Current trends and applications of machine learning in tribology—A review
Machine learning (ML) and artificial intelligence (AI) are rising stars in many scientific
disciplines and industries, and high hopes are being pinned upon them. Likewise, ML and …
disciplines and industries, and high hopes are being pinned upon them. Likewise, ML and …
The role of artificial neural networks in prediction of mechanical and tribological properties of composites—a comprehensive review
The artificial neural network (ANN) approach motivated by the biological nervous system is
an inspiring mathematical tool that simulates many complicated engineering applications …
an inspiring mathematical tool that simulates many complicated engineering applications …
Enhanced ANN predictive model for composite pipes subjected to low-velocity impact loads
This paper presents an enhanced artificial neural network (ANN) to predict the displacement
in composite pipes impacted by a drop weight having different velocities. The impact …
in composite pipes impacted by a drop weight having different velocities. The impact …
Development of machine learning methods for mechanical problems associated with fibre composite materials: A review
M Liu, H Li, H Zhou, H Zhang, G Huang - Composites Communications, 2024 - Elsevier
Fibre composite materials (FCMs) are widely used in the aerospace, military defence, and
engineering manufacturing industries due to their high strength and high modulus …
engineering manufacturing industries due to their high strength and high modulus …
Artificial intelligence in materials modeling and design
In recent decades, the use of artificial intelligence (AI) techniques in the field of materials
modeling has received significant attention owing to their excellent ability to analyze a vast …
modeling has received significant attention owing to their excellent ability to analyze a vast …
A review of recent advances and applications of machine learning in tribology
In tribology, a considerable number of computational and experimental approaches to
understand the interfacial characteristics of material surfaces in motion and tribological …
understand the interfacial characteristics of material surfaces in motion and tribological …
Study on friction and wear behavior of polyphenylene sulfide composites reinforced by short carbon fibers and sub-micro TiO2 particles
Polyphenylene sulfide (PPS) composites filled with short carbon fibers (SCFs)(up to
15vol.%) and sub-micro-scale TiO2 particles (up to 7vol.%) were prepared by extrusion and …
15vol.%) and sub-micro-scale TiO2 particles (up to 7vol.%) were prepared by extrusion and …
Properties prediction of composites based on machine learning models: A focus on statistical index approaches
Composites have a wide range of applications across various industries due to their high
strength-to-weight ratio, corrosion resistance, durability, versatility, and lightweight …
strength-to-weight ratio, corrosion resistance, durability, versatility, and lightweight …
Quantification of the out-of-plane loading fatigue response of bistable CFRP laminates using a machine learning approach
This study proposes data-driven machine learning models to predict the nonlinear load-
displacement response in constant amplitude high-cycle fatigue loading of unsymmetric …
displacement response in constant amplitude high-cycle fatigue loading of unsymmetric …
Triboinformatics: Machine learning algorithms and data topology methods for tribology
Friction and wear are very common phenomena found virtually everywhere. However, it is
very difficult to predict tribological (ie related to friction and wear) structure–property …
very difficult to predict tribological (ie related to friction and wear) structure–property …