut être vendu séparément. Une publication du groupe Gisi, Antony Parc II 10 place du Général-de-Gaulle - BP 20156 - 92186 Antony Cedex. Directeur de publication : Christophe Czajka Impression : Roto France Impression 77185 Lognes Photo de couverture : Julien Aubert/Finlay, Jackson, Olson, Gillet, Université Paris Diderot/IPGP/CNRS

L’USINE NOUVELLE i n° 3464 supplEmEnt i apRil 14 2016

e are going to need more than the good intentions of governments if we are to limit global warming to less than 2° now and feed 9 billion humans in the future. Public-sector and economic players must do everything in their power to meet these challenges. Although it is no miracle solution, simulation enables us to be good diagnosticians by predicting changes, especially climate change. Simulation also provides invaluable decision-making tools to improve how we manage resources and deal with natural hazards. By modeling living organisms, simulation will facilitate AURÉLIE human existence on the only planet we’ve got. BARBAUX Scientists already know how to model crop and microassistant EDitoR, algae growth. And models can be created in every l’usinE DiGitalE domain, as Antoine Petit, INRIA’s CEO, explains. We can use the same corpus of mathematics to simulate physical and biological phenomena, such as biochemical reactions and cell migration. Fluid mechanics techniques used to calculate planes’ air penetration have “Combined with artificial been reused to model blood flow around the body. Other intelligence technology, models techniques adapted to the will become better adapted.” pharmaceuticals industry will soon help us simulate clinical trials, thus reducing how long it takes for treatments to come onto the market. Coupling patient data with general models is leading the way for patient-specific medicine and more reliable diagnoses. Combined with artificial intelligence technology, models will become better adapted and more able to be rebuilt from huge amounts of data. This means scientists will have an even greater responsibility. Just as the parameters chosen for climate models determines how close they come to real conditions, so too the quality of modeling living organisms is the key to renewing medical science and even human existence. Despite space exploration, 9 billion human beings will have to live on a single planet with limited resources. ❚❚

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Solar System

evenTs

CalCulatinG PlanEt ninE

D.R. ; CAlTECH

the First numerical simulation trophies In 2015, TERATEC organized the first numerical simulation trophies. The six prizewinners were revealed on 23 June at the TERATEC Forum, held at the École Polytechnique in Palaiseau (Essonne). There were five categories, showcasing the simulation expertise of start-ups and SMEs, as well as the ability of the French public-sector research ecosystem to collaborate with private companies. Since the simulation expertise of big French companies is now well-established, they were not included in these awards. The start-up trophy was awarded to CybeleTech, which is simulating plant growth [see page 26]. The SME trophy, showcasing a company that has used Five categories numerical to showcase calculation the expertise technology of French start-ups to develop and smEs. new products or services was awarded to Principia, which is simulating seabed-surface links in offshore systems. The European Center for Research and Advanced Training in Scientific Computation (CERFACS) was the joint winner (with Turbomeca) of the collaboration trophy, which rewards groupings between a big company and an SME. This award was given for collaborative simulation work on a turbojet combustion chamber and first-stage turbine. The innovation trophy was awarded to HydrOcean, a start-up that has industrialized its SPH (Smooth Particle Hydrodynamic) simulation method for application to fast, complex fluid flows [see page 24]. Finally, the first jury prize for SME projects displaying exemplary innovation and promoting the use of numerical computation was awarded to Distene for its mesh generation tool, MeshGems. TERATEC also made special mention of Danielson Engineering, an SME that designs and manufactures prototype thermal engines for the automobile, aeronautics, and defense industries. The company is using numerical simulation to develop digital models with very similar performance to real engines. ❚❚ JeAn-FrAnçois PrevérAud

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Using mathematical models, researchers at the California Institute of Technology (Caltech) believe they have discovered a ninth planet in the solar system. They reached this conclusion while trying to explain the behavior of celestial objects in the Kuiper Belt, beyond Neptune’s orbit. Six of these objects have an elliptical orbit converging to the same point and on the same 30° tilt, suggesting that they are “attracted” by an invisible mass. Since the probability of this being coincidence is only 0.007%, the data could be explained by the influence of a ninth

Planet nine could be ten times heavier than earth.

planet’s gravity. This hypothetical planet could have an extraordinary mass – ten times that of Earth – and orbit twenty times farther from the sun on average than Neptune. Planet Nine could also take 10,00020,000 years to rotate around the sun. ❚❚ Julien Bergounhoux

Industry

a nEW 3D simulation ClustER The it3D event, organized in autumn by the Bordeaux-based company Immersion, boosted the local 3D simulation industry. It even generated an idea for a cluster bringing together companies such as ESI Group, Lumiscaphe, and Diodasoft. Used intensively in the aeronautics and automobile industries for the past decade, 3D simulation now needs to be assimilated by their sub-contractors over the next five years. The hardware has become accessible and «the ‘Factory of the Future’ plan launched by the French state is a fantastic opportunity to introduce this technology,» explains Christophe Chartier, Immersion’s CEO. ❚❚ nicolAs césAr

Training

FRanCE’s FiRst RiVER simulatoR A consortium run by the Compagnie Nationale du Rhône took delivery of France’s first river navigation simulator in mid-March. This 3D simulator was designed by Alyotech and is used for training and improving the skills of boat pilots navigating the Rivers Rhône and Saöne, especially the trickiest sections. The device has a 10-metre cylindrical screen with a 240° angle of vision, together with a helm station that can be configured into five types of boat. The pilot’s cabin equipment, as well as the signaling system, currents and water-column density, weather conditions, river traffic, time of day, etc. are

An infinite number of scenarios can be tested in complete safety.

also modular. The scenarios include various types of breakdown and alerts to replicate as many situations as possible. ❚❚ J. B.

simulation

Computing

tERa 1000 in sERViCE at tHE CEa-Dam Atos has just delivered the first phase of the new TERA 1000 supercomputer to the French Atomic Energy and Alternative Energies Commission, Military Applications Division (CEA-DAM). This supercomputer has double the theoretical computing power of the previous generation TERA 100 supercomputer and is five times more energy efficient.

“The TERA 1000 is the third generation of supercomputer resulting from the Bull/ CEA-DAM partnership, which started in the early 2000s. The computing power has been increased 5,000-fold,” says François Geleznikoff, the CEA’s director of military applications. The first phase of TERA 1000 comprises two computing systems: one based on an Intel Xeon E5 v3 processor and another on an Intel Xeon Phi processor. This installation is a forerunner of the future generation exascale (1,018 flops) supercomputers that will come into service by 2020. ❚❚ J.-F. P.

Computing

240 tERaFloPs at tHE CERFaCs The European Center for Research and Advanced Training in Scientific Computation (Cerfacs) took delivery of a new supercomputer. Built by the Chinese company Lenovo, with 240 teraflops of computing power (1 teraflop is equivalent to 1 trillion floating point operations per second), and will triple the computing power at this Toulouse-based research center. Some 1.2 million Euros have been invested in this new computer, which replaces a 20-teraflop HP supercomputer and completes another 53-teraflop supercomputer built by Bull. The Cerfacs is a fundamental and applied research center specializing in numerical modeling and simulation. It deals with technical and scientific topics in various fields of public-sector and industrial research:

Fluid Mechanics

siEmEns aCQuiREs CD-aDaPCo

Siemens has acquired CD-adapco for 970 million dollars to complete its portfolio of numerical simulation tools for products and industrial processes. CD-adapco specializes in fluid mechanics (Star-CD), solid mechanics, electrochemistry, and acoustics. The company generates turnover of approximately 200 million dollars, an increase of 12% a year over the past three years, and employs more than 900 people. Environment

HYDRoCEan at BuREau VERitas

240 x 1 trillion operations per second.

aeronautics, the automobile industry, space, climate studies, etc. Approximately 150 researchers, engineers, and administrative staff work at the Cerfacs. ❚❚ Ridha LoukiL

Bureau Veritas recently acquired HydrOcean, a spin-off of the École Centrale de Nantes specializing in numerical simulation of fluid dynamics for the maritime sector. HydrOcean was set up in 2007 by Erwan Jacquin and the École Centrale de Nantes. It provides design and optimization services for ships, offshore structures, racing yachts, and marine-energy recovery systems. Sound and Light

Consequences of a 100-year Flood in Paris

D.R.

if the River Seine bursts its banks, the floodwaters will rise gradually and are not expected to cause casualties. a prediction made by the organizers of the Eu Sequana exercise, which between the 7 and 18 of March 2016 simulated a 100-year flood. Nevertheless, a flood like the one in 1910, when the floodwaters rose 8.62 meters, would have major consequences on the ile-de-France region’s life and economy. according to numerical simulations by the Paris Police Prefecture, such a flood could result in 5 million disaster victims, affect 400,000 direct jobs, and leave 1.5 inhabitants without electricity. a study by the organization for Economic Cooperation and development estimates that property damage could be 3-30 billion Euros and cost 0.1-3% of France’s GdP over five years. ❚❚ A. B. L’uSiNE NouvELLE I N° 3464 SupplEmENT I apRIl 14 2016

oPtis sWalloWs uP GEnEsis

The French software vendor Optis that specializes in light simulation has acquired Genesis, another French software vendor with expertise in sound simulation and perception. Both companies share a common simulation philosophy based on using the physics of phenomena they simulate. Tools simulating human sight and hearing will help both companies’ designers take account of “user experiences” to develop their products.

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“moDElinG is a corE activity at inria” Simulation, especially modeling, is a core activity at the French National Institute for Research in Computer Science and Automation (INRIA), as its CEO, Antoine Petit, explains. INTERVIEWED BY AURÉLIE BARBAUX

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What type of simulation work does INRIA do? Modeling is a long-standing core activity at INRIA since we simulate models, which are needed in every field. But the big difficulty lies in designing appropriate models. For example, climate modeling is extremely difficult since there are several models rather than just one. Climate change controversies have all focused on whether or not these models are valid. It’s hard to know whether or not a model is correct, especially since no single model can take into account every parameter. You have to omit some of the less important parameters, and this causes disagreements. You say that everything can be modeled, but INRIA can’t be at the cutting edge of every field. The French school of mathematics is regarded as one of the best in the world. In some sense, we’re intrinsically good at modeling. What’s good about modeling exercises is that they require the cooperation of mathematicians and computer scientists with people working in applied sectors. Therefore, we are not better in any specific applied field than in another. We’ve developed our programs in response to

