Publications

Recent manuscripts

Shape Holomorphy of Boundary Integral Operators on Multiple Open Arcs

J. Pinto; F. Henriquez; C. Jerez-Hanckes 

Journal Of Fourier Analysis And Applications. 2024-04-01. Vol. 30, num. 2, p. 14. DOI : 10.1007/s00041-024-10071-5.

Model reduction of coupled systems based on non-intrusive approximations of the boundary response maps

N. Discacciati; J. S. Hesthaven 

Computer Methods In Applied Mechanics And Engineering. 2024-01-18. Vol. 420, p. 116770. DOI : 10.1016/j.cma.2024.116770.

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

F. Pichi; B. Moya; J. S. Hesthaven 

Journal Of Computational Physics. 2024-01-17. Vol. 501, p. 112762. DOI : 10.1016/j.jcp.2024.112762.

Positional Embeddings for Solving PDEs with Evolutional Deep Neural Networks

M. Kast; J. S. Hesthaven 

Journal Of Computational Physics. 2024-07-01. Vol. 508, p. 112986. DOI : 10.1016/j.jcp.2024.112986.

Non-intrusive data-driven reduced-order modeling for time-dependent parametrized problems

J. Duan; J. S. Hesthaven 

Journal Of Computational Physics. 2023-11-15. Vol. 497, p. 112621. DOI : 10.1016/j.jcp.2023.112621.

Massively parallel nodal discontinous Galerkin finite element method simulator for room acoustics

A. Melander; E. Strom; F. Pind; A. P. Engsig-Karup; C-H. Jeong et al. 

International Journal Of High Performance Computing Applications. 2023-11-16. DOI : 10.1177/10943420231208948.

An adaptive moving mesh finite difference scheme for tokamak magneto-hydrodynamic simulations

J. Wang; J. M. Duan; Z. W. Ma; W. Zhang 

Computer Physics Communications. 2023-10-16. Vol. 294, p. 108951. DOI : 10.1016/j.cpc.2023.108951.

Reduced order modeling of parametrized pulsatile blood flows: Hematocrit percentage and heart rate

C. Farias; C. Bayona-Roa; E. Castillo; R. C. Cabrales; R. Reyes 

International Journal Of Engineering Science. 2023-12-01. Vol. 193, p. 103943. DOI : 10.1016/j.ijengsci.2023.103943.

High-order accurate well-balanced energy stable adaptive moving mesh finite difference schemes for the shallow water equations with non-flat bottom topography

Z. Zhang; J. Duan; H. Tang 

Journal Of Computational Physics. 2023-11-01. Vol. 492, p. 112451. DOI : 10.1016/j.jcp.2023.112451.

Adaptive Symplectic Model Order Reduction Of Parametric Particle-Based Vlasov-Poisson Equation

J. S. Hesthaven; C. Pagliantini; N. Ripamonti 

Mathematics Of Computation. 2023-08-24. DOI : 10.1090/mcom/3885.

Reduced order models for coupled systems

N. Discacciati / J. S. Hesthaven (Dir.)  

Lausanne, EPFL, 2023. 

A new variable shape parameter strategy for RBF approximation using neural networks

F. N. Mojarrad; M. H. Veiga; J. S. Hesthaven; P. oeffner 

Computers & Mathematics With Applications. 2023-05-23. Vol. 143, p. 151-168. DOI : 10.1016/j.camwa.2023.05.005.

Localized model order reduction and domain decomposition methods for coupled heterogeneous systems

N. Discacciati; J. S. S. Hesthaven 

International Journal For Numerical Methods In Engineering. 2023-05-25. DOI : 10.1002/nme.7295.

Reduced order modeling for parametrized generalized Newtonian fluid flows

R. Reyes; O. Ruz; C. Bayona-Roa; E. Castillo; A. Tello 

Journal Of Computational Physics. 2023-03-31. Vol. 484, p. 112086. DOI : 10.1016/j.jcp.2023.112086.

