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Simulating abundances of stable water isotopologues, i.e. molecules differing in their isotopic composition, within climate models allows for comparisons with proxy data and, thus, for testing hypotheses about past climate and validating…

Atmospheric and Oceanic Physics · Physics 2023-11-28 Jonathan Wider , Jakob Kruse , Nils Weitzel , Janica C. Bühler , Ullrich Köthe , Kira Rehfeld

The potential energy loss of aging buildings traps building owners in a cycle of underfunding operations and overpaying maintenance costs. Energy auditors intending to generate an energy model of a target building for performance assessment…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Zihao Wang , Yu Hou , Lucio Soibelman

In the whole aircraft structural optimization loop, thermal analysis plays a very important role. But it faces a severe computational burden when directly applying traditional numerical analysis tools, especially when each optimization…

Machine Learning · Computer Science 2022-03-17 Kairui Bao , Wen Yao , Xiaoya Zhang , Wei Peng , Yu Li

Lattice thermal conductivity ($\kappa_L$) is a key physical property governing heat transport in solids, with direct relevance to thermoelectrics, thermal barrier coatings, and heat management applications. However, while experimental…

Materials Science · Physics 2025-11-24 Piyush Paliwal , Aftab Alam

Traditional entropy-based methods - such as cross-entropy loss in classification problems - have long been essential tools for representing the information uncertainty and physical disorder in data and for developing artificial intelligence…

Machine Learning · Computer Science 2026-01-06 Shun Wang , Shun-Li Shang , Zi-Kui Liu , Wenrui Hao

The imminent impact of immersive technologies in society urges for active research in real-time and interactive physics simulation for virtual worlds to be realistic. In this context, realistic means to be compliant to the laws of physics.…

Graphics · Computer Science 2023-02-10 Quercus Hernández , Alberto Badías , Francisco Chinesta , Elías Cueto

A surrogate model is developed to predict the convective heat transfer coefficient of liquid sodium (Na) flow within rectangular miniature heat sinks. Initially, kernel-based machine learning techniques and shallow neural network are…

Machine Learning · Computer Science 2025-09-09 Reza Pirayeshshirazinezhad

The thermodynamic entropy of coarse-grained (CG) models stands as one of the most important properties for quantifying the missing information during the CG process and for establishing transferable (or extendible) CG interactions. However,…

Chemical Physics · Physics 2024-04-10 Jaehyeok Jin , David R. Reichman

As global climate change intensifies, accurate weather forecasting has become increasingly important, affecting agriculture, energy management, environmental protection, and daily life. This study introduces a hybrid model combining…

Machine Learning · Computer Science 2024-10-22 Yuhao Gong , Yuchen Zhang , Fei Wang , Chi-Han Lee

Measurements of surface temperature fields are used to determine the heat transfer by conduction and convection from an inhomogeneously heated metallic tube into environment. For most of the here reported measurements we use a low-cost…

Applied Physics · Physics 2019-09-05 Samuel Jankových , Peter Bokes

Polyurethane (PU) possesses excellent thermal properties, making it an ideal material for thermal insulation. Incorporating Phase Change Materials (PCMs) capsules into Polyurethane (PU) has proven to be an effective strategy for enhancing…

Computational Physics · Physics 2023-11-17 Bokai Liu , Yizheng Wang , Timon Rabczuk , Thomas Olofsson , Weizhuo Lu

By combining ab initio quantum mechanics calculation and Drude model, electron temperature and lattice temperature dependent electron thermal conductivity is calculated and implemented into a multiscale model of laser material interaction,…

Computational Physics · Physics 2016-11-07 Pengfei Ji , Yuwen Zhang

In this paper, we propose an iterative convolution-thresholding method (ICTM) based on prediction-correction for solving the topology optimization problem in steady-state heat transfer equations. The problem is formulated as a constrained…

Numerical Analysis · Mathematics 2024-01-03 Huangxin Chen , Piaopiao Dong , Dong Wang , Xiao-Ping Wang

In human-centered intelligent building, real-time measurements of human thermal comfort play critical roles and supply feedback control signals for building heating, ventilation, and air conditioning (HVAC) systems. Due to the challenges of…

Computer Vision and Pattern Recognition · Computer Science 2018-12-18 Xiaogang Cheng , Bin Yang , Kaige Tan , Erik Isaksson , Liren Li , Anders Hedman , Thomas Olofsson , Haibo Li

Effective thermal conductivity is an important property of composites for different thermal management applications. Although physics-based methods, such as effective medium theory and solving partial differential equation, dominate the…

Computational Physics · Physics 2019-04-15 Qingyuan Rong , Han Wei , Hua Bao

This paper introduces an adaptive physics-guided neural network (APGNN) framework for predicting quality attributes from image data by integrating physical laws into deep learning models. The APGNN adaptively balances data-driven and…

Methodology · Statistics 2024-11-18 David Shulman , Itai Dattner

A novel, learning-based method for in situ estimation of soil properties using a physics-infused neural network (PINN) is presented. The network is trained to produce estimates of soil cohesion, angle of internal friction, soil-tool…

Robotics · Computer Science 2023-09-07 W. Jacob Wagner , Ahmet Soylemezoglu , Dustin Nottage , Katherine Driggs-Campbell

The lattice thermal conductivity ($\kappa_{\rm L} $) is a critical property of thermoelectrics, thermal barrier coating materials and semiconductors. While accurate empirical measurements of $\kappa_{\rm L} $ are extremely challenging, it…

Materials Science · Physics 2019-08-06 Lihua Chen , Huan Tran , Rohit Batra , Chiho Kim , Rampi Ramprasad

Wind power forecasting plays a critical role in modern energy systems, facilitating the integration of renewable energy sources into the power grid. Accurate prediction of wind energy output is essential for managing the inherent…

Machine Learning · Computer Science 2024-12-18 Ali Forootani , Danial Esmaeili Aliabadi , Daniela Thraen

Understanding thermal stress evolution in metal additive manufacturing (AM) is crucial for producing high-quality components. Recent advancements in machine learning (ML) have shown great potential for modeling complex multiphysics problems…

Machine Learning · Computer Science 2024-12-30 R. Sharma , Y. B. Guo