AI for tribology: Present and future
With remarkable learning capabilities and swift operational speeds, artificial intelligence (AI)
can assist researchers in swiftly extracting valuable patterns, trends, and associations from …
can assist researchers in swiftly extracting valuable patterns, trends, and associations from …
[HTML][HTML] Fluid injection-induced fault slip during unconventional energy development: A review
An unusual increase in seismicity rate near the development and production sites of
unconventional energy (eg, natural gas and geothermal fluids) has been attributed to …
unconventional energy (eg, natural gas and geothermal fluids) has been attributed to …
Investigating the influence of water on swelling deformation and mechanical behavior of mudstone considering water softening effect
T Wang, C Yan - Engineering Geology, 2023 - Elsevier
Mudstone not only swells and deforms but also be softened during water absorption
because it contains many hydrophilic clay minerals. To study the influence of water on the …
because it contains many hydrophilic clay minerals. To study the influence of water on the …
Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes
Predicting failure in solids has broad applications including earthquake prediction which
remains an unattainable goal. However, recent machine learning work shows that laboratory …
remains an unattainable goal. However, recent machine learning work shows that laboratory …
Deep learning aided inverse design of the buckling-guided assembly for 3D frame structures
Buckling-guided assembly of three-dimensional (3D) mesostructures from pre-defined 2D
precursor patterns has arisen increasing attention, owing to the compelling advantages in …
precursor patterns has arisen increasing attention, owing to the compelling advantages in …
Deep learning for laboratory earthquake prediction and autoregressive forecasting of fault zone stress
Earthquake forecasting and prediction have long and in some cases sordid histories but
recent work has rekindled interest based on advances in early warning, hazard assessment …
recent work has rekindled interest based on advances in early warning, hazard assessment …
Generative artificial intelligence GPT-4 accelerates knowledge mining and machine learning for synthetic biology
Knowledge mining from synthetic biology journal articles for machine learning (ML)
applications is a labor-intensive process. The development of natural language processing …
applications is a labor-intensive process. The development of natural language processing …
Microfracture behavior and energy evolution of heterogeneous mudstone subjected to moisture diffusion
Moisture has a great effect on the microstructure of mudstone and the stability of muddy
strata. Due to many clay minerals in mudstone, swelling deformation and even disintegration …
strata. Due to many clay minerals in mudstone, swelling deformation and even disintegration …
[HTML][HTML] Explainable machine learning for labquake prediction using catalog-driven features
S Karimpouli, D Caus, H Grover… - Earth and Planetary …, 2023 - Elsevier
Recently, Machine learning (ML) has been widely utilized for laboratory earthquake
(labquake) prediction using various types of data. This study pioneers in time to failure (TTF) …
(labquake) prediction using various types of data. This study pioneers in time to failure (TTF) …
Data-driven multiscale modelling of granular materials via knowledge transfer and sharing
Abstract Machine learning approaches have found immense potential to revolutionise the
constitutive modelling of granular materials. However, data scarcity poses a significant …
constitutive modelling of granular materials. However, data scarcity poses a significant …