ReLU Neural Network Galerkin BEM

R. Aylwin; F. Henriquez; C. Schwab 

Journal Of Scientific Computing. 2023-05-01. Vol. 95, num. 2, p. 41. DOI : 10.1007/s10915-023-02120-w.

An artificial neural network approach to bifurcating phenomena in computational fluid dynamics

F. Pichi; F. Ballarin; G. Rozza; J. S. Hesthaven 

Computers & Fluids. 2023-02-08. Vol. 254, p. 105813. DOI : 10.1016/j.compfluid.2023.105813.

High-order accurate entropy stable adaptive moving mesh finite difference schemes for (multi-component) compressible Euler equations with the stiffened equation of state

S. Li; J. Duan; H. Tang 

Computer Methods In Applied Mechanics And Engineering. 2022-09-01. Vol. 399, p. 115311. DOI : 10.1016/j.cma.2022.115311.

Fourier Collocation and Reduced Basis Methods for Fast Modeling of Compressible Flows

J. Yu; D. Ray; J. S. Hesthaven 

Communications In Computational Physics. 2022-09-01. Vol. 32, num. 3, p. 595-637. DOI : 10.4208/cicp.OA-2021-0180.

Reduced basis methods for numerical room acoustic simulations with parametrized boundaries

H. Sampedro Llopis; A. P. Engsig-Karup; C-H. Jeong; F. Pind; J. S. Hesthaven 

Journal Of The Acoustical Society Of America. 2022-08-01. Vol. 152, num. 2, p. 851-865. DOI : 10.1121/10.0012696.

Model order reduction for compressible flows solved using the discontinuous Galerkin methods

J. Yu; J. S. Hesthaven 

Journal Of Computational Physics. 2022-11-01. Vol. 468, p. 111452. DOI : 10.1016/j.jcp.2022.111452.

Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier–Stokes equations with model order reduction

F. Pichi; M. Strazzullo; F. Ballarin; G. Rozza 

ESAIM: Mathematical Modelling and Numerical Analysis. 2022-06-27. Vol. 56, num. 4, p. 1361-1400. DOI : 10.1051/m2an/2022044.

Model order reduction for bifurcating phenomena in fluid-structure interaction problems

M. Khamlich; F. Pichi; G. Rozza 

International Journal For Numerical Methods In Fluids. 2022-06-04. Vol. 94, num. 10, p. 1611-1640. DOI : 10.1002/fld.5118.

Structure-preserving approaches and data-driven closure modeling for model order reduction

N. Ripamonti / J. S. Hesthaven (Dir.)  

Lausanne, EPFL, 2022. 

Preface to the Focused Issue on WENO Schemes

S. Gottlieb; J. S. Hesthaven; J. Qiu; C-W. Shu; Q. Zhang et al. 

Communications On Applied Mathematics And Computation. 2022-05-13. DOI : 10.1007/s42967-022-00196-z.

Rank-adaptive structure-preserving model order reduction of Hamiltonian systems

J. S. Hesthaven; C. Pagliantini; N. Ripamonti 

Esaim-Mathematical Modelling And Numerical Analysis. 2022-03-08. Vol. 56, num. 2, p. 617-650. DOI : 10.1051/m2an/2022013.

An analytical solution of the isentropic vortex problem in the special relativistic magnetohydrodynamics

J. Duan; H. Tang 

Journal Of Computational Physics. 2022-05-01. Vol. 456, p. 110903. DOI : 10.1016/j.jcp.2021.110903.

High-order accurate entropy stable adaptive moving mesh finite difference schemes for special relativistic (magneto)hydrodynamics

J. Duan; H. Tang 

Journal Of Computational Physics. 2022-05-01. Vol. 456, p. 111038. DOI : 10.1016/j.jcp.2022.111038.

Multi-fidelity regression using artificial neural networks: Efficient approximation of parameter-dependent output quantities

M. Guo; A. Manzoni; M. Amendt; P. Conti; J. S. Hesthaven 

Computer Methods In Applied Mechanics And Engineering. 2022-02-01. Vol. 389, p. 114378. DOI : 10.1016/j.cma.2021.114378.

