Publications

Recent manuscripts

Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism

Q. Wang; N. Ripamonti; J. S. Hesthaven 

Journal of Computational Physics. 2019-08-18. 

A comparative study of earthquake source models in high- order accurate tsunami simulations

M. Hajihassanpour; B. Bonev; J. S. Hesthaven 

Ocean Modelling. 2019-08-14. DOI : 10.1016/j.ocemod.2019.101429.

Controlling the bias error of Fokker- Planck methods for rarefied gas dynamics simulations

P. Jenny; S. Kuchlin; H. Gorji 

Physics of Fluids. 2019-06-12. Vol. 31. DOI : 10.1063/1.5097884.

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

H. Gorji; S. Kuchlin; P. Jenny 

Physics of Fluids. 2019-06-12. Vol. 31. DOI : 10.1063/1.5097902.

MATHICSE Technical Report: Constraint-Aware Neural Networks for Riemann Problems

J. Magiera; D. Ray; J. S. Hesthaven; C. Rohde 

2019-04-28

MATHICSE Technical Report: Time domain room acoustic simulations using a spectral element method

F. Pind; A. P. Engsig-Karup; C-H. Jeong; J. S. Hesthaven; M. S. Meiling et al. 

2019-04-28

MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring

C. Bigoni; J. S. Hesthaven 

2019-04-10

MATHICSE Technical Report: A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

M. Kast; M. Guo; J. S. Hesthaven 

2019-04-10

MATHICSE Technical Report: Controlling oscillations in high-order Discontinuous Galerkin schemes using artificial\ viscosity tuned by neural networks

N. Discacciati; J. S. Hesthaven; D. Ray 

2019-01-28

Gaussian Process Regression for Maximum Entropy Distribution

M. Sadr; M. Torrilhon; H. Gorji 

2019

Entropic Fokker-Planck Kinetic Model

H. Gorji; M. Torrilhon 

2019

Comparative study between Cubic and Ellipsoidal Fokker-Planck kinetic models

E. Jun; M. Pfeiffer; L. Mieussens; M. Gorji 

AIAA Journal. 2019. DOI : 10.2514/1.J057935.

Accurate particle time integration for solving Vlasov-Fokker-Planck equations with specified electromagnetic fields

P. Jenny; M. Gorji 

Journal of Computational Physics. 2019. DOI : 10.1016/j.jcp.2019.02.040.

Projective multiscale time-integration for electrostatic particle-in-cell methods

P. Cazeaux; J. S. Hesthaven 

Computer Physics Communications. 2019. Vol. 236, p. 34-50. DOI : 10.1016/j.cpc.2018.10.012.

RBF Based CWENO Method

J. S. Hesthaven; F. Mönkeberg; S. Zaninelli 

2018-11-09. ICOSAHOM 2018, London, UK,

Model order reduction for large-scale structures with local nonlinearities

Z. Zhang; M. Guo; J. S. Hesthaven 

2018-11-09. 

Detecting troubled-cells on two-dimensional unstructured grids using a neural network

D. Ray; J. S. Hesthaven 

2018-11-01. 

Data-driven reduced order modeling for time-dependent problems

M. Guo; J. S. Hesthaven 

Computer Methods in Applied Mechanics and Engineering. 2018-10. Vol. 345, p. 75-99. DOI : 10.1016/j.cma.2018.10.029.

Entropy stable essentially non-oscillatory methods based on RBF reconstructions

J. S. Hesthaven; F. Mönkeberg 

Mathematical Modeling and Numerical Analysis. 2018-08-14. 

Conservative Model Order Reduction for Fluid Flow

B. Maboudi Afkham; N. Ripamonti; Q. Wang; J. S. Hesthaven 

Advances in reduced order modeling; Springer Verlag, 2018-08-06.

