The papers that I have authored that have appeared in refereed journals are listed below. Where possible, I have included the actual paper.

Shin, Minwoo, Cory D. Hauck, and Ryan G. McClarren. “A Collision-Based Hybrid Method for the BGK Equation.” Journal of Computational Physics (2024): 112784.

Krief, Menahem, and Ryan G. McClarren. “Self-similar solutions for the non-equilibrium nonlinear supersonic Marshak wave problem.” Physics of Fluids 36.1 (2024).

Lan, Qing, Ryan G. McClarren, and Karthik Vishwanath. “Neural network-based inverse model for diffuse reflectance spectroscopy.” Biomedical Optics Express 14.9 (2023): 4725-4738.

Smith, Ethan, Ilham Variansyah, and Ryan McClarren. “Variable dynamic mode decomposition for estimating time eigenvalues in nuclear systems.” Nuclear Science and Engineering 197.8 (2023): 1769-1778.

Bennett, William, and Ryan G. McClarren. “Benchmark solutions for radiative transfer with a moving mesh and exact uncollided source treatments.” Nuclear Science and Engineering (2023): 1-31.

Pasmann, S., Variansyah, I., Kelley, C. T., & McClarren, R. (2023). “A Quasi–Monte Carlo Method With Krylov Linear Solvers for Multigroup Neutron Transport Simulations.” Nuclear Science and Engineering, 197(6), 1159-1173.

Whewell, Ben, et al. “Multigroup Neutron Transport Using a Collision-Based Hybrid Method.” Nuclear science and engineering (2023): 1-20.

Vander Wal, Michael D., Ryan G. McClarren, and Kelli D. Humbird. “Transfer learning as a method to reproduce high-fidelity non-local thermodynamic equilibrium opacities in simulations.” Journal of Plasma Physics 89.1 (2023): 895890103.

Peng, Zhuogang, and Ryan G. McClarren. “A sweep-based low-rank method for the discrete ordinate transport equation.” Journal of Computational Physics 473 (2023): 111748.

Pasmann, Sam, et al. “A Quasi–Monte Carlo Method With Krylov Linear Solvers for Multigroup Neutron Transport Simulations.” Nuclear Science and Engineering (2023): 1-15.

Vander Wal, Michael D., Ryan G. McClarren, and Kelli D. Humbird. “Transfer learning of high-fidelity opacity spectra in autoencoders and surrogate models.” IEEE Transactions on Plasma Science (2023).

Bennett, William, and Ryan G. McClarren. “Accurate solutions to time dependent transport problems with a moving mesh and exact uncollided source treatments.” Annals of Nuclear Energy 180 (2023): 109474.

Smith, Ethan, Ilham Variansyah, and Ryan McClarren. “Variable Dynamic Mode Decomposition For Estimating Time Eigenvalues in Nuclear Systems.” Nuclear Science and Engineering (2022): 1-10.

Kusch, Jonas, et al. “A low-rank power iteration scheme for neutron transport criticality problems.” Journal of Computational Physics 470 (2022): 111587.

Variansyah, Ilham, and Ryan G. McClarren. “Analysis of Population Control Techniques for Time-Dependent and Eigenvalue Monte Carlo Neutron Transport Calculations.” Nuclear Science and Engineering 196.11 (2022): 1280-1305.

Whewell, Ben, and Ryan G. McClarren. “Data reduction in deterministic neutron transport calculations using machine learning.” Annals of Nuclear Energy 176 (2022): 109276.

Bennett, William, and Ryan G. McClarren. “Benchmarks for infinite medium, time dependent transport problems with isotropic scattering.” Journal of Computational and Theoretical Transport 51.4 (2022): 205-221.

Vander Wal, Michael D., Ryan G. McClarren, and Kelli D. Humbird. “Neural network surrogate models for absorptivity and emissivity spectra of multiple elements.” Machine Learning with Applications 8 (2022): 100308.

Alldredge, Graham, Martin Frank, Jonas Kusch, and Ryan McClarren. “A realizable filtered intrusive polynomial moment method.” Journal of Computational and Applied Mathematics (2022): 114055.