Luc Pérénom

INTERVIEW

interest in modeling from various disciplines, it happened in healthcare twelve years ago. But we work with every sector and, on the whole, the techniques are always the same. What environmental research is INRIA carrying out and who are you working with? We’re working with institutions such as Météo France, Institut Pierre-Simon-Laplace, and the University of Versailles on climate modeling – more specifically on air quality – and in partnership with companies such as EDF, modeling wind circulation to help position wind turbines. Environmental research is not limited to climate issues. Have you developed the results of this research yet? Generally speaking, I don’t like the term «development» since it’s often put into the same category as financial spin-offs. This isn’t necessarily the case and other types of value can take precedence over monetary value. For example, over the past thirty years INRI has initiated 120 start-ups, which have created 3,000 jobs. Several start-ups a year are launched in the healthcare sector. It’s a bit early for this in the environmental sector, even though some topics lend themselves to development. In collaboration with the cities of Paris and San Francisco, we’ve designed a smartphone application called SoundCity, which measures city noise pollution and enables users to collect data. We also have a project looking at microalgae as a protein and energy source, modeling how environmental conditions affect growth according to microalgae type. This project is part of the BIOCORE program in Montpellier. Do you need new models to simulate living organisms or can you adapt existing models? There’s often a common basis. For example, fluid mechanics techniques used to simulate aeroplanes’ air penetration are now being used to model blood flow around the body. We can reuse an entire corpus of mathematics when we switch from one application to another. How many teams work on modeling? INRIA employs 2,700 people, including 1,800 researchers (600 of whom have permanent contracts). Modeling could potentially interest any of our teams, especially life-science research groups (25% of our total teams). Part of our work involves running calculation codes on increasingly powerful computers. To move from petaflops to exaflops, we have dedicated simulation (rather than modeling) teams writing software stacks to get the best use out of these new supercomputers. We’re working with manufacturers – especially Bull and Hewlett Packard – as well as on virtual supercomputers to take into account processor-failure probabilities. Since some computer codes use much more electricity than others, we’re designing algorithms to minimize power consumption and are also working on dedicated hardware. Research is a long-term effort whereas digital technology moves very quickly. How do you reconcile these different paces? It’s a popular misconception that digital technology moves very quickly, although it’s true that this technology L’UsINE NoUVELLE i n° 3464 suPPLEmEnt i aPriL 14 2016

“the French school of mathematics is regarded as one of the best in the world. in some sense, we’re intrinsically good at modeling.”

can come onto the market very quickly. In 2003, the French National Science Fund, which was replaced by the National Research Agency (ARN), launched three new areas of activity: computer security, bulk data, and new mathematical interfaces. These are today’s research topics. But it would be a mistake to think that some amazing new research topic is going to emerge in six months’ time that will put all our researchers out of a job. They know what the topics of the future will be. What are your main current areas of research? Everything relating to modeling and simulation, of course. We’re conducting research on the Internet of Things, data and big data, developing new algorithms for data processing, display, encoding, and transport. Another major research area is cybersecurity, cryptography, and protocols. Robotics is also a key topic and we’re very interested in autonomous cars. We also run many multi-disciplinary research programs at the interface of various disciplines. What happened to the initiative giving sMEs access to your laboratories? We cooperate with companies in several ways. First, companies benefit from skills transfers whenever our researchers move into the business world. We’ve also set up a dozen joint laboratories with the main industrial groups: Microsoft, Alcatel-Nokia, Total, EDF, Orange, Alstom, Airbus Group, etc. What’s more, we’ve established many start-ups. Finally, our INRIA innovation labs collaborate with SMEs – on much shorter deadlines than with big groups – to change innovations into products. We’ve already set up a dozen such innovation labs and another is currently being established with Safety Line, to reduce airplanes’ fuel consumption. In 2015, we also launched INRIA Tech in Lille, with support from EuraTechnologie Center of Excellence. Although its name is inspired by CEA Tech, we’re not doing the same thing. INRIA Tech has a dozen engineers – and not researchers – providing initial responses to industrial needs. It’s got off to an encouraging start. ❚❚ 7

CD-aDapCo

we need to SIMULAte tHe PLAnet now Even if global warming slows down, it will continue to radically change our environment. Numerical simulation is helping predict these changes. BY ALAIN CLAPAUD, THIERRY LUCAS, AND JEAN-FRANÇOIS PREVÉRAUD

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SIMULAtIon

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he agreement signed by 195 countries at the COP21 conference in December 2015 is historic, imperfect, and very ambitious. Working towards global warming of less than 2°C – with an aim of 1.5°C to meet the needs of the most vulnerable states – was not easy to negotiate. Furthermore, funding for energy transition in developing countries is far from certain after 2020. Nevertheless, things seem to be in motion. Apart from their financial resources, Western countries have something else to share and promote in the fight against global warming: their technological expertise in numerical simulation. Modeling natural systems helps understand and predict climate change, of course, as well as the consequences of climate disruption (flooding, rising sea levels, and catastrophes) and ways to optimize natural resources. In the L’USINE NOUVELLE i n° 3464 supplEmEnt i april 14 2016

race to calculate natural resources under threat – such as water – and resources that need developing – such as solar, wind, tidal, and other renewable energy sources – France, with its long tradition of applied mathematics teaching, is in a strong position. French researchers, industrialists, and a start-up incubator are working on new simulation models. They are aiming to reproduce ever more advanced phenomena on their computer displays and study new approaches to numerical simulation making it easier for everyone to take up. ❚❚

Modeling the behaviour of industrial buildings before construction helps assess and limit the dispersion of pollutants into the atmosphere.

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environment

a FREnCH savoiR FaiRE French laboratories have become experts at simulating our environment – whether airconditioning systems, storms or major industrial catastrophes – as demonstrated below. By AlAin ClApAud

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ust when we are seeing the first consequences of climate change – including in France – simulation is playing an increasingly important role in protecting our environment and combating global warming. Simulation calculations are used on all fronts to protect the environment: optimizing human infrastructures and water/energy resources, predicting coastal erosion in the face of rising sea levels, forecasting catastrophes, modeling pollution phenomena, etc. And French experts – at EDF, Suez, Veolia, the CNRS, the National Institute for Research in Computer Science and Automation (INRIA), the Scientific and Technical Center for Building (CSTB), and the National Research and Safety Institute (INRS) – are often at the cutting edge of innovation, providing original solutions.

proteCtion From ClimAte HAZArdS

The worldwide agreement signed at the COP21 conference in December 2015 set nations new targets to limit CO2 discharged into the atmosphere. Many countries are already facing climate change. France – especially its coastline – has not been spared, as Antoine Rousseau, an INRIA researcher in charge of the LEMON team (coastline, environment, models, and numerical tools), underlines: “Coastlines face three risks: storms and tsunamis, erosion and flooding. We need to design mathematical models to understand what’s happening long term, as well as ‘realtime’ risk-management simulation tools to evacuate flood zones in time,” he explains. It’s not easy. Every process brought into play – whether winds, currents or ground motion – is very complex. The equations require vast amounts of calculation, not to mention the difficulty of coupling these simulations when each process changes at its own pace. Erosion is caused by water/sediment interactions when seabeds influence coastal currents and vice versa. “Currents change within hours whereas modifications to sandy seabeds occur over several months or years. From a mathematical perspective, 10

in Bordeaux, the ramses supercomputer delivers real time flood prevention and control of wastewater treatment plants.

coupling phenomena is very difficult,” says Rousseau. But it’s not impossible. A program funded by the French National Research Agency (ANR) enabled Rousseau’s research team to limit silting up in the Sète (Hérault) area. The team used their calculation codes to place geotextile “socks” on the seabed; these “socks” modify currents and hence limit coastal erosion. While simulation is invaluable for long and medium-term environmental forecasting, it is also essential for dealing with natural catastrophes. The LEMON team is collaborating closely with the University of Montpellier on real-time modeling of city flood scenarios. Their goal is to design tools for use by the Prefecture and firefighters during evacuations. “The issue here is working out whether we need a rough, very quick forecast or should wait for a better quality forecast. It’s about finding a compromise. Mathematics has role to play in improving the model (at constant calculation time) and hence forecasting quality,” says Rousseau.

simulation

“We’re working on more eco-friendly materials” KaRim aÏt-moKHtaR, Director of the Environmental Engineering Laboratory (LaSIE FRE CNRS 3474) What progress have you made on numerical simulation research? We’re working on materials, especially on simulating transfer of aggressive agents. This will help work out how long structures such as the Millau Viaduct will last in relation to their environment. The goal is to design more eco-friendly coatings than those used currently, which often consist of chemical compounds with low

biodegradability. Another area of research is focusing on buildings’ energy consumption and quality of life. one of your teams is working on theoretical aspects, why is that? Our theorists are aiming to make simulation cheaper and faster by developing new calculation methods. Computational Fluid Dynamics (CFD) codes use a lot of computing resources, especially for long-term simulations. But if you use more approximate models, such as zonal or empirical models, you lose the subtlety of meshing. ❚❚

William Daniels ; D.R.

Better uSe oF nAturAl reSourCeS

Suez Environnement is also interested in this operational simulation. “In the event of storms, we have to manage water arriving suddenly in the network,” explains Bertrand Vanden Bossche, who manages the R&D portfolio of the Smart Solutions business. In the Paris region, Vanden Bossche’s team has started installing extremely complex calculation models combining meteorological data and radar image analysis from Météo France. “This enables us to calculate runoff, i.e. the volume of water that is going to pour into our network. Once we know the water levels in our storage basins and networks, we can organize the correct pumping strategy to ensure wastewater treatment plants are not sent any more water they can actually accept. At the same time, we try to avoid discharging potentially polluted water into the natural environment,” says Vanden Bossche. In Bordeaux, Suez has gone even further using algorithms to control sluice-gate height and launch pumping operations to absorb rainwater as effectively as possible. l’uSine nouvelle i n° 3464 supplement i apRil 14 2016

Simulation can also be used to act on the causes of global warming, helping the main industrial countries reduce their CO2 emissions. In particular, simulation helps increase the level of renewable energy sources in each country’s energy mix by making them more cost-effective. Photovoltaics, wind power, tidal turbines and new energy sources require heavy investment. The five offshore wind farms authorized for construction off the French coast represent a 7-billion Euro investment. It is therefore essential to have reliable calculations of each turbine’s potential wind power, i.e. estimate as accurately as possible how much energy it will produce over its life span. “Calculating wind turbines’ potential power over their 20-25-year life span requires sophisticated statistical and dynamics models to understand wind interactions where turbines are located,” explains Pierre-Guy Thérond, director of new technology at EDF Énergies Nouvelles. To achieve this, EDF is increasingly abandoning simple simulation models based on laminar flow. Instead, the company is turning to Navier-Stokes fluid mechanics equations (or CFD equations for fluid dynamics calculations), which have until now been used in aeronautics. Thérond justifies this far more expensive choice in terms of computing power. “CFD models give a better representation of turbulence effects. In complex zones – i.e. very rugged terrain on which wind turbines are surrounded by complex wind movements 11

simulation

Cyclone Xynthia – Simulation goes to court in February 2010, Cyclone Xynthia – combined with a high tidal coefficient – caused breaches of several dikes and flooding in the Vendée. some 29 people were killed, despite the warning issued by météo France. “the French Geological survey (BRGm) has been active in explaining Cyclone Xynthia’s physical causes in reports submitted to the authorities. these assessments were based largely on numerical simulation,” says Fabrice Dupros, the BRGm’s head of high-performance computing. the insurance companies maif, aXa and maaf funded the Johanna research project, which cross-checked simulation data with insurance claims. a model has been drawn up linking very high resolution coastal flooding data (water height, current speed) with building damage. this model will help choose construction materials and urban development strategies to prevent the consequences of such catastrophes as far as possible. ❚❚

and vortexes – the laminar flow hypothesis is no longer sufficient,” he states. EDF’s approach has optimized windturbine location in relation to relief and to one another. This approach prevents the wake of the first wind turbines facing the wind from compromising the efficiency of those placed behind them. Water is another natural resource that must be optimized. As a result of rising average temperatures and the world’s population increasing to 8 billion people by 2025, the amount of water available per inhabitant will drop by almost a third worldwide. France will not escape this trend since farmers in southern France are already affected by watercourse pumping restrictions every summer. Here too, simulation has a role to play, as the Astuce & Tic consortium – which studied water-table changes on the Crau Plain – has shown. The triangle formed by Arles, Salon-de-Provence and Fos12

sur-Mer (south of the Alpilles) covers a water table that is very important for this region and is subject to both climate constraints and heavy demographic pressure. Fabienne Trolard, director of research at INRA, has assessed the impact of global warming and economic development on this area. Her calculations show that a 14% reduction in grassland combined with a 30% drop in irrigation water and a 30% rise in drinking water extraction would cause a 1.5-13-meter drop in the water table, depending on the location studied. This key data must guide political decisions for urban development in this area. Water supply network operators are also directly confronted with the need to protect water resources, especially from pollution threatening water quality. Suez Environnement is simulating how pollutants spread through soil to assess the impact of agricultural fertilizer on groundwater.