Greedy Non-Intrusive Reduced Order Model for Fluid Dynamics

W. Chen; J. S. Hesthaven; B. Junqiang; Y. Qiu; Y. Tihao et al. 

AIAA Journal. 2018-06-24. Vol. 56, p. 12. DOI : 10.2514/1.J056161.

Estimation of groundwater storage from seismic data using deep learning

T. Lahivaara; A. Pasanen; L. Karkkainen; J. M. Huttunen; J. S. Hesthaven et al. 

Geophysics Research Letters. 2018-06-24. 

A data-driven shock capturing approach for discontinuous Galekin methods

J. Yu; J. S. Hesthaven; C. Yan 

2018-06-18. 

Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem

Q. Wang; J. S. Hesthaven; D. Ray 

Journal of Computational Physics. 2018-06-18. Vol. 384, p. 289-307. DOI : 10.1016/j.jcp.2019.01.031.

POD-Kriging reduced method’s application in Tandem Cylinders’ flow

W. Chen; B. Junqiang; J. S. Hesthaven; Q. Yasong; Q. Lei et al. 

Journal of Northwestern Polytechnical University. 2018-06-01. 

Controlling oscillations in high-order schemes using neural networks

N. Discacciati 

2018.

Treatment of long-range interactions arising in the Enskog-Vlasov description of dense fluids

M. Gorji 

Journal of Computational Physics. 2018. 

Scaling and Resilience in Numerical Algorithms for Exascale Computing

A. S. Nielsen / J. S. Hesthaven (Dir.)  

Lausanne: EPFL, 2018. DOI : 10.5075/epfl-thesis-8926.

Geometric Model Order Reduction

B. Maboudi Afkham / J. S. Hesthaven (Dir.)  

Lausanne: EPFL, 2018. DOI : 10.5075/epfl-thesis-8923.

Structure-Preserving Reduced Basis Methods for Hamiltonian Systems with a Nonlinear Poisson Structure

J. S. Hesthaven; C. Pagliantini 

Foundations of Computational Mathematics. 2018. 

A nodal discontinuous Galerkin finite element method for the poroelastic wave equation

K. Shukla; J. S. Hesthaven; J. M. Carcione; R. Ye; J. de la Puenta et al. 

Computational Geoscience. 2018. DOI : 10.1007/s10596-019-9809-1.

Logarithmic Gradient Transformation and Chaos Expansion of Ito Processes

M. H. Gorji 

2018. 

Discontinuous Galerkin Discretizations of the Boltzmann Equations in 2D: semi-analytic time stepping and absorbing boundary layers

A. Karakus; N. Chalmers; J. S. Hesthaven; T. Warburton 

2018. DOI : 10.1016/j.jcp.2019.03.050.

Symplectic Model-Reduction with a Weighted Inner Product

B. Maboudi Afkham; A. Bhatt; B. Haasdonk; J. S. Hesthaven 

SIAM Journal of Scientific Computing. 2018. 

Flowfield Reconstruction Method Using Artificial Neural Network

J. Yu; J. S. Hesthaven 

AIAA Journal. 2018.  p. 1-17. DOI : 10.2514/1.J057108.

Reduced order modeling for nonlinear structural analysis using Gaussian process regression

M. Guo; J. S. Hesthaven 

Computer Methods in Applied Mechanics and Engineering. 2018. Vol. 341, p. 807-826. DOI : 10.1016/j.cma.2018.07.017.

Discontinuous Galerkin scheme for the spherical shallow water equations with applications to tsunami modeling and prediction

B. Bonev; J. S. Hesthaven; F. X. Giraldo; M. A. Kopera 

Journal of Computational Physics. 2018. Vol. 362, p. 425-448. DOI : 10.1016/j.jcp.2018.02.008.

An artificial neural network as a troubled-cell indicator

D. Ray; J. S. Hesthaven 

Journal of computational physics. 2018. Vol. 367, p. 166-191. DOI : 10.1016/j.jcp.2018.04.029.

