Related papers: Modeling meso-scale energy localization in shocked…
Recent advances in combustion science have led to the generation of large volumes of data from high-fidelity simulations, detailed chemical-kinetic calculations and engine-relevant measurements and create new opportunities for data-driven…
The nucleation and propagation of disconnections play an essential role during twin growth. Atomistic methods can reveal such small structural features on twin facets and model their motion, yet are limited by the simulation length and time…
This paper aims to enhance the efficiency of validation and verification campaigns involving fuel sloshing phenomena. Our first contribution is the development of an open-source, high-fidelity and computationally efficient two-dimensional…
The paper presents an $ab$ $initio$ study of temperature-induced nanostructural evolution of hydrogen-rich voids in amorphous silicon. By using large $a$-Si models, obtained from classical molecular-dynamics simulations, with a realistic…
While robotics research continues to propose strategies for collision avoidance in human-robot interaction, the reality of constrained environments and future humanoid systems makes contact inevitable. To mitigate injury risks,…
Building design optimization often depends on physics-based simulation tools such as EnergyPlus, which, although accurate, are computationally expensive and slow. Surrogate models provide a faster alternative, yet most are…
Optimization and uncertainty quantification have been playing an increasingly important role in computational hemodynamics. However, existing methods based on principled modeling and classic numerical techniques have faced significant…
We construct a two-zone model to describe H and He burning on the surface of an accreting neutron star and use it to study the triggering of type I X-ray bursts. Although highly simplified, the model reproduces all of the bursting regimes…
From their birth in the manufacturing process, materials inherently contain defects that affect the mechanical behavior across multiple length and time-scales, including vacancies, dislocations, voids and cracks. Understanding, modeling,…
The response of materials to dynamical, or shock, loading is important to planetary science, aerospace engineering, and energetic materials. Thermal-activated processes, including chemical reactions and phase transitions, are significantly…
This paper introduces a novel two-stage machine learning-based surrogate modeling framework to address inverse problems in scientific and engineering fields. In the first stage of the proposed framework, a machine learning model termed the…
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…
We present a finite element-inspired hypergraph neural network framework for predicting flow-induced vibrations in freely oscillating cylinders. The surrogate architecture transforms unstructured computational meshes into node-element…
Through their lifetime sunspots undergo a change in their area and shape and, as they decay, they fragment into smaller structures. Here, for the first time we analyze the spatial structure of magnetohydrodynamic (MHD) slow body and fast…
We describe new scenarios of generating curvature perturbations when inflaton (curvaton) has significant interactions. We consider a ``spot'', which arises from interactions associated with enhanced symmetric point (ESP) on the trajectory.…
Despite the growing level of technological advancement that characterizes extrusion-deposition additive manufacturing technology, there remains a significant knowledge gap in fully understanding the process-structure-property relationship…
The present article addresses an early-stage attempt on replacing the analyticity-based sink strength terms in rate equations by surrogate models of machine learning representation. Here we emphasise, in the context of multiscale modelling,…
We study the chaotic-like behavior of cosmological simulations by quantifying how minute perturbations grow over time and manifest as macroscopic differences in galaxy properties. When we run pairs of 'shadow' simulations that are identical…
Fatigue crack growth is one of the most common types of deterioration in metal structures with significant implications on their reliability. Recent advances in Structural Health Monitoring (SHM) have motivated the use of structural…
A hybrid mesoscopic multi-particle collision model is used to study diffusion-influenced reaction kinetics. The mesoscopic particle dynamics conserves mass, momentum and energy so that hydrodynamic effects are fully taken into account.…