SHOWCASE for Engineering Graduate Student Research
Tuesday, October 16, 2012 Waterfront Place Hotel
Welcome, The WVU Office of Research and Economic Development, through support provided by the Claude Worthington Benedum Foundation, has launched an initiative to encourage innovation and commercialization through research. The initiative, titled LIINC (Linking Innovation, Industry and Commercialization), is designed to bring faculty and graduate student expertise and talent to the attention of our industry partners through networking events. This particular event focuses on engineering research. To our industry partners, we greatly appreciate your attendance at this event and we hope this opportunity has better informed you about the research taking place at WVU. To facilitate new partnerships and future collaboration, this booklet contains brief abstracts of our graduate student and faculty research activities. We strongly encourage you to contact them to further learn about and discuss their research in greater detail. On behalf of our faculty and graduate students, we thank you for your participation and we hope you will see WVU as a trusted partner for continued collaboration. Lindsay Emery Business Development Manager of LIINC WVU Office of Research & Economic Development 304-293-0391 email@example.com Name Badge Key Blue: Industry Gold: WVU 2
GRADUATE STUDENT RESEARCH High-Temperature Nano-Derived Micro-sensors for Online Monitoring of Emissions and Chemical Processes The emissions of SOx, NOx and H2S gases from coal-fired power plants, industrial processes, and transportation vehicles remain a significant concern for air quality. Assertive environmental challenges must be overcome by controlling the emissions of SOx, NOx and H2S within these applications. The objective of this proposed work is to develop micro-scale, chemical sensors and sensor arrays composed of nano-derived, metal-oxide composite materials to detect the aforementioned gases and further incorporation of sensors for other chemicals such as CO, CO 2 and CH4 within high-temperature environments (>500°C). Applications:
Implementation of sensor arrays within broad sensor nets.
Gas concentration testing for three-dimensional fuel and emission maps within various industrial processes and energy applications.
Potential real-time monitoring within engines.
Inexpensive way for gas detecting and accuracy.
In-situ application capability.
Simple operation, no need for well-trained personnel.
Student: Engin Ciftyurek firstname.lastname@example.org PI: Ed Sabolsky Ed.email@example.com
Reservoir Management of Shale Assets Importance of shale assets cannot be overemphasized. In this unique project, we apply a novel method that integrates traditional reservoir engineering analysis with pattern recognition capabilities of artificial intelligence and data mining to shale reservoirs. This new technology helps engineers to develop full field models and to forecast reservoir performance in order to accommodate field development strategies. The technique that is named Top -Down Intelligent Reservoir Modeling (TDM) is a formalized and comprehensive, full-field empirical shale model. It integrates all aspects of shale reservoir development from well configuration and reservoir characterization, to completion and stimulation. In this new approach instead of imposing our understanding of the flow mechanism, the impact of multi-stage hydraulic fractures, and the production process on the reservoir model, we allow the production history, well log, and hydraulic fracturing data to force their will on our model and to determine its behavior. The uniqueness of this technique is that it incorporates the so-called “hard data” directly into the reservoir model, such that the model can be used to optimize the hydraulic fracture process. The “hard data” refers to field measurements during the hydraulic fracturing process such as fluid and proppant type and amount, injection pressure and rate as well as proppant concentration. Applications:
The technique can be applied in any type of reservoirs with wide-ranging reservoir properties, different well patterns and variety of well numbers.
By using Top-Down Intelligent Reservoir model, petroleum engineers would be able to predict reservoir performance and perform practical reservoir management.