eDF ; umR6143 m2C - équipe ClaReC / CnRs photothèque.

representation of wind-force distribution on a wind farm.

simulation

June, 28th 2016 • Teratec Forum École Polytechnique • 2nd edition

REVEAL AND REWARD THE DIGITAL SIMULATION, HPC AND BIG DATA CHAMPIONS

A flooding scenario in la Faute-sur-mer (vendée), based on detailed topography of one of its neighborhoods.

improvinG inFrAStruCture deSiGn

While simulation promotes better use of renewable energy, it can also be used to improve construction work and make buildings more energy efficient. “We’ve developed a simulation code called MATHIS (modeling buildings’ aeraulics, thermics and unsteady humidity),” explains Maxime Roger, director of climatology, aerodynamics, pollution, and water purification at the CSTB. This is no conventional fluid mechanics code, such as those used to model wind, but rather a nodal code representing every room within a building in the form of nodes. Each node is interconnected to models representing air vents and other accessories in systems. Buildings’ ventilation, hygrometry, and other parameters can also be represented over a year, taking into account many different use scenarios.”The CSTB believes this simplified simulation will facilitate its uptake by architects and design offices, especially for compliance with RT 2012 thermal regulations. Nevertheless, CFD calculations are still essential for simulating more complex phenomena, e.g. studying the impact of buildings and infrastructures on their environment. Cheaper access to computing capacity makes it possible to simulate how wind acts on a structure and takes into account the surrounding buildings within a several hundred-meter radius. More developed numerical models can also simulate phenomena such as rain. “We know how to model driving rain in stadiums or semi-open spaces, such as shopping malls partly covered by a canopy,” explains Sylvain Aguinaga, head of the CSTB’s numerical modeling division. It is impossible to carry out small-scale simulation of water droplet dispersion in wind tunnels; such phenomena can only be predicted via numerical simulation. “Our clients – design offices and architects – therefore use concomitant rain/wind scenarios to predict whether or not terraces and gangways will be in the rain. We then suggest modifications to a building’s geometry before construction and hence limit these phenomena,” continues Aguinaga. Simulations of buildings’ microclimate are increasingly sophisticated. The Center for Research in Architectural Methods (CERMA) – a CNRS laboratory now merged into the Nantes Center for Research in Urban Architecture – has developed solar simulation software called Solene. This software enables architects to view shade buildings will cast l’uSine nouvelle i n° 3464 supplement i apRil 14 2016

You have a project or an innovative approach ? Send us your application file and confront yourself with the best people in the digital simulation field ! The prize list will be unveiled by the Usine Digitale team and its sponsors during a night at the heart of Teratec Forum on June, 28 2016 at Ecole Polytechnique

Discover our Award categories :

Submit your fore application be ! April 22, 2016

J Start-up Award J Collaboration Award J SMB Award J Grand prix of simulation J Innovation Award J Simulation personality Award

Become a sponsor of the Awards, contact Béatrice Allègre : +33 (1) 77 92 93 62 Email : ballegre@infopro-digital.com Organized with :

Find out more : http://evenements.infopro-digital.com/usine-digitale/trophees/ Ask for your application file to : trophee_simulation@infopro-digital.com

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Sabella’s d10 turbine runs on numerical simulation

on the ground, calculate how long sunshine will last at any point in a 3D scene, and estimate direct natural light levels outside buildings and in their rooms. Although these tools are now standard in architects’ and design offices’ palettes, Solene has developed and integrated increasingly complex factors. The impact of grassy areas, ponds and trees planted around buildings is now integrated into calculations. In addition, for buildings’ thermo-aeraulic calculations, the Solene software can be coupled with fluid dynamics simulation tools such as those supplied by the software vendor Fluent. Simulating local microclimates means architects can calculate as accurately as possible how comfortable buildings will be (both inside and outside) for their users. This would avoid buildings such as the recently constructed 20 Fenchurch Street skyscraper in London, whose solar glare dazzles strollers by and melts the plastic components of vehicles parked in front of it.

ComBAtinG pollution

D.R.

modeling sea currents and sea beds helped decide the best location for the tidal turbine.

this tidal turbine was submerged in June 2015 and connected to ushant island’s (Finistère) power grid in november 2015. the D10 is the first tidal turbine designed by sabella to be tested full-size. sabella turned to the engineering company artelia – which had modeled the seabed around ushant island – to choose a location for its tidal turbine. “Currents were modeled using bathymetric readings and seacurrent measurements. the installation site was chosen on 14

the basis of this data, the swell and its planarity,” says erwann nicolas, head of mechanical engineering design at sabella. the tidal turbine’s structure and blades were also sized using simulation calculations. CFD simulation, which was required for detailed design of the nacelle and carbon fiber blades, was done by hydrocean. engineers studied the mechanical and vibratory strength of the shaft and blades, as well as the turbine’s fatigue. ❚❚

Although a lot of resources have been poured into simulating natural phenomena, considerable investment has also been made in simulating the effects of human activity. There is nothing unusual these days about consulting pollution maps for major cities, in the same way as we check weather forecasts. Vivien Mallet, an INRIA researcher, underlines the progress made in forecasting since the 1980s: “Simulation and observations made using sensor networks now correlate more closely, which has really helped improve weather forecasts. This is especially true for air-quality forecasts, which are often very uncertain,” explains Mallet. For this reason, researchers improving these models have installed many new sensors. Data from weather and airquality monitoring stations – e.g. AIRPARIF – is already supplemented by satellite images and is increasingly established using the Internet of Things. Smart pollution sensors have been installed on Lyon’s tramways and are expected to appear on public streetlights in more and more French cities. All these data sources will feed into numerical models to produce more reliable pollution forecasts. Even cell phones can serve as sensors. For example, the SoundCity application uses cell phones to measure city noise pollution. Besides forecasting atmospheric pollution levels several hours in advance, simulation also helps respond to catastrophes. For example, we can simulate how a dirty bomb would explode in Place de l’Hôtel-de-Ville in Paris; depending on the weather, this will tell us the arrondissements in which to raise the alarm. Numerical simulation is also used when constructing new petrochemical facilities to see the impact of toxic discharged into the atmosphere. During the Fukishima disaster, the French Institute for Radiological Protection and Nuclear Safety (IRSN) made operational forecasts to find out whether or not the population was going to be exposed to radionuclide emissions. “We need high-quality weather data for reliable forecasts,” says Mallet. Radioactive smoke plumes move according to wind direction and the risk to the population varies according to whether the wind is blowing inland or out to sea. “Weather

simulation

SoundCity – listening to cities via smartphones

noise pollution map in paris, drawn up using data sent from smartphones.

the soundCity application was developed as part of inRia’s Citylab initiative on smart cities. the application uses smartphone microphones to measure noise all day long. “the application gives people an idea of their personal noise exposure, while the data also helps correct city noise maps,” explains Vivien mallet, an inRia researcher. the main problem is the poor quality of readings, which are measured using mobile applications that are, by definition, very unstable. “this project also plans to make progress on combining numerical simulation with observations using poor-quality mobile sensors. Currently, although the application sends about 1 million measurements every 4 days, only about 2-3% of them can be used to correct noise maps. “We’re hoping that participatory data collection will enable us to correct and hone our simulations and forecasts.” ❚❚

info@noesissolutions.com id8.noesissolutions.com

l’uSine nouvelle i n° 3464 supplement i apRil 14 2016

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forecasts can be very uncertain, especially in light winds. During the Fukishima disaster, Japanese scientists used operational simulation to predict smoke-plume movements and decide when they could discharge gas into the atmosphere to stop the reactor chamber exploding. We now want to calculate not only where smoke plumes will go, but also

how much confidence we can have in these forecasts. We want to quantify models’ uncertainty in order to make the best possible decisions,” explains Mallet. Numerical simulation is about aiding humans make the best decisions to protect their environment. Equations developed in French laboratories help achieve this goal. ❚❚

KEEpERs oF tHE planEt Climate simulation models served as the basis for the conclusions of the IPCC report. Teams of researchers around the world are striving to complete and improve their models. By tHierry luCAS

n

one of them appeared on the podium at COP21 or made any decisions affecting the future of our planet. And yet without them nothing can be done. We’re referring to the hundreds of researchers and engineers throughout the world who are modeling climate change, i.e. converting global climate phenomena into equations. The goal, after lengthy calculations using the world’s most powerful computers, is to predict likely temperature and precipitation changes over the next twenty, fifty, and even one hundred years.

prediCtinG ClimAte CHAnGe – CollABorAtive WorK

This enormous task, coupling vast amounts of simulation, is largely collaborative. Global atmosphere, landmasses (with their relief and vegetation), oceans, pack ice, clouds, atmospheric dust, CO2 and other greenhouse gases have all been simulated. Experts are now striving to validate and couple their models. “The first atmosphere models appeared in the 1960s and were derived from those developed for weather forecasting. Simplified ocean models have been around since the 1970s, but only became 3 D from the 1990s onwards,” says Michel Déqué, a researcher at the French National Center for Meteorological Research (Météo France).

ComBininG 20-30 modelS

Increasingly powerful computers mean that atmosphere and ocean models can now be coupled. Demand from the

Intergovernmental Panel on Climate Change (IPCC) has boosted development of this technology since it is impossible to calculate CO2-linked global warming without a coupled atmosphere/ocean model. This core climate simulation is central to the world’s 20-30 climate models. The French research community has focused on two global models: one produced by Météo France and another by the Institut Pierre-Simon-Laplace (IPSL), a federation of nine specialist environmental laboratories. Other major research groups have been formed: the National Center for Atmospheric Research (Colorado) and the Geophysical Fluid Dynamics Laboratory (Princeton University, New Jersey) in the USA; the Hadley Centre for Climate Prediction and Research in the UK; and the Max-Planck Institute for Meteorology in Germany.

diSCrepAnCieS BetWeen reSeArCHerS’ “meSHeS”

There are no fundamental discrepancies between research teams’ core models, even though each team has its own method of dividing up the atmosphere for calculations. For example, each “mesh” in one type of meshing devised is a parallelepiped, 100-200 km long on both sides but becoming thinner as it approaches the earth’s surface. The parameters (temperature, wind speed, etc.) within each mesh are average values, which are varied over time to simulate climate change. Laboratories are also developing many specific models for glaciers, aerosol impact, changes in vegetation, etc. These models have either not yet been integrated into climate models

a Global tEst bEd Climate-modeling researchers have been regularly comparing their results since 1995. every five or six years, Cmips (Coupled model intercomparison projects) invite research teams throughout the world to run their models on shared scenarios. these projects aim to assess climate models’ performance, 16

see where they diverge, and thus further progress in climate science. simulation carried out for Cmip5 served as the basis for the fifth intergovernmental panel on Climate Change (ipCC) report’s conclusions in 2013. Researchers are currently designing scenarios in preparation for Cmip6. this time,

small amounts of simulation will help compare the various core models, while specialized models – for example on the effect of aerosols – will undergo a series of tests. the exercises are expected to start in 2016 and 2017. several years’ research will then be needed to capitalize on the results.

