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Stochastic collocation (SC) is a well-known non-intrusive method of constructing surrogate models for uncertainty quantification. In dynamical systems, SC is especially suited for full-field uncertainty propagation that characterizes the…

Numerical Analysis · Mathematics 2023-10-18 Saibal De , Reese E. Jones , Hemanth Kolla

This paper aims to comprehensively investigate the efficacy of various Model Order Reduction (MOR) and deep learning techniques in predicting heat transfer in a pulsed jet impinging on a concave surface. Expanding on the previous…

Numerical Analysis · Mathematics 2024-02-19 Sajad Salavatidezfouli , Saeid Rakhsha , Armin Sheidani , Giovanni Stabile , Gianluigi Rozza

Bed load transport is the movement of particles along the top of a bed through rolling, saltation, and suspension created by turbulent lift above the bed surface. In recent years, there has been a resurgence of interest in the idea that bed…

Geophysics · Physics 2023-12-27 Mark W. McClure

The viscosity of the suspension consisting of fine particles dispersed in a Newtonian liquid diverges close to the jamming packing fraction. The contact microstructure in suspensions governs this macroscopic behavior in the vicinity of…

Soft Condensed Matter · Physics 2025-02-28 Armin Aminimajd , Joao Maia , Abhinendra Singh

The optimization of well locations and controls is an important step in the design of subsurface flow operations such as oil production or geological CO2 storage. These optimization problems can be computationally expensive, however, as…

Geophysics · Physics 2024-05-16 Haoyu Tang , Louis J. Durlofsky

Simulation-based inference techniques are indispensable for parameter estimation of mechanistic and simulable models with intractable likelihoods. While traditional statistical approaches like approximate Bayesian computation and Bayesian…

Methodology · Statistics 2024-03-08 Ryan P. Kelly , David J. Nott , David T. Frazier , David J. Warne , Chris Drovandi

Computational fluid dynamics (CFD) simulations, a critical tool in various engineering applications, often require significant time and compute power to predict flow properties. The high computational cost associated with CFD simulations…

Machine Learning · Computer Science 2022-05-18 Tongtao Zhang , Biswadip Dey , Krishna Veeraraghavan , Harshad Kulkarni , Amit Chakraborty

Data-driven surrogate models are increasingly adopted to accelerate vehicle design. However, open-source multi-fidelity datasets and empirical guidelines linking dataset size to model performance remain limited. This study investigates the…

Machine Learning · Computer Science 2026-01-21 Yiren Shen , Juan J. Alonso

For many systems in science and engineering, the governing differential equation is either not known or known in an approximate sense. Analyses and design of such systems are governed by data collected from the field and/or laboratory…

Machine Learning · Computer Science 2021-02-03 Souvik Chakraborty

Numerical solutions of partial differential equations (PDEs) require expensive simulations, limiting their application in design optimization, model-based control, and large-scale inverse problems. Surrogate modeling techniques seek to…

Computational Physics · Physics 2022-05-18 James Duvall , Karthik Duraisamy , Shaowu Pan

This paper presents the coupled model of a hydraulic fracturing and proppant transport. The former is described in terms of enhanced pseudo-3D model that considers height growth across two symmetric stress barriers, while the latter is…

The high-pressure transportation process of pipeline necessitates an accurate hydraulic transient simulation tool to prevent slack line flow and over-pressure, which can endanger pipeline operations. However, current numerical solution…

Computational Engineering, Finance, and Science · Computer Science 2024-09-18 Jian Du , Haochong Li , Qi Liao , Jun Shen , Jianqin Zheng , Yongtu Liang

We present a combined numerical and data-driven workflow for efficient prediction of nonlinear, instationary convection-diffusion-reaction dynamics on a two-dimensional phenotypic domain, motivated by macroscopic modeling of cancer cell…

Computational Engineering, Finance, and Science · Computer Science 2026-02-02 Michael Urs Lars Kastor , Jan Rottmayer , Anna Hundertmark , Nicolas Ralph Gauger

Machine-learning-based parameterizations (i.e. representation of sub-grid processes) of global climate models or turbulent simulations have recently been proposed as a powerful alternative to physical, but empirical, representations,…

Machine Learning · Computer Science 2023-09-20 Mohamed Aziz Bhouri , Liran Peng , Michael S. Pritchard , Pierre Gentine

The growing use of composite materials in engineering applications has accelerated the demand for computational methods to accurately predict their complex behavior. Multiscale modeling based on computational homogenization is a potentially…

Numerical Analysis · Mathematics 2024-10-18 N. Kovács , M. A. Maia , I. B. C. M. Rocha , C. Furtado , P. P. Camanho , F. P. van der Meer

Reservoir simulations are computationally expensive in the well control and well placement optimization. Generally, numerous simulation runs (realizations) are needed in order to achieve the optimal well locations. In this paper, we propose…

Machine Learning · Computer Science 2022-03-23 Haoyu Tang , Wennan Long

Aerodynamic optimization is crucial for developing eco-friendly, aerodynamic, and stylish cars, which requires close collaboration between aerodynamicists and stylists, a collaboration impaired by the time-consuming nature of aerodynamic…

Machine Learning · Computer Science 2025-08-05 Sam Jacob Jacob , Markus Mrosek , Carsten Othmer , Harald Köstler

Understanding structure-property relations is essential to optimally design materials for specific applications. Two-scale simulations are often employed to analyze the effect of the microstructure on a component's macroscopic properties.…

Computational Engineering, Finance, and Science · Computer Science 2022-10-25 Theron Guo , Francesco A. B. Silva , Ondřej Rokoš , Karen Veroy

Aggregation and settling are crucial phenomena that involve particulate systems. For particle sizes of millimetre and above, there are reasonable accurate predicting tools. However for smaller particle sizes, there appears to be a void in…

Fluid Dynamics · Physics 2016-01-15 D D Liyanage , Rajika J K A Thamali , A A K Kumbalatara , J A Weliwita , S Witharana

Simulating reactive dissolution of solid minerals in porous media has many subsurface applications, including carbon capture and storage (CCS), geothermal systems and oil & gas recovery. As traditional direct numerical simulators are…

Machine Learning · Computer Science 2025-12-16 Marcos Cirne , Hannah Menke , Alhasan Abdellatif , Julien Maes , Florian Doster , Ahmed H. Elsheikh