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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Welcome
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Posts
Blog Post number 1
Published:
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portfolio
Two-way coupled Cloud-In-Cell modeling of non-isothermal particle-laden flows: a Subgrid Particle-Averaged Reynolds Stress-Equivalent (SPARSE) formulation
Published:
Together with Gustaaf Jacobs and H.S. Udaykumar, at San Diego State University I worked on developing a two-way coupled Cloud-In-Cell (CIC) formulation for particle-laden flows that accounts for cloud size and subgrid-scale stresses using averaging techniques, and for cloud deformation using methods from continuum mechanics. It traces a physical cloud of particles as a point and distributes its influence on the carrier flow via a multivariate Gaussian distribution function.
Multilevel Monte Carlo
Published:
Together with Daniel Tartakovsky and Sebastian Bosma, at Stanford University I developed an accelerated multilevel Monte Carlo approach via stratification/Latin hypercube sampling for the estimation of cumulative distribution functions.
Global sensitivity analysis and UQ for design accelerated by Deep Neural Networks (DNNs)
Published:
Together with Daniel Tartakosvky, Eric Hall and Markos Katsoulakis, at Stanford University I worked on developing DNN approaches to accelerate mutual information-based sensitivity studies and uncertainty quantification for design of multiscale systems.
Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning
Published:
Together with Svyatoslav Korneev, Kyle Pietrzyk and Morad Behandish, at PARC, a Xerox Company I worked on developing an approach for speeding up quality prediction for 3D printed parts generated through liquid metal jetting by using operator learning to predict the mapping between initial and final states of droplet depositions in a moving subdomain approach.
publications
Noise propagation in hybrid models of nonlinear systems: The Ginzburg-Landau equation
Published in Journal of Computational Physics, 2014
Abstract
Recommended citation: S. Taverniers, F.J. Alexander, and D.M. Tartakovsky. Noise propagation in hybrid models of nonlinear systems: The Ginzburg-Landau equation. J. Comp. Phys., 262:313-324 (2014). https://doi.org/10.1016/j.jcp.2014.01.015
Physics-based statistical learning approach to mesoscopic model selection
Published in Physical Review E, 2014
Abstract
Recommended citation: S. Taverniers, T.S. Haut, K. Barros, F.J. Alexander, and T. Lookman. Physics-based statistical learning approach to mesoscopic model selection. Phys. Rev. E 92, 053301 (2015). https://doi.org/10.1103/PhysRevE.92.053301
Conservative tightly-coupled simulations of stochastic multiscale systems
Published in Journal of Computational Physics, 2016
Abstract
Recommended citation: S. Taverniers, A.Y. Pigarov, and D.M. Tartakovsky. Conservative tightly-coupled simulations of stochastic multiscale systems. J. Comput. Phys., 313:400-414 (2016). https://doi.org/10.1016/j.jcp.2016.02.047
A tightly-coupled domain-decomposition approach for highly nonlinear stochastic multiphysics systems
Published in Journal of Computational Physics, 2017
Abstract
Recommended citation: S. Taverniers and D.M. Tartakovsky. A tightly-coupled domain-decomposition approach for highly nonlinear stochastic multiphysics systems. J. Comput. Phys., 330:884-901 (2017). https://doi.org/10.1016/j.jcp.2016.10.052
Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor
Published in Journal of Computational Physics, 2017
Abstract
Recommended citation: S. Taverniers and D.M. Tartakovsky. Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor. J. Comput. Phys., 348:139-150 (2017). https://doi.org/10.1016/j.jcp.2017.07.008
Two-way coupled Cloud-In-Cell modeling of non-isothermal particle-laden flows: A Subgrid Particle-Averaged Reynolds Stress-Equivalent (SPARSE) formulation
Published in Journal of Computational Physics, 2019
Abstract
Recommended citation: S. Taverniers, H.S. Udaykumar, and G.B. Jacobs. Two-way coupled Cloud-In-Cell modeling of non-isothermal particle-laden flows: A Subgrid Particle-Averaged Reynolds Stress-Equivalent (SPARSE) formulation. J. Comput. Phys., 390:595--618 (2019). https://doi.org/10.1016/j.jcp.2019.01.001
Estimation of distributions via multilevel Monte Carlo with stratified sampling