Non-intrusive reduced order modeling of nonlinear problems using neural networks

J. S. Hesthaven; S. Ubbiali 

Journal of Computational Physics. 2018. Vol. 363, p. 55-78. DOI : 10.1016/j.jcp.2018.02.037.

Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography

T. Lahivaara; L. Karkkainen; J. M. Huttunen; J. S. Hesthaven 

Journal of the Acoustical Society of America. 2018. Vol. 143, p. 1148. DOI : 10.1121/1.5024341.

Research and Education in Computational Science and Engineering

U. Ruede; K. Willcox; L. C. McInnes; H. De Sterck; G. Biros et al. 

Siam Review. 2018. Vol. 60, num. 3, p. 707-754. DOI : 10.1137/16M1096840.

Numerical methods for conservation laws: From analysis to algorithms

J. S. Hesthaven 

Philadelphia: SIAM Publishing, 2017.

A comparative study of shock capturing models for the discontinuous Galerkin method

J. Yu; J. S. Hesthaven 

Journal of Computational Physics. 2017. 

Efficient Preconditioning of hp-FEM Matrices by Hierarchical Low-Rank Approximations

P. Gatto; J. S. Hesthaven 

Journal Of Scientific Computing. 2017. Vol. 72, num. 1, p. 49-80. DOI : 10.1007/s10915-016-0347-x.

Large-Scale Tsunami Simulations using the Discontinuous Galerkin Method

B. Bonev; F. Giraldo; J. S. Hesthaven 

27th Biennial Conference on Numerical Analysis, Glasgow, UK, June 27-30, 2017.

Communication-aware adaptive parareal with application to a nonlinear hyperbolic system of partial dierential equations

A. S. Nielsen; G. Brunner; J. S. Hesthaven 

Journal of Computational Physics. 2017. Vol. 15, p. 483-505. DOI : 10.1016/j.jcp.2018.04.056.

Structure-Preserving Model-Reduction of Dissipative Hamiltonian Systems

B. Maboudi Afkham; J. S. Hesthaven 

Journal of Scientific Computing. 2017. 

A greedy non-intrusive reduced order model for fluid dynamics

W. Chen; J. S. Hesthaven; B. Junqiang; Z. Yang; Y. Tihao 

Journal of Northwestern Polytechnical University. 2017. 

High-Order Accurate Local Schemes for Fractional Differential Equations

D. Baffet; J. S. Hesthaven 

Journal Of Scientific Computing. 2017. Vol. 70, num. 1, p. 355-385. DOI : 10.1007/s10915-015-0089-1.

Identification of a Predator-Prey System from Simulation Data of a Convection Model

M. Dam; M. Brøns; J. J. Rasmussen; V. Naulin; J. S. Hesthaven 

Physics of Plasmas. 2017. Vol. 24, p. 022310 1-10. DOI : 10.1063/1.4977057.

Efficient preconditioning of hp-FEM matrices arising from time-varying problems: an application to topology optimization

P. Gatto; J. S. Hesthaven; R. Christiansen 

Computer Methods in Applied Mechanics and Engineering. 2017. Vol. 322, p. 81-96. DOI : 10.1016/j.cma.2017.04.027.

Adaptive WENO methods based on radial basis functions reconstruction

C. Bigoni; J. S. Hesthaven 

Journal of Scientific Computing. 2017. Vol. 72, num. 3, p. 986-1020. DOI : 10.1007/s10915-017-0383-1.

High-Order Accurate Adaptive Kernel Compression Time-Stepping Schemes for Fractional Differential Equations

D. H. Baffet; J. S. Hesthaven 

Journal of Scientific Computing. 2017. Vol. 72, num. 3, p. 1169-1195. DOI : 10.1007/s10915-017-0393-z.

Structure preserving model reduction of parametric Hamiltonian systems

B. Maboudi Afkham; J. S. Hesthaven 

Siam Journal on Scientific Computing. 2017. Vol. 39, num. 6, p. A2616-A2644. DOI : 10.1137/17M1111991.

