Thermal Conductivity Design for Locally Orthotropic Materials

2013 ◽  
Vol 577-578 ◽  
pp. 437-440
Author(s):  
Romana Piat ◽  
Yuriy Sinchuk
Keyword(s):  
Thermal Conductivity ◽  
Computational Model ◽  
Optimization Problems ◽  
Hot Spot ◽  
Orthotropic Materials ◽  
Principal Stresses ◽  
Material Orientation ◽  
Elasticity Problems ◽  
Optimal Material ◽  
Orientation Optimization

In this paper the development of a computational model for the thermal conductivity design for locally orthotropic materials is presented. The material orientation of a two-dimensional locally orthotropic solid subjected to thermal loads is designed for minimization of the local temperature. Two optimization problems are considered: the minimization of the highest (hot-spot) temperature and the minimization of the temperature according to the weights distribution. For both problems rules for calculation of the optimal material orientation are derived analytically. The analysis is based on the idea of the principal stresses method for optimization of material orientation in linear elasticity problems. The results of the analysis are implemented and the developed computational model is tested on an example of the lamella orientation optimization in a metal-ceramic composite.

Thermal Performance Optimization in Electric Vehicle Power Trains by Locally Orthotropic Surface Layer Design

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Mario Petrovic ◽  
Tsuyoshi Nomura ◽  
Takayuki Yamada ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki
Keyword(s):  
Thermal Conductivity ◽  
Surface Layer ◽  
Scalar Field ◽  
Heat Flow ◽  
Performance Optimization ◽  
Orthotropic Material ◽  
Material Distribution ◽  
Optimal Orientation ◽  
Material Orientation ◽  
Orientation Optimization

In this paper, the application of orthotropic material orientation optimization for controlling heat flow in electric car power trains is presented. The design process is applied to a case model, which conducts heat while storing heat-sensitive electronic components. The core of the case is designed using a low thermal conductivity material on order to focus the heat flow into the surface layer, which is designed using a high thermal conductivity material. Material orthotropy is achieved in the surface layer of the case by removing the material at points determined by the optimization analysis. For this purpose, an orthotropic material orientation optimization method was extended to calculate optimal material distribution. This is achieved by transforming the initially obtained optimal orientation vector field into a scalar field through the use of coupled time-dependent nonisotropic Helmholtz equations. Multiple parameters allow the control of the scalar field and therefore the control over material distribution in accordance to the optimal orientation. This allows the material distribution pattern to be scaled depending on the desired manufacturing method. The analysis method is applied to divert heat flow from a specific section of the model while focusing the heat flow to another section. The results are shown for a model with a 0.1 mm thick surface layer of copper and are compared to those results from several other materials and layer thicknesses. Finally, the manufactured design is presented.

scholarly journals Optimization of the composition in a composite material for microelectronics application using the Ising model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoshihiko Imanaka ◽  
Toshihisa Anazawa ◽  
Fumiaki Kumasaka ◽  
Hideyuki Jippo
Keyword(s):  
Thermal Conductivity ◽  
Thermal Expansion ◽  
Ising Model ◽  
Specific Gravity ◽  
Simulated Annealing Algorithm ◽  
Optimization Problems ◽  
Industrial Applications ◽  
Thermal Dissipation ◽  
Materials Informatics ◽  
Combinatorial Optimization Problems

AbstractTailored material is necessary in many industrial applications since material properties directly determine the characteristics of components. However, the conventional trial and error approach is costly and time-consuming. Therefore, materials informatics is expected to overcome these drawbacks. Here, we show a new materials informatics approach applying the Ising model for solving discrete combinatorial optimization problems. In this study, the composition of the composite, aimed at developing a heat sink with three necessary properties: high thermal dissipation, attachability to Si, and a low weight, is optimized. We formulate an energy function equation concerning three objective terms with regard to the thermal conductivity, thermal expansion and specific gravity, with the composition variable and two constrained terms with a quadratic unconstrained binary optimization style equivalent to the Ising model and calculated by a simulated annealing algorithm. The composite properties of the composition selected from ten constituents are verified by the empirical mixture rule of the composite. As a result, an optimized composition with high thermal conductivity, thermal expansion close to that of Si, and a low specific gravity is acquired.

