Physics-guided, physics-informed, and physics-encoded neural networks in scientific computing
Recent breakthroughs in computing power have made it feasible to use machine learning
and deep learning to advance scientific computing in many fields, including fluid mechanics …
and deep learning to advance scientific computing in many fields, including fluid mechanics …
[HTML][HTML] 3D building model generation from MLS point cloud and 3D mesh using multi-source data fusion
The high-precision generation of 3D building models is a controversial research topic in the
field of smart cities. However, due to the limitations of single-source data, existing methods …
field of smart cities. However, due to the limitations of single-source data, existing methods …
Human trajectory prediction via neural social physics
Trajectory prediction has been widely pursued in many fields, and many model-based and
model-free methods have been explored. The former include rule-based, geometric or …
model-free methods have been explored. The former include rule-based, geometric or …
Physics-guided, physics-informed, and physics-encoded neural networks and operators in scientific computing: Fluid and solid mechanics
SA Faroughi, NM Pawar… - Journal of …, 2024 - asmedigitalcollection.asme.org
Advancements in computing power have recently made it possible to utilize machine
learning and deep learning to push scientific computing forward in a range of disciplines …
learning and deep learning to push scientific computing forward in a range of disciplines …
[HTML][HTML] Mechanisms of aortic dissection: from pathological changes to experimental and in silico models
Aortic dissection continues to be responsible for significant morbidity and mortality, although
recent advances in medical data assimilation and in experimental and in silico models have …
recent advances in medical data assimilation and in experimental and in silico models have …
Deep learning for computational hemodynamics: A brief review of recent advances
A Taebi - Fluids, 2022 - mdpi.com
Computational fluid dynamics (CFD) modeling of blood flow plays an important role in better
understanding various medical conditions, designing more effective drug delivery systems …
understanding various medical conditions, designing more effective drug delivery systems …
A novel agricultural machinery intelligent design system based on integrating image processing and knowledge reasoning
Agricultural machinery intelligence is the inevitable direction of agricultural machinery
design, and the systems in these designs are important tools. In this paper, to address the …
design, and the systems in these designs are important tools. In this paper, to address the …
LAFlowNet: A dynamic graph method for the prediction of velocity and pressure fields in left atrium and left atrial appendage
The blood flow patterns within the left atrium (LA) and left atrial appendage (LAA) are crucial
for diagnosing and treating thrombosis and stroke. Although computational fluid dynamics …
for diagnosing and treating thrombosis and stroke. Although computational fluid dynamics …
Meshing using neural networks for improving the efficiency of computer modelling
C Lock, O Hassan, R Sevilla, J Jones - Engineering with Computers, 2023 - Springer
This work presents a novel approach capable of predicting an appropriate spacing function
that can be used to generate a near-optimal mesh suitable for simulation. The main …
that can be used to generate a near-optimal mesh suitable for simulation. The main …
Bayesian Differentiable Physics for Cloth Digitalization
We propose a new method for cloth digitalization. Deviating from existing methods which
learn from data captured under relatively casual settings we propose to learn from data …
learn from data captured under relatively casual settings we propose to learn from data …