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or have been done so in simplified form. “It’s not necessarily worthwhile integrating everything since this isn’t the best use of computing resources or budgets,” says Déqué.

nasa / sVs

empiriCAl eQuAtionS For SuB-meSH pHenomenA

The regularly observed discrepancies between climate models – especially during international atmospheric model intercomparison projects [see box opposite] – have already given researchers a lot to do. The cause of this problem has been identified by researchers as “sub-mesh” phenomena, which play a key role at a sub-mesh (i.e. smaller) scale. Submesh phenomena include radiation exchanges, air turbulence in the atmospheric layer near the earth’s surface, the role of clouds and sulfate-containing aerosols, etc. Basing calculations on theory alone is not enough. Researchers need to fine-tune their models using empirical equations, which are gradually being improved by the results of measurements and observations. Clouds in particular, which cover large areas above oceans, play a key role. “Although clouds have a significant impact on global temperature changes, their role remains poorly understood. Clouds are l’uSine nouvelle i n° 3464 supplement i apRil 14 2016

responsible for many of the discrepancies between various climate models’ results,” says Jean-Yves Grandpeix, a researcher at the Dynamic Meteorology Laboratory (LMD), a joint research unit on three sites: the École Polytechnique in Palaiseau (Essonne), the École Normale Supérieure, and Université Pierre-et-Marie-Curie in Paris.

Simulated precipitation rates for typhoon Hagupit, which struck the philippines in 2014.

improvinG dAtA ACCurACy

Climate-model discrepancies led to projects using satellites to measure clouds in 2007, the results of which are starting to be taken into account. As with other sub-mesh phenomena, each research team is fine-tuning its models by moving back and forth between actual results and expected values. Another challenge for climatologists is to fine-tune their calculations, i.e. reduce mesh size. This presupposes simulation programs that can use supercomputer power to maximum advantage by distributing calculations over many parallel processors. For this reason, teams of computer scientists (20-30 people at the Institut Pierre-Simon-Laplace) work alongside physicists and now play a key role transforming climate models into effective simulation codes. ❚❚ 17

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INTERVIEW

“WEatHER FoRCastinG REliEs ComPlEtElY on simulation” The quality of weather forecasts depends on how much computing power we have, as Météo France’s deputy director general, Olivier Gupta, explains. INTERVIEWED BY JULIEN BERGOUNHOUX

What was Météo France’s role at the COP 21? Let’s put our role back into its proper place. The COP 21 was primarily a series of political and strategic negotiations whereas we were involved in its preparatory stages. Météo France’s research teams contributed to the Intergovernmental Panel on Climate Change (IPCC) report, which served as a basis for political negotiations. We provided simulations for the fifth IPCC report that were carried out using the ARPEGEClimate model. The same model used for weather forecasting but set for climate simulation. Weather forecasting and climate prediction are two aspects of the same science. We also initiated various COP 21 side events. In particular, we were behind the C3 Challenge hackathon that ran throughout 2015. There was also a scientific conference at UNESCO in July and the Climate Train in collaboration with SNCF, which was the brainchild of one of our engineers. In addition, we were planning various events for school children but they had to be cancelled for security reasons. What role does simulation play in today’s weather forecasting? A central and increasingly important role. Weather forecasting and climate prediction are both based on simulating the atmosphere. People often think that weather forecasting is based on statistics. They imagine us making comparisons with the past and with various situations to deduce tomorrow’s weather by analogy. This idea, while widespread, is wrong. Weather forecasting has relied completely on simulation for decades. The quality of forecasts therefore depends on how much computing power we have. This power has a direct

“a significant amount of computation time is devoted to initializing models rather than to actual weather forecasting. We do this using data assimilation algorithms.” 18

impact on mesh refinement for a territory and on how sophisticated atmospheric calculations can be. The other essential parameter is algorithms, which vary in their effectiveness at solving equations and incorporating observations to initialize models. A significant amount of computation time is devoted to initializing models rather than to actual weather forecasting. New data has to be integrated intelligently since it does not cover the whole grid. We mix old and new data and then weight the two. The skill lies in choosing the right weighting for the initial state to match reality as closely as possible. Otherwise, the model will rapidly diverge from reality. Part of our research involves fine-tuning these algorithms. Who works on these models? The Météo France research center in Toulouse, which employs 300 people, or 10% of our workforce. For models, we collaborate extensively with international centers, especially the European Center for Medium-Range Weather Forecasts (ECMWF). It is an inter-governmental organization. We’re co-developing an atmosphere model on a global scale, ARPEGE and the European model IFS are two versions. As a result of this collaboration, we exert a major leverage effect and obtain excellent results even with a modest-sized team. We’re the leading organization in the ALADIN consortium – which brings together twelve European countries, three North African countries and Turkey – on limited-area models. This consortium is developing fine-mesh models for 24-hour forecasts. Do you tackle more specific fields? Absolutely. Our team in Grenoble is responsible for snowpack simulation, to predict the risk of avalanches. Which is another of our roles. The team focuses on the atmosphere, as well as the mechanics of snow-layer accumulation, how snow layers are configured by wind, the probability of creep, etc. They’ve developed a specific model for this research. We’re also committed to cutting-edge research on urban climate modeling. One of our research units is modeling town-specific features, which helps local decision-makers assess the need for green roofs, whitewashed roads, and dampened

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We run the model several times, slightly changing its initial conditions to study various scenarios. We can now do this for the fine-mesh model rather than just the global model. Our contract runs until early 2019 and the supercomputer will be upgraded mid-term to approximately 5 petaflops. This computer is split into two units: the first is for the operational system whereas the other is for climate simulation research and for developing the weather forecasting operational system of the future. Models must be tested before they are rolled out. Since it’s essential that we provide a continuous service, the research half of the computer can switch automatically to production mode to ensure an operational service. Furthermore, the two halves of this configuration are physically separated (by several kilometers) to guarantee service in the event of an accident. This supercomputer is combined with a regularly upgraded storage system. We reached 40 petabytes of storage capacity this year, and will achieve a hundred or so petabytes by the end of 2017.

ground and road surfaces. Our model can simulate the effect of these actions on the temperature, especially during heat waves. This is an increasingly important territorial issue in the fight against global warming. Some of our researchers are working on air quality. Others are simulating land surfaces since transfers, humidity, vegetation, and soil sealing all need to be modeled. We’re also simulating the upper ocean (waves and swell), running back-trajectories to calculate flotsam and jetsam and pollutant (hydrocarbon) drift. These are all joint research units attached to both Météo France and the French National Center for Scientific Research (CNRS), which also ensures we have close ties with academia.

Luc Pérénom

What technical resources do you use? The supercomputer we’ve been renting from Bull since 2014 is in Toulouse; its peak power is one petaflop. One of our tasks is to purchase computing power suited to our requirements, the models we use and their frequency at the best possible price. This power allows us to produce immediate predictive models covering a few hours and focused on France. We also provide overall fine mesh forecasting.

“We’re the leading organization in the alaDin consortium – which brings together 16 countries – on limited-area models. this consortium is developing fine-mesh models for 24-hour forecasts.” L’UsINE NOUVELLE i n° 3464 suPPLEmEnt i aPriL 14 2016

Why do you rent instead of buying? Since the equipment is replaced every 5-6 years, it doesn’t make much difference. It’s a formality more than anything. We switched to renting about ten years ago (as did equivalent organizations) and only purchase computing power. The supercomputer is on our premises and we provide its power supply and coolants. But we have it on a rental agreement. What are the main areas of simulation development at Météo France? We have four areas of development for simulating atmospheric phenomena. First, we want to take more and more observations into account. A lot of data now comes from satellites, with new instruments. Our first, and very complex, task is to invent new algorithms. We must then initialize the model intelligently, reconciling observations with results from the previous model. Data assimilation algorithms are a big project and we must choose the most promising technique. Our third area of development is physics (equations for models). Considering the full-scale experiments that are now possible, we must improve our modeling. One area of research involves probing what happens inside clouds. We’re using instrumented planes to achieve better understanding of phenomena such as Cévenol episodes, which is helping us improve our equations. Our fourth area of development is connected with resolution. The global model’s resolution is 7.5 km whereas the resolution of the fine-mesh model over an extended metropolis (Western Europe and North Africa) is 1.3 km. Once you go beyond a certain resolution, new problems appear. For example, if slopes become too steep the grid computing and numerical schemes must be modified. In addition, our code must be better optimized to hardware architecture. One of our main current research projects is on model scalability and adapting models to massively parallel architecture. This is a no-degradation, gain factor. For this research, we’re working with the ECMWF and the European Center for Research and Advanced Training in Scientific Computation (CERFACS), which is located on our Toulouse site and in which we are shareholders. ❚❚ 19

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The Aircity project – developed by Aria Technologies – takes the influence of buildings into account when assessing how city air pollution is dispersed by wind.

C

limate change and the deployment of new energy sources have given simulation a real boost. Offshore and even nuclear entrepreneurs and engineers have seized on environmental modelling. Some of the start-ups and SMEs launched by these experts have made a real name for themselves on this new market. Here are eleven of these outstanding companies, which are highly rated by the sector’s experts.

ArIA TeCHNOLOGIes Is ANALYZING POLLUTANT DIsPersION

Aria Technologies was set up in 1990. The company produces a numerical simulation software suite and carries out studies on air pollutant dispersion, climate analysis, and renewable energy sources. Tools intended for industrialists – in cities such as Rome, Rio de Janeiro, Peking – and researchers. Some 65% of studies carried out by Aria Technologies are exports. The company’s climate change business is currently expanding rapidly. This work covers storm frequency calculations, the impact of rising temperatures on urban pollution, and city dwellers’ energy consumption in fifty years’ time.