McClarren, Ryan G., James A. Rossmanith, and Minwoo Shin. “Semi-implicit Hybrid Discrete HTN Approximation of Thermal Radiative Transfer.” Journal of Scientific Computing 90, no. 1 (2022): 1-29.

McClarren, Ryan G., and Terry S. Haut. “Data-driven acceleration of thermal radiation transfer calculations with the dynamic mode decomposition and a sequential singular value decomposition.” Journal of Computational Physics 448 (2022): 110756.

Peng, Zhuogang, and Ryan G. McClarren. “A high-order/low-order (HOLO) algorithm for preserving conservation in time-dependent low-rank transport calculations.” Journal of Computational Physics 447 (2021): 110672.

Bennett, William, and Ryan G. McClarren. “Self-similar solutions for high-energy density radiative transfer with separate ion and electron temperatures.” Proceedings of the Royal Society A 477, no. 2249 (2021): 20210119.

McClarren, Ryan G., I. L. Tregillis, Todd J. Urbatsch, and E. S. Dodd. “High-energy density hohlraum design using forward and inverse deep neural networks.” Physics Letters A 396 (2021): 127243.

Lan, Qing, Ryan G. McClarren, and Karthik Vishwanath. “Neural network forward model and transfer learning calibration from Monte Carlo to diffuse reflectance spectroscopy.” Optical Tomography and Spectroscopy of Tissue XIV. Vol. 11639. International Society for Optics and Photonics, 2021.

Latimer, C., József Kópházi, Matthew D. Eaton, and Ryan G. McClarren. “Spatial adaptivity of the SAAF and Weighted Least Squares (WLS) forms of the neutron transport equation using constraint based, locally refined, isogeometric analysis (IGA) with dual weighted residual (DWR) error measures.” Journal of Computational Physics 426 (2021): 109941.

Peng, Zhuogang, Ryan G. McClarren, and Martin Frank. “A low-rank method for two-dimensional time-dependent radiation transport calculations.” Journal of Computational Physics 421 (2020): 109735.

Holladay, Daniel A., Christopher J. Fontes, Wesley P. Even, and Ryan G. McClarren. “An accelerated approach to inline non-LTE modeling.” High Energy Density Physics 34 (2020): 100746.

Latimer, C., Kópházi, J., Eaton, M. D., & McClarren, R. G.  “A geometry conforming, isogeometric, weighted least squares (WLS) method for the neutron transport equation with discrete ordinate (SN) angular discretisation.” Progress in Nuclear Energy 121 (2020): 103238.

Latimer, C., Kópházi, J., Eaton, M. D., & McClarren, R. G. “A geometry conforming isogeometric method for the self-adjoint angular flux (SAAF) form of the neutron transport equation with a discrete ordinate (SN) angular discretisation.” Annals of Nuclear Energy 136 (2020): 107049.

Kusch, Jonas, Ryan G. McClarren, and Martin Frank. “Filtered stochastic galerkin methods for hyperbolic equations.” Journal of Computational Physics 403 (2020): 109073.

Humbird, Kelli D., J. Luc Peterson, and Ryan G. McClarren. “Transfer learning to model inertial confinement fusion experiments.” IEEE Transactions on Plasma Science (2019).

Humbird, Kelli D., J. Luc Peterson, and Ryan G. McClarren. “Parameter inference with deep jointly informed neural networks.” Statistical Analysis and Data Mining: The ASA Data Science Journal 12.6 (2019): 496-504.

Consuelo Fuenzalida, Carlos Jerez-Hanckes, and Ryan G. McClarren. “Uncertainty Quantification for Multigroup Diffusion Equations Using Sparse Tensor Approximations“, SIAM Journal on Scientific Computing 41.3 (2019).

R.G. McClarren “Calculating Time Eigenvalues of the Neutron Transport Equation with Dynamic Mode Decomposition“, Nuclear Science and Engineering, DOI: 10.1080/00295639.2018.1565014 (2019).

