Thesis

  • M. J. Zahr, Adaptive model reduction to accelerate optimization problems governed by partial differential equations. PhD thesis, Stanford University, August 2016. [ bib | thesis ]

Book chapters

  • M. J. Zahr and P.-O. Persson, “Energetically optimal flapping wing motions via adjoint-based optimization and high-order discretizations,” in Frontiers in PDE-Constrained Optimization, Springer, 2017. [ bib | paper ]

Journal papers

  • M. J. Zahr and P.-O. Persson, “An optimization-based approach for high-order accurate discretization of conservation laws with discontinuous solutions,” Journal of Computational Physics, in review 2018. [ bib | paper | arxiv ]

  • M. J. Zahr, P. Avery, and C. Farhat, “A multilevel projection-based model order reduction framework for nonlinear dynamic multiscale problems in structural and solid mechanics,” International Journal for Numerical Methods in Engineering, 2017. [ bib | DOI | link ]

  • M. J. Zahr, P.-O. Persson, and J. Wilkening, “A fully discrete adjoint method for optimization of flow problems on deforming domains with time-periodicity constraints,” Computers & Fluids, 2016. [ bib | DOI | link | arxiv ]

  • M. J. Zahr and P.-O. Persson, “An adjoint method for a high-order discretization of deforming domain conservation laws for optimization of flow problems,” Journal of Computational Physics, vol. 326, no. Supplement C, pp. 516 -- 543, 2016. [ bib | DOI | link | arxiv ]

  • M. J. Zahr and C. Farhat, “Progressive construction of a parametric reduced-order model for PDE-constrained optimization,” International Journal for Numerical Methods in Engineering, vol. 102, no. 5, pp. 1111--1135, 2015. [ bib | DOI | link | arxiv ]

  • D. Amsallem, M. J. Zahr, and K. Washabaugh, “Fast local reduced basis updates for the efficient reduction of nonlinear systems with hyper-reduction,” Advances in Computational Mathematics, pp. 1--44, 2015. [ bib | DOI | link ]

  • D. Amsallem, M. J. Zahr, Y. Choi, and C. Farhat, “Design optimization using hyper-reduced-order models,” Structural and Multidisciplinary Optimization, pp. 1--22, 2014. [ bib | DOI | link ]

  • D. Amsallem, M. J. Zahr, and C. Farhat, “Nonlinear model order reduction based on local reduced-order bases,” International Journal for Numerical Methods in Engineering, vol. 92, no. 10, pp. 891--916, 2012. [ bib | DOI | link ]

Conference papers

  • M. J. Zahr and P.-O. Persson, “An optimization-based discontinuous Galerkin approach for high-order accurate shock tracking,” in AIAA Science and Technology Forum and Exposition (SciTech2018), (Kissimmee, Florida), American Institute of Aeronautics and Astronautics, 1/8/2018 -- 1/12/2018. [ bib | paper ]

  • J. Wang, M. J. Zahr, and P.-O. Persson, “Energetically optimal flapping flight based on a fully discrete adjoint method with explicit treatment of flapping frequency,” in Proc. of the 23rd AIAA Computational Fluid Dynamics Conference, (Denver, Colorado), American Institute of Aeronautics and Astronautics, 6/5/2017 -- 6/9/2017. [ bib | link | paper ]

  • M. J. Zahr and P.-O. Persson, “High-order, time-dependent aerodynamic optimization using a discontinuous Galerkin discretization of the Navier-Stokes equations,” in AIAA Science and Technology Forum and Exposition (SciTech 2016), (San Diego, California), 1/4/2016 -- 1/8/2016. [ bib | link | paper ]

  • D. De Santis, M. J. Zahr, and C. Farhat, “Gradient-based aerodynamic shape optimization using the FIVER embedded boundary method,” in AIAA Science and Technology Forum and Exposition (SciTech 2016), (San Diego, California), 1/4/2016 -- 1/8/2016. [ bib | link | paper ]

  • K. Washabaugh, M. J. Zahr, and C. Farhat, “On the use of discrete nonlinear reduced-order models for the prediction of steady-state flows past parametrically deformed complex geometries,” in AIAA Science and Technology Forum and Exposition (SciTech 2016), (San Diego, California), 1/4/2016 -- 1/8/2016. [ bib | link ]

  • M. J. Zahr and P.-O. Persson, “Performance tuning of Newton-GMRES methods for discontinuous Galerkin discretizations of the Navier-Stokes equations,” in Proc. of the 21st AIAA Computational Fluid Dynamics Conference, vol. AIAA-2013-2685, American Institute of Aeronautics and Astronautics, 6/24/2013 -- 6/27/2013. [ bib | link | paper ]

  • M. J. Zahr, D. Amsallem, and C. Farhat, “Construction of parametrically-robust CFD-based reduced-order models for PDE-constrained optimization,” in Proc. of the 21st AIAA Computational Fluid Dynamics Conference, vol. AIAA-2013-2685, American Institute of Aeronautics and Astronautics, 6/24/2013 -- 6/27/2013. [ bib | link | paper ]

  • K. Washabaugh, D. Amsallem, M. J. Zahr, and C. Farhat, “Nonlinear model reduction for CFD problems using local reduced-order bases,” in 42nd AIAA Fluid Dynamics Conference and Exhibit, Fluid Dynamics and Co-located Conferences, vol. 2686, 6/25/2012 -- 6/28/2012. [ bib | link | paper ]

  • D. Amsallem, M. J. Zahr, and C. Farhat, “On the robustness of residual minimization for constructing POD-based reduced-order CFD models,” in 43rd AIAA Fluid Dynamics Conference and Exhibit, (San Diego, California), 6/27/2011 -- 6/30/2011. [ bib | link | paper ]

  • K. Carlberg, J. Cortial, D. Amsallem, M. J. Zahr, and C. Farhat, “The GNAT nonlinear model reduction method and its application to fluid dynamics problems,” in AIAA Paper 2011-3112, 6th AIAA Theoretical Fluid Mechanics Conference, (Honolulu, Hawaii), 6/27/2011 -- 6/30/2011. [ bib | link ]

Technical reports

  • M. J. Zahr and S. Govindjee, “Theoretical and numerical foundations for the use of microcolumns as angular motion sensors,” tech. rep., University of California, Berkeley, 2011. [ bib | paper ]

  • M. J. Zahr, K. Carlberg, D. Amsallem, and C. Farhat, “Comparison of model reduction techniques on high-fidelity linear and nonlinear electrical, mechanical, and biological systems,” tech. rep., University of California, Berkeley, 2010. [ bib | paper ]

  • M. J. Zahr, N. Luco, and H. Ryu, “Mitigation of seismic risk pertaining to non-ductile reinforced concrete buildings using seismic risk maps,” tech. rep., United States Geologic Survey (USGS), 2009. [ bib | paper ]