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 …
Metamodel based high-fidelity stochastic analysis of composite laminates: A concise review with critical comparative assessment
This paper presents a concise state-of-the-art review along with an exhaustive comparative
investigation on surrogate models for critical comparative assessment of uncertainty in …
investigation on surrogate models for critical comparative assessment of uncertainty in …
Transfer learning based multi-fidelity physics informed deep neural network
S Chakraborty - Journal of Computational Physics, 2021 - Elsevier
For many systems in science and engineering, the governing differential equation is either
not known or known in an approximate sense. Analyses and design of such systems are …
not known or known in an approximate sense. Analyses and design of such systems are …
A Kriging-based decoupled non-probability reliability-based design optimization scheme for piezoelectric PID control systems
L Wang, Y Zhao, J Liu - Mechanical Systems and Signal Processing, 2023 - Elsevier
When dealing with optimization problems, the introduction of uncertainty will greatly
increase the difficulty of solving the problem. The traditional reliability-based design …
increase the difficulty of solving the problem. The traditional reliability-based design …
[HTML][HTML] The role of surrogate models in the development of digital twins of dynamic systems
Digital twin technology has significant promise, relevance and potential of widespread
applicability in various industrial sectors such as aerospace, infrastructure and automotive …
applicability in various industrial sectors such as aerospace, infrastructure and automotive …
Data-driven uncertainty quantification and sensitivity studies in free vibration behavior of bio-inspired helicoidal laminated composite cylindrical shells
The uncertainty in the ply orientation of bio-inspired helicoidal laminated composite
cylindrical shells is quantified. The frequencies obtained from the higher-order shear …
cylindrical shells is quantified. The frequencies obtained from the higher-order shear …
Random forest-based surrogates for transforming the behavioral predictions of laminated composite plates and shells from FSDT to Elasticity solutions
In the present work, a surrogate model based on the Random Forest (RF) machine learning
is employed for transforming the First-order Shear Deformation Theory (FSDT) based …
is employed for transforming the First-order Shear Deformation Theory (FSDT) based …
[หนังสือ][B] System-and data-driven methods and algorithms
An increasing complexity of models used to predict real-world systems leads to the need for
algorithms to replace complex models with far simpler ones, while preserving the accuracy …
algorithms to replace complex models with far simpler ones, while preserving the accuracy …
Thermal reliability-based design optimization using Kriging model of PCM based pin fin heat sink
This paper deals with the thermal reliability optimization of a pin fin heat sink (HS) filled with
phase change material (PCM) in order to study the heat transfer performance for cooling of …
phase change material (PCM) in order to study the heat transfer performance for cooling of …
[HTML][HTML] A dimension-wise method and its improvement for multidisciplinary interval uncertainty analysis
L Wang, C **ong, X Wang, M Xu, Y Li - Applied Mathematical Modelling, 2018 - Elsevier
Considering that uncertain factors widely exist in practical engineering, this study develops
an improved dimension-wise method for multidisciplinary interval uncertainty analysis, in …
an improved dimension-wise method for multidisciplinary interval uncertainty analysis, in …