Space-dependent source determination in a time-fractional diffusion equation using a local discontinuous Galerkin method

S. Yeganeh; R. Mokhtari; J. S. Hesthaven 

BIT Numerical Mathematics. 2017. Vol. 57, num. 3, p. 685-707. DOI : 10.1007/s10543-017-0648-y.

A kernel compression scheme for fractional differential equations

D. H. Baffet; J. S. Hesthaven 

Siam Journal on Numerical Analysis. 2017. Vol. 55, num. 2, p. 496-520. DOI : 10.1137/15M1043960.

Spectral Methods for Hyperbolic Problems

J. S. Hesthaven 

Handbook of Numerical Methods for Hyperbolic Problems Basic and Fundamental Issues; Elsevier Publishing, 2016. p. 441-466.

Spectral methods for tempered fractional differential equations

L. Zhao; W. Deng; J. S. Hesthaven 

Mathematics of Computation. 2016. 

Fault Tolerance in the Parareal Method

A. S. Nielsen; J. S. Hesthaven 

2016. ACM Workshop on Fault-Tolerance for HPC at Extreme Scale (FTXS). p. 1-8. DOI : 10.1145/2909428.2909431.

On the use of ANOVA expansions in reduced basis methods for high-dimensional parametric partial differential equations

J. S. Hesthaven; S. Zhang 

Journal of Scientific Computing. 2016. Vol. 69, num. 1, p. 292-313. DOI : 10.1007/s10915-016-0194-9.

Certified Reduced Basis Methods for Parametrized Partial Differential Equations

J. S. Hesthaven; G. Rozza; B. Stamm 

Springer Verlag, 2015.

Hyperbolic Problems: Theory and Computation

J. S. Hesthaven; J-H. Jung; A. Tesdall 

Journal Of Scientific Computing. 2015. Vol. 64, num. 3, p. 587-590. DOI : 10.1007/s10915-015-0065-9.

An Adjoint Approach for Stabilizing the Parareal Method

F. Chen; J. S. Hesthaven; Y. Maday; A. S. Nielsen 

Comptes rendus des séances de l'Académie des Sciences. Série A, Sciences mathématiques**. 2015. 

Special Issue on "Fractional PDEs: Theory, Numerics, and Applications"

G. E. Karniadakis; J. S. Hesthaven; I. Podlubny 

Journal Of Computational Physics. 2015. Vol. 293, p. 1-3. DOI : 10.1016/j.jcp.2015.04.007.

Accuracy of high order and spectral methods for hyperbolic conservation laws with discontinuous solutions

J. Zudrop; J. S. Hesthaven 

Siam Journal on Numerical Analysis. 2015. Vol. 53, num. 4, p. 1857-1875. DOI : 10.1137/140992758.

Nodal discontinuous Galerkin methods for fractional diffusion equations on 2D domain with triangular meshes

L. Qiu; W. Deng; J. S. Hesthaven 

Journal of Computational Physics. 2015. Vol. 298, p. 678-694. DOI : 10.1016/j.jcp.2015.06.022.

Numerical approximation of the fractional Laplacian via hp-finite elements, with an application to image denoising

P. Gatto; J. S. Hesthaven 

Journal of Scientific Computing. 2015. Vol. 65, num. 1, p. 249-270. DOI : 10.1007/s10915-014-9959-1.

A Parareal Method for Time-fractional Differential Equations

Q. Xu; J. S. Hesthaven; F. Chen 

Journal of Computational Physics. 2015. Vol. 293, p. 173-183. DOI : 10.1016/j.jcp.2014.11.034.

Local discontinuous Galerkin methods for fractional ordinary differential equations

W. Deng; J. S. Hesthaven 

Bit Numerical Mathematics. 2015. Vol. 55, num. 4, p. 967-985. DOI : 10.1007/s10543-014-0531-z.

