Multiscale computational method for heat conduction problems of composite structures with diverse periodic configurations in different subdomains

AbstractThe present paper considers the linear static thermal stress analysis of composite structures by means of a shell finite element with variable through-thethickness kinematic. The temperature profile along the thickness direction is calculated by solving the Fourier heat conduction equation. The refined models considered are both Equivalent Single Layer (ESL) and Layer Wise (LW) and are grouped in the Unified Formulation by Carrera (CUF). These permit the distribution of displacements, stresses along the thickness of the multilayered shell to be accurately described. The shell element has nine nodes, and the Mixed Interpolation of Tensorial Components (MITC) method is used to contrast the membrane and shear locking phenomenon. The governing equations are derived from the Principle of Virtual Displacement (PVD). Cross-ply plate, cylindrical and spherical shells with simply-supported edges and subjected to bi-sinusoidal thermal load are analyzed.Various thickness ratios and curvature ratios are considered. The results, obtained with different theories contained in the CUF, are compared with both the elasticity solutions given in the literature and the analytical solutions obtained using the CUF and the Navier’s method. Finally, plates and shells with different lamination and boundary conditions are analyzed using high-order theories in order to provide FEM benchmark solutions.

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Multiscale Computational Method for Dynamic Thermo-Mechanical Problems of Composite Structures with Diverse Periodic Configurations in Different Subdomains

Journal of Scientific Computing ◽

10.1007/s10915-018-00904-z ◽

2019 ◽

Vol 79 (3) ◽

pp. 1630-1666 ◽

Cited By ~ 1

Author(s):

Hao Dong ◽

Xiaojing Zheng ◽

Junzhi Cui ◽

Yufeng Nie ◽

Zhiqiang Yang ◽

...

Keyword(s):

Composite Structures ◽

Computational Method

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A computational method to solve for the heat conduction temperature field based on data-driven approach

Thermal Science ◽

10.2298/tsci200822165l ◽

2021 ◽

pp. 165-165

Author(s):

Kun Li ◽

Shiquan Shan ◽

Qi Zhang ◽

Xichuan Cai ◽

Zhou Zhijun

Keyword(s):

Temperature Field ◽

Heat Conduction ◽

Steady State ◽

Transient State ◽

Absolute Error ◽

Computational Method ◽

Data Driven ◽

One Dimensional ◽

Data Driven Approach ◽

The One

In this paper, a computational method for solving for the one-dimensional heat conduction temperature field is proposed based on a data-driven approach. The traditional numerical solution requires algebraic processing of the heat conduction differential equations, and necessitates the use of a complex mathematical derivation process to solve for the temperature field. In this paper, a temperature field solution model called HTM (Hidden Temperature Method) is proposed. This model uses an artificial neural network to establish the correspondence relationship of the node temperature values during the iterative process, so as to obtain the "Data to Data" solution. In this work, one example of one-dimensional steady state and three examples of one-dimensional transient state are selected, and the calculated values are compared to those obtained by traditional numerical methods. The mean-absolute error(MAE)of the steady state is only 0.2508, and among the three transient cases, the maximum mean-square error(MSE) is only 2.6875, indicating that the model is highly accurate in both steady-state and transient conditions. This shows that the HTM simulation can be applied to the solution of the heat conduction temperature field. This study provides a basis for the further optimization of the HTM algorithm.

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