Radiation heat transfer between human and cryocabin walls

The paper considers the particular case of intensive radiation heat transfer in the system consisting of a human body and cryocabin walls of cryosauna. Calculations for three models have been made, namely, human-vertical wall, which is arranged parallel to a human, human-vertical wall, which is positioned at a certain angle, and a human-cryosauna. Analytical calculations are compared with Ansys-bassed numerical calculations. The impact of radiation heat transfer in this radiation-convective heat transfer problem is estimated. Conclusions are drawn about taking into account the radiation heat transfer and a rational method for calculating this heat transfer problem.

Semianalytical Solution of Transient Heat Transfer for Laminated Structures under Time-Varying Boundary Conditions

In order to solve the transient heat transfer problem of the laminated structure, a semianalytical method based on calculus is adopted. First, the time domain is divided into tiny time segments; the analytical solution of transient heat transfer of laminated structures in the segments is derived by using the method of separation of variables. Then, the semianalytical solution of transient heat transfer in the whole time domain is obtained by circulation. The transient heat transfer of the three-layer structure is analyzed by the semianalytical solution. Three time-varying boundary conditions (a: square wave, b: triangular wave, and c: sinusoidal wave) are applied to the surface of the laminated structure. The influence of some key parameters on the temperature field of the laminated structure is analyzed. It is found that the surface temperature of the laminated structure increases fastest when heated by square wave, and the maximum temperature can reach at 377°C, the temperature rises the most slowly when heated by the triangular wave, and the maximum temperature is 347°C. The novelty of this work is that the analytical method is used to analyze the nonlinear heat transfer problem, which is different from the general numerical method, and this method can be applied to solve the heat transfer problem of general laminated structures.

A Multiple Regression Convolutional Neural Network for Estimating Multi-parameters Based on Overall Data in the Inverse Heat Transfer Problem

The inverse heat transfer problem (IHTP) is a central task for estimating parameters in heat transfer. It is ill-posedness that is characterised by instability and non-uniqueness of the solution. Recently, novel algorithms using deep learning and neural networks for application of various sparse data in the inverse heat transfer problem. In order to overcome the optimization problem of input nodes under sparse data, we try to use the overall data of the target as the basis for inversion. In this work, we used an improved convolutional neural network (CNN) to estimate multi-parameters in the inverse heat transfer problem. Computational fluid dynamics (CFD) and deep learning are fused to provide datasets for training of the proposed model. The proposed model was verified by experiments with a cubic cavity. Additionally, the improved CNN model was used to predict the different parameters of the more complex armored vehicle model. The results showed that the model has good prediction accuracy for estimating multi-parameters on different datasets. These attempts of introducing convolutional neural network to the IHTP in the present study were successful and it was significant for the study of the inverse heat transfer problem of estimating multi-parameters.

A quasi-transient coupling approach to the modeling of conjugate heat transfer in the autoclave

Structural aerospace composite parts are generally cured in an autoclave. To achieve a homogeneous curing, computational fluid dynamics simulations have been increasingly used in thermal optimization. However, a transient computational fluid dynamics simulation of autoclave processing is resource intensive. This article outlines the concept of a quasi-transient coupling strategy to deal with the conjugate heat transfer problem inside an autoclave. In this approach, a computational fluid dynamics model is coupled with a finite element method (FEM) model through incorporating an empirical-based analytic equation, which describes the dependence of the heat transfer coefficient on pressure and temperature, into the computational fluid dynamics computations. This approach bridges the temporal disparities between the fluid and the solid, thus minimizing the global computing time. To validate this method, two simulation cases have been studied. In both cases, two different coupling computations are compared, namely a full-transient simulation as the reference computation and the introduced quasi-transient simulation. First, the quasi-transient coupling approach is implemented by performing the transient heat transfer analysis on a flat plate. The results indicate that this approach can predict accurate transient temperature fields, and the computational effort is reduced by up to 87%. Subsequently, this method is used in a real autoclave and validated by known experimental data. The simulation results are in good agreement with the experimental results, with a mean temperature error lower than 1.9°C. This indicates the capability and efficiency of this approach in solving a conjugate heat transfer problem for autoclave processing.