SCHOLARS@TAMU

Lou, J., & Morel, J. E. (2021). A variable Eddington factor method with different spatial discretizations for the radiative transfer equation and the hydrodynamics/radiation-moment equations. Journal of Computational Physics. 439, 110393-110393.

Till, A. T., Adams, M. L., & Morel, J. E. (2021). The Finite-Element with Discontiguous-Support Method. Nuclear Science and Engineering. 196(1), 53-74.

Vermaak, J., Ragusa, J. C., & Morel, J. E. (2021). Massively Parallel Transport Sweeps on Meshes with Cyclic Dependencies. Journal of Computational Physics. 425, 109892-109892.

Hanophy, J., Southworth, B. S., Li, R., Manteuffel, T., & Morel, J. (2020). Parallel Approximate Ideal Restriction Multigrid for Solving the SN Transport Equations. Nuclear Science and Engineering. 194(11), 989-1008.

Zhang, Y., Ragusa, J. C., & Morel, J. E. (2020). Model Error Estimation for the Simplified PN Radiation Transport Equations. Nuclear Science and Engineering. 194(10), 903-926.

Larsen, E. W., & Morel, J. E. (2010). Advances in Discrete-Ordinates Methodology. Nuclear Computational Science. 1-84. Springer Netherlands.

Morel, J. E. (2006). Discrete-Ordinates Methods for Radiative Transfer in the Non-Relativistic Stellar Regime. SPECTRAL AND HIGH ORDER METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS ICOSAHOM 2014. Lecture Notes in Computational Science and Engineering. 69-81. Springer-Verlag.

Hardy, Z., Morel, J., & Ahrens, C. (2019). Dynamic Mode Decompo- sition for Subcritical Metal Systems. M&C 2019: International Con- ference on Mathematics and Computational Methods Applied to Nu- clear Science and Engineering.

Behne, P., Ragusa, J., & Morel, J. (2019). Model Order Reduction for Sn Radiation Transport. M&C 2019: International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering.

Hanophy, J., Southworth, B., Manteuffel, T., Morel, J., & Li, R. (2019). Performance of Parallel Approximate Ideal Restriction Multigrid for Transport Applications. M&C 2019: International Con- ference on Mathematics and Computational Methods Applied to Nu- clear Science and Engineering.

Zhang, Y., & Morel, J. (2018). Transport Error Estimation via Non-Recursive Residual Monte Carlo. PHYSOR 2018: Reactor Physics Paving The Way Towards More Efficient Systems.

Bruss, D., Morel, J., & Ragusa, J. (2017). Adjoint-Based Uncer- tainty Quantification for Radiation Transport Calculations with Un- certain Cross-Section Data. https://www.kns.org/paper/inter paper/lists/n conf name/MC2017/, M&C 2017 - International Conference on Mathematics & Computational Methods Applied to Nuclear Science & Engineering.

Sheriffdeen, S., Ragusa, J. C., Morel, J. E., Adams, M. L., & Bui-Thanh, T. (2019). Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models.