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A methodology for handling block-to-block coupling of nonconforming, multiblock summation-by-parts finite difference methods is proposed. The coupling is based on the construction of projection operators that move a finite difference grid…

Numerical Analysis · Mathematics 2021-06-03 Jeremy E. Kozdon , Lucas C. Wilcox

Inverse uncertainty quantification (UQ) tasks such as parameter estimation are computationally demanding whenever dealing with physics-based models, and typically require repeated evaluations of complex numerical solvers. When partial…

Machine Learning · Computer Science 2025-12-19 Filippo Zacchei , Paolo Conti , Attilio Alberto Frangi , Andrea Manzoni

The objective of this work is to assess the impact of parameter uncertainty on hypersonic aerothermal surface heating predictions in Reynolds-Averaged Navier-Stokes (RANS) simulations using non-intrusive uncertainty quantification (UQ)…

Fluid Dynamics · Physics 2024-05-28 Jeremy Redding , Nick Plewacki , Himakar Ganti , Luis Bravo , Prashant Khare

Neural network (NN) potentials promise highly accurate molecular dynamics (MD) simulations within the computational complexity of classical MD force fields. However, when applied outside their training domain, NN potential predictions can…

Chemical Physics · Physics 2023-07-28 Stephan Thaler , Gregor Doehner , Julija Zavadlav

The present paper describes the development of a novel and comprehensive computational framework to simulate solidification problems in materials processing, specifically casting processes. Heat transfer, solidification and fluid flow due…

Numerical Analysis · Computer Science 2020-10-06 Shantanu Shahane , Narayana Aluru , Placid Ferreira , Shiv G Kapoor , Surya Pratap Vanka

A finite element method for solving nonlinear differential equations on a grid, with potential applicability to computational fluid dynamics (CFD), is developed and tested. The current method facilitates the computation of solutions of a…

Computational Physics · Physics 2014-09-04 Jesper Tveit

The work focuses on gathering high-fidelity and low-fidelity numerical simulations data using Nektar++ (Solver based on Applied Mathematics) and XFOIL respectively. The utilization of the higher polynomial distribution in calculating the…

Machine Learning · Computer Science 2025-03-12 Swapnil Kumar

Many-body interactions can play a relevant role in water properties. Here we study by Monte Carlo simulations a coarse-grained model for bulk water that includes many-body interactions associated to water cooperativity. The model is…

Statistical Mechanics · Physics 2016-10-04 Luis Enrique Coronas , Valentino Bianco , Arne Zantop , Giancarlo Franzese

Attaining the ultimate precision remains a central objective in the engineering of nanoscale systems and the investigation of nonequilibrium processes. While thermodynamic and kinetic uncertainty relations establish fundamental precision…

Quantum Physics · Physics 2026-04-08 Hayato Yunoki , Yoshihiko Hasegawa

Quantitative prediction of thermodynamic properties in solution is essential for translating atomistic simulations into reliable chemical insight. As an exemplar system, the behaviour of CaCO$_3$ in water has been widely studied to…

We extend a class of recently derived thermodynamic uncertainty relations to vector-valued observables. In contrast to the scalar-valued observables examined previously, this multidimensional thermodynamic uncertainty relation provides a…

Statistical Mechanics · Physics 2019-10-22 Andreas Dechant

Multiphase systems are ubiquitous in engineering, biology, and materials science, where understanding their complex interactions and rheological behavior is crucial for advancing applications ranging from emulsion stability to cellular…

Fluid Dynamics · Physics 2025-10-27 Andres Santiago Espinosa-Moreno , Nicolas Moreno , Marco Ellero

In measurement-based quantum computing (MBQC), computation is carried out by a sequence of measurements and corrections on an entangled state. Flow, and related concepts, are powerful techniques for characterising the dependence of the…

Quantum Physics · Physics 2023-03-13 Robert I. Booth , Aleks Kissinger , Damian Markham , Clément Meignant , Simon Perdrix

Building on our previously introduced Multi-cell Monte Carlo (MC)^2 method for modeling phase coexistence, this paper provides important improvements for efficient determination of phase equilibria in solids. The (MC)^2 method uses multiple…

Materials Science · Physics 2020-07-01 Edwin Antillon , Maryam Ghazisaeidi

The modeling and uncertainty quantification of closed curves is an important problem in the field of shape analysis, and can have significant ramifications for subsequent statistical tasks. Many of these tasks involve collections of closed…

Machine Learning · Statistics 2023-03-15 Hengrui Luo , Justin D. Strait

We formulate a well posed interface formulation for canonical one-dimensional evaporation two-phase model problems (the Stefan and Sucking problems) commonly used to validate production codes. We focus on the interface between the vapor and…

Numerical Analysis · Mathematics 2026-04-28 Jan Nordström

As multimodal learning finds applications in a wide variety of high-stakes societal tasks, investigating their robustness becomes important. Existing work has focused on understanding the robustness of vision-and-language models to…

Machine Learning · Computer Science 2022-11-07 Gaurav Verma , Vishwa Vinay , Ryan A. Rossi , Srijan Kumar

In this paper we propose a general framework for the uncertainty quantification of quantities of interest for high-contrast single-phase flow problems. It is based on the generalized multiscale finite element method (GMsFEM) and multilevel…

Numerical Analysis · Mathematics 2015-06-18 Yalchin Efendiev , Bangti Jin , Michael Presho , Xiaosi Tan

Ventilated cavities in the wake of a two-dimensional bluff body are studied experimentally via time-resolved X-ray densitometry. With a systematic variation of flow velocity and gas injection rate, expressed as Froude number ($Fr$) and…

In this work, we consider the problem of bounding the values of a covariance function corresponding to a continuous-time stationary stochastic process or signal. Specifically, for two signals whose covariance functions agree on a finite…

Signal Processing · Electrical Eng. & Systems 2021-10-07 Filip Elvander , Johan Karlsson , Toon van Waterschoot