The advantage of this approach is its flexibility in data requirement. In-
stead of imposing our vague knowledge of flow and transport mechanism in shale, we let the data identify its functional relationship using pattern recognition techniques in a non-linear and complex system. Student: Soodabeh Esmaili firstname.lastname@example.org PI: Shahab Mohaghegh Shahab.email@example.com
Wireless Network Performance Analysis using Parallel Computing The disclosed work develops a hardware and software infrastructure for high-performance simulation of wireless communication networks. The software is an open-source library based on MATLAB having ease-of-use and accessibility as primary design goals. The hardware utilized by the library is a high-performance parallel computing cluster containing over 400 processing cores enabling researchers to perform simulation much faster than is possible using a single desktop PC containing only a handful of cores. Users interact with the software using concise MATLAB and web-based interfaces. The goal of wireless communication research is to improve the energy, spectral, and throughput performance of wireless networks, such as cellular phone, Wi-Fi/802.11, and HDTV satellite networks. Improvements provide benefits such as longer phone battery life and faster download speeds. Investigating the performance of wireless networks using a combination of mathematical analysis and simulation is often much more cost effective than building hardware prototypes. As an example of performance benefit, the energy efficiency of a novel two-way relaying technique utilizing technologies found in the UMTS cellular standard was simulated, varying parameters such as modulation order and channel code rate. The simulation regime was run using both a single desktop PC and the developed infrastructure. Using a single PC, the regime required several weeks to execute, while requiring less than a day using the infrastructure. The long-term goal of the project is to extend available processing power using a volunteer computing model in which users freely obtain the
software and donate their own computing cores to the pool of available cores. Users receive credit for donated computing time, while paying for desired access beyond the credit obtained through donation. Applications:
Performance analysis and improvement of wireless communication network through simulation.
Support for simulating technology in common wireless standards, such as LTE, UMTS, cdma2000, and WiMAX
Explicit support for parallel computing, reducing time required for simulation.
Software freely available under an open-source license.
Student: Terry Ferrett firstname.lastname@example.org PI: Matthew Valenti Matthew.email@example.com
Numerical and Experimental Study on the Ability of Dynamic Roughness to Alter the Development of a Leading Edge Vortex Dynamic stall is an unsteady aerodynamic phenomenon which occurs when an aerodynamic lifting device, such as an airfoil or wing, undergoes a rapid pitching motion or is impulsively started at a high angle of attack. A large leading edge vortex is formed during the maneuver which increases fluid acceleration over the lifting body, thus sustaining lift to angles of attack significantly beyond the static stall angle of attack. As this vortex is shed downstream there is an abrupt and drastic increase in drag, large shift in pitching moment, and loss of lift. The disclosed technology uses what is termed Dynamic Roughness to delay the formation of the leading edge vortex during a rapid pitching maneuver. The elimination of the leading edge vortex while also delaying flow separation will lead to sustained lift without the drag penalty.
UAVs (Unmanned Aerial Vehicles)
Helicopter rotor blades
Aircraft that mimic biological flyers
Student: Chris Griffin firstname.lastname@example.org PI: Wade Huebsch Wade.email@example.com
Monte Carlo-based Spray Cooling Model for Accurate Heat Flux Predictions Spray cooling with phase change shows promise to achieve the highest rates of heat transfer from microelectronic components and other high energy density devices. The extreme complexity of the flow created by the impact of millions of droplets per second per cm2 creates a need for a heat transfer design model which incorporates enough physical detail to yield accurate predictions while being sufficiently simplified to allow its use in routine design computations. The disclosed model will be able to accurately predict the heat flux as a function of spray flowrate and temperature and the heated surface temperature, as well as predict the dryout of the heater surface at the onset of the critical heat flux, in a reasonable computational time. The disclosed technology incorporates empirical correlations developed from experiments and CFD simulations that approximate the spray cooling physics occurring on a heated impingement surface. The disclosed model when used will provide a cost effective tool that will be able to provide accurate baseline specs for a spray cooling system. This would reduce the number of experiments and simulations needed when designing a spray cooling system.
