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The passive safety is a crucial feature of advanced nuclear reactor (Gen IV) design. During loss of power scenarios, the downcomer plays a crucial role. The fluid-flow behavior in the downcomer can involve forced to mixed to natural…

Fluid Dynamics · Physics 2022-03-29 Tri Nguyen , Elia Merzari , Cheng-Kai Tai , Igor A. Bolotnov

A new analysis technique for the inference of degree of dissociation of weakly collisional hydrogen plasmas was developed and tested with an experiment. Neutrals in low temperature plasmas are critical to a wide range of plasma-based…

Plasma Physics · Physics 2025-05-05 Bin Ahn

Grand Canonical Monte Carlo is an important method for performing molecular-level simulations and assisting the study and development of nanoporous materials for gas capture application. These simulations are based on the use of force…

Understanding the thermal behavior of additive manufacturing (AM) processes is crucial for enhancing the quality control and enabling customized process design. Most purely physics-based computational models suffer from intensive…

Machine Learning · Computer Science 2023-01-20 Shuheng Liao , Tianju Xue , Jihoon Jeong , Samantha Webster , Kornel Ehmann , Jian Cao

For a sustained human presence on the Moon, robust in-situ resource utilisation supply chains to provide consumables and propellant are necessary. A promising process is molten salt electrolysis, which typically requires temperatures in…

Computational Physics · Physics 2025-12-13 Julius Mercz , Philipp Reiss , Christian Reiter

LES/PDF approaches can be used for simulating challenging turbulent combustion configurations with strong turbulence chemistry interactions. Transported PDF methods are computationally expensive compared to flamelet-like turbulent…

Fluid Dynamics · Physics 2023-10-27 Ashish S. Newale , Pushan Sharma , Stephen B. Pope , Perrine Pepiot

This article proposes a novel high-performance computing approach for the prediction of the temperature field in powder bed fusion (PBF) additive manufacturing processes. In contrast to many existing approaches to part-scale simulations,…

Computational Engineering, Finance, and Science · Computer Science 2023-09-18 Sebastian D. Proell , Peter Munch , Martin Kronbichler , Wolfgang A. Wall , Christoph Meier

While multiple sensors are used for real-time monitoring in additive manufacturing, not all provide practical or reliable process insights. For example, high-speed X-ray imaging offers valuable spatial information about subsurface melt pool…

Machine Learning · Computer Science 2025-09-04 Satyajit Mojumder , Pallock Halder , Tiana Tonge

Metal hydrides are promising candidates for hydrogen storage applications. From a materials discovery perspective, an accurate, efficient computational workflow is urgently required that can rapidly analyze/predict thermodynamic properties…

Materials Science · Physics 2023-08-08 Swati Rana , Dayadeep S. Monder , Abhijit Chatterjee

Aim: We present an improved database of temperature dependent rate coefficients for rotational state-to-state transitions in H$_{2}$O + H$_{2}$O collisions. The database includes 231 transitions between the lower $para$- and 210 transitions…

Chemical Physics · Physics 2023-10-19 Bikramaditya Mandal , Dmitri Babikov

This study presents the MATRICS framework (Modeling Aggregated Tensors for Relativistic Ion Collision Simulations) that implements modular workflows to enable parallel execution of particle generation, grid construction, and tensor…

Computational Physics · Physics 2025-06-25 Lipei Du

Due to extreme chemical, thermal, and radiation environments, existing molten salt property databases lack the necessary experimental thermal properties of reactor-relevant salt compositions. Meanwhile, simulating these properties directly…

Materials Science · Physics 2024-05-20 Stephen T. Lam , Shubhojit Banerjee , Rajni Chahal

The development of nuclear fuels requires unsteady/transient testing for design process and qualification under postulated accident conditions. Breach, rupture, fracture, melting, and other fuel failure modes may occur during the use of…

Instrumentation and Detectors · Physics 2020-05-04 Nima Fathi , Patrick McDaniel , Nicolas Woolstenhulme , Cassiano de Oliveira , Lance Hone , Joshua Daw

Numerical models are widely used to simulate the earth system, but they are computationally expensive and often depend on many uncertain input parameters. Their effective use requires calibration and uncertainty quantification, which…

Methodology · Statistics 2026-03-06 Tristan Contant , Yawen Guan , Ander Wilson , Adrian K. Turner , Deborah Sulsky

Thermal errors in machine tools significantly impact machining precision and productivity. Traditional thermal error correction/compensation methods rely on measured temperature-deformation fields or on transfer functions. Most existing…

Machine Learning · Computer Science 2025-10-07 C. Coelho , M. Hohmann , D. Fernández , L. Penter , S. Ihlenfeldt , O. Niggemann

Materials with higher operating temperatures than today's state of the art can improve system performance in several applications and enable new technologies. Under most scenarios, a protective oxide scale with high melting temperatures and…

Materials Science · Physics 2020-07-27 Zachary D. McClure , Alejandro H. Strachan

Computer simulations are becoming an essential tool in many scientific fields from molecular dynamics to aeronautics. In glaciology, future predictions of sea level change require input from ice sheet models. Due to uncertainties in the…

We apply estimation theory to a system formed by two interacting trapped ions. By using the Fisher matrix formalism, we introduce a simple scheme for estimation of the temperature of the longitudinal vibrational modes of the ions. We use…

Quantum Physics · Physics 2022-05-26 O. P. de Sá Neto , H. A. S. Costa , G. A. Prataviera , M. C. de Oliveira

Phase diagrams serve as a highly informative tool for materials design, encapsulating information about the phases that a material can manifest under specific conditions. In this work, we develop a method in which Bayesian inference is…

Materials Science · Physics 2023-09-06 Timofei Miryashkin , Olga Klimanova , Vladimir Ladygin , Alexander Shapeev

We present a data-driven, differentiable neural network model designed to learn the temperature field, its gradient, and the cooling rate, while implicitly representing the melt pool boundary as a level set in laser powder bed fusion. The…