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Newsletter EnginSoft Year 7 n属3 -


Aerodynamic and Acoustic Optimization of Radial Fans In this work the multiple objective optimization of radial fans with respect to aerodynamic efficiency and noise generation has been performed. This has been achieved by coupling together an LSTM In-house Excel-VBA Impeller Design Tool (EVIDenT), the CAD program ProEngineer, the grid generator ANSYS ICEM and the CFD solver ANSYS CFX, as well as the LSTM In-house Acoustic Code SPySI (Sound Prediction by Surface Integration) within the optimization software modeFRONTIER速. From a technical point of view, the coupling of the different tools was one of the main challenges solved with modeFRONTIER速. The input variables for the optimization were the shape parameter, i.e. the wrap angle of the impeller and its number of blades. All simulations have been performed in a 2D scenario in order to capture primary fundamental aspects relevant to the impeller design. As a result of the optimization, the efficiency of the radial fans has been improved as well as the noise level reduced substantially. A set of non-dominated solutions (Pareto solutions) have been obtained which can be used according to the specific user requirements. The results show that the integration of acoustics and transient flow simulations within a multiple objective fully automated optimization process is feasible. Having established the fully integrated and automated process an extension also to 3D computations can be readily performed.

Fig. 1 - In-house Excel-VBA Impeller Design Tool (EVIDenT)

exported to the grid generator ANSYS ICEM where another script generates also automatically the grids, Figure 2. The grid is exported to CFX, the flow domain is automatically set up, Figure 4, and the solver starts to run to compute the CFD solution. The results of the CFD simulation before and after the optimization are shown in the stream line plots of Figure 3. One can clearly see that in the optimized design the flow velocities in the impeller where reduced keeping, however, the same pressure and flow rate, as well as reducing

Introduction The aim of this work is to analyze the possibility of optimization with modeFRONTIER速 [1] by integration of In-house and commercial tools in order to automate turbomachinery design with respect to efficiency and noise generation. The starting step in the optimization process is the design of impellers with the In-house ExcelVBA Impeller Design Tool (EVIDenT), which delivers high performance starting blade shapes Fig. 3 - Radial impeller for the fully integrated optimization process. The Fig. 2 - Wrap angle main optimization parameters in this work were the wrap angle, Figure 1, and the number of blades. Many other parameters can be included, e.g. the blade inlet and outlet angles, shroud shape, but the scope of this work was to establish the optimization work flow. Even so, with those two parameters already very good results were achieved. These geometries are then exported into the CAD program ProEngineer where the impeller, e.g. Figure 1, and the corresponding flow domains are generated. These geometries are then fully automatically Fig. 4 - Grid and fluid domain solver setup in ANSYS CFX Pre.


- Newsletter EnginSoft Year 7 n°3

modeFRONTIER® offers all features needed in order to integrate the automation processes of the different programs and to perform powerful optimizations.

Fig. 5 - CFD analysis of non optimized (left) and optimized impeller (right)

Fig. 6 - Sound pressure level of non optimized (left) and optimized (right) impeller

Multi-objective optimization In this case, as there were 2 objectives, a multiobjective algorithm had to be chosen. Therefore the MOGA II algorithm was selected with 5 generations and combined with a DOE Sobol of 8 designs. The work flow in modeFRONTIER® is shown in Figure 8. Here the different tools and scripts used are integrated [6] using the modeFRONTIER® workflow connectors. The input variable nodes are used for the optimization inputs (e.g. number of blades and shape parameter). These are then connected to the first node (1), the In-house Excel-VBA Impeller Design Tool (EVIDenT) through the scheduler (8), shown in Figure 8. This design tool EVIDenT generates the information about the number of blades and the data for the shape of the blades and writes them out as text files. These files are then passed to the python node (2), which passes the variables in the script to the CAD program ProEngineer (3). ProEngineer then creates the flow domain for the blades as a parasolid file, which is then transferred to the ICEM node (4). To this node (4) also the ICEM script and the parasolid files for the other parts of the geometry are transferred. Here in node (4) then the mesh is created and transferred as a CFX5 file to the CFX node (5). In this node (5) some additional CFX5 files and scripts for pre and post processing arrive also from the transfer and support file nodes. Node (5) runs then simulation, calculates the efficiency and writes out the result as a text file. From the CFX node (5) CSV (Comma separated Value) files are transferred to the next tool in node (5), which consist of the acoustic In-house tool SPySI. It runs the SPySI tool and writes out the results, i.e. the sound pressure level, as text file. These files are then transferred to the output nodes (6), which are then finally transferred to design