R.G. McClarren, “Time-Eigenvalue Estimation using the Dynamic Mode Decomposition“, Proceedings of NECDC 2018 (LA-UR-18-25770) (2018).

R.G. McClarren, Grace Cummings, and I.L. Tregillis “Machine Learning to Estimate Dante Response for Hohlraum Design“, Proceedings of NECDC 2018 (LA-UR-18-25817) (2018).

Humbird, K. D., J. L. Peterson, and R. G. McClarren. “Transfer learning to model inertial confinement fusion experiments.” arXiv preprint arXiv:1812.06055 (2018).

Humbird, K. D., J. L. Peterson, and R. G. McClarren. “Predicting the time-evolution of multi-physics systems with sequence-to-sequence models.” arXiv preprint arXiv:1811.05852 (2018).

Kusch, Jonas, Ryan G. McClarren, and Martin Frank. “Filtered Stochastic Galerkin Methods For Hyperbolic Equations.” arXiv preprint arXiv:1808.00819 (2018).

R.G. McClarren, and Alex R. Long. “One-Dimensional Models for Time-Dependent Transport in Solid Cylinders.” Journal of Computational and Theoretical Transport (2018): 1-14.

Anuar, Nuraslinda, Craig Marianno, and Ryan G. McClarren. “Employing MCNP to optimize experimental design for compressed sensing neutron source imaging.” Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (2018).

Zheng, Weixiong, Ryan G. McClarren, and Jim E. Morel. “An Accurate Globally Conservative Subdomain Discontinuous Least-Squares Scheme for Solving Neutron Transport Problems.” Nuclear Science and Engineering 189.3 (2018): 259-271.

Humbird, Kelli D., J. Luc Peterson, and Ryan G. McClarren. “Deep Neural Network Initialization With Decision Trees.” IEEE transactions on neural networks and learning systems(2018).

W. Zheng, R.G. McClarren, “Accurate least-squares PN scaling based on problem optical thickness for solving neutron transport problems“, Progress in Nuclear Energy 101 (2017): 394-400.

C. Pu, and R.G. McClarren. “Mathematical and Numerical Validation of the Simplified Spherical Harmonics Approach for Time-Dependent Anisotropic-Scattering Transport Problems in Homogeneous Media” , Journal of Computational and Theoretical Transport  46(5), 2017.

A. Gonzalez, and R.G. McClarren. “Approximate One-Dimensional Models for Monoenergetic Neutral Particle Transport in Ducts with Wall Migration.” Journal of Computational and Theoretical Transport 46(4), 242-257, 2017.

K.D. Humbird, R.G. McClarren, “Adjoint-based sensitivity analysis for high- energy density radiative transfer using flux-limited diffusion“, High Energy Density Physics, 22, 12-16.

M.P. Laiu, C.D. Hauck, R.G. McClarren, D.P. O’Leary, and A.L. Tits, “Positive Filtered Pn Moment Closures For Linear Kinetic Equations”, SIAM Journal on Numerical Analysis, 54(6), 3214-3238, 2017.

V.M. Laboure, R.G. McClarren, and Y. Wang, “Globally Conservative, Hybrid Self-Adjoint Angular Flux and Least-Squares Method Compatible with Void”, Nuclear Science and Engineering, 185(2), 294-306, 2017.

V.M. Laboure, R.G. McClarren, and C.D. Hauck, “Implicit filtered PN for high-energy density thermal radiation transport using discontinuous Galerkin finite elements”, Journal of Computational Physics, 321 624–643, 2016.

M. Hanus and R.G. McClarren, “On the Use of Symmetrized Transport Equation in Goal-Oriented Adaptivity“, Journal of Computational and Theoretical Transport , 45 (4), 1–20, 2016.

P.A. Vaquer, R.G. McClarren, and Y.A. Ayzman, “A Compressed Sensing Framework for Monte Carlo Transport Simulations Using Random Disjoint Tallies“,  Journal of Computational and Theoretical Transport, 45 (3), 219-229, 2016.

