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Modeling thermal states for complex space missions, such as the surface exploration of airless bodies, requires high computation, whether used in ground-based analysis for spacecraft design or during onboard reasoning for autonomous…

Machine Learning · Computer Science 2024-09-06 Manaswin Oddiraju , Zaki Hasnain , Saptarshi Bandyopadhyay , Eric Sunada , Souma Chowdhury

We apply nested-sampling (NS) Bayesian analysis [AshtonEA22] to a model for the transport of MHD-scale solar wind fluctuations. The dual objectives are to obtain improved constraints on parameters present in the turbulence transport model…

Solar and Stellar Astrophysics · Physics 2024-12-12 Mark Bishop , Sean Ougthon , Tulasi Parashar , Yvette Perrott

Airport performance prediction with a reasonable look-ahead time is a challenging task and has been attempted by various prior research. Traffic, demand, weather, and traffic management actions are all critical inputs to any prediction…

Machine Learning · Computer Science 2021-11-09 Liya Wang , Alex Tien , Jason Chou

Constructing reduced models for turbulent transport is essential for accelerating profile predictions and enabling many-query tasks such as uncertainty quantification, parameter scans, and design optimization. This paper presents…

We set up a mapping procedure able to translate the evolution of the radial profile of fast ions, interacting with Toroidal Alfv\'en Eigenmodes, into the dynamics of an equivalent one dimensional bump-on-tail system. We apply this mapping…

In this work, we study the interplay between triangularity and micro-tearing turbulence using linear and nonlinear flux tube GENE simulations. We consider scenarios with negative and positive triangularity plasma shaping taken from existing…

Plasma Physics · Physics 2025-07-29 Alessandro Balestri , Justin Ball , Stefano Coda

In this paper we develop a framework for moment-based adaptive time integration of deterministic multifrequency thermal radiation transpot (TRT). We generalize our recent semi-implicit-explicit (IMEX) integration framework for gray TRT to…

Numerical Analysis · Mathematics 2026-02-11 Ben S. Southworth , Steven Walton , Steven B. Roberts , HyeongKae Park

This paper uses the gyro-moment (GM) approach as a multi-fidelity tool to explore the effect of triangularity on tokamak edge turbulence. Considering experimental data from an L-mode DIII-D discharge, we conduct gyrokinetic (GK) simulations…

Plasma Physics · Physics 2024-07-19 A. C. D. Hoffmann , P. Ricci

We derive the transient-time correlation function (TTCF) expression for the computation of phase variables of inhomogenous confined atomistic fluids undergoing boundary-driven planar shear (Couette) flow at constant pressure. Using…

Soft Condensed Matter · Physics 2022-05-24 Luca Maffioli , Edward R. Smith , James P. Ewen , Peter J. Daivis , Daniele Dini , B. D. Todd

Temperature dependence of the tunnel magnetoresistance (TMR) was calculated in range of the quantum-ballistic model in the magnetic tunnel junctions (MTJs) with embedded nanoparticles (NPs). The electron tunnel transport through NP was…

Mesoscale and Nanoscale Physics · Physics 2016-03-28 Arthur Useinov , Chih-Huang Lai

Separated flow transition is a very popular phenomenon in gas turbines, especially low-pressure turbines (LPT). Low-fidelity simulations are often used for gas turbine design. However, they are unable to predict separated flow transition…

Fluid Dynamics · Physics 2024-09-13 Harshal D. Akolekar

Time integrated spectroscopic measurements are carried out to characterize transient plasma stream produced in a coaxial pulsed plasma accelerator. This method allows the estimation of different plasma parameters and its evolution with…

Plasma Physics · Physics 2020-08-04 A. Ahmed , S. Singha , S. Borthakur , N. K. Neog , T. K. Borthakur , J. Ghosh

The transport of heat and particles in the relatively collisional edge regions of magnetically confined plasmas is a scientifically challenging and technologically important problem. Understanding and predicting this transport requires the…

Plasma Physics · Physics 2017-04-26 Ben Dudson , Jarrod Leddy

The understanding of the material properties of the layered transition metal dichalcogenides (TMDs) is critical for their applications in structural composites. The data-driven machine learning (ML) based approaches are being developed in…

This study presents novel predictive models using Graph Neural Networks (GNNs) for simulating thermal dynamics in Laser Powder Bed Fusion (L-PBF) processes. By developing and validating Single-Laser GNN (SL-GNN) and Multi-Laser GNN (ML-GNN)…

Machine Learning · Computer Science 2024-07-22 Riddhiman Raut , Amit Kumar Ball , Amrita Basak

Science-based simulation tools such as Finite Element (FE) models are routinely used in scientific and engineering applications. While their success is strongly dependent on our understanding of underlying governing physical laws, they…

Machine Learning · Computer Science 2021-03-31 Navid Zobeiry , Anoush Poursartip

Turbulent transport remains one of the principal obstacles to achieving efficient magnetic confinement in fusion devices. Two of the dominant drivers of the turbulence are microscale instabilities fuelled by electron- and ion-temperature…

Spherical tokamaks (STs) have many desirable features that make them a suitable choice for fusion power plants. To understand their confinement properties, accurate calculation of turbulent micro-instabilities is necessary for tokamak…

The present study assesses RANS-based turbulence models to simulate isothermal flow in a combustor representing a constituent can combustor of can-annular configuration used in jet engines. Two-equation models (standard $k-\epsilon$,…

Fluid Dynamics · Physics 2024-06-25 Aishvarya Kumar , Ram Prakash Bharti

Self-consistent full-size turbulent-transport simulations of the divertor and SOL of existing tokamaks have recently become feasible. This enables the direct comparison of turbulence simulations against experimental measurements. In this…