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Alireza Doostan - Publications

Affiliations: 
Applied Mathematics University of Colorado, Boulder, Boulder, CO, United States 
Area:
Applied Mathematics
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50 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Dunton AM, Jofre L, Iaccarino G, Doostan A. Pass-efficient methods for compression of high-dimensional turbulent flow data Journal of Computational Physics. 109704. DOI: 10.1016/J.Jcp.2020.109704  0.385
2020 Choi H, Kim J, Doostan A, Park KC. Acceleration of uncertainty propagation through Lagrange multipliers in partitioned stochastic method Computer Methods in Applied Mechanics and Engineering. 362: 112837. DOI: 10.1016/J.Cma.2020.112837  0.455
2020 De S, Maute K, Doostan A. Bi-fidelity stochastic gradient descent for structural optimization under uncertainty Computational Mechanics. 1-27. DOI: 10.1007/S00466-020-01870-W  0.434
2019 Skinner RW, Doostan A, Peters EL, Evans JA, Jansen KE. Reduced-Basis Multifidelity Approach for Efficient Parametric Study of NACA Airfoils Aiaa Journal. 57: 1481-1491. DOI: 10.2514/1.J057452  0.372
2019 Pettersson P, Doostan A, Nordström J. Level set methods for stochastic discontinuity detection in nonlinear problems Journal of Computational Physics. 392: 511-531. DOI: 10.1016/J.Jcp.2019.04.053  0.421
2018 Fairbanks HR, Jofre L, Geraci G, Iaccarino G, Doostan A. Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence Journal of Computational Physics. 402: 108996. DOI: 10.1016/J.Jcp.2019.108996  0.435
2018 Hampton J, Fairbanks HR, Narayan AC, Doostan A. Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction Journal of Computational Physics. 368: 315-332. DOI: 10.1016/J.Jcp.2018.04.015  0.422
2018 Hampton J, Doostan A. Basis adaptive sample efficient polynomial chaos (BASE-PC) Journal of Computational Physics. 371: 20-49. DOI: 10.1016/J.Jcp.2018.03.035  0.463
2018 Diaz P, Doostan A, Hampton J. Sparse polynomial chaos expansions via compressed sensing and D-optimal design Computer Methods in Applied Mechanics and Engineering. 336: 640-666. DOI: 10.1016/J.Cma.2018.03.020  0.416
2017 Reynolds MJ, Beylkin G, Doostan A. Optimization via separated representations and the canonical tensor decomposition Journal of Computational Physics. 348: 220-230. DOI: 10.1016/J.Jcp.2017.07.012  0.327
2017 Fairbanks HR, Doostan A, Ketelsen C, Iaccarino G. A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems Journal of Computational Physics. 341: 121-139. DOI: 10.1016/J.Jcp.2017.03.060  0.4
2017 Hadigol M, Doostan A. Least squares polynomial chaos expansion: A review of sampling strategies Computer Methods in Applied Mechanics and Engineering. 332: 382-407. DOI: 10.1016/J.Cma.2017.12.019  0.386
2017 Balducci M, Jones B, Doostan A. Orbit uncertainty propagation and sensitivity analysis with separated representations Celestial Mechanics and Dynamical Astronomy. 129: 105-136. DOI: 10.1007/S10569-017-9767-7  0.431
2017 Constantine PG, Doostan A. Time‐dependent global sensitivity analysis with active subspaces for a lithium ion battery model Statistical Analysis and Data Mining. 10: 243-262. DOI: 10.1002/Sam.11347  0.331
2016 Schiavazzi DE, Doostan A, Iaccarino G, Marsden AL. A generalized multi-resolution expansion for uncertainty propagation with application to cardiovascular modeling. Computer Methods in Applied Mechanics and Engineering. 314: 196-221. PMID 28845061 DOI: 10.1016/J.Cma.2016.09.024  0.477
2016 Reynolds MJ, Doostan A, Beylkin G. Randomized Alternating Least Squares for Canonical Tensor Decompositions: Application to A PDE With Random Data Siam Journal On Scientific Computing. 38: A2634-A2664. DOI: 10.1137/15M1042802  0.379