W. Zheng and R.G. McClarren, “Emulation-Based Calibration for Parameters in Parameterized Phonon Spectrum of ZrHx in TRIGA Reactor Simulations“, Nuclear Science and Engineering, 183 (1), 2016.

W. Zheng and R.G. McClarren, “Moment Closures Based on Minimizing the Residual of the P N Angular Expansion in Radiation Transport“, Journal of Computational Physics, 314, 682-699, 2016. ArXiv link.

W. Zheng and R.G. McClarren, “Semi-analytic Benchmark for Multi-group Free-gas Legendre Moments and the Application of Gauss quadrature in Generating Thermal Scattering Legendre Moments“, Annals of Nuclear Energy, 85 , 1131-1140, 2015.

A. Kumar, P.V. Tsvetkov, and R.G. McClarren, “Linear Regression and Sensitivity Analysis in Nuclear Reactor Design“, Annals of Nuclear Energy, 85 , 798-811, 2015.

A.M. Holgado, J.M. Ferguson, R.G. McClarren, “Anti-Diffusive-Like-Behaviour in Semi-Analytic Radiative Shocks via Multigroup Sn Transport“, High-Energy-Density Physics, 17A, 114–118, 2015.

R.G McClarren, M.L Adams, P.A. Vaquer, and C. Strack, “The asymptotic drift-diffusion limit of thermal neutrons“, Journal of Computational and Theoretical Transport, 43(1-7) 402-417, 2014. PDF

R. Smedley-Stevenson, R.G McClarren, “Asymptotic diffusion limit of cell temperature discretisation schemes for thermal radiation transport“, Journal of Computational Physics, 286, 214-235, 2015. PDF

T.K. Lane and R.G McClarren, “New self-similar radiation-hydrodynamics solutions in the high-energy density, equilibrium diffusion limit”, New Journal of Physics, 15 , 095013, 2013. PDF

C.D. Hauck and R.G. McClarren, “A Collision-Based Hybrid Method for Time Dependent, Linear, Kinetic Transport Equations”, Multiscale Modeling and Simulation,11(4), 1197-1227, 2013.

A. Chakraborty, B.K. Mallick, R.G. McClarren, et al. “Spline-based Emulators for Radiative Shock Experiments with Measurement Error”, Journal of the American Statistical Association, 108, Issue 502, 2013. PDF

H.F. Stripling, R.G. McClarren, et al. “A Calibration and Data Assimilation Method using the Bayesian MARS Emulator,” Annals of Nuclear Energy, 52, 103-112, 2012. PDF

R.P. Drake, F.W. Doss, R.G. McClarren, et al. “Radiative Effects in Radiative Shocks in Shock Tubes”, High Energy Density Physics, 7, 130-140, 2011. PDF

R.G. McClarren and D. Holladay, “Electron-Ion-Radiation Coupling Benchmarks For Verification of HEDP/IFE Codes”, Fusion Science and Technology, 60, 2, 600-604, 2011. PDF

R.G. McClarren, “Theoretical Aspects of the Simplified Pn  Equations”, Transport Theory and Statistical Physics, 39, 73-109, 2010. PDF

J.E. Morel and R.G. McClarren, “Stability of Explicit Radiation-Material Coupling in Radiative Transfer Calculations”, Journal of Quantitative Spectroscopy and Radiative Transfer, 112 , 10, 1518-1524, 2011. PDF

J.D. Densmore and R.G. McClarren, “Moment Analysis of Angular Approximation Methods for Time-Dependent Radiation Transport”, Transport Theory and Statistical Physics, 39, 192-233, 2010. PDF

R.G. McClarren, R.P. Drake, J.E. Morel, and J.P. Holloway, “Theory of Radiative Shocks in the Mixed, Optically Thick-Thin Case”, Physics of Plasmas, 17, 093301, 2010. PDF

R.G. McClarren and J.G. Wohlbier, “Analytic Solutions for Ion-Electron-Radiation Coupling With Radiation and Electron Diffusion”, Journal of Quantitative Spectroscopy and Radiative Transfer, 112, 119-130, 2010.