Modeling 3D Magma Dynamics Using a Discontinuous Galerkin Method

S. Tirupathi; J. S. Hesthaven; Y. Liang 

Communications in Computational Physics. 2015. Vol. 18, num. 01, p. 230-246. DOI : 10.4208/cicp.090314.151214a.

Multilevel and Local Timestepping Discontinuous Galerkin Methods for Magma Dynamics

S. Tirupathi; J. S. Hesthaven; Y. Liang; M. Parmentier 

Computational Geosciences. 2015. Vol. 19, num. 4, p. 965-978. DOI : 10.1007/s10596-015-9514-7.

Reduced basis multiscale finite element methods for elliptic problems

J. S. Hesthaven; S. Zhang; X. Zhu 

Multiscale Modeling and Simulation. 2015. Vol. 13, num. 1, p. 316-337. DOI : 10.1137/120898024.

A Multi-domain Spectral Method for Time-fractional Differential Equations

F. Chen; Q. Xu; J. S. Hesthaven 

Journal of Computational Physics. 2015. Vol. 293, p. 157-172. DOI : 10.1016/j.jcp.2014.10.016.

On the Use of Reduced Basis Methods to Accelerate and Stabilize the Parareal Method

F. Chen; J. S. Hesthaven; X. Zhu 

2014. Workshop on Reduced Basis, POD and Reduced Order Methods for Model and Computational Reduction: towards Real-time Computing and Visualization', Lausanne, CH, p. 187-214. DOI : 10.1007/978-3-319-02090-7_7.

Applications of Model Reduction Techniques in Aerospace Combustors

R. Munipalli; Z. Liu; X. Zhu; S. Menon; J. S. Hesthaven 

2014. AIAA Conference.

Time-domain finite element methods for Maxwell's equations in metamaterials

J. S. Hesthaven 

Siam Review. 2014. Vol. 56, num. 1, p. 202-203.

Analysis and application of the nodal discontinuous Galerkin method for wave propagation in metamaterials

J. Li; J. S. Hesthaven 

Journal Of Computational Physics. 2014. Vol. 258, p. 915-930. DOI : 10.1016/j.jcp.2013.11.018.

Model Reduction Opportunities in Detailed Simulations of Combustion Dynamics

R. Munipalli; X. Zhu; S. Menon; J. S. Hesthaven 

Aiaa Journal. 2014. 

Spectral and High Order Methods for Partial Differential Equations - ICOSAHOM 2012

 

Switzerland: Springer Verlag, 2014.

Discontinuous Galerkin method for fractional convection-diffusion equations

Q. Xu; J. S. Hesthaven 

Siam Journal on Numerical Analysis. 2014. Vol. 52, num. 1, p. 405-423. DOI : 10.1137/130918174.

High-order multiscale finite element method for elliptic problems

J. S. Hesthaven; S. Zhang; X. Zhu 

Multiscale Modeling and Simulation. 2014. Vol. 12, num. 2, p. 650-666. DOI : 10.1137/120898024.

Efficient greedy algorithms for high-dimensional parameter spaces with applications to empirical interpolation and reduced basis methods

J. S. Hesthaven; B. Stamm; S. Zhang 

Mathematical Modelling and Numerical Analysis. 2014. Vol. 48, num. 01, p. 259-283. DOI : 10.1051/m2an/2013100.

Multiscale modeling of sound propagation through the lung parenchyma

P. Cazeaux; J. S. Hesthaven 

Mathematical Modelling and Numerical Analysis. 2014. Vol. 48, num. 1, p. 27-52. DOI : 10.1051/m2an/2013093.

Stable multi-domain spectral penalty methods for fractional partial differential equations

Q. Xu; J. S. Hesthaven 

Journal of Computational Physics. 2014. Vol. 257, p. 241-258. DOI : 10.1016/j.jcp.2013.09.041.

Fast prediction and evaluation of gravitational waveforms using surrogate models

S. E. Field; C. R. Galley; J. S. Hesthaven; J. Kaye; M. Tiglio 

Physical Review X. 2014. Vol. 4, p. 031006-1-031006-21. DOI : 10.1103/PhysRevX.4.031006.

