Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
A review on stochastic multiscale analysis for FRP composite structures
Fibre reinforced polymer (FRP) composites have been increasingly applied in engineering
structures especially for achieving high demands on structural performance, but they are …
structures especially for achieving high demands on structural performance, but they are …
[HTML][HTML] On quantifying uncertainty in lightning strike damage of composite laminates: A hybrid stochastic framework of coupled transient thermal-electrical simulations
Lightning strike damage can severely affect the thermo-mechanical performance of
composite laminates. It is essential to quantify the effect of lightning strikes considering the …
composite laminates. It is essential to quantify the effect of lightning strikes considering the …
Flexoelectricity and surface effects on coupled electromechanical responses of graphene reinforced functionally graded nanocomposites: A unified size-dependent …
Owing to inhomogeneous strain and high surface-to-volume ratio in nanostructures, it is
imperative to account for the flexoelectricity as well as surface effect while analyzing the size …
imperative to account for the flexoelectricity as well as surface effect while analyzing the size …
[HTML][HTML] Multi-fidelity machine learning based uncertainty quantification of progressive damage in composite laminates through optimal data fusion
RS Chahar, T Mukhopadhyay - Engineering Applications of Artificial …, 2023 - Elsevier
Recently machine learning (ML) based approaches have gained significant attention in
dealing with computationally intensive analyses such as uncertainty quantification of …
dealing with computationally intensive analyses such as uncertainty quantification of …
Stochastic buckling analysis of sandwich plates: the importance of higher order modes
The stochastic buckling behaviour of sandwich plates is presented considering uncertain
system parameters (material and geometric uncertainty). The higher-order-zigzag theory …
system parameters (material and geometric uncertainty). The higher-order-zigzag theory …
Machine learning based stochastic dynamic analysis of functionally graded shells
This paper presents stochastic dynamic characterization of functionally graded shells based
on an efficient Support Vector Machine assisted finite element (FE) approach. Different shell …
on an efficient Support Vector Machine assisted finite element (FE) approach. Different shell …
Printable carbon nanotube-liquid elastomer-based multifunctional adhesive sensors for monitoring physiological parameters
Developing a printed elastomeric wearable sensor with good conformity and proper
adhesion to skin, coupled with the capability of monitoring various physiological parameters …
adhesion to skin, coupled with the capability of monitoring various physiological parameters …
Machine learning aided stochastic structural free vibration analysis for functionally graded bar-type structures
This paper presents a machine learning aided stochastic free vibration analysis for
functionally graded (FG) bar-type structures through finite element method (FEM). The …
functionally graded (FG) bar-type structures through finite element method (FEM). The …
On machine learning assisted data-driven bridging of FSDT and HOZT for high-fidelity uncertainty quantification of laminated composite and sandwich plates
First-order shear deformation theory (FSDT) is less accurate compared to higher-order
theories like higher-order zigzag theory (HOZT). In case of large-scale simulation-based …
theories like higher-order zigzag theory (HOZT). In case of large-scale simulation-based …