AriA Technologies

specialization Atmospheric simulation Date set up 1990 Locations Boulogne-Billancourt (Hauts-de-Seine), Rio de Janeiro (Brazil), Milan (Italy) Workforce 45 people T/O (2014) 4 million Euros

mArkeTs

smes, natuRal element eXPeRts Several outstanding French companies are at the cutting edge of environmental simulation, whether of air and land phenomena, pollution, or renewable energy sources. bY ALAIN CLAPAUD

KeY Clients total, Cea, Renault, suez

NUmTeCH Is PreDICTING AIr POLLUTION

Numtech is located on La Pardieu Technology Park (in Aubières, near ClermontFerrand) and specializes in weather forecasting and simulating pollutant dispersion into the atmosphere. The company’s operational systems feed data 24/7 into air monitoring stations run by associations such as AirPARIF and AirPACA. Numtech opened its first subsidiary in Morocco a year ago. Pierre Béal – the company’s founder – is also looking into providing pollution forecasts in very fine scale. This service, called NOA, is at the preparation stage and could give two-hourly city pollution forecasts, accurate to within a few meters. Ideal for planning your run! specialization Atmospheric event modelling and simulation Date set up April 2000 Location Aubière (Puy-de-Dôme) Workforce 20 people T/O (2014) 1.3 million Euros

KeY Clients eDF, suez environnement, total, areva, Cofiroute, airparif

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more than 250,000 inhabitants, and electromagnetic wave propagation maps. Geomod is collaborating with the CSTB to develop its Mithra software suite. KeY Clients suez, Veolia, lyonnaise des eaux, siaaP, Bouygues travaux Publics

INNOseA Is OPTImIZING mArINe eNerGY sOUrCes

Innosea – a spin-off from the École Centrale de Nantes – is an engineering company specializing in renewable marine energy (RME). Its business covers all aspects of RME use. As such, Innosea has carried out calculations for EDF’s offshore wind-farm foundations in Courseulles-sur-Mer (Calvados) and Saint-Nazaire (Loire-Atlantique). Innosea’s engineers are working on the next generation of floating wind turbines, and on tidal energy and wave energy converters. specialization Simulation of renewable marine energy sources Date set up 2012 Location Nantes (Loire-Atlantique) Workforce 21 people T/O (2014) 732,000 Euros

meteodyn’s wind assessment on a wind farm.

meTeODYN Is CALCULATING reNeWAbLe eNerGY sOUrCes

Meteodyn was set up by Didier Delaunay – a CSTB (French Scientific and Technical Center for Buildings) researcher – and has positioned itself on the market for wind and climatology numerical simulation using its own solvers. The company produces and markets a range of calculation software and carries out studies for wind-farm operators in Europe, China, and India. Meteodyn now employs around fifteen people abroad. It also carries out calculations for the construction business, simulating building ventilation and helping architects construct passive buildings. The company has diversified into solar energy and has carried out several solar-farm feasibility studies, especially for China. specialization Simulation of renewable energy sources Date set up 2003 Location Nantes (Loire-Atlantique) Workforce 50 people T/O (2015) 3.2 million Euros

KeY Clients eDF, iberdrola, enel, General electric, Joyful melody Wind energy Company (China)

GeOmOD Is PreDICTING PreCIPITATION ImPACT

Geomod’s hydrology business involves assessing the impact of precipitation on city wastewater systems. Suez, Veolia, Lyonnaise des Eaux, and the Greater Paris Sanitation Authority (SIAAP) all use Geomod’s calculation codes. But this is not the only string to Philippe Bischoff’s bow. He has also positioned Geomod on more «land-based» calculations. For example, noise maps for urban agglomerations of

MeTeodyn

specialization Hydrology and electromagnetic wave pollution Date set up October 1995 Locations Lyon (Rhône), Brest (Finistère) Workforce 12 people T/O (2014) 1.4 million Euros

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KeY Clients eDF, enBW

DATAPOLe Is PreDICTING WAsTe VOLUmes

If ocean currents and valley winds can be modelled, why not human behavior too? This principle has inspired Datapole, a start-up established by Frédéric Gagnaire in 2010. The company’s initial idea was to provide local authorities with a tool for forecasting waste volumes generated by their citizens, thus enabling them to optimize resources allocated to waste collection. Datapole’s predictive models are based on collection data, weather forecasts, and shop retail data. Datapole has since developed its initial offer to produce an electricity consumption tool (PrediWatt), and will shortly be adding a building management tool. specialization Forward-looking resource management software Date set up May 2010 Location Paris – La Plaine Saint-Denis (Seine-Saint-Denis) Workforce 11 people T/O (2015) 410,000 Euros

KeY Clients engie, Plaine Commune agglomeration community, Chevreuse Valley public waste authority

NeXTFLOW sOFTWAre Is DesIGNING FLOWs AND WAVes

Nextflow Software is a spinoff from HydrOcean, a specialist hydrodynamics firm bought out by Bureau Veritas in September 2015. Nextflow has taken over HydrOcean’s software vendor business. A dozen people have joined this start-up, including Erwan Jacquin, HydrOcean’s founder. Nextflow’s current business should ensure a 1-2 millionEuro turnover, and the company will continue working with the École Centrale de Nantes to codevelop simulation models. Nextflow has particular expertise in simulating wave effects, which is invaluable for designing ship hulls, offshore platforms, and for building offshore wind farms. specialization Fluid mechanics simulation software Date set up June 2015 Location Nantes (Loire-Atlantique) Workforce 10 people T/O Not applicable

KeY Clients Renault, michelin, airbus Helicopters

simulation

OPTIFLUIDes Is mODeLING FLUID DIsPersION

OptiFluides is located on La Doua science campus in Villeurbanne (Rhône) and has developed process simulation and modelling expertise. To achieve this, the start-up’s founder Nicolas Boisson used simulation codes produced by the software vendor Fluent. OptiFluide’s calculations simulate flows in industrial plants, thus enabling petrochemical companies to optimize their processes. OptiFluide also models air pollutant dispersion as part of risk assessments for industrial sites.

specialization Simulation of liquid, gas, and multiphase flows Date set up June 2011 Location Villeurbanne (Rhône) Workforce 5 people T/O (2015) 400,000 Euros

KeY Clients total, eDF, Bluestar silicones, solvay

OPeN OCeAN FOr Web-bAseD OCeAN ANALYsIs

AmplisIm is assessing the impact of pollutants on air quality in urban and industrial environments.

Jérôme Cuny and Renaud Laborbe set up Open Ocean in 2011 to put their ocean simulation knowledge online. Although simulation codes are very complex and generate large volumes of data, Open Ocean gives access to calculation results via a simple web interface. The company’s Metocean Analytics platform is the fruit of three years’ work. This platform is for industrialists developing projects in the tidal energy, offshore wind turbine, and offshore oil sectors. Open Ocean’s clients include Engie and Sabella. Open Ocean raised 1.6 million Euros in 2015 and intends to increase its workforce from 11 to 16 people by the end of this year. specialization Online solutions for ocean/weather analysis Date set up 2011 Locations Paris and Brest (Finistère) Workforce 11 people T/O (2014) 96,500 Euros

AmPLIsIm FOr AIr-QUALITY sImULATION “As A serVICe”

AmpliSIM was set up in Paris in 2015 by Sylvie Perdriel – a former Aria Technologies’ employee – and Olivier Oldrini, the founder of the consultancy firm Mokili. AmT/O Not applicable pliSIM offers an air-quality simulation service for design and engineering offices. This cloud-based service assesses the impact of industrial-plant and road-traffic pollutant emissions on surrounding neighborhoods. AmpliSIM’s founders use open-source simulation codes recommended by the US Environmental Protection Agency, and free software (OpenFoam and EDF R&D department’s Code_Saturne software). AmpliSIM is currently negotiating with Qarnot Computing and Bull to increase its computing power. specialization Air-quality simulation Date set up March 2015 Location Paris Workforce 2 people

KeY Clients engie, sabella

KeY PaRtneRs Bull, eDF

eDF sTOre & FOreCAsT Is COUPLING WeATHer FOreCAsTs AND reNeWAbLe eNerGY

EDF SF is a spin-off from EDF launched by three researchers at EDF’s R&D department. They wanted to set up a company to market the fruit of their research. Their Pegase software (an EMS – energy management system) uses energy consumption and meteorological data for precise management of battery charging/discharging processes coupled to wind farms and photovoltaic panels. This solution is suitable for islands since batteries compensate for intermittent energy resources. Following a pilot project in La Réunion, EDF Énergies Nouvelles’s photovoltaic power station in French Guiana was the first facility to benefit from Pegase’s calculations. specialization Energy management software Date set up March 2014 Location Incubateur Agoranov (Paris) Workforce 10 people T/O (2014) 474,000 Euros

open oceAn ; AMplisiM

Open Ocean’s online decisionmaking tool can model ocean currents, wind, and waves.

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KeY Clients eDF Énergies nouvelles, Électricité de mayotte, enercal

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2016 HPC BIGDATA SIMULATION Les c lĂŠs du futu r Unlocking the future Les 28 & 29 juin / June 2016 Ecole Polytechnique Palaiseau - France

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a reaL sTar

CYBElEtECH, numERiCal FaRminG Agriculture needs to produce bigger, higher quality yields while also reducing its pollution. CybeleTech has taken up this challenge by incorporating farmland data into plant-growth simulation. by Jean-François Prevéraud

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Models based on real-Time Measurements

Saguez met Philippe de Reffye – the agronomist in this story (who is not one of CybeleTech’s cofounders) – in the early 2000s. Together they developed a model to simulate plant growth and architecture, for use in agronomy and imaging. In 2003, they set up the Digiplante joint research unit at the École Centrale de Paris. Under Cournède’s leadership, this research team developed a plant-growth model used in an online tourist application produced by Île-de-France regional council: 3D simulation of the gardens at the Palace of Versailles. This application appealed to Lambert, who was looking for a plant-growth model to synthesize and exploit his own data. “I thought, if these guys can produce this, I need to meet them,” he recounts. Several projects were launched to validate the feasibility of this approach and test its relevance. Following successful results, Saguez, Cournède and Lambert set up CybeleTech at the end of 2011. The company’s first orders came from a satellite operator that wanted to develop 26

Modelling crop growth optimizes the use of fertilizers, water and treatments to improve yield.

its image-based service offer, and a seed company that had started using modelling for genotype selection. CybeleTech’s expertise enabled Digiplante’s mechanistic plant-growth models to be combined with satellite images showing plant biomass potential at any point on a given piece of land. According to the weather conditions forecast, farmers can now calculate the correct fertilizer and phytosanitary treatment needed to achieve set added-value targets while also causing as little pollution as possible.

Towards Plant PLM

This solution means farmers can base their decisions on real-time crop measurements rather than on extrapolations from previous years’ experience. It is now possible to accurately predict disease onset according to a plant’s actual stage of development. Consequently, farmers can give plants more protection while also intervening less often. In the short term, this approach will meet the challenges facing agriculture: to

D.R.

hat do you get if you take an agronomist, a numerical simulation researcher, a student engineer mad about IT developments, an agri-food marketing expert and bring them together under a name evoking the Phrygian goddess of nature and abundance? CybeleTech, of course – a French start-up established at the end of 2011 to model plant growth. “As is often the case, CybeleTech’s story is first and foremost about human encounters rather than technology,” explains Marie-Joseph Lambert, Novartis Agro’s former director of business forecasting. Together with the mathematician Christian Saguez, his PhD student Paul-Henry Cournède, and two other members of the Digiplante team (Professor Véronique Letort – Cournède’s deputy – and Benoit Bayol), Lambert is one of CybeleTech’s five cofounders.

simulation

tHREE KEY PlaYERs maRiE-JosEPH lamBERt, director – Cofounder

Marie-Joseph Lambert trained in sales and marketing before pursuing his career in various industrial groups. He became Novartis Agro’s director of commercial policy and distribution marketing in 1997, and its director of business forecasting in 2000. After the company merged with Zeneca, he was key account manager Europe from 2001 to 2005, before joining CybeleTech as its director. CHRistian saGuEz, Ceo – Cofounder