Small high density electronics
Future space-based power systems
Lidar instruments, and laser diode arrays for earth satellites and defense -related space systems
Research institutions designing spray cooling based experiments
Accurately predict the heat flux of a spray cooling apparatus in a reasonable time frame
Allows for a preliminary performance specs of a spray cooling system before committing to a design
Lessens the need for experiments and CFD simulations to design a system
Predict the dry out time of a spray droplet impact crater which can lead to device failure
Student: Nicholas Hillen firstname.lastname@example.org PI: John Kuhlman John.email@example.com
Plant-wide Control System Design An optimally designed control system is important for any plant which frequently operates under off-design conditions. Since plants have not been designed to operate optimally under these conditions, loss of efficiency is inevitable. The control system needs to be designed so that operations are kept at near optimal conditions even under off-design operations. This means the control system must provide good servo control, disturbance rejection, and economic performance. For the design of such a control system
one must determine what variables should be controlled within the plant, how would they be controlled, what their set-points should be, and what should be the structure of the control system. This disclosed method is a systematic approach to optimal control system design which can be applied to large-scale commercial systems with many unit operations and a high degree of process nonlinearity and significant interaction. The method identifies controlled variables which will maximize controllability and economic performance, and then identify the optimal control structure for controlling the identified controlled variables. Applications: ď‚ˇ
For the design of control systems of processes which operate frequently at off-design conditions
Method can be applied to grass-roots plants or retrofitting of existing control systems
Improved economic and environmental operation of processes
Student: Dustin Jones firstname.lastname@example.org PI: Debangsu Bhattacharyya Debangsu.email@example.com
Face Recognition in the MWIR Band using Face-based Features The ability to recognize an individual in both day and night time environments is a challenging issue in biometrics. The middle-wave infrared (MWIR) band can be utilized to capture thermo-grams of individuals. The disclosed methodology extracts and utilizes unique characteristics on the facial thermo-grams to identify individuals with high confidence, regardless of the environment and lighting conditions. Before the disclosed algorithm is executed, diffusion and segmentation are applied to the MWIR images to extract features. These features con-
sist of subcutaneous information (veins), edges of facial features, and wrinkles. Feature minutiae points are then extracted, filtered and matched, using thinning, binarization, and an maximum allowable distance between points. The results yield a perfect (100%) rank-1 recognition rate for a set of 50 subjects. Applications:
Military and law enforcement.
Degenerated faces and individuals wearing disguises.
Thermo grams can be acquired in day or nighttime environments.
MWIR imaging passive, allowing obscure and unobtrusive acquisition of subjects.
MWIR sensor is high definition.
No testing or training needed, disclosed algorithm utilizes direct matching.
Difficult to counterfeit without system failure.
Student: Nnamdi Osia firstname.lastname@example.org PI: Thirimachos Bourlai Thirimachos.email@example.com
Precision Petrophysical Analysis Laboratory (PPAL) Marcellus Shale is an expansive Devonian shale play in the Appalachian Basin which has emerged as the major target of the exploration and development in recent years. The shale gas resources are significant but there are substantial challenges to transform these resources to reserves. Key among them is the lack of complete understanding of these complex reservoirs. Accurate measurements of the porosity and permeability of Marcellus Shale from core samples as well as their integration with other measure-
ments can provide a basis to better understand and characterize the shale. A state-of-art experimental set-up (PPAL) has been designed and assembled to measure the effective porosity and permeability of the shale as a function of confining stress. PPAL can make precise measurements under steady state conditions which more accurately reflect the natural gas flow through the shale. Applications:
The permeability and porosity of the ultra-low shale samples can be accurately measured.
The impact of net stress on permeability and porosity can be investigated.
The accurate assessment of Marcellus Shale will significantly contribute to efficient development and availability of domestic gas reserves.
Student: Mehrdad Zamirian firstname.lastname@example.org PI: Khashayar Aminian email@example.com
“Excel in research, creative activity, and innovation in all disciplines.” —Goal 2, WVU 2020 Strategic Plan for the Future
Hosted by Linking Innovation, Industry and Commercialization (LIINC)
For more information on LIINC, please visit the website at: http://innovation.research.wvu.edu or contact Lindsay Emery directly at firstname.lastname@example.org 304-293-0391 Made possible from the support of the Claude Worthington Benedum Foundation