R.G. McClarren, D. Ryu , R.P. Drake, et al. , “A Physics Informed Emulator for Laser-Driven Radiating Shock Simulations”, Reliability Engineering and System Safety, 96 , 9, 1194-1207, 2010.

H.F. Stripling, M.L. Adams, R.G. McClarren, B.K. Mallick, “The Method of Manufactured Universes for Validating Uncertainty Quantification Methods”, Reliability Engineering and System Safety, 96 , 9, 1242-1256, 2010.

J.P. Holloway, D. Bingham, C.-C. Chou, F. Doss, R. Paul Drake, B. Fryxell, M. Grosskopf , B. van der Holst, Ryan McClarren, et al., “Predictive Modeling of a Radiative Shock System”, Reliability Engineering and System Safety, 96, 9, 1184-1193, 2010.

R.G. McClarren and R.P. Drake, “Anti-diffusive radiation flow in the cooling layer of a radiating shock”, Journal of Quantitative Spectroscopy and Radiative Transfer, 111,  2095-2105 2010.

R.G. McClarren and C.D. Hauck, “Robust and Accurate Filtered Spherical Harmonics Expansions for Radiative Transfer”, Journal of Computational Physics, 229 , 16, 5597-5614, 2010.

R.G. McClarren and C.D. Hauck, “Simulating Radiative Transfer with Filtered Spherical Harmonics”, Physics Letters A, 374 ,22, 2290-2296, 2010.

C.D. Hauck and R.G. McClarren, “Positive PN  Closures”, SIAM Journal on Scientific Computing, 32, 5, 2603-2626, 2010.

R.G. McClarren and T.J. Urbatsch, “A Modified Implicit Monte Carlo Method for Time-Dependent Radiative Transfer With Adaptive Material Coupling”, Journal of Computational Physics, 228, 16, 5669-5686, 2009.

C.D. Hauck, R.B. Lowrie, and R.G. McClarren, “Methods for Diffusive Relaxation in the PN  Equations”, Quaderni di Matematica, 24 , 197-244, 2009.

G. Thoreson, R.G. McClarren, and J.H. Chang, “High Resolution Time Integration for Sn  Radiation Transport,” Annals of Nuclear Energy, 36, 263-267, 2009.

R.G. McClarren and R.B. Lowrie, “The Effects of Slope Limiting on Asymptotic-Preserving Numerical Methods for Hyperbolic Conservation Laws,” Journal of Computational Physics, 227, 23, 9711-9726, 2008.

R.G. McClarren and R.B. Lowrie, “Manufactured Solutions for the P1  Radiation-Hydrodynamics Equations,” Journal of Quantitative Spectroscopy and Radiative Transfer, 109,15, 2590-2602, 2008.

R.G. McClarren, T.M. Evans, R.B. Lowrie, and J.D. Densmore, “Semi-Implicit Time Integration for PN  Thermal Radiative Transfer,” Journal of Computational Physics, 227, 7561-7586, 2008.

R.G. McClarren, J.P. Holloway, T.A. Brunner, “On Solutions to the Pn  Equations for Thermal Radiative Transfer,” Journal of Computational Physics, 227, 3, 2864-2885, 2008.

R.G. McClarren, J.P. Holloway, “Quasi-Linear Time Integration for the Pn Equations,” Nuclear Science and Engineering, 159 , 330-337, 2008.

R.G. McClarren, J.P. Holloway, T.A. Brunner, “Analytic P1 Solutions for Time-Dependent, Thermal Radiative Transfer in Several Geometries,” Journal of Quantitative Spectroscopy and Radiative Transfer, 109, 3, 389-403, 2008.

R.G. McClarren, J.P. Holloway, T.A. Brunner, and T.A. Mehlhorn, “A Quasi-Linear Implicit Riemann Solver for the Time-Dependent Pn  Equations,” Nuclear Science and Engineering, 155 , 290-299, 2007.