Population pharmacokinetic model selection assisted by machine learning

E. Sibieude; A. Khandelwal; P. Girard; J. S. Hesthaven; N. Terranova 

Journal Of Pharmacokinetics And Pharmacodynamics. 2022. Vol. 49, p. 257–270. DOI : 10.1007/s10928-021-09793-6.

Preface to Focused Issue on Discontinuous Galerkin Methods PREFACE

J. S. Hesthaven; J. Ryan; C-W. Shu; J. van der Vegt; Y. Xu et al. 

Communications On Applied Mathematics And Computation. 2022. Vol. 4, p. 1-2. DOI : 10.1007/s42967-021-00170-1.

Discovery of Slow Variables in a Class Of Multiscale Stochastic Systems Via Neural Networks

P. Zielinski; J. S. Hesthaven 

Journal of Nonlinear Science. 2022-08-01. Vol. 32, num. 4, p. 51. DOI : 10.1007/s00332-022-09808-7.

A hierarchical preconditioner for wave problems in quasilinear complexity

B. Bonev; J. S. Hesthaven 

SIAM Journal on Scientific Computing. 2022-01-27. Vol. 44, num. 1, p. A198-A229. DOI : 10.1137/20M1365958.

Logarithmic Gradient Transformation and Chaos Expansion of Ito Processes

M. H. Gorji 

Communications in Mathematics and Statistics. 2022. Vol. 10, p. 215–231. DOI : 10.1007/s40304-020-00219-2.

A data-driven shock capturing approach for discontinuous Galekin methods

J. Yu; J. S. Hesthaven; C. Yan 

Computers & Fluids. 2022-09-15. Vol. 245, p. 105592. DOI : 10.1016/j.compfluid.2022.105592.

Modeling synchronization in globally coupled oscillatory systems using model order reduction

N. Discacciati; J. S. Hesthaven 

Chaos. 2021-05-01. Vol. 31, num. 5, p. 053127. DOI : 10.1063/5.0031142.

Efficient algorithms for wave problems

B. Bonev / J. S. Hesthaven (Dir.)  

Lausanne, EPFL, 2021. 

Physics-informed machine learning for reduced-order modeling of nonlinear problems

W. Chen; Q. Wang; J. S. Hesthaven; C. Zhang 

Journal of Computational Physics. 2021-08-27. Vol. 446, p. 110666. DOI : 10.1016/j.jcp.2021.110666.

Structure-Preserving Reduced Basis Methods For Poisson Systems

J. S. Hesthaven; C. Pagliantini 

Mathematics Of Computation. 2021-07-01. Vol. 90, num. 330, p. 1701-1740. DOI : 10.1090/mcom/3618.

Fast screening of covariates in population models empowered by machine learning

E. Sibieude; A. Khandelwal; J. S. Hesthaven; P. Girard; N. Terranova 

Journal Of Pharmacokinetics And Pharmacodynamics. 2021-05-21. Vol. 48, p. 597–609. DOI : 10.1007/s10928-021-09757-w.

Non-Intrusive Reduced Order Modeling of Convection Dominated Flows Using Artificial Neural Networks with Application to Rayleigh-Taylor Instability

Z. Gao; Q. Liu; J. S. Hesthaven; B-S. Wang; W. S. Don et al. 

Communications In Computational Physics. 2021-07-01. Vol. 30, num. 1, p. 97-123. DOI : 10.4208/cicp.OA-2020-0064.

Pointwise error estimate in difference setting for the two-dimensional nonlinear fractional complex Ginzburg-Landau equation

Q. Zhang; J. S. Hesthaven; Z-z. Sun; Y. Ren 

Advances In Computational Mathematics. 2021-06-01. Vol. 47, num. 3, p. 35. DOI : 10.1007/s10444-021-09862-x.

Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks

L. Schwander; D. Ray; J. S. Hesthaven 

Journal Of Computational Physics. 2021-04-15. Vol. 431, p. 110144. DOI : 10.1016/j.jcp.2021.110144.

