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Publication search results
found 9 matches
- 2019
- Steven Atkinson, Nicholas Zabaras:
Structured Bayesian Gaussian process latent variable model: Applications to data-driven dimensionality reduction and high-dimensional inversion. J. Comput. Phys. 383: 166-195 (2019) - Gregory Beylkin, Lucas Monzón, Xinshuo Yang:
Reduction of multivariate mixtures and its applications. J. Comput. Phys. 383: 94-124 (2019) - Nicholas Geneva, Nicholas Zabaras:
Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks. J. Comput. Phys. 383: 125-147 (2019) - Chitrarth Lav, Richard D. Sandberg, Jimmy Philip:
A framework to develop data-driven turbulence models for flows with organised unsteadiness. J. Comput. Phys. 383: 148-165 (2019) - Yixin Lin, G. R. Liu, Guangyu Wang:
A particle-based free surface detection method and its application to the surface tension effects simulation in smoothed particle hydrodynamics (SPH). J. Comput. Phys. 383: 196-206 (2019) - Ju Liu, Alison L. Marsden:
A robust and efficient iterative method for hyper-elastodynamics with nested block preconditioning. J. Comput. Phys. 383: 72-93 (2019) - Henning Scheufler, Johan Roenby:
Accurate and efficient surface reconstruction from volume fraction data on general meshes. J. Comput. Phys. 383: 1-23 (2019) - Brian C. Vermeire, Niki A. Loppi, Peter E. Vincent:
Optimal Runge-Kutta schemes for pseudo time-stepping with high-order unstructured methods. J. Comput. Phys. 383: 55-71 (2019) - Zhiguo Yang, Lianlei Lin, Suchuan Dong:
A family of second-order energy-stable schemes for Cahn-Hilliard type equations. J. Comput. Phys. 383: 24-54 (2019)
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