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Data re-use for preliminary thermal-mechanical design of gas turbine engines

Part of: ISABE 2017

Published online by Cambridge University Press:  04 January 2018

Gan Lu ,
Feng Wang ,
Luca di Mare ,
Mike Moss  and
Gordon May
Gan Lu*
Affiliation:
Vibration UTC, Mechanical Engineering Dept., Imperial College London, London, UK
Feng Wang
Affiliation:
Vibration UTC, Mechanical Engineering Dept., Imperial College London, London, UK
Luca di Mare
Affiliation:
Vibration UTC, Mechanical Engineering Dept., Imperial College London, London, UK
Mike Moss
Affiliation:
Design Systems Engineering, Rolls-Royce plc, Derby, UK
Gordon May
Affiliation:
Design Systems Engineering, Rolls-Royce plc, Derby, UK
*
[email protected]
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Abstract

Thermal-mechanical design is a time-consuming process even at its preliminary design stage. This is due to the large number of components and boundary condition data, the complexity of the geometry, and the iterative nature of the design process. The conventional design process separates the geometric and physical models and results in considerable human interventions during the design process. By assigning the breakpoints to engine assembly features as internal parameters, this article reports a novel feature-based design approach where the associated boundary conditions are represented parametrically along the feature geometric contours. They are updated automatically as per the geometrical changes, including topological changes, and hence bridging the gap between the geometric and physical models. The current approach enables data re-use of both the geometries and physical information from previous engine designs to generate new designs, dispensing with the excessive human interventions. Although the methodology is generic and applicable to other design scenarios, its capability is demonstrated in this article by some representative challenging industrial applications, sitting in the 2D preliminary gas-turbine design domain. The test cases show that the method can significantly reduce the time-cost of the iterative thermal-mechanical design flow.

Keywords

BC data re-useAutomatic BC healingCAD-CAE integrationMulti-fidelity and multi-resolution design and analysis
Type
Research Article
Information
The Aeronautical Journal , Volume 122 , Issue 1249 , March 2018 , pp. 462 - 486
Copyright
Copyright © Royal Aeronautical Society 2018 

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Footnotes

A version of this paper was presented at the ISABE 2017 Conference, 3-8 September 2017, Manchester, UK.

