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New manufacturing techniques such as 3D printing have recently enabled the creation of previously infeasible chemical reactor designs. Optimizing the geometry of the next generation of chemical reactors is important to understand the…

Computational Engineering, Finance, and Science · Computer Science 2022-11-01 Tom Savage , Nausheen Basha , Omar Matar , Ehecatl Antonio Del-Rio Chanona

Additive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. Identifying promising configurations within such spaces presents a significant challenge for current…

Computational Engineering, Finance, and Science · Computer Science 2024-06-07 Tom Savage , Nausheen Basha , Jonathan McDonough , James Krassowski , Omar K Matar , Ehecatl Antonio del Rio Chanona

Developing accurate models for chemical reactors is often challenging due to the complexity of reaction kinetics and process dynamics. Traditional approaches require retraining models for each new system, limiting generalizability and…

Computational Engineering, Finance, and Science · Computer Science 2025-05-29 Zihao Wang , Zhe Wu

Multi-fidelity modelling arises in many situations in computational science and engineering world. It enables accurate inference even when only a small set of accurate data is available. Those data often come from a high-fidelity model,…

Machine Learning · Statistics 2022-04-12 Jiahao Zhang , Shiqi Zhang , Guang Lin

Accurate simulation of the printing process is essential for improving print quality, reducing waste, and optimizing the printing parameters of extrusion-based additive manufacturing. Traditional additive manufacturing simulations are very…

Graphics · Computer Science 2025-07-23 Dhruv Gamdha , Kumar Saurabh , Baskar Ganapathysubramanian , Adarsh Krishnamurthy

Computational studies of chemical reactions in complex environments such as proteins, nanostructures, or on surfaces require accurate and efficient atomistic models applicable to the nanometer scale. In general, an accurate parametrization…

Chemical Physics · Physics 2020-02-18 Christoph Brunken , Markus Reiher

This work introduces an innovative parallel, fully-distributed finite element framework for growing geometries and its application to metal additive manufacturing. It is well-known that virtual part design and qualification in additive…

Computational Engineering, Finance, and Science · Computer Science 2019-04-30 Eric Neiva , Santiago Badia , Alberto F. Martín , Michele Chiumenti

The need for efficient computational screening of molecular candidates that possess desired properties frequently arises in various scientific and engineering problems, including drug discovery and materials design. However, the large size…

Optimization and Control · Mathematics 2023-01-05 Hyun-Myung Woo , Xiaoning Qian , Li Tan , Shantenu Jha , Francis J. Alexander , Edward R. Dougherty , Byung-Jun Yoon

Due to their cost, experiments for inertial confinement fusion (ICF) heavily rely on numerical simulations to guide design. As simulation technology progresses, so too can the fidelity of models used to plan for new experiments. However,…

Plasma Physics · Physics 2024-06-11 J. Wang , N. Chiang , A. Gillette , J. L. Peterson

Building a new generation of fission reactors in the United States presents many technical and regulatory challenges. One important challenge is the need to share and present results from new high-fidelity, high-performance simulations in…

Computational Engineering, Finance, and Science · Computer Science 2014-07-11 Jay Jay Billings , Jordan H. Deyton , S. Forest Hull , Eric J. Lingerfelt , Anna Wojtowicz

This work presents a high-fidelity computational fluid dynamics (CFD) and data-driven modeling framework for assembly-level flow characterization in a four-loop pressurized water reactor (PWR). A full lower-plenum and core-inlet domain was…

Multi-fidelity Gaussian process is a common approach to address the extensive computationally demanding algorithms such as optimization, calibration and uncertainty quantification. Adaptive sampling for multi-fidelity Gaussian process is a…

Machine Learning · Statistics 2019-07-30 Sayan Ghosh , Jesper Kristensen , Yiming Zhang , Waad Subber , Liping Wang

Multi-fidelity models are of great importance due to their capability of fusing information coming from different numerical simulations, surrogates, and sensors. We focus on the approximation of high-dimensional scalar functions with low…

Numerical Analysis · Mathematics 2023-09-13 Francesco Romor , Marco Tezzele , Markus Mrosek , Carsten Othmer , Gianluigi Rozza

Challenges in multi-fidelity modeling relate to accuracy, uncertainty estimation and high-dimensionality. A novel additive structure is introduced in which the highest fidelity solution is written as a sum of the lowest fidelity solution…

Machine Learning · Computer Science 2021-04-09 Wei W. Xing , Akeel A. Shah , Peng Wang , Shandian Zhe Qian Fu , Robert. M. Kirby

High precision atomic data is indispensable for experiments involving studies of fundamental interactions, astrophysics, atomic clocks, plasma science, and others. We develop new parallel atomic structure codes and explore the difficulties…

Atomic Physics · Physics 2021-03-11 C. Cheung , M. S. Safronova , S. G. Porsev

The design of inertial fusion experiments is a complex task as driver energy must be delivered in a precise manner to a structured target to achieve a fast, but hydrodynamically stable, implosion. Radiation-hydrodynamics simulation codes…

Plasma Physics · Physics 2025-08-29 A. J. Crilly , P. W. Moloney , D. Shi , E. A. Ferdinandi

Nuclear fusion using magnetic confinement holds promise as a viable method for sustainable energy. However, most fusion devices have been experimental and as we move towards energy reactors, we are entering into a new paradigm of…

Plasma Physics · Physics 2023-10-04 Timothy Nunn , Vignesh Gopakumar , Sebastien Kahn

Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel and determining its reliability is critical for the success of advanced nuclear technologies. However, TRISO failure probabilities are small and the associated…

Simulation models of critical systems often have parameters that need to be calibrated using observed data. For expensive simulation models, calibration is done using an emulator of the simulation model built on simulation output at…

Methodology · Statistics 2023-08-24 Özge Sürer , Matthew Plumlee , Stefan M. Wild

As modern electronic devices are increasingly miniaturized and integrated, their performance relies more heavily on effective thermal management. Two-phase cooling methods enhanced by porous surfaces, which capitalize on thin-film…

Machine Learning · Computer Science 2023-10-31 Jonathan Tammer Eweis-LaBolle , Chuanning Zhao , Yoonjin Won , Ramin Bostanabad
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