2016 Peng J, Hampton J, Doostan A. On polynomial chaos expansion via gradient-enhanced ℓ1-minimization Journal of Computational Physics. 310: 440-458. DOI: 10.1016/J.Jcp.2015.12.049  0.471
2016 Pettersson P, Nordström J, Doostan A. A well-posed and stable stochastic Galerkin formulation of theincompressible Navier-Stokes equations with random data Journal of Computational Physics. 306: 92-116. DOI: 10.1016/J.Jcp.2015.11.027  0.426
2015 Jones BA, Parrish N, Doostan A. Postmaneuver collision probability estimation using sparse polynomial chaos expansions Journal of Guidance, Control, and Dynamics. 38: 1425-1437. DOI: 10.2514/1.G000595  0.446
2015 Hadigol M, Maute K, Doostan A. On uncertainty quantification of lithium-ion batteries: Application to an LiC6/LiCoO2 cell Journal of Power Sources. 300: 507-524. DOI: 10.1016/J.Jpowsour.2015.09.060  0.366
2015 Hampton J, Doostan A. Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies Journal of Computational Physics. 280: 363-386. DOI: 10.1016/J.Jcp.2014.09.019  0.437
2015 Hampton J, Doostan A. Coherence motivated sampling and convergence analysis of least squares polynomial Chaos regression Computer Methods in Applied Mechanics and Engineering. 290: 73-97. DOI: 10.1016/J.Cma.2015.02.006  0.428
2015 Feldhacker JD, Jones BA, Doostan A, Hampton J. Reduced cost mission design using surrogate models Advances in Space Research. DOI: 10.1016/J.Asr.2015.11.002  0.42
2015 Lang C, Sharma A, Doostan A, Maute K. Heaviside enriched extended stochastic FEM for problems with uncertain material interfaces Computational Mechanics. DOI: 10.1007/S00466-015-1199-1  0.426
2014 Schiavazzi D, Doostan A, Iaccarino G. Sparse multiresolution regression for uncertainty propagation International Journal For Uncertainty Quantification. 4: 303-331. DOI: 10.1615/Int.J.Uncertaintyquantification.2014010147  0.48
2014 Jagalur Mohan J, Sahni O, Doostan A, Oberai AA. Variational Multiscale Analysis: The Fine-Scale Green's Function for Stochastic Partial Differential Equations Siam/Asa Journal On Uncertainty Quantification. 2: 397-422. DOI: 10.1137/130940359  0.326
2014 Peng J, Hampton J, Doostan A. A weighted ℓ1-minimization approach for sparse polynomial chaos expansions Journal of Computational Physics. 267: 92-111. DOI: 10.1016/J.Jcp.2014.02.024  0.421
2014 Hadigol M, Doostan A, Matthies HG, Niekamp R. Partitioned treatment of uncertainty in coupled domain problems: A separated representation approach Computer Methods in Applied Mechanics and Engineering. 274: 103-124. DOI: 10.1016/J.Cma.2014.02.004  0.432
2014 Lang C, Makhija D, Doostan A, Maute K. A simple and efficient preconditioning scheme for heaviside enriched XFEM Computational Mechanics. 54: 1357-1374. DOI: 10.1007/S00466-014-1063-8  0.445
2014 Hadigol M, Doostan A, Matthies HG, Niekamp R. Partitioned solution of coupled stochastic problems Computational Methods in Applied Sciences. 33: 405-422. DOI: 10.1007/978-3-319-06136-8_16  0.365
2014 Brezina M, Doostan A, Manteuffel T, Mccormick S, Ruge J. Smoothed aggregation algebraic multigrid for stochastic PDE problems with layered materials Numerical Linear Algebra With Applications. 21: 239-255. DOI: 10.1002/Nla.1924  0.408
2014 Balducci M, Jones B, Doostan A. Orbit uncertainty propagation with separated representations Advances in the Astronautical Sciences. 150: 2469-2487.  0.351
2013 Jones BA, Doostan A, Born GH. Nonlinear propagation of orbit uncertainty using non-intrusive polynomial chaos Journal of Guidance, Control, and Dynamics. 36: 430-444. DOI: 10.2514/1.57599  0.443
2013 Doostan A, Validi A, Iaccarino G. Non-intrusive low-rank separated approximation of high-dimensional stochastic models Computer Methods in Applied Mechanics and Engineering. 263: 42-55. DOI: 10.1016/J.Cma.2013.04.003  0.482