Fig. 7 - Prototypes

substantially the sound pressure level. In Figure 4 three prototypes are shown. The modeFRONTIER® optimization environment As described above, the work flow was carried out by integrating and automating with scripts a set of commercial (ProEngineer [2], ANSYS ICEM [3] and ANSYS CFX [4]) and In-house tools (Python based acoustic tool SPySI [5] and Inhouse Microsoft Excel-VBA Impeller Design Tool EVIDenT [6]). But how to integrate all these commercial and In-house tools in order to perform a multi-objective optimization? The answer was to use modeFRONTIER®. The multiobjective optimization environment tool

Fig. 8 - Work flow of the optimization process

Newsletter EnginSoft Year 7 n°3 -


[5] Scheit, C., Karic, B., Delgado, A., Epple, P. and Becker, S. (2009) Experimental and Computational Study of Radial Impellers With Respect to Efficiency and Noise Production. Conference on Modeling Fluid Flow (CMFF’09) The 14th International Conference on Fluid Flow Technologies Budapest, Hungary, September 9-12. [6] Masood, Rao M. A. (2010) Principle Study of Optimization of Radial Fans with respect to Aerodynamics and Aeroacoustics, Master Thesis, LSTM, University of Erlangen-Nürnberg.

Fig. 9 - The Pareto Front

objective nodes (7). These nodes make sure that efficiency is maximized and the noise level is minimized. Based on this information, the scheduler node (8) analyzes and generates a new design. Results obtained with modeFRONTIER® In this work a total of 96 possible designs were run, out of which 35 designs were evaluated. From those the final three optimized designs were selected and compared with the three original starting designs. A set of non-dominated solutions, as shown in Figure 9, have been found which showed substantial improvements in the efficiency and reduction in the noise level. In the case of a multi-objective optimization, there is no single best design but rather a set of non-dominated designs. The best design with respect to efficiency has an increase of 35%, while the best design with respect to noise level has a reduction of 3 dB as compared to the original design, which means a reduction of 50% in the sound power level Conclusions This work has shown, Figure 8, how it is possible to integrate and automate different codes, i.e. the In-house Excel EVIDenT code, ProEngineer, ANSYS ICEM, ANSYS CFX and the In-house Acoustic tool SPySI in modeFRONTIER® and finally how to establish and carry out an multi-objective optimization in this environment The efficiency of radial fans has been improved as well as the noise level reduced noticeably. A set of non-dominated solutions (Pareto solutions) have been obtained which can be used according to the user needs. References [1] modeFRONTIER®: [2] Pro/Engineer Wildfire: [3] ANSYS ICEM CFD: [4] ANSYS CFX:

Institute of Fluid Mechanics - Technical Faculty Friedrich-Alexander - University Erlangen-Nürnberg MSc. Engr. Rao Muhammad Atif Masood M.Sc Christoph Scheit Dr.-Ing. Philipp Epple Prof. Dr. A. Delgado - Professor and Head

The Institute of Fluid Mechanics (Lehrstuhl für Strömungsmechanik - LSTM) of the Friedrich-AlexanderUniversität Erlangen-Nürnberg has 8 departments working on a large variety of research topics: Aerodynamics, Turbulence, Aeroacoustics, chemical reacting flows, fluid flow process automatization, bio and medical technology, numerical flow simulation, process fluid dynamics and Turbomachinery, instationary fluid mechanics, Engineering of Advanced Materials and thermo-fluid-dynamics of bio technological processes. There are about 70 researchers working at the LSTM. The LSTM has many years of experience in the design, numerical computation and aerodynamic and acoustic optimization of turbomachines of all kinds – axial, diagonal and radial. The aerodynamic design and acoustic computation are done with Inhouse-codes as well as with commercial tools.

Der Lehrstuhl für Strömungsmechanik (LSTM) der FriedrichAlexander-Universität Erlangen-Nürnberg setzt sich aus 8 Forschungsbereichen mit einer sehr breit angelegten thematischen Ausrichtung zusammen: Aerodynamik, Turbulenz und Aeroakustik, Strömungen mit chemischen Reaktionen, Prozessautomatisierung von Strömungen in Bio- und Medizintechnik, Numerische Strömungsmechanik, Prozessfluiddynamik und Strömungsmaschinen, Instationäre Strömungsmechanik, Engineering of Advanced Materials und Thermofluiddynamik biotechnischer Prozesse. Insgesamt arbeiten und forschen hier ca. 70 Mitarbeiter und Mitarbeiterinnen. Der LSTM besitzt langjährige Erfahrung in der Auslegung, numerischen Berechnung und strömungsmechanischen und akustische Optimierung von Turbomaschinen aller Bauformen (radial, diagonal und axial). Die strömungsmechanische Auslegung und akustische Berechnung erfolgen sowohl mit Inhouse-Codes wie auch über kommerziellen Tools.

Aerodynamic and Acoustic Optimization of Radial Fans