Christian Saguez graduated from the École Centrale de Paris in 1972, and was director of international and industrial relations at the French National Institute for Research in Computer Science and Automation (INRIA). He subsequently founded and was CEO of Simulog, and was also

increase production 1.5-fold while also reducing inputs by 30-40% and improving the sanitary quality of products. “The next stage of this technology will enable farmers to select plant varieties for sowing and draw up a complete protocol for growing them on a given piece of land, varying this protocol according to the qualities expected in the end L’usine nouveLLe I N° 3464 SUPPLEMENT I APRIL 14 2016

director of industrial relations and subsidiaries at the French National Center for Space Studies (CNES). At the same time, he was also a professor at the École Centrale de Paris, where he set up the Mathematics Applied to Systems (MAS) Laboratory. He was president of the TER@TEC Association (European Competence Center for HighPerformance Numerical Simulation) until 2009. He is a member of the French Academy of Technology’s Communication and IT Technology Commission, as well as president of the Scilab Consortium. Paul-HEnRY CouRnèdE,

scientific advisor – Cofounder

Paul-Henry Cournède graduated from the École Centrale de Paris (1997) and Cambridge University, and has a PhD in applied mathematics (2001). He is director of the CentraleSupélec’s Digiplante team, working on mathematical modeling of plant growth in the MAS laboratory.

product. It will be a sort of ‘plant PLM’ [ed. note: product lifecycle management], connecting every step of the process from start to finish,” explains Lambert. CybeleTech currently carries out a dozen ad hoc studies a year for industrialists, but its short-term plan is to provide online services for farmers. This will provide farmers – via their cooperatives – with the seed and inputs they need to maximize yield on each piece of land. CybeleTech is currently working on arable crops (cereals, oilseeds), market-garden produce (tomatoes, strawberries), and perennial crops (vines). The company plans to expand into forestry (developing the value of forest resources, adapting to climate change), and tropical products (coffee, cocoa beans, cotton, bananas). For Lambert, this means CybeleTech could generate turnover of 5-10 million Euros over the next five years. ❚❚ 27

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J

ean-Hilaire Renaudat farms 1,200 hectares north of Châteauroux (Indre) and belongs to a new generation of farmers at the cutting edge of digital technology. In a few days’ time, he will be applying nitrogen fertilizer to his soft wheat, barley, and rapeseed crops. What’s special about this is that the amount of fertilizer Renaudat applies is entirely adjusted to data collected by sensors on his field crop sprayer. The N-Sensor software developed by the Norwegian group Yara measures crops’ light reflectance to calculate their biomass and nitrogen requirements. The German agricultural giant Bayer uses the same method to adjust fungicide levels, as does a combine harvester-mounted software program that calculates yields in real time while they are harvested. Renaudat sees many advantages in using these new tools: “We made a return on our investment within four years. We’ve cut down on nitrogen fertilizer, have less crop disease, and produce higher, more protein-rich yields,” he says, clearly delighted. Renaudat also uses his smartphone to calculate the nitrogen requirements of his rapeseed. As in industry, digital tools mean farmers can now keep track of running their business. Above all, these tools help farmers anticipate, increase yields, and predict the quantity and quality of harvests even before production is over. This radical shake up has been dubbed the “third agricultural revolution” in some quarters, following the first revolution that turned agriculture into a commercial business and the second that mechanized it and introduced chemical fertilizers to increase yields. The past few years have witnessed an abundance of decision-making and simulation solutions: adjusted irrigation, crop-disease forecasting, yield simulation, milking robots on dairy farms, calving prediction, automated cowshed cleaning, etc. “One of the main challenges is to improve eco-friendly crop management by limiting the use of agricultural inputs,” says Jacques Mathieu, director of Arvalis Plant Institute.

DIGITAL TRANSFORMATION

tHE nEW aGRiCultuRal REVolution Challenges in agricultural modeling – simulating wheat growth, optimizing inputs, predicting milk production, etc. – have spurred on start-ups and yielded a bumper crop of innovations.

by ADRIEN CAHUZAC

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Requirements Calculated to Within a Square Meter

Arvalis and Airbus Defence & Space developed Farmstar in 2003; it was one of the first systems to make crop-management recommendations based on satellite photos. Although Farmstar has always been very popular with farmers, other systems have gradually caught up. Drones are now used for precision farming, and France seems far ahead of other European countries on this technology. Airinov is a start-up that was established in a barn in Poitou-Charentes by two engineers and a farmer’s son back in 2010. Within a few years, the company has become the French number one on agridrone-based recommendations for nitrogen fertilization. Airinov has developed quad-band sensors that can, for example, work out rapeseed weight and calculate chlorophyll levels in wheat using green and infra-red light wavelengths emitted by the plants. Airnov then calculates how much nitrogen is required for each square meter of a land parcel. “Our technology is the most advanced in Europe. After five years of trial and error, we found our business model thanks to a partnership with the French drone manufacturer Parrot, which invested capital with us,” explains Romain Faroux, Airinov’s cofounder. Airinov’s technology offers

sebastien sindeu ; d.R.

Airinov drones calculate the nitrogen requirements of wheat and rapeseed.

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“Our start-ups must move into the industrial phase” maRinE PouYat, Director of the Renaissance Numérique think tank and head of the legal department at the French Federation of E-commerce and Distance Selling (FEVAD). Why did you send the government an official report on agriculture and digital technology last November? Agriculture is facing many challenges. It must feed the planet, be eco-friendly, make its profession more attractive, as well as reconnect with consumers and win back their trust. We’ve made sixteen proposals to rethink agricultural

production, distribution and consumption in the digital era. What are these proposals? We want farmers to receive training and support to purchase precision digital tools, especially tools reconciling yield targets with sustainable development. We also suggest setting up regional open data experimental programs in some branches of agriculture. This will bring production costs and retail prices back into balance. What’s more, we believe that cooperatives – which have access to agricultural and

market data – should be at the forefront of agricultural big data strategies to defend farmers’ interests. Has France adequately got the measure of this new agricultural revolution? France has a large pool of start-ups, which must now move their solutions into a more industrial phase. French public and private stakeholders should seize on this official report now or else it will be too late. We’re facing international competition from very powerful groups. ❚❚

We equip, you compute

Genci (Grand équipement national de calcul intensif) makes available powerful HPC resources to French scientific communities and also to industrials wishing to conduct research in link with an academic PI, in all fields.

Climate changes

Reducing pollutant emissions

L’USINE NOUvELLE i n° 3464 supplement i apRil 14 2016

Prevention of seismic damages

Propagation of major fires www.genci.fr

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Arvalis models the resistance of plants to water shortage using sensor data and cameras (RGb images of photosynthesis).

many benefits. “Although satellite images are expensive, they’re worthwhile if you can recover the cost on large land parcels or areas. Drones can be used for more occasional missions, even though they’re still expensive to access [Ed. note: 25,000 Euros for Airinov’s solution],” says Véronique Bellon-Maurel, director of the ecotechnology department at the French National Research Institute of Science and Technology for the Environment and Agriculture (IRSTEA). Since 2014, several chambers of agriculture in the GrandOuest region of France have been offering decision-making

pascal Guittet

“our challenge is to promote this data to third parties. some of them, like thales, could use it to simulate plant growth.” François Houllier, president of the French national institute for agricultural Research (inRa)

30

services based on drone images. “Drones fly over areas very quickly and precisely. Weather conditions sometimes make it harder to use satellites, although drones can’t fly in strong wind,” says Nassim Hamiti, an agricultural equipment project leader at the Permanent Assembly of Chambers of Agriculture (APCA). Another constraint is that, for the time being, drone-based services are limited to nitrogen-input recommendations for rapeseed and soft wheat, although Airinov is extending this to other crops. Many other French start-ups like Airinov have appeared in the field of agricultural digital technology. After tough early years, some of them are consolidating and have moved into a more industrial phase. One example is Naïo, a Toulousebased start-up established in 2010. Naïo developed the Oz robot for mechanical weeding of market-garden crops on land parcels covering less than ten hectares. “Oz features eleven infra-red sensors on its front and sides, together with four electric-motor driven wheels. These wheels are powered by lead batteries giving Oz four hours of autonomy,” explains Gaëtan Séverac, Naio’s cofounder. Although Naïo has only sold about thirty of its Oz robots – which sell for 21,000 Euros

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Standardized Computer Language to benefit from digital technology, we need a single computer language to speed things up. the agro edi europe association – set up twenty years ago by agricultural organizations to improve traceability and data exchange between phytosanitary suppliers and users – is standardizing remote-sensing data. “this new language should be operational by the end of the first half of 2016 and will apply in particular to all drone operators. cooperatives and chambers of agriculture will be able to change

supplier more easily,” says bruno prépin, ceO of agro edi europe. the association is also working with the union Française des semenciers (uFs, a French trade association for seed companies and plant breeders) on seed production, and in the poultry sector to standardize computer data among operators. “this will benefit French industrialists, making them more productive and distinctive,” says prépin, who hopes the French system will be rolled out in europe. ❚❚

each – the company has just developed Oz’s big brother: a high-clearance robot called Anatis. This robot was designed in collaboration with the French manufacturer Carré and is for weeding land parcels bigger than ten hectares. But that’s not all it does since Anatis features 3D cameras and many sensors to collect data on humidity, soil temperature, weed infestation, density, and plant development stage. Digital technology is also radically changing agricultural research, leading technology institutes to adapt their research programs. Two of Arvalis Plant Institute’s experimental farms are currently specialist “digital farms”. The first – in Boigneville (Essonne) – specializes in arable crops, while the second – in Saint-Hilaire-en-Woëvre (Meuse) – specializes in mixed farming and cattle rearing (beef production). By the end of 2016, both farms will have implemented digital production management, combining existing techniques with test tools and prototypes from external companies.

A Phenotyping Experimental Station

Fundamental research is also adopting digital tools to improve its efficiency. Since 2013, the French National Institute for Agricultural Research (INRA) has been working

d.R.

“one of the main challenges is to improve eco-friendly crop management by limiting the use of agricultural inputs.” Jacques mathieu, director of arvalis plant institute

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with Arvalis on a national high-throughput cereal phenotyping program called Phénome. One of the main platforms for this 24-million Euro project jointly funded by the French “Investment for the Future” initiative is in the commune of Ouzouer-le-Marché, deep in Le Loir-et-Cher. This site has eight large, mobile greenhouses in the middle of a field. Sensors measure rainfall, soil humidity, wind, etc. At the far end of the land parcel is an imposing boom on a railmounted gantry. This boom – fitted with many sensors and cameras – takes photos to analyze plants’ phenotype (i.e. their physical characteristics) and chlorophyll content. “The goal is to create controlled water stress in plants and stop rain falling on the plot,” explains Yann Flodrops, director of the experimental station. This pioneering European program will help scientists select varieties consuming less inputs (water, nitrogen, and pesticides) and identify phenotype genes.