Published in Journal of Computational Physics, 2020
Abstract
Recommended citation: S. Taverniers and D.M. Tartakovsky. Estimation of distributions via multilevel Monte Carlo with stratified sampling. J. Comp. Phys., 419:109572 (2020). https://doi.org/10.1016/j.jcp.2020.109572
Accelerated multilevel Monte Carlo with kernel‐based smoothing and Latinized stratification
Published in Water Resources Research, 2020
Abstract
Recommended citation: S. Taverniers, S.B.M. Bosma, and D.M. Tartakovsky. Accelerated multilevel Monte Carlo with kernel‐based smoothing and Latinized stratification. Water Resources Res., 56, e2019WR026984 (2020). https://doi.org/10.1029/2019WR026984
GINNs: Graph-Informed Neural Networks for Multiscale Physics
Published in Journal of Computational Physics, 2021
Abstract
Recommended citation: E.J. Hall, S. Taverniers, M.A. Katsoulakis, and D.M. Tartakovsky. GINNs: Graph-Informed Neural Networks for Multiscale Physics. J. Comp. Phys., 433:110192 (2021). https://doi.org/10.1016/j.jcp.2021.110192
Mutual Information for explainable deep learning of multiscale systems
Published in Journal of Computational Physics, 2021
Abstract
Recommended citation: S. Taverniers, E.J. Hall, M.A. Katsoulakis, and D.M. Tartakovsky. Mutual Information for explainable deep learning of multiscale systems. J. Comp. Phys., 444:110551 (2021). https://doi.org/10.1016/j.jcp.2021.110551
A localized artificial diffusivity approach inspired by TVD schemes and its consistent application to compressible flows
Published in Stanford University Center for Turbulence Research Annual Research Briefs 2021, 2021
Abstract
Recommended citation: S. Mirjalili, S. Taverniers, H. Collis, M. Behandish, and A. Mani. A localized artificial diffusivity approach inspired by TVD schemes and its consistent application to compressible flows. CTR Annual Research Briefs., 169-182 (2021). http://web.stanford.edu/group/ctr/ResBriefs/2021/16_Mirjalili.pdf
Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning
Published in AI-Based Design and Manufacturing (ADAM) workshop at the 36th AAAI Conference on Artificial Intelligence (2022), 2022
Abstract
Recommended citation: S. Taverniers, S. Korneev, K.M. Pietrzyk, and M. Behandish. Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning. 36th AAAI Conference on Artificial Intelligence, (2022). https://arxiv.org/abs/2202.03665
Inverse asymptotic treatment: Capturing discontinuities in fluid flows via equation modification
Published in Journal of Computational Science, 2023
Abstract
Recommended citation: S. Mirjalili, S. Taverniers, H. Collis, M. Behandish, and A. Mani. Inverse asymptotic treatment: Capturing discontinuities in fluid flows via equation modification. <iJ. Comput. Sci., 73:102141 (2023). https://doi.org/10.1016/j.jocs.2023.102141
A multi-physics compiler for generating numerical solvers from differential equations
Published in arXiv, 2023
Abstract
Recommended citation: J.T. Maxwell III, M. Behandish, and S. Taverniers. A multi-physics compiler for generating numerical solvers from differential equations (2023). https://arxiv.org/abs/2311.16404
A finite element method to compute the damping rate and frequency of oscillating fluids inside microfluidic nozzles
Published in Journal of Computational Physics, 2025
Abstract
Recommended citation: S. Taverniers, S. Korneev, C. Somarakis, M. Behandish, and A.J. Lew. A finite element method to compute the damping rate and frequency of oscillating fluids inside microfluidic nozzles. <iInt. J. Numer. Meth. Fl., 0:1-18 (2025). https://doi.org/10.1002/fld.5373
talks
Cloud-In-Cell modeling of shocked particle-laden flows at a SPARSE
cost
Published:
Oral presentation at the 11th Southern California Flow Physics Symposium (So Cal Fluids XI).
A SPARSE
-cost CIC model for particle-laden flows with two-way inter-phase coupling
Published:
Oral presentation at the 12th Southern California Flow Physics Symposium (So Cal Fluids XII).
Two-way coupled cloud-in-cell modeling of non-isothermal particle-laden flows at a SPARSE
cost
Published:
Invited talk at Applied Mathematics seminar.
Statistical and physics-informed machine-learning approaches for multi-scale systems
Published:
Invited dealer talk.
Graph-Informed Neural Networks
Published:
Oral presentation at AAAI-MLPS 2021.
Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning
Published:
Oral presentation at AAAI-ADAM 2022.