Proper Generalized Decomposition based dynamic data-driven control of thermal processes

Computer Methods in Applied Mechanics and Engineering

Volumn 213-216, Issue , 2012, Pages 29-41

  Ghnatios, Ch ^a   Masson, F ^a   Huerta, A ^b   Leygue, A ^a   Cueto, E ^c   Chinesta, F ^a  

^a AIRBUS GROUP INNOVATIONS   (Germany)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^c UNIVERSITY OF ZARAGOZA   (Spain)

Author keywords

Control; Dynamic Data Driven Application Systems; Parametric models; Proper Generalized Decomposition; Real time; Thermal processes

Indexed keywords

APPLIED SCIENCE; CURSE OF DIMENSIONALITY; DATA-DRIVEN APPLICATIONS; DATA-DRIVEN CONTROL; ENGINEERING SCIENCE; MEASUREMENT DEVICE; MULTI-DIMENSIONAL SPACE; NEW DIMENSIONS; PARAMETRIC MODELS; PARAMETRIC SPACES; POST PROCESSING; REAL ENGINEERING; REAL TIME; SIMULATION TECHNIQUE; SIMULATION TOOL; SIMULATION-BASED; SYSTEM RECONFIGURATION; THERMAL PROCESS;

CONTROL; REAL TIME CONTROL;

PROCESS CONTROL;

EID: 84855784902     PISSN: 00457825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cma.2011.11.018     Document Type: Article

References (37)