Orléans – Plant Digital valley

The advent of thousands or even millions pieces of agricultural data from fields and research programs presupposes high-security data storage facilities. The INRA has built two data centers – one in Toulouse (Haute-Garonne) in 2014 and another in Bruyères-le-Châtel (Essonne) in October 2015 – which each cost four million Euros. “The challenge is to promote this data to third parties such as Thales, which use it to simulate plant growth,” says François Houllier, president of INRA. Although entering the digital era is a major change for agriculture, digital projects and initiatives remain scattered. Faced with global foreign giants at the cutting edge of agricultural digital technology – such as John Deere and Monsanto – French projects urgently need to pool their efforts. Some joint initiatives are starting to emerge: for example, the three-year Smart Agriculture System project launched in 2014. This project brings together the Végépolys, Céréales Vallée, DREAM Eau & Milieux competitiveness clusters and private groups such as Limagrain. Its purpose is to design an innovative wheat modeling, yield forecasting, and decisionmaking system. “Seed companies will be able to market their seeds faster. Farmers will be able to discover constraints more quickly, predict water requirements, and increase production. This will give a real competitive advantage,” says an enthusiastic Christian Saguez, CEO of the start-up CybeleTech, one of the project’s partners. Alongside this project, a plant digital valley – Agreen Tech Valley – is to be established in Orléans and its suburbs (Loiret) in 2017. This initiative is expected to bring together several agricultural companies – such as Axéréal, Kuhn and Sofiprotéol – as well as the University of Orléans. “France has all the skills it needs to hold a strong position in the international digital agriculture race. We’re well positioned on IT technology and agriculture. It’s now up to us to move into the industrial phase,” says Saguez, who is also vice-president of Agreen Tech Valley. In the future, French agriculture will be distinguished by its technology and France’s ability to export this technology, as well as by its production. This is the challenge facing French agriculture if it wishes to retain its world ranking. ❚❚

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European Pole

HPC BigData Simulation

Unlocking the future ■ ■ ■ ■ ■

Mastering technology Industrial Research Dissemination across industries Teaching and training International cooperations

Teaching & Research

Industrial companies

Contact & Information Tel. +33 (0)9 70 65 02 10 jean-pascal.jegu@teratec.fr Campus TERATEC 2 rue de la Piquetterie 91680 Bruyères-le-Châtel France

Technology 33 companies

www.teratec.eu

simulatioN

PortfoLio

Nature revealed Forces, movement, flow, growth and turbulence: when simulation unveils the environment. By Jean-Louis saLque and Bernard VidaL

tree growth and crown interaction.

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simulatioN

distribution of carbon dioxide emmisions in earth’s atmosphere.

representation of ocean surface temperature in the Gulf of Mexico.

Chlorophyll evolution in an unstable seabed.

Nasa ; INrIa - CIrad ; INrIa - CNrs ; CNrs ; TaCC

Wave dispersion along the bow of a boat.

L’usine nouVeLLe I N° 3464 supplEmENT I aprIl 14 2016

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simulatioN

Modeling atmospheric dispersion of pollutants.

representation of the magnetic field in the earth’s core. Vortex lines of a tornado.

Propagation of seismic waves throughout the planet.

earth’s magnetic fields.

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simulatioN

trajectory of air particles around a sailboat.

Modeling a north atlantic type ocean.

OpTIfluIdEs ; CNrs ; TaCC ; uCsC ; INrIa-CNrs ; uNIvErsITé dE Jyväshylä (fINlaNdE)

Modeling the temperature of currents at a depth of 30 meters off the Cape of Good Hope.

3d visualization of fluid flow in porous rock. L’usine nouVeLLe I N° 3464 supplEmENT I aprIl 14 2016

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Virtual-reality helmets help train staff to use machines without disrupting production.

aFFoRDaBlE immERsion FoR EVERYonE The advent of mass virtual reality will benefit companies – especially small ones – by making immersive simulation more accessible. BY Julien Bergounhoux

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C

omputer-aided design (CAD) is the traditional bastion of virtual reality. Until now, only big groups were able to invest in Cave Automatic Virtual Environments (CAVEs) –rooms equipped with projectors for virtual-environment work – e.g. to enter and interact in simulated cockpits. These companies have devoted huge amounts of money to virtual reality: Renault spent three million euros on a CAVE in 2013. The cost of this technology has limited its take-up. Nevertheless, CAVEs make huge profits for manufacturers. It took the car manufacturer Jaguar just three weeks to make a return on a CAVE costing £3 million. Big manufacturers such as Dassault Aviation stopped making physical mock-ups a long time ago and now design their products using virtual reality, from the assembly line to maintenance.

FroM FighTer PlAneS To eleCTriCAl APPliAnCeS

The advent of HMDs (head-mounted displays) for immersive simulation are changing this model. By significantly reducing costs – which have dropped from around a million to approximately a thousand or even a hundred Euros –HMDs have made virtual reality affordable for all compa-

Seb Kuntz ; D.R.

VirTuAl reAliTY

simulation

JEUDI 9 JUIN 2016 - PARIS

« it won’t be easy for CAVes to survive »

FaBiEn BaRati CEO and cofounder of Emissive have you noticed more interest in virtual reality? Yes. We’ve been working in this field for the past ten years. Over the past few months, we’ve sensed that demand is increasing. It hasn’t yet rocketed, but it’s really growing. Will these helmets replace existing equipment, even in big companies? I don’t see how CAVE’s [Ed. note: rooms with projectors, for virtual-

environment work] will survive since they’re very expensive to install and maintain. Even projector light bulbs are almost as expensive as investing in virtual helmets. I think it’s a decision that will be made quickly, especially since CAVEs don’t provide any additional advantages. Their multi-user dimension is very limited. What are you setting up using these systems? We’re working on “The Enemy”, a documentary pitting visitors against enemy combatants in an armed conflict. The documentary combines ten connected helmets in the same virtual environment and will enable visitors to move about in an area covering 200-300 m2. ❚❚

e date ! Réservez votr

CONFÉRENCE

« La data c’est la santé ! » AVEC LA PARTICIPATION EXCEPTIONNELLE DE

Thomas LANDRAIN

Nathalie MAUBON

Malika MIR

Pascale SAUVAGE

Président LA PAILLASSE

Présidente HCS PHARMA

Chief Information & Digital Officer Directrice de la stratégie IPSEN PHARMA ASIP • Malika MIR revient sur la transformation digitale d’IPSEN Pharma

nies, even the smallest design offices. This technology was previously limited to planes, boats and cars, but is now used – as at the German company Miele – for kitchen appliances. Virtual-reality solutions are not limited to viewing images. When connected to systems – either hand-held peripherals or motion sensors – they enable users to interact naturally with their virtual environment, and even move about in it [see box on following page]. The advantage of virtual reality compared to screen-based 3D representation is that images are viewed life-size and in spatial dimensions. When plans on CAD software are hard for non-specialists to understand, all relevant departments (marketing, maintenance, and even end clients) can be involved at the very early stages of a product’s life cycle. This collaboration can also be achieved remotely since the relevant parties can come together in a virtual environment from several physical sites.

AnTiCiPATing uSeS

Virtual reality can also simulate use in real conditions, especially for architecture. For example, it helps architects

• Pascale SAUVAGE de l’ASIP et Jean-Yves QUENTEL de MENSIA TECHNOLOGIES vous donnent les clés pour réussir sur ce marché très réglementé • Éric DESSERTENNE de BIOCORP vous dit comment passer du gadget à l’outil médical professionnel • Thomas LANDRAIN de LA PAILLASSE imagine avec vous la (e) santé en 2030 • Découvrez les 10 startups de la e-santé à suivre selon L’Usine Digitale Avec le soutien de :

Programme complet et inscriptions sur : http://evenements.infopro-digital.com/usine-digitale/ conference-conference-e-sante-2015-4067 Contact : Elvire ROULET e-mail : eroulet@infopro-digital.com tél. : +33 (0)1 77 92 93 36

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decide whether people will have the sun in their eyes in a particular location, or if a room will be cramped once it’s been furnished. This applies to all work areas. For example, virtual reality can integrate virtual humans to test the ergonomics of assembly line workstations before they are built. Neuromarketing is another example. Virtual reality could replace conventional market studies, which use imitation stores, display cases, and products. Companies will be able to create their own virtual supermarkets, which are much cheaper and can be configured however they like. These supermarkets will enable every aspect of an experiment to be simulated and recorded. In addition, their settings can be changed according to where customers go in them and what they look at.

training – e.g. train-checking procedures – for several years now. Virtual environments do not disorientate people, even non-technical staff. They also take up far less room, provide more exhaustive training (every possible configuration can be gone over as often as you like), and are much quicker to set up. This technology also facilitates distance training of both large groups and handfuls of students, even when they are geographically scattered. Staff can be trained to use new equipment before it is installed. Even after equipment is up and running, simulation enables staff to train without holding up production. Lastly, this technology is more accessible and provides a completely safe setting in which to raise staff awareness of high-risk environments. For example, fire-fighters or staff in specific industrial settings (nuclear power stations, oil rigs, etc.). There are now applications for virtual reality in medical settings: it helps medical students view the full complexity of the human body, learn about anatomy in detail, diagnose virtual patients, and even practice operations. ❚❚

SiMPliFYing AnD Pooling TrAining

Apart from design, training is another area that will be transformed by virtual reality. Here too, big companies such as SNCF have been using virtual reality solutions for staff

thREE solutions to KEEp an EYE on oCuluS riFT

SPREADING THE WORD Price 699 euros Release Date March 2016 Manufacturer Oculus, a Facebook subsidiary

hololenS

THE ALTERNATIVE OPTION Price 3,000 dollars Release Date March 2016 Manufacturer Microsoft

hTC ViVe

THE MOST COMPLETE SOLUTION Price 799 dollars Release Date April 1st, 2016

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Manufacturer HTC

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Oculus Rift is behind the revival of virtual reality helmets. the project was launched in 2012 and the start-up’s growing success led to its buy-out by Facebook in March 2014. two years later, the definitive version of this helmet is about to be released. Oculus touch – two controllers designed for completely natural interaction in virtual environments – will also be released for use with this solution. Rift helmets are the yardstick by which other solutions should measure themselves. Microsoft has taken another route with its HoloLens helmet. Instead of preventing users from seeing the world around them, this helmet superimposes holograms on it to enhance users’ vision. the helmet is not just a user interface; it is also a fully autonomous computer in its own right. It runs on Windows 10 and is hence compatible with many applications, enabling interaction with virtual elements and motion sensors. unlike Oculus and HtC, Microsoft’s priority target is professional use.

this helmet is coproduced by HtC (a smartphone manufacturer) and Valve (software vendor of the Steam platform, which has revolutionized the sale of online games). It rivals Oculus Rift helmets and features distinctive Lighthouse base stations, which are placed in the corner of a room so that users can move about in a virtual environment. the HtC Vive helmet also has a camera, enabling users to see transparent silhouettes of the real world while in the virtual world by simply pressing a button.

DISRUPT THE INDUSTRIAL LANDSCAPE

G/OM/16.21/A Images courtesy of EADS Innovation Works and Ford.

