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Analytical finite-integral-transform and gradient-enhanced machine learning approach for thermoelastic analysis of FGM spherical structures with arbitrary properties
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作者 Palash Das Dipayan Mondal +2 位作者 Md.Ashraful Islam Md.Abdullah Al Mohotadi Prokash Chandra Roy 《Theoretical & Applied Mechanics Letters》 2025年第3期269-283,共15页
This study introduces a novel mathematical model that combines the finite integral transform(FIT)and gradientenhanced physics-informed neural network(g-PINN)to address thermomechanical problems in functionally graded ... This study introduces a novel mathematical model that combines the finite integral transform(FIT)and gradientenhanced physics-informed neural network(g-PINN)to address thermomechanical problems in functionally graded materials with varying properties.The model employs a multilayer heterostructure homogeneous approach within the FIT to linearize and approximate various parameters,such as the thermal conductivity,specific heat,density,stiffness,thermal expansion coefficient,and Poisson’s ratio.The provided FIT and g-PINN techniques are highly proficient in solving the PDEs of energy equations and equations of motion in a spherical domain,particularly when dealing with space-time dependent boundary conditions.The FIT method simplifies the governing partial differential equations into ordinary differential equations for efficient solutions,whereas the g-PINN bypasses linearization,achieving high accuracy with fewer training data(error<3.8%).The approach is applied to a spherical pressure vessel,solving energy and motion equations under complex boundary conditions.Furthermore,extensive parametric studies are conducted herein to demonstrate the impact of different property profiles and radial locations on the transient evolution and dynamic propagation of thermomechanical stresses.However,the accuracy of the presented approach is evaluated by comparing the g-PINN results,which have an error of less than 3.8%.Moreover,this model offers significant potential for optimizing materials in hightemperature reactors and chemical plants,improving safety,extending lifespan,and reducing thermal fatigue under extreme processing conditions. 展开更多
关键词 finite integral transform Gradient-enhanced physics-informed neural network Transient heat conduction Thermoelastic stresses Shock loads Functionally graded materials sphere
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Analytical modeling on the vibration response of a beam-stiffened Mindlin thick plate with free boundary conditions
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作者 Hui Guo Kai Zhang 《International Journal of Mechanical System Dynamics》 2023年第2期119-126,共8页
This paper presents a new analytical solution for the vibration response of a beamstiffened Mindlin plate having a completely free boundary condition by utilizing a finite cosine integral transform.In the solution,the... This paper presents a new analytical solution for the vibration response of a beamstiffened Mindlin plate having a completely free boundary condition by utilizing a finite cosine integral transform.In the solution,the unknown coupling force and moments at the beam/plate interface and the unknown modal constants from the integral transform are determined by the continuity and compatibility conditions at the interface as well as the boundary conditions.It provides an easily implemented tool for exploring complex edge value problems for a class of higher-order partial differential equations represented by fully free‐stiffened Mindlin thick plates.The validity of the model is evaluated by comparing the calculated free and forced vibration responses of the beam‐stiffened plate with those calculated using a beamstiffened thin plate and those from finite element analysis. 展开更多
关键词 VIBRATION beam-stiffened mindlin thick plate free boundary condition finite integral transform
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