1. Ammar A., Mokdad B., Chinesta F., Keunings R. A new family of solvers for some classes of multidimensional partial differential equations encountered in kinetic theory modeling of complex fluids. J. Non-Newtonian Fluid Mech. 2006, 139:153-176.
2. Ammar A., Mokdad B., Chinesta F., Keunings R. A new family of solvers for some classes of multidimensional partial differential equations encountered in kinetic theory modeling of complex fluids. Part II: Transient simulation using space-time separated representations. J. Non-Newtonian Fluid Mech. 2007, 144:98-121.
3. Ammar A., Normandin M., Daim F., Gonzalez D., Cueto E., Chinesta F. Non-incremental strategies based on separated representations: applications in computational rheology. Communications in Mathematical Sciences 2010, 8/3:671-695.
4. Ammar A., Chinesta F., Diez P., Huerta A. An error estimator for separated representations of highly multidimensional models. Comput. Methods Appl. Mech. Engrg. 2010, 199:1872-1880.
5. Ammar A., Normandin M., Chinesta F. Solving parametric complex fluids models in rheometric flows. J. Non-Newtonian Fluid Mech. 2010, 165(23-24):1588-1601.
6. Boucard P.-A., Ladeveze P. Une application de la méthode LATIN au calcul multirésolution de structures non linéaires. Rev. Eur. Eléments Finis. 1999, 8:903-920. (In french).
7. Boucard P.-A., Buytet S., Guidault P.-A. A multiscale strategy for structural optimization. Int. J. Numer. Methods Engrg. 2009, 78(1):101-126.
8. Ammar A., Chinesta F., Diez P., Huerta A. An error estimator for separated representations of highly multidimensional models. Comput. Methods Appl. Mech. Engrg. 2010, 199(25-28):1872-1880.. ISSN 0045-7825. 10.1016/j.cma.2010.02.01.
9. Chinesta F., Ammar A., Joyot P. The nanometric and micrometric scales of the structure and mechanics of materials revisited: an introduction to the challenges of fully deterministic numerical descriptions. Int. J. Multiscale Comput. Engrg. 2008, 6/3:91-213.
10. Chinesta F., Ammar A., Cueto E. Recent advances in the use of the proper generalized decomposition for solving multidimensional models. Arch. Comput. Methods Engrg. 2010, 17(4):327-350.
11. Chinesta F., Ammar A., Cueto E. Proper generalized decomposition of multiscale models. Int. J. Numer. Methods Engrg 2010, 83(8-9):1114-1132.
12. Chinesta F., Ammar A., Cueto E. On the use of proper generalized decompositions for solving the multidimensional chemical master equation. Eur. J. Comput. Mech. 2010, 19:53-64.
13. F. Chinesta, P. Ladeveze, E. Cueto. A short review on model order reduction based on proper generalized decomposition, Arch. Comput. Methods Engrg., (in press). doi:10.1007/s11831-011-9064-7.
14. F. Darema, Engineering/scientific and commercial applications: differences, similarities, and future evolution, in: Proceedings of the Second Hellenic European Conference on Mathematics and Informatics, HERMIS, vol. 1, 1994, pp. 367-374.
15. Dennis J.E., Schnabel R.B. Numerical methods for unconstrained optimization and nonlinear equations. Classics in Applied Mathematics, 16, Corrected reprint of the 1983 original 1996, Society for Industrial and Applied Mathematics (SIAM), PA.
16. Michopoulos John, Tsompanopoulou Panagiota, Houstis Elias N., Farhat Charbel, Lesoinne Michel., Rice John R., Joshi Anupam On a data-driven environment for multiphysics applications. Future Generat. Comput. Syst. 2005, 21(6):953-968.
17. Farhat C., Michopoulos J.G., Chang F.K., Guibas L.J., Lew A.J. Towards a dynamic data driven system for structural and material health monitoring. Lecture Notes in Computer Science 2006, vol. 3993:456-464. Springer-Verlag. V.N. Alexandrov, G.D. Alexandrov, P.M.A. van Albada, J. Sloot, J. Dongarra (Eds.).
18. Amsallem D., Cortial J., Farhat C. Toward real-time CFD-based aeroelastic computations using a database of reduced-order information. AIAA J. 2010, 48:2029-2037.
19. Gonzalez D., Ammar A., Chinesta F., Cueto E. Recent advances in the use of separated representations. Int. J. Numer. Methods Engrg. 2010, 81(5):637-659.
20. Heyberger C., Boucard P.-A., Neron D. Multiparametric analysis within the proper generalized decomposition framework. Comput. Mech. 2011, 10.1007/s00466-011-0646-x.
21. Vipul Hingne, Anupam Joshi, Elias Houstis, John Michopoulos, On the Grid and Sensor Networks, IEEE/ACM International Workshop on Grid Computing, p. 166, Fourth International Workshop on Grid Computing, 2003.
22. Ladeveze P. Nonlinear Computational Structural Mechanics 1999, Springer, NY.
23. Ladeveze P., Passieux J.-C., Neron D. The LATIN multiscale computational method and the proper generalized decomposition. Comput. Methods Appl. Mech. Engrg. 2010, 199(21-22):1287-1296.
24. Laughlin R.B., Pines David. The theory of everything. Proc. Natl. Acad. Sci. 2000, 97(1):28-31.
25. Lamari H., Ammar A., Cartraud P., Legrain G., Jacquemin F., Chinesta F. Routes for efficient computational homogenization of non-linear materials using the proper generalized decomposition. Arch. Comput. Methods Engrg. 2010, 17(4):373-391.
26. C. Le Bris, T. Lelièvre, Y. Maday, Results and questions on a nonlinear approximation approach for solving high-dimensional partial differential equations, Construct. Approx., doi:10.1007/s00365-009-9071-1.
27. Leonenko G.M., Phillips T.N. On the solution of the Fokker-Planck equation using a high-order reduced basis approximation. Comput. Methods Appl. Mech. Engrg. 2009, 199(1-4):58-168.
28. John G. Michopoulos, Panayota Tsompanopoulou, Elias N. Houstis, Anupam Joshi, Sasikanth Avancha, Haiping Zhang,Towards agent-based grid-enabled and sensor-driven fire dynamics simulation harnessed over bluetooth and Wi-Fi devices, in: ASME Conference Proceedings 2005, vol. 111, 2005. doi:10.1115/detc2005-84770.
29. John Michopoulos, Panagiota Tsompanopoulou, Elias N. Houstis, Anupam Joshi, Agent-based simulation of data-driven fire propagation dynamics, in: International Conference on Computational Science, 2004, pp. 732-739.
30. Nouy A., Ladeveze P. Multiscale computational strategy with time and space homogenization: a radial-type approximation technique for solving microproblems. Int. J. Multiscale Comput. Engrg. 2004, 170(2).
31. Nouy A. Recent developments in spectral stochastic methods for the solution of stochastic partial differential equations. Arch. Comput. Methods Engrg. 2009, 16(3):251-285.
32. Nouy A. Proper generalized decompositions and separated representations for the numerical solution of high-dimensional stochastic problems. Arch. Comput. Methods Engrg. 2010, 17(4):403-434.
33. J.T. Oden, T. Belytschko, J. Fish, T.J.R. Hughes, C. Johnson, D. Keyes, A. Laub, L. Petzold, D. Srolovitz, S.Yip, Simulation-based engineering science: revolutionizing engineering science through simulation, NSF Blue Ribbon Panel on SBES, 2006.
34. Eftang J.L., Knezevic D.J., Patera A.T. An hp certified reduced basis method for parametrized parabolic partial differential equations. Math. Comput. Model. Dynam. Syst. 2011, 17(4):395-422.
35. Pruliere E., Chinesta F., Ammar A. On the deterministic solution of parametric models by using the proper generalized decomposition. Math. Comput. Simulat. 2010, 81(4):791-810.
36. DDDAS Workshop 2000 Final Report, Arlington, VA, USA, Technical report, National Science Foundation, 2000.
37. DDDAS Workshop 2006 Final Report, Arlington, VA, USA, Technical report, National Science Foundation, 2006.