David Amsallem

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David Amsallem, Ph.D.
Department of Aeronautics & Astronautics
Stanford University

Lab: Farhat Research Group

Google Scholar: Personal Profile

ResearchGate: Profile

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(a) Nonlinear model reduction of the flow around the CRM

(b) Fast aeroelastic predictions for the F-16

(c) Real-time flutter predictions on an iPhone

(d) Simulation of the effect of blast on a vehicle

(e) Propagation of signals in neurons

(f) Inverse solution of acoustic scattering around a submarine

Research Interests

I am interested in developing fast computational methods for the prediction of the behavior of physical systems. These predictions can be used for analysis, design optimization, uncertainty quantification and control. I have focused recently on the simulation of fluid-structure interaction, turbulent flows, nonlinear structural mechanics, signal propagation in neurons and circuit simulation.

Below is a list of key topics I have focused on in the last few years:

Education

Journal Publications

  • D. Amsallem, R. Tezaur, C. Farhat. Real-Time Solution of Computational Problems Using Databases of Parametric Linear Reduced-Order Models With Arbitrary Underlying Meshes, Submitted for publication, 2015  —  arXiv submission.

  • Y. Choi, D. Amsallem, C. Farhat. Gradient-Based Constrained Optimization Using a Database of Linear Reduced-Order Models, Submitted for publication, 2015  —  arXiv submission.

  • D. Amsallem, D. Neumann, Y. Choi, C. Farhat. Linearized Aeroelastic Computations in the Frequency Domain Based on Computational Fluid Dynamics, Submitted for publication, 2015  —  arXiv submission.

  • D. Amsallem, J. Nordstrom. Stable Model Reduction of Neurons by Non-Negative Discrete Empirical Interpolation, Submitted for publication, 2015 – submission.

  • M. Balajewicz, D. Amsallem, C. Farhat. Projection-Based Model Reduction for Contact Problems, Submitted for publication, 2015  —  arXiv submission.

  • R. Abgrall, D. Amsallem. Robust Model Reduction by L1-norm Minimization and Approximation via Dictionaries: Applications to Linear and Nonlinear Hyperbolic Problems, Submitted for publication, 2015  —  arXiv submission.

  • F. Negri, A. Manzoni, D. Amsallem. Efficient Model Reduction of Parametrized Systems by Matrix Discrete Empirical Interpolation, Submitted for publication, 2015  —  submission.

  • A. Paul-Dubois-Taine, D. Amsallem. An Adaptive and Efficient Greedy Procedure for the Optimal Training of Parametric Reduced-Order Models, IJNME, Vol. 102, May 2015, pp. 1262-1292  —  preprint

  • D. Amsallem, U. Hetmaniuk. A Posteriori Error Estimators for Linear Reduced Order Model Using Krylov-Based Integrators, IJNME, Vol. 102, May 2015, pp. 1238-1261  —  preprint.

  • D. Amsallem, C. Farhat, B. Haasdonk. Special Issue on Model Reduction, IJNME, Vol. 102, May 2015, pp. 931-932  —  preprint.

  • D. Amsallem, M. Zahr, Y. Choi, C. Farhat. Design Optimization Using Hyper-Reduced-Order Models, Structural and Multidisciplinary Optimization, Vol. 51, April 2015, pp. 919-940  —  preprint.

  • D. Amsallem, M. Zahr, K. Washabaugh. Fast Local Reduced Basis Updates for the Efficient Reduction of Nonlinear Systems with Hyper-Reduction, publushed online, Special Issue on Model Reduction of Parameterized Systems, Advances in Computational Mathematics (ACOM), February 2015  —  preprint.

  • D. Amsallem, C. Farhat. On the Stability of Projection-Based Linear Reduced-Order Models: Descriptor vs Non-Descriptor Forms, Springer MS&A series, Vol. 8: Reduced Order Methods for modeling and computational reduction, 2014  —  preprint.

  • D. Amsallem, U. Hetmaniuk. Error Estimates for Galerkin Reduced-Order Models of the Semi-Discrete Wave Equation, ESAIM: Mathematical Modelling and Numerical Analysis, Vol. 48, January 2014, pp. 135-163  —  preprint.

  • D. Amsallem, J. Nordstrom. High-Order Accurate Difference Schemes for the Hodgkin-Huxley Equations, Journal of Computational Physics, Vol. 252, November 2013, pp. 573-590  —  preprint.

  • C. Farhat, E. Chiu, D. Amsallem, J-S Schotte, R. Ohayon. On the Modeling of Fuel Sloshing and Its Physical Effects on Flutter, AIAA Journal, Vol. 51, September 2013, pp. 2252-2265  —  preprint.

  • K. Carlberg, C. Farhat, J. Cortial, D. Amsallem. The GNAT Method for Nonlinear Model Reduction: Effective Implementation and Application to Computational Fluid Dynamics and Turbulent Flows, Journal of Computational Physics, Vol. 241, June 2013, pp 623-647  —  preprint.

  • D. Amsallem, M. Zahr, C. Farhat. Nonlinear Model Order Reduction Based on Local Reduced-Order Bases, IJNME, Vol. 92, December 2012, pp. 891-916  —  preprint.

  • D. Amsallem, C. Farhat. Stabilization of Projection-Based Reduced-Order Models, IJNME, Vol. 91, July 2012, pp. 358-377  —  preprint.

  • D. Amsallem, C. Farhat. An Online Method for Interpolating Linear Parametric Reduced-Order Models, SIAM Journal on Scientific Computing, Vol. 33, Issue 5, September 2011, pp. 2169-2198  —  pdf. #2 Journal Top Download in September and October 2011.

  • D. Amsallem, J. Cortial, C. Farhat. Towards Real-Time CFD-Based Aeroelastic Computations Using a Database of Reduced-Order Information, AIAA Journal, Vol. 48, September 2010, pp. 2029-2037  —  preprint.

  • D. Amsallem, J. Cortial, K. Carlberg, C. Farhat. A Method for Interpolating on Manifolds Structural Dynamics Reduced-Order Models, IJNME, Vol. 80, November 2009, pp. 1241-1258  —  preprint.

  • D. Amsallem, C. Farhat. Interpolation Method for the Adaptation of Reduced-Order Models to Parameter Changes and Its Application to Aeroelasticity. AIAA Journal, Vol. 46, July 2008, pp. 1803-1813  —  preprint.

Selected Refereed Conference Papers

  • D. Amsallem, J. Roychowdhury. ModSpec: An Open, Flexible Specification Framework for Multi-Domain Modeling. 41st IEEE/ACM International Conference on Computer-Aided Design, November 6-10 2011, San Jose, CA.