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 …
A review on physics-informed data-driven remaining useful life prediction: Challenges and opportunities
H Li, Z Zhang, T Li, X Si - Mechanical Systems and Signal Processing, 2024 - Elsevier
Remaining useful life (RUL) prediction, known as 'prognostics', has long been recognized as
one of the key technologies in prognostics and health management (PHM) to maintain the …
one of the key technologies in prognostics and health management (PHM) to maintain the …
Defect driven physics-informed neural network framework for fatigue life prediction of additively manufactured materials
Additive manufacturing (AM) has attracted many attentions because of its design freedom
and rapid manufacturing; however, it is still limited in actual application due to the existing …
and rapid manufacturing; however, it is still limited in actual application due to the existing …
[HTML][HTML] Correlation of residual stress, hardness and surface roughness with crack initiation and fatigue strength of surface treated additive manufactured AlSi10Mg …
Post-processing methods are widely used to address the issues caused by surface
imperfections and bulk defects in additive manufactured materials. In our previous studies …
imperfections and bulk defects in additive manufactured materials. In our previous studies …
Physics-guided, physics-informed, and physics-encoded neural networks and operators in scientific computing: Fluid and solid mechanics
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 …
High-temperature high-cycle fatigue performance and machine learning-based fatigue life prediction of additively manufactured Hastelloy X
L Lei, B Li, H Wang, G Huang, F Xuan - International Journal of Fatigue, 2024 - Elsevier
Uncertainties in fatigue life of laser powder bed fusion (L-PBF) additively manufactured parts
arise from microstructural heterogeneities and randomly dispersed defects generated during …
arise from microstructural heterogeneities and randomly dispersed defects generated during …
[HTML][HTML] Evaluating fatigue onset in metallic materials: Problem, current focus and future perspectives
E Salvati - International Journal of Fatigue, 2024 - Elsevier
The impact of mechanical fatigue on load-bearing metallic components and structures is
highly significant, encompassing economy, environment and safety aspects. For nearly 200 …
highly significant, encompassing economy, environment and safety aspects. For nearly 200 …
Defect sensitivity and fatigue design: Deterministic and probabilistic aspects in AM metallic materials
Fatigue performance in both traditional and additively manufactured materials is severely
affected by the presence of defects, which deserve special attention to ensure the in-service …
affected by the presence of defects, which deserve special attention to ensure the in-service …
Time lapse in situ X-ray imaging of failure in structural materials under cyclic loads and extreme environments
W Qian, S Wu, L Lei, Q Hu, C Liu - Journal of Materials Science & …, 2024 - Elsevier
Damage evolution characterization and performance evaluation under realistic conditions
are essential to ensure reliable operation of critical safety components. However, previous …
are essential to ensure reliable operation of critical safety components. However, previous …
[HTML][HTML] Machine learning for predicting fatigue properties of additively manufactured materials
Fatigue properties of materials by Additive Manufacturing (AM) depend on many factors
such as AM processing parameter, microstructure, residual stress, surface roughness …
such as AM processing parameter, microstructure, residual stress, surface roughness …