INNOVATE WITH VIRTUAL PROTOTYPING

BRING YOUR PRODUC T TO LIFE VIRTUALLY: Build, test and experience your virtual prototype Get your product right the ďŹ rst time! Lessen the impact on our environment 41

w w w.esi-group.com / innovate | innovate@esi-group.com

simulation

although most cars already have automated-driving features, the transition to full automation is not going to happen overnight.

tHE QuEst FoR FullY autonomous VEHiClEs Before autonomous vehicles take to our roads, engineers and researchers are using simulation to improve their performance in all situations. by Frédéric Parisot

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t

he 2015 ITS world congress in Bordeaux included a demonstration of half-a-dozen cars in autonomous mode. Car manufacturers, auto parts companies, and engineers, they all came to show off their wares. However, the race towards autonomous vehicles is not over yet. There remain many challenges – especially in simulation – since autonomous vehicles are not ready for the average driver. “Although automation technology exists, we need to make it cheaper and ensure it works in every situation,” says Marc Charlet, general manager of Mov’eo competitiveness cluster. Most features of autonomous vehicles are now available as advanced driver assistance systems. They are included in all current executive models; from emergency braking and adaptive cruise control to traffic jam assistants. But according to the SAE international standard J3016 on automated driving, these are level 3 automation features. Although vehicles can self-drive in some situations, drivers must be ready to take control again at any moment. Level 4 automation, where the vehicle can cope with any situation even if the driver does not retake control of the steering wheel, has yet to be achieved. Simulation engineers and researchers have a major role to

D.R. ; InRIa / J. Wallace

dEsiGN oFFicE

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play in reaching this goal. “We’re working on three aspects to produce decision-making autonomous vehicles: knowledge of the surrounding environment, understanding situations, and calculating safe trajectories conforming to various comfort and fuel-economy criteria,” says Frédéric Mathis, director of the Vehicles program at the VEDECOM Institute. To find their way around, autonomous vehicles have sensors and image-recognition algorithms that identify road markings, traffic lights, and road signs. But that is not enough; autonomous vehicles need to communicate with other road users and with the road infrastructure to anticipate as many situations as possible. Although communication standards exist, they remain to be applied. “We’re developing simulation platforms for inter-vehicle communication,” confirms Bruno Grandjean, program director at Véhicule du Futur competitiveness cluster. “The idea is to put real vehicles into a virtual environment, which can be controlled and hence replicated. We then test communication between various makes of car model and simulate ramp-up, when thousands of vehicles are communicating with one another simultaneously.” Once vehicles can find their way around, they must be able to identify high-risk situations. “There are some real challenges for perception systems since vehicles encounter all sorts of objects on roads. To avoid overreacting, autonomous vehicles must distinguish between genuine obstacles and those presenting no danger. We’re using sensor fusion to tackle these issues,” says Vincent Abadie, head of innovation for advanced driver assistance systems at PSA Peugeot Citroën. According to Sébastien Glaser, team leader of the Autonomous Vehicle project at the VEDECOM Institute, sensor fusion has become the key to success in recent years: “Accidents are caused by a combination of various factors, for example, when roads are wet and drivers have the sun in their eyes. We need to develop databases of sensor signals from all these situations and then use them in our simulation models. This will enable us to check that at least one sensor can detect obstacles in poor driving conditions.”

Making the right decisions

Once vehicles know their surrounding environment and have identified situations, they must be able to make the right decisions. “To work out the rules for this, we’re developing decision tree-based expert systems,” explains Fawzi Nashashibi, research director at the French National Institute for Research in Computer Science and Automation (INRIA). “We’ve integrated advanced mathematical techniques such as fuzzy logic since cars have to ask themselves many questions to make apparently simple decisions (whether to accelerate, brake, overtake, etc.). For example, they need to know whether they are complying with the Highway Code, whether their fuel consumption is reasonable, and whether it will be comfortable for passengers when they brake. All this requires constant real-time optimization of criteria.” Technology for constant optimization is very IT-intensive. “We’ve opted for staged simulation,” explains Glaser. “First, we simulate features in an ideal environment. Then we introduce error using another simulator. Finally, we use a l’usiNE NouvEllE I n° 3464 SuPPleMenT I aPRIl 14 2016

star French companies behind the Wheel

ever since setting up the national Institute for Transport and Safety Research (InReTS) in 1985, France has been a leading supplier of autonomous-vehicle technology. The French national Institute for Research in computer Science and automation (InRIa) in particular supplies many car manufacturers and auto parts companies. France has a network of recognized SMes in this sector. French simulation expertise includes

Voxelia – specializing in road traffic engineering – and cIVITec, whose multicriteria simulation platform Pro-SiVIc is used to validate autonomousvehicle features. France also has algorithm champions: nexyad, a signal processing specialist supplying road- and obstacledetection modules; Datasio, which has developed big databased analytics tools; and Innov+, for driver vigilance monitoring devices. ❚❚

third simulator to compare the results with the trajectory chosen by a human being in a similar situation.” For Dominique Gruyer, director of the Vehicle Infrastructure Driver Interactions (VIVIC) laboratory at the French Institute of Science and Technology for Transport, Development and Networks (IFSTTAR), the main difficulty lies in the diversity of phenomena to be represented: “Simulating each scenario involves modeling road features, other road users, obstacles, the surrounding environment, as well as the driver’s concentration level and direction of sight. Different simulation motors are used for each scenario.” Car manufacturers still have work to do if they want to bring out their first level 4 autonomous vehicles by 2018. ❚❚ 43

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iNNovaTioN

networks of ConneCted objeCts, it’s a Challenge Vast emerging networks of connected objects and sensors will force this sector to use simulation, says Wind River’s Michel Genard. by SylvaiN aRNulf

f

or the time being, all is well on the Internet of Things. Deployment of networks for sensors and connected objects is still largely at the small-scale experimental stage. But projects involving the Internet of Things (IoT) in smart cities, business and industry 4.0 –which are integrating sensors into logistics, road and airport infrastructures, etc.– are expected to pick up pace. As a result, there will be hundreds of millions of connected objects and widespread network interconnections, giving rise to increasingly complex systems of systems. We will have to oversee the deployment of connected objects themselves, as well as their software configuration, links to gateways and hubs, and communication with cloud-based exchanges. This is a real challenge. “The hardest thing is not independently connecting millions or even billions of objects, but rather creating millions of systems that will themselves depend on millions of systems,” warns Michel Genard, a French expat in California who is vice-president of the simulation tools & lifecycle solutions department at Wind River, an American embedded software company (a division of Intel). For the IoT to create value, even smarter, and hence complex, networks will have to be devised. “We’re talking about systems that can detect breakdowns, issue alerts and reconfigure themselves completely autonomously on a large scale involving thousands of objects and sensors,” sums up Genard.

D.R.

very early simulation

Using simulation at the very early stages of projects would be the best way to create these high-performance systems. Simulation would help design, configure, and size systems, as well as simulate how they operate during use to ensure they are ready as soon as they are deployed. Virtual simulation of every component in physical systems is already possible. Each object – with its software, memory, processor, battery, radio chip, etc. – is reconstructed virtually. The network environment is also recreated to take real operating conditions into account. It is thus possible to design a network’s architecture and then carry out a battery of tests to see how each component reacts. The more simulators anticipate, the 44

Simulation tools for networks of connected objects are ready, but underutilized. “We’re still spreading the word about them,” says Wind River’s Michel Genard. Nevertheless, some pioneers have started using these tools. “We’re working with a Japanese company that designed a smart

meter with a European industrialist. They simulated 1,000 meters on a system to see early on how it was going to react. Simulation was used to assess the impact of radio-signal power, weather, environment, building position, etc. on the system’s configuration.”

more protection there is from breakdowns and bugs. But it is impossible to anticipate everything. Simulation tools are therefore mobilized throughout a network’s lifecycle. “IoT systems are by definition never finished,” underlines Genard. “Applications are regularly updated by cloud services.”

Replicating breakdowns to understand them

Simulation is also very useful in the event of breakdowns. “Simulators can replicate breakdowns; they’re a bit like the film ‘Avatar’ – the real and virtual worlds coexist in them. As a result of simulation’s infinite computing power, we have control over time; we can pause, rewind or fast forward,” says Genard. “It takes just 1 second to do what would normally take 100 or 1,000.” This works when pinpointing incidents in real life or when predicting them. Simulation is an essential investment, especially compared with the cost of potential massive breakdowns. “Time control is priceless. We need to reason in terms of the cost of system failure and its impact on business rather than focusing on development costs,” says Genard decisively. This factor is even more important for sensor networks linked to critical businesses such as water and energy, for which security issues are paramount. ❚❚

Simulation-driven Innovation™

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simulation

aeronautics

solaR imPulsE 100% CalCulatED

Consulting and engineering firm Altran used an unconventional approach to design a solar-powered airplane. Soon they will use the same method to draw up flight plans. by Jean-François Prevéraud

s

olar Impulse is a pure product of simulation. Altran had to go back to the drawing board to design a solarpowered airplane capable not only of circumnavigating the globe but also of predicting every flight situation and establishing the best routes. “To pull off a project like this, you have to constantly push the limits without going too far. Simulation helped us to achieve this,” says Christian Le Liepvre, who is in charge of the Solar Impulse project at the Altran Foundation for Innovation. So how did engineers simulate a project like this one, without any experience to draw on? “We were well beyond the realm of conventional simulation, which adjusts virtual reality to the real world. That’s why we used unconventional exploratory simulation,” explains Christophe Béesau, an advanced simulation expert at Altran.

an airplane behavioral Model

Conventional simulation represents physics as explained by the general theory of systems. But innovation moves beyond existing engineering knowledge. And the further away you move, the more the experts disagree on how to achieve desired outcomes. Before anything is settled, simulation is therefore used to optimize design processes. This ensures the best possible solutions to problems, using currently or shortly available technology. “Since the end of the 1990s, we’ve been developing mathematical methods and tools to analyze complexity. Our goal is to establish the most direct routes for problem-solving and find ways to build exploratory simulation models,” continues Béesau. Exploratory simulation gives mathematical rather than physical (by definition

AltrAn

“unconventional simulation is a wonderful opportunity to change how we think about problems.” Christophe Béesau, an advanced simulation expert at Altran

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solar impulse’s flight trajectory calculated using altran’s simulation model.

unknown) representations of systems. It enables IT experts to create unconventional simulation models containing enough physical representation to guide engineers. Using 25,000 parameters, this approach helped make design decisions for the Solar Impulse in eighteen months rather than the five years needed for conventional simulation backed up by physical tests. “This method enabled us to recommend a four- rather than two-engine approach,” recounts Béesau. “We also built an airplane behavioral model to assess various design options, some of which – such as slenderness – are counterintuitive and completely unlike gliders’ slenderness.”

a tailor-Made supercomputer

Before constructing the airplane, unconventional simulation of virtual flights was used to validate its in-flight behavior and simulate its mission, i.e. virtually fly the airplane behavioral model on a given route in the most likely flight conditions. These conditions were established using weather forecasts from the American National Oceanic and Atmospheric Administration and were updated every six hours. The energy efficiency aspect of flight feasibility was also validated using unconventional simulation. “This year, we’ll be taking into account fifty probabilistic weather scenarios for each flight, thus increasing opportunities for takeoff,” explains Le Liepvre. To this end, Altran has developed its own supercomputer, with about ten teraflops of computing power and optimum architecture for running very large-scale unconventional simulation. “It’s a wonderful opportunity to step up the pace by changing how we think about problems,” concludes Béesau. ❚❚

European pole of competence HPC BigData Simulation

Teratec Campus

CEA Very Large Computing Center An infrastructure for high-end HPC, open to industrials partners with CCRT Centre de Calcul Recherche et technologie. 1.4 Pflop/s of secured parallel computing power, made available to large industrial companies, sharing competencies,costs and innovations through sustainable partnerships with CEA.

Industry. Large companies, SMEs and start-up companies

develop their activities at TERATEC campus, all along the high performance IT value chain – from components and system levels to software and applications.

www-hpc.cea.fr

Research. Several research teams work at TERATEC Campus to investigate new usages of HPC and harness and deploy new heavy computing and Big Data technologies.

www.teratec.eu

Contacts & Informations Teratec

jean-pascal.jegu@teratec.fr Tel. +33 (0)9 70 65 02 10 Campus Teratec 2 rue de la Piquetterie 91680 Bruyères-le-Châtel - France

Contacts & Informations CEA - TGCC - CCRT

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christine.menache@cea.fr Tel. +33 (0)1 69 26 62 56 TGCC 2 rue de la Piquetterie 91680 Bruyères-le-Châtel - France

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