2013 Pettersson P, Doostan A, Nordström J. On stability and monotonicity requirements of finite difference approximations of stochastic conservation laws with random viscosity Computer Methods in Applied Mechanics and Engineering. 258: 134-151. DOI: 10.1016/J.Cma.2013.02.009  0.411
2013 Jones BA, Doostan A. Satellite collision probability estimation using polynomial chaos expansions Advances in Space Research. 52: 1860-1875. DOI: 10.1016/J.Asr.2013.08.027  0.444
2013 Lang C, Doostan A, Maute K. Extended stochastic FEM for diffusion problems with uncertain material interfaces Computational Mechanics. 51: 1031-1049. DOI: 10.1007/S00466-012-0785-8  0.395
2012 Mehrez L, Doostan A, Moens D, Vandepitte D. Stochastic identification of composite material properties from limited experimental databases, Part II: Uncertainty modelling Mechanical Systems and Signal Processing. 27: 484-498. DOI: 10.1016/J.Ymssp.2011.09.001  0.403
2011 Doostan A, Owhadi H. A non-adapted sparse approximation of PDEs with stochastic inputs Journal of Computational Physics. 230: 3015-3034. DOI: 10.1016/J.Jcp.2011.01.002  0.454
2010 Hajirasouliha I, Doostan A. A simplified model for seismic response prediction of concentrically braced frames Advances in Engineering Software. 41: 497-505. DOI: 10.1016/J.Advengsoft.2009.10.008  0.329
2010 Mehrez L, Doostan A, Moens D, Vandepitte D. A validation study of a stochastic representation of composite material properties from limited experimental data Proceedings of Isma 2010 - International Conference On Noise and Vibration Engineering, Including Usd 2010. 4903-4924.  0.329
2009 Chantrasmi T, Doostan A, Iaccarino G. Padé-Legendre approximants for uncertainty analysis with discontinuous response surfaces Journal of Computational Physics. 228: 7159-7180. DOI: 10.1016/J.Jcp.2009.06.024  0.448
2009 Doostan A, Iaccarino G. A least-squares approximation of partial differential equations with high-dimensional random inputs Journal of Computational Physics. 228: 4332-4345. DOI: 10.1016/J.Jcp.2009.03.006  0.487
2009 Constantine PG, Doostan A, Iaccarino G. A hybrid collocation/Galerkin scheme for convective heat transfer problems with stochastic boundary conditions International Journal For Numerical Methods in Engineering. 80: 868-880. DOI: 10.1002/Nme.2564  0.375
2008 Ghanem RG, Doostan A, Red-Horse J. A probabilistic construction of model validation Computer Methods in Applied Mechanics and Engineering. 197: 2585-2595. DOI: 10.1016/J.Cma.2007.08.029  0.426
2007 Ghanem R, Saad G, Doostan A. Efficient solution of stochastic systems: Application to the embankment dam problem Structural Safety. 29: 238-251. DOI: 10.1016/J.Strusafe.2006.07.015  0.488
2007 Doostan A, Ghanem RG, Red-Horse J. Stochastic model reduction for chaos representations Computer Methods in Applied Mechanics and Engineering. 196: 3951-3966. DOI: 10.1016/J.Cma.2006.10.047  0.463
2007 Ghanem R, Red-Horse J, Benjamin A, Doostan A, Yu Z. Stochastic process model for material properties under incomplete information Collection of Technical Papers - Aiaa/Asme/Asce/Ahs/Asc Structures, Structural Dynamics and Materials Conference. 4: 3271-3277.  0.345
2006 Ghanem RG, Doostan A. On the construction and analysis of stochastic models: Characterization and propagation of the errors associated with limited data Journal of Computational Physics. 217: 63-81. DOI: 10.1016/J.Jcp.2006.01.037  0.43
2005 Moghaddam H, Hajirasouliha I, Doostan A. Optimum seismic design of concentrically braced steel frames: Concepts and design procedures Journal of Constructional Steel Research. 61: 151-166. DOI: 10.1016/J.Jcsr.2004.08.002  0.329
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