Influence of the Material and Thickness of the Specimen on an Infrared Stress Image

2004 ◽  
Vol 261-263 ◽  
pp. 1641-1646
Author(s):  
Kenji Machida ◽  
Mamtimin Gheni
Keyword(s):  
Thermal Conductivity ◽  
Hybrid Method ◽  
Thermal Conduction ◽  
Crack Problem ◽  
High Stress ◽  
High Accuracy ◽  
Problem Analysis ◽  
Principal Stresses ◽  
Distribution Form ◽  
Stress Components

The thickness dependency of the temperature image obtained by an infrared thermography was investigated using specimens with three kinds of materials and four kinds of the thickness of the specimen. Only the sum of the principal stresses which is the first invariant of stress tensor is measured, and it is impossible to measure individual stress components directly. Then, the infrared hybrid method was developed to separate individual stress components. Although the form of the contour line of low stress side differs greatly, the distribution form of high stress side was considerably alike. The stress intensity factor of material with low thermal conductivity can be estimated with high accuracy by the infrared hybrid method. On the crack problem, it was elucidated that the influence of thermal conduction is large and an inverse problem analysis is required.

Orthotropic material orientation optimization method in composite laminates

2017 ◽  
Vol 57 (2) ◽  
pp. 815-828 ◽  
Author(s):  
Mario Petrovic ◽  
Tsuyoshi Nomura ◽  
Takayuki Yamada ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki
Keyword(s):  
Composite Laminates ◽  
Orthotropic Material ◽  
Optimization Method ◽  
Material Orientation ◽  
Orientation Optimization

scholarly journals Application of Rough Ant Colony Algorithm in Adolescent Psychology

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Tao Cong ◽  
Lin Jiang ◽  
Qihang Sun ◽  
Yang Li
Keyword(s):  
Big Data ◽  
Juvenile Delinquency ◽  
Ant Colony Algorithm ◽  
Optimization Problems ◽  
Hot Spot ◽  
Rapid Development ◽  
Ant Colony ◽  
Good Effect ◽  
Adolescent Psychology ◽  
Combinatorial Optimization Problems

With the rapid development of big data, big data research in the security protection industry has been increasingly regarded as a hot spot. This article mainly aims at solving the problem of predicting the tendency of juvenile delinquency based on the experimental data of juvenile blindly following psychological crime. To solve this problem, this paper proposes a rough ant colony classification algorithm, referred to as RoughAC, which first uses the concept of upper and lower approximate sets in rough sets to determine the degree of membership. In addition, in the ant colony algorithm, we use the membership value to update the pheromone. Experiments show that the algorithm can not only solve the premature convergence problem caused by stagnation near the local optimal solution but also solve the continuous domain and combinatorial optimization problems and achieve better classification results. Moreover, the algorithm has a good effect on predicting classification and can provide guidance for predicting the tendency of juvenile delinquency.

Backside Hot Spot Detection

2002 ◽  
Author(s):  
Félix Beaudoin ◽  
Philippe Perdu ◽  
Romain Desplats ◽  
Lionel Dantas de Morais ◽  
Olivier Crepel ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Hot Spot ◽  
Substrate Thickness ◽  
Thermal Dependence ◽  
Experimental Conditions ◽  
Chip Area ◽  
Detection Techniques ◽  
Defect Position ◽  
Spot Detection ◽  
Transient Simulations

Abstract Defects localization from the IC’s backside using hot spot detection techniques is discussed. Simulations are used to validate the applicability of hot spot detection from the silicon backside and to determine the optimal experimental conditions. The effects of the dissipated power, the substrate thickness and the defect position relative to the chip area are studied. These simulations take into account the thermal dependence of the silicon thermal conductivity. Transient simulations are also performed to evaluate the effect of modulating the power on the backside temperature difference. Backside Liquid Crystal Microscopy as well as Infrared Thermography and Thermal Laser Stimulation results on defective ICs are presented.

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