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In this study, we present the first simulation results of the formation of dislocation cell wall microstructures in tantalum subjected to shock loading. Dislocation patterns and cell wall formation are important to understanding the…

Materials Science · Physics 2023-05-04 Jaehyun Cho , Luke L. Hsiung , Robert E. Rudd , Sylvie Aubry

Uncertainties from model parameters and model discrepancy from small-scale models impact the accuracy and reliability of predictions of large-scale systems. Inadequate representation of these uncertainties may result in inaccurate and…

Methodology · Statistics 2014-12-18 K. Sham Bhat , David S. Mebane , Curtis B. Storlie , Priyadarshi Mahapatra

We investigate the structure and equilibrium linear-response dynamics of suspensions of hard colloidal dumbbells using Brownian Dynamics computer simulations. The focus lies on the dense fluid and plastic crystal states of the colloids with…

Soft Condensed Matter · Physics 2015-07-10 Nils Heptner , Joachim Dzubiella

Plastic deformation in polycrystals is governed by the interplay between intra-granular slip and grain boundary-mediated plasticity. However, while the role played by bulk dislocations is relatively well-understood, the contribution of…

Materials Science · Physics 2017-10-02 Nikhil Chandra Admal , Giacomo Po , Jaime Marian

We use atomistic simulations to investigate grain boundary (GB) phase transitions in el- emental body-centered cubic (bcc) metal tungsten. Motivated by recent modeling study of grain boundary phase transitions in [100] symmetric tilt…

Materials Science · Physics 2018-04-17 Timofey Frolov , Qiang Zhu , Tomas Oppelstrup , Jaime Marian , Robert E. Rudd

Molecular Dynamics (MD) simulations have been carried out to investigate the deformation behaviour of <110>/{111} body centered cubic (BCC) Fe nanowires under tensile and compressive loading. An embedded atom method (EAM) potential was used…

Materials Science · Physics 2014-09-12 G. Sainath , B. K. Choudhary , T. Jayakumar

Subject-specific modeling is a powerful tool in cardiovascular research, providing insights beyond the reach of current clinical diagnostics. Limitations in available clinical data require the incorporation of uncertainty into models to…

Applications · Statistics 2025-07-16 Amirreza Kachabi , Sofia Altieri Correa , Naomi C. Chesler , Mitchel J. Colebank

We perform a model-independent fit of the short-distance couplings $C_{7,9,10}$ within the Standard Model set of $b\to s\gamma$ and $b\to s\bar\ell\ell$ operators. Our analysis of $B \to K^* \gamma$, $B \to K^{(*)} \bar\ell\ell$ and $B_s…

High Energy Physics - Phenomenology · Physics 2012-08-10 Frederik Beaujean , Christoph Bobeth , Danny van Dyk , Christian Wacker

Inverse Uncertainty Quantification (UQ), or Bayesian calibration, is the process to quantify the uncertainties of random input parameters based on experimental data. The introduction of model discrepancy term is significant because…

Applications · Statistics 2019-07-24 Xu Wu , Koroush Shirvan , Tomasz Kozlowski

The Hubbard model, which augments independent-electron band theory with a single parameter to describe electron-electron correlations, is widely regarded to be the `standard model' of condensed matter physics. The model has been remarkably…

Strongly Correlated Electrons · Physics 2016-02-17 S. M. Griffin , P. Staar , T. C. Schulthess , M. Troyer , N. A. Spaldin

We simulate structure in the vicinity of different size nanovoids using a new variant of the Molecular Statics, wherein atomic structure in the vicinity of nanovoids and the parameters that define the displacements of atoms placed in…

Materials Science · Physics 2022-02-02 A. V. Nazarov , A. P. Melnikov , A. A. Mikheev , I. V. Ershova

This work introduces a model for large-strain, geometrically nonlinear elasto-plastic dynamics in single crystals. The key feature of our model is that the plastic dynamics are entirely driven by the movement of dislocations, that is,…

Materials Science · Physics 2022-02-11 Thomas Hudson , Filip Rindler

Prominent features of simulated moving bed (SMB) chromatography processes in the downstream processing is based on the determination of operating conditions. However, effects of different types of uncertainties have to be studied and…

Computational Engineering, Finance, and Science · Computer Science 2021-07-16 Qiao-Le He , Liming Zhao

Discrete models of dislocations in cubic crystal lattices having one or two atoms per unit cell are proposed. These models have the standard linear anisotropic elasticity as their continuum limit and their main ingredients are the elastic…

Materials Science · Physics 2009-11-13 L. L. Bonilla , A. Carpio , I. Plans

In many safety-critical applications such as autonomous driving and surgical robots, it is desirable to obtain prediction uncertainties from object detection modules to help support safe decision-making. Specifically, such modules need to…

Machine Learning · Computer Science 2018-11-29 Buu Phan , Rick Salay , Krzysztof Czarnecki , Vahdat Abdelzad , Taylor Denouden , Sachin Vernekar

Numerical modeling of morphodynamics presents significant challenges in engineering due to uncertainties arising from inaccurate inputs, model errors, and limited computing resources. Accurate results are essential for optimizing strategies…

Computation · Statistics 2026-01-07 Cédric Goeury , Fabien Souillé

Accurate predictions of thermo-mechanically coupled process in metals can lead to a reduction of cost and an increase of productivity in manufacturing processes such as forming. For modeling these coupled processes with the finite element…

Materials Science · Physics 2019-05-30 Jifeng Li , Ignacio Romero , Javier Segurado

Many extensions of the Standard Model predict large numbers of additional unstable particles whose decays in the early universe are tightly constrained by observational data. For example, the decays of such particles can alter the ratios of…

High Energy Physics - Phenomenology · Physics 2019-02-20 Keith R. Dienes , Jason Kumar , Patrick Stengel , Brooks Thomas

Calibration of computer models is a key step in making inferences, predictions, and decisions for complex science and engineering systems. We formulate and analyze a nonparametric Bayesian methodology for computer model calibration. This…

Methodology · Statistics 2025-12-01 Haiyi Shi , Lei Yang , Jiarui Chi , Troy Butler , Haonan Wang , Derek Bingham , Don Estep

The expected growth in wind energy capacity requires efficient and accurate models for wind farm layout optimization, control, and annual energy predictions. Although analytical wake models are widely used for these applications, several…

Fluid Dynamics · Physics 2023-02-16 Frederik Aerts , Luca Lanzilao , Johan Meyers
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