High-order accurate methods for solving Maxwell's equations: Applications to photonic crystals and thin layer coatings

S. Chun; J. S. Hesthaven 

Saarbrucken, Germany: Scholar-Press, 2013.

On the use of reduced basis methods to accelerate and stabilize the Parareal method

F. Chen; J. S. Hesthaven; X. Zhu 

Reduced Order Methods for modeling and computational reduction; Milano: Springer Publishing, 2013. p. 187-214.

Local discontinuous Galerkin methods for fractional diffusion equations

W. Deng; J. S. Hesthaven 

Mathematical Modelling and Numerical Analysis. 2013. Vol. 47, num. 6, p. 1845-1864. DOI : 10.1051/m2an/2013091.

Multi-dimensional hybrid Fourier continuation-WENO solvers for conservation laws

K. Shahbazi; J. S. Hesthaven; X. Zhu 

Journal of Computational Physics. 2013. Vol. 253, p. 209-225. DOI : 10.1016/j.jcp.2013.07.009.

A generalization of the Wiener rational basis functions on infinite intervals, Part II - Numerical investigation

A. C. Narayan; J. S. Hesthaven 

Journal of Computational and Applied Mathematics. 2013. Vol. 237, num. 1, p. 18-34. DOI : 10.1016/j.cam.2012.06.036.

Spectral methods: algorithms, analysis and applications [book review of MR2867779]

J. S. Hesthaven 

SIAM Review. 2013. Vol. 55, num. 2, p. 405-406.

High-Order Discontinuous Galerkin Methods by GPU Metaprogramming

A. Kloeckner; T. Warburton; J. S. Hesthaven 

GPU Solutions to Multi-scale Problems in Science and Engineering; Springer Verlag, 2012.

Special Issue in Memory of Professor David Gottlieb

 

France: SMAI Publications, 2012.

Solving Wave Equations on Unstructured Geometries

A. Klöckner; T. Warburton; J. S. Hesthaven 

GPU Computing Gems Jade Edition; Morgan Kaufmann, 2012. p. 225-242.

Accurate reconstruction of discontinuous functions using the singular pade-chebyshev method

A. L. Tampos; J. E. C. Lope; J. S. Hesthaven 

IAENG International Journal of Applied Mathematics. 2012. Vol. 42, num. 4, p. 242-249.

Computation of connection coefficients and measure modifications for orthogonal polynomials

A. Narayan; J. S. Hesthaven 

BIT Numerical Mathematics. 2012. Vol. 52, num. 2, p. 457-483. DOI : 10.1007/s10543-011-0363-z.

Certified Reduced Basis Method for the Electric Field Integral Equation

J. S. Hesthaven; B. Stamm; S. Zhang 

SIAM Journal on Scientific Computing. 2012. Vol. 34, num. 3, p. A1777-A1799. DOI : 10.1137/110848268.

A reduced basis method for electromagnetic scattering by multiple particles in three dimensions

M. Ganesh; J. S. Hesthaven; B. Stamm 

Journal of Computational Physics. 2012. Vol. 231, num. 23, p. 7756-7779. DOI : 10.1016/j.jcp.2012.07.008.

Certified reduced basis method for electromagnetic scattering and radar cross section estimation

Y. Chen; J. S. Hesthaven; Y. Maday; J. Rodriguez; X. Zhu 

Computer Methods in Applied Mechanics and Engineering. 2012. Vol. 233--236, num. C, p. 92-108. DOI : 10.1016/j.cma.2012.04.013.

Numerical simulations with a first-order BSSN formulation of Einstein's field equations

J. D. Brown; P. Diener; S. E. Field; J. S. Hesthaven; F. Herrmann et al. 

Physical Review D. 2012. Vol. 85, num. 8, p. 084004. DOI : 10.1103/PhysRevD.85.084004.