A phenomenological extended-reaction boundary model for time-domain wave-based acoustic simulations under sparse reflection conditions using a wave splitting method

F. Pind; C-H. Jeong; J. S. Hesthaven; A. P. Engsig-Karup; J. Stromann-Andersen 

Applied Acoustics. 2021-01-15. Vol. 172, p. 107596. DOI : 10.1016/j.apacoust.2020.107596.

Entropic Fokker-Planck kinetic model

M. H. Gorji; M. Torrilhon 

Journal of Computational Physics. 2021-04-01. Vol. 430, p. 110034. DOI : 10.1016/j.jcp.2020.110034.

Hybrid high-resolution RBF-ENO method

J. S. Hesthaven; F. Mönkeberg 

Journal of Computational Physics: X. 2021. Vol. 12, p. 100089. DOI : 10.1016/j.jcpx.2021.100089.

Coupling kinetic and continuum using data-driven maximum entropy distribution

M. Sadr; Q. Wang; H. Gorji 

Journal of Computational Physics. 2021. Vol. 444, p. 110542. DOI : 10.1016/j.jcp.2021.110542.

Fokker-Planck-Poisson kinetics: Multi-phase flow beyond equilibrium

M. Sadr; M. Pfeiffer; H. Gorji 

Journal of Fluid Mechanics. 2021. Vol. 920, p. A46. DOI : 10.1017/jfm.2021.461.

Dynamical Reduced Basis Methods for Hamiltonian Systems

C. Pagliantini 

Numerische Mathematik. 2021. Vol. 148, p. 409–448. DOI : 10.1007/s00211-021-01211-w.

A Local Discontinuous Galerkin Method for Two-Dimensional Time Fractional Diffusion Equations

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

Communications On Applied Mathematics And Computation. 2020-12-01. Vol. 2, num. 4, p. 689-709. DOI : 10.1007/s42967-020-00065-7.

Time-domain room acoustic simulations with extended-reacting porous absorbers using the discontinuous Galerkin method

F. Pind; C-H. Jeong; A. P. Engsig-Karup; J. S. Hesthaven; J. Stromann-Andersen 

Journal Of The Acoustical Society Of America. 2020-11-01. Vol. 148, num. 5, p. 2851-2863. DOI : 10.1121/10.0002448.

Characterization of image spaces of Riemann-Liouville fractional integral operators on Sobolev spaces W-m,W-p (omega)

L. Zhao; W. Deng; J. S. Hesthaven 

Science China-Mathematics. 2020-11-18. Vol. 64, p. 2611–2636. DOI : 10.1007/s11425-019-1720-1.

Apparent diffusion coefficient measured by diffusion MRI of moving and deforming domains

I. Mekkaoui; J. Pousin; J. Hesthaven; J-R. Li 

Journal Of Magnetic Resonance. 2020-09-01. Vol. 318, p. 106809. DOI : 10.1016/j.jmr.2020.106809.

Controlling oscillations in spectral schemes using Artificial Neural Networks

L. Schwander 

2020-09-14.

Numerical methods for structural anomaly detection using model order reduction and data-driven techniques

C. Bigoni / J. S. Hesthaven (Dir.)  

Lausanne, EPFL, 2020. 

Massive parallel nodal discontinuous Galerkin finite element method simulator for room acoustics

A. Melander; E. Strøm; F. Pind; A. Engsig-Karup; C-H. Jeong et al. 

International Journal of High Performance Computing Applications. 2020-09-06. 

High-order essentially nonoscillatory methods based on radial basis functions

F. Mönkeberg / J. S. Hesthaven (Dir.)  

Lausanne, EPFL, 2020. 

Physics-informed machine learning for reduced-order modeling of nonlinear problems

W. Chen; Q. Wang; J. S. Hesthaven; C. Zhang 

2020-07-23. 

Rare event simulation for large-scale structures with local nonlinearities

Z. Zhang; J. S. Hesthaven 

Computer Methods In Applied Mechanics And Engineering. 2020-07-01. Vol. 366, p. 113051. DOI : 10.1016/j.cma.2020.113051.