References

REFERENCES

1. Robinson, T.T., Armstrong, C.G. and Fairey, R. Automated mixed dimensional modelling from 2D and 3D CAD models, Finite Elements in Analysis and Design, 2011, pp 151-165.CrossRefGoogle Scholar
2. Chong, C.S., Senthil Kumar, A. and Lee, K.H. Automatic solid decomposition and reduction for non-manifold geometric model generation, Computer-Aided Design, 2004, pp 1357-1369.CrossRefGoogle Scholar
3. Thakur, A., Gopal, B.A. and Gupta, S.K. A survey of CAD model simplification techniques for physics-based simulation applications, Computer-Aided Design, 2009, 41, (2), pp 65-80.CrossRefGoogle Scholar
4. Hun, L.S. A CAD-CAE integration approach using feature-based multi-resolution and multi-abstraction modelling techniques, Computer-Aided Design, 2005, 37, (9), pp 941-955.Google Scholar
5. Srinivas, R. and Shapiro, V. Topological framework for part families, J of Computing and Information Science in Engineering, 2002, 2, (4), pp 246-255.Google Scholar
6. Liang-Chyau, S. and Lin, J.T. Representation scheme for defining and operating form features, Computer-Aided Design, 1993, 25, (6), pp 333-347.Google Scholar
7. Gomes, A.J. and Teixeira, J.G. Form feature modelling in a hybrid CSG/BRep scheme, Computers & Graphics, 1991, 15, (2), pp 217-229.Google Scholar
8. Hoffmann, C.M. and Juan, R. Erep: an editable high-level representation for geometric design and analysis, 1992.Google Scholar
9. Shah, J.J. and Martti, M. Parametric and Feature-based CAD/CAM: Concepts, Techniques, and Applications, 1995, John Wiley & Sons, USA.Google Scholar
10. Shah, J., Mantyla, J.M. and Nau, D.S. Advances in Feature-based Manufacturing, vol. 20, Elsevier, 1994, USA.Google Scholar
11. Samareh, J.A. Geometry modeling and grid generation for design and optimization, Computational Aerosciences in the 21st Century, 2000, pp. 211-229.Google Scholar
12. Bronsvoort, W.F., Bidarra, R. and Nyirenda, P.J. Developments in feature modelling, Computer-Aided Design and Applications, 2006, 3, (5), pp 655-664.Google Scholar
13. Rafael, B. and Bronsvoort, W.F. Semantic feature modelling, Computer-Aided Design, 2000, 32, (3), pp 201-225.Google Scholar
14. Rafael, S., Eastman, C.M. and Lee, G. Parametric 3D modeling in building construction with examples from precast concrete, Automation in Construction, 2004, 13, (3), pp 291-312.Google Scholar
15. Hoffmann, C.M. and Joan-Arinyo, R. On user-defined features, Computer-Aided Design, 1998, 30, (5), pp 321-332.CrossRefGoogle Scholar
16. Rezayat, M. Midsurface abstraction from 3D solid models: General theory and applications, Computer-Aided Design, 1996, pp 905-915.Google Scholar
17. Ghang, L., Sacks, R. and Eastman, C.M. Specifying parametric building object behavior (BOB) for a building information modeling system, Automation in Construction, 2006, 15, (6), pp 758-776.Google Scholar
18. Cavieres, A., Russell, G. and Tristan, A.-H. Knowledge-based parametric tools for concrete masonry walls: Conceptual design and preliminary structural analysis, Automation in Construction, 2011, 20, (6), pp 716-728.Google Scholar
19. Roehl, P. et al A federated intelligent product environment, 8th Symposium on Multidisciplinary Analysis and Optimization, 2000, Long Beach, CA, USA.Google Scholar
20. Foucaulta, G., Cuillirea, J.-C., Franoisa, L.V.J.-C. and Maranzanac, R. Adaptation of CAD model topology for finite element analysis, Computer-Aided Design, 2008, 40, (2), pp 176-196.Google Scholar
21. Pratt, M.J., Bill, D. and Ranger, T. Towards the standardized exchange of parameterized feature-based CAD models, Computer-Aided Design, 2005, pp 1251-1265.Google Scholar
22. Kim, J. et al Standardized data exchange of CAD models with design intent, Computer-Aided Design, 2008, pp 760-777.Google Scholar
23. Sheffer, A. et al Virtual topology operators for meshing, Int J of Computational Geometry & Applications, 2000, pp 309-331.Google Scholar
24. Sheffer, A. Model simplification for meshing using face clustering, Computer-Aided Design, 2001, pp 925-934.Google Scholar
25. Nolan, D.C. et al Defining simulation intent, Computer-aided Design, 2015, pp 50-63.CrossRefGoogle Scholar
26. Tierney, C.M. et al Using virtual topology operations to generate analysis topology, Computer-Aided Design, 2017, pp 154-167.Google Scholar
27. Tierney, C.M. et al Generating analysis topology using virtual topology operators, Procedia Engineering, 2015, pp 226-238.CrossRefGoogle Scholar
28. Foucault, G. et al Generalizing the advancing front method to composite surfaces in the context of meshing constraints topology, Computer-Aided Design, 2013, pp 1408-1425.Google Scholar
29. Mare, L.D., Kulkarni, D.Y., Wang, F., Romanov, A., Ramar, P.R. and Zachariadis, Z.I. Virtual gas turbines: Geometry and conceptual description, ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition, 2011 Vancouver, Canada.Google Scholar
30. Red, E., Jensen, G., Weerakoon, P., French, D., Benzley, S. and Merkley, K. Architectural limitations in multi-user computer-aided engineering applications, Computer and Information Science, 2013, 6, (4), p 1.Google Scholar
31. Sheffer, A. et al Hexahedral mesh generation using the embedded Voronoi graph, Engineering with Computers, 1999, pp 248-262.Google Scholar
32. Kulkarni, D. PhD Thesis: Feature-based Computational Geometry and Secondary Air System Modelling for Virtual Gas Turbines, PhD thesis, 2013, Imperial College London.Google Scholar
33. Lee, K.Y., Armstrong, C.G., Price, M.A. and Lamont, J.H. A small feature suppression/unsuppression system for preparing B-rep models for analysis, Proceedings of the 2005 ACM Symposium on Solid and Physical Modelling, 2005, Boston, USA.Google Scholar
34. Gujarathi, G.P. and Ma, Y.-S. Parametric CAD/CAE integration using a common data model, J of Manufacturing Systems, 2011, 30, (3), pp 118-132.Google Scholar
35. Tierney, C., Nolan, D., Robinson, T. and Armstrong, C. Managing equivalent representations of design and analysis models, Computer-Aided Design and Applications, 2014, 11, (2), pp 193-205.Google Scholar
36. Lidong, W. The integrated CAD/CAE system based on the common standard in information exchange and the common model in geometric representation, Int J of Computational Systems Engineering, 2013, 1, (3), pp 211-216.Google Scholar
37. Wang, F. and di Mare, L. Hybrid meshing using constrained Delaunay triangulation for viscous flow simulations, Int J for Numerical Methods in Engineering, 2016, 108, pp 1667-1685. doi: 10.1002/nme.5272.Google Scholar