STeCC: Smart Testing with Contact Counting Enhances Covid-19 Mitigation by Bluetooth App Based Contact Tracing

H. Gorji; M. Arnoldini; D. Jenny; W. Hardt; P. Jenny 

Medrxiv. 2020. DOI : 10.1101/2020.03.27.20045237.

Gaussian Process Regression for Maximum Entropy Distribution

M. Sadr; M. Torrilhon; H. Gorji 

Journal of Computational Physics. 2020. Vol. 418, p. 109644. DOI : 10.1016/j.jcp.2020.109644.

Nature of Crack Path Instabilities in Thin Sheets Cut by Blunt Objects

E. Hamm; I. Sivak; B. Roman 

Physical Review Letters. 2020-04-29. Vol. 124, num. 17, p. 174101. DOI : 10.1103/PhysRevLett.124.174101.

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

M. Kast; M. Guo; J. S. Hesthaven 

Computer Methods In Applied Mechanics And Engineering. 2020-06-01. Vol. 364, p. 112947. DOI : 10.1016/j.cma.2020.112947.

Systematic sensor placement for structural anomaly detection in the absence of damaged states

C. Bigoni; Z. Zhang; J. S. Hesthaven 

Computer Methods in Applied Mechanics and Engineering. 2020-08-18. Vol. 371, p. 113315. DOI : 10.1016/j.cma.2020.113315.

Simulation-based Anomaly Detection and Damage Localization: An application to Structural Health Monitoring

C. Bigoni; J. S. Hesthaven 

Computer Methods In Applied Mechanics And Engineering. 2020-05-01. Vol. 363, p. 112896. DOI : 10.1016/j.cma.2020.112896.

Constraint-aware neural networks for Riemann problems

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

Journal Of Computational Physics. 2020-05-15. Vol. 409, p. 109345. DOI : 10.1016/j.jcp.2020.109345.

Controlling oscillations in high-order Discontinuous Galerkin schemes using artificial viscosity tuned by neural networks

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

Journal Of Computational Physics. 2020-05-15. Vol. 409, p. 109304. DOI : 10.1016/j.jcp.2020.109304.

A Study of Several Artificial Viscosity Models within the Discontinuous Galerkin Framework

J. Yu; J. S. Hesthaven 

Communications In Computational Physics. 2020-05-01. Vol. 27, num. 5, p. 1309-1343. DOI : 10.4208/cicp.OA-2019-0118.

Two-Dimensional RBF-ENO Method on Unstructured Grids

J. S. Hesthaven; F. Monkeberg 

Journal Of Scientific Computing. 2020-03-11. Vol. 82, num. 3, p. 76. DOI : 10.1007/s10915-020-01176-2.

A Homotopy Method with Adaptive Basis Selection for Computing Multiple Solutions of Differential Equations

W. Hao; J. Hesthaven; G. Lin; B. Zheng 

Journal Of Scientific Computing. 2020-01-13. Vol. 82, num. 1, p. 19. DOI : 10.1007/s10915-020-01123-1.

Effective diffusion tensor measured by diffusion MRI of moving and deforming domains

I. Mekkaoui; J. Pousin; J. S. Hesthaven; J-R. Li 

Journal of Magnetic Resonance. 2020. 

A p-weighted limiter for the discontinuous Galerkin method on one-dimensional and two-dimensional triangular grids

W. Li; Q. Wang; Y-X. Ren 

Journal of Computational Physics. 2020-01-09. Vol. 407, p. 109246. DOI : 10.1016/j.jcp.2020.109246.

Waves at a fluid-solid interface: Explicit versus implicit formulation of boundary conditions using a discontinuous Galerkin method

K. Shukla; J. M. Carcione; J. S. Hesthaven; E. L’heureux 

The Journal of the Acoustical Society of America. 2020. Vol. 147, num. 5, p. 3136-3150. DOI : 10.1121/10.0001170.

An edge detector based on artificial neural network with application to hybrid Compact-WENO finite difference schemes

X. Wan; W-S. Don; Z. Gao; J. S. Hesthaven 

Journal Of Scientific Computing. 2020-06-03. Vol. 83, num. 3, p. 49. DOI : 10.1007/s10915-020-01237-6.

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. 2020. Vol. 410, p. 109402. DOI : 10.1016/j.jcp.2020.109402.

RBF Based CWENO Method

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

2020. ICOSAHOM 2018, London, UK, July 9-13, 2018. p. 191–201. DOI : 10.1007/978-3-030-39647-3_14.

Conservative Model Order Reduction for Fluid Flow

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

Quantification of Uncertainty: Improving Efficiency and Technology; Cham: Springer, 2020-07-31. p. 282.

Non-intrusive reduced-order modeling for fluid problems: A brief review

J. Yu; C. Yan; M. Guo 

Proceedings Of The Institution Of Mechanical Engineers Part G-Journal Of Aerospace Engineering. 2019-12-01.  p. 0954410019890721. DOI : 10.1177/0954410019890721.

Modeling extended-reaction boundary conditions in time-domain wave-based simulations of room acoustics

F. Pind; C-H. Jeong; J. S. Hesthaven; A. Engsig-Karup; J. Stromann-Andersen 

2019-10-31. 

Compact high order finite volume method on unstructured grids IV: Explicit multi-step reconstruction schemes on compact stencil

Y-S. Zhang; Y-X. Ren; Q. Wang 

Journal of Computational Physics. 2019-11-01. Vol. 396, p. 161-192. DOI : 10.1016/j.jcp.2019.06.054.

Time domain room acoustic simulations using the spectral element method

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

Journal Of The Acoustical Society Of America. 2019-06-01. Vol. 145, num. 6, p. 3299-3310. DOI : 10.1121/1.5109396.

Gaussian Process Regression for Maximum Entropy Distribution

M. Sadr; M. Torrilhon; H. Gorji 

2019

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, num. 6, p. 062005. 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, num. 6, p. 062008. 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

Comparative study between Cubic and Ellipsoidal Fokker-Planck kinetic models

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

AIAA Journal. 2019. Vol. 57, num. 6, p. 2524-2533. 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. Vol. 387, p. 430-445. DOI : 10.1016/j.jcp.2019.02.040.

A Minimally Intrusive Low-Memory Approach to Resilience for Existing Transient Solvers

C. D. Cantwell; A. S. Nielsen 

Journal Of Scientific Computing. 2019-01-01. Vol. 78, num. 1, p. 565-581. DOI : 10.1007/s10915-018-0778-7.

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

Model order reduction for large-scale structures with local nonlinearities

Z. Zhang; M. Guo; J. S. Hesthaven 

Computer Methods In Applied Mechanics and Engineering. 2019-08-15. Vol. 353, p. 491-515. DOI : 10.1016/j.cma.2019.04.042.

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

M. Sadr; M. Gorji 

Journal of Computational Physics. 2019. Vol. 378, p. 129-142. DOI : 10.1016/j.jcp.2018.11.005.

Entropy stable essentially non-oscillatory methods based on RBF reconstructions

J. S. Hesthaven; F. Mönkeberg 

Mathematical Modeling and Numerical Analysis. 2019. Vol. 53, num. 3, p. 925-958. DOI : 10.1051/m2an/2019011.

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. Vol. 141, p. 101429. DOI : 10.1016/j.ocemod.2019.101429.

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. 2019. Vol. 23, p. 595–615. DOI : 10.1007/s10596-019-9809-1.

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. 2019. Vol. 67, num. 8, p. 2115-2126. DOI : 10.1111/1365-2478.12831.

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 

Journal of Computational Physics. 2019. Vol. 390, p. 175-202. DOI : 10.1016/j.jcp.2019.03.050.

Structure-Preserving Model-Reduction of Dissipative Hamiltonian Systems

B. Maboudi Afkham; J. S. Hesthaven 

Journal of Scientific Computing. 2019. Vol. 81, p. 3–21. DOI : 10.1007/s10915-018-0653-6.

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.