Thermal Structural Optimization Research Articles

Thermal-Structural optimization of a rapid thermal response mold: Comprehensive simulation of a heating rod system and a fluid cooling system implemented MSR-PSO-FEM

In this work, the heating and cooling systems of a rapid thermal response mold (RTRM) are optimized applying the response surface methodology (RSM) and an optimization technique. An experiment design with six factors and three levels was carried out, and variables such as the distance between the heating rods, and the distance between the cooling channel and the heating plate, among others, were analyzed. First, thermal, and thermal-structural resistance analyses were performed using the finite element method (FEM), and response surface mathematical models were developed using the mixed regression and response surface models. Then, the analysis of variance (ANOVA) method was used to verify the precision of these models. With the models obtained, the position of the heating rods and the dimensions of the cooling channels were optimized, minimizing at the same time the heating and cooling time and maintaining a reasonable temperature distribution and structural resistance, using the Particle Swarm Optimization (PSO). The results show that it is possible to reduce the heating time by 43%, which is significantly. The cooling time in the molding cycle by 29%, thus improving the effectiveness of the heating and cooling system with respect to the cooling plate, the Von Mises stress reported an improvement in its structural value of 67% with respect to the initial value.

Thermal-Structural Optimization of Light with LED Packaging

A systematic numerical and experimental method is developed to optimize a caution lamp with multichips LED chips. Here, we intend to describe the thermal performance of LED caution lamp with multiple LED chips through the structural optimization by the finite element method. One type of caution lamp was made and the highest temperatures of LED chips have been test after the optimization. This optimization method is useful for design and manufacturing of caution lamps with multiple LED chips. Compared with the simulation and the experiment data, the high temperature of LEDs were reduced by choosing fitting parameters. It indicates that the results and methods used in this paper can provide the guidance in the understanding of thermal management for LED lamps design.

Thermal-Structural Optimization of Light with LED Packaging

At present, the light-emitting-diode (LED) has been a tremendous surge in its application as a new type of generation lighting source. The thermal performance and structural reliability of LED system have been investigated by different conditions in electronic package [1]. With the minimization of the LED packaging, the reliability problem, especially, the thermal reliability becomes more and more seriously. Hence the heat dissipation for LED system becomes much crucial. Lots of heat management methods have been investigated for LED system designing and manufacturing. The most popular cooling method used in the LED system is the passive cooling, however, its cooling efficiency is very low. It is very significant to develop the heat dissipation method [2, 3]. A systematic numerical and experimental method is developed to optimize a caution lamp with multichips LEDs in this paper. Here we intend to describe the thermal performance of LED caution lamp with multiple LED chips through the structural optimization by the finite element method. And to understand the thermal characteristics of the caution lamp with difference structural parameters. After the optimization, one type of caution lamp was made and the highest temperatures of LED chips have been test. This optimization method is useful for design and manufacturing of caution lamps with multiple LED chips. After numerical simulation, we prepared the caution lamp sample with six LED chips according to the results. The Thermalcouples are used to test the temperature of the lamp. Compared with the simulation and the experiment data, the high temperature of LEDs were reduced by choosing fitting parameters. It indicates that the results and methods used in this paper can provide the guidance in the understanding of thermal management for LED lamps design. Figure 1 show temperature distribution of light structures before and after thermal-structural optimization. Figure 2 show the test principle connection and test system. Figure 1

On Thermal Structure Optimization of a Power LED Lighting

In this paper, using APDL language to generate the analysis file the LED lamp heat sink of finite element model is established. The length, width and numbers of the heat sink fins being design variables, the maximum junction temperature of LED being the objective function, the mathematical model is set up and optimized using ANSYS thermal analysis software. The results show that the longer the length of heat sink fins, the lower the maximum junction temperature of the chip; the wider the fins width, the higher the maximum chip junction temperature; with the increasing of the numbers of fins, the maximum junction temperature will go down; but when reaching a certain value, the junction temperature will slowly ncrease again. Under the conditions of the LED chip junction temperature not exceeding 60°C, the heat sink structure optimized values were: fin length is 62.5mm, fin width is 1 mm, the number of fins is 20.

Multipoint approximation development: thermal structural optimization case study

Function approximation is one of the most important fields of research in design optimization. Accurate function approximation reduces the repetitive cost of finite element analysis. Many local approximations, such as one- and two-point local approximations, are already available. These are, however, only valid in a small domain and require stringent move-limits on design variables. The objective of this research is to achieve an efficient and accurate multipoint approximation to constraints by integrating the most accurate segment of all local approximations previously constructed. The proposed multipoint approximation is constructed by combining weighting functions with local function approximations. With function and gradient information at a series of points, local approximations are established at those points. Once established, all local approximations are blended into a multipoint approximation by use of a weighting function. Function and gradient values of this multipoint approximation correspond directly with exact counterparts at the points where the local approximations were generated. Finally, the multipoint approximation is applied to a plate and wing box thermal-structural optimization. Published in 2000 by John Wiley & Sons, Ltd.

Multipoint approximation development: thermal structural optimization case study

Multipoint approximation development: thermal structural optimization case study

Structural Optimization with Thermal and Mechanical Constraints

This paper reports on the testing of the adaptability of the new approximation tools for thermal structural optimization. A finite element based procedure is proposed for obtaining minimum mass design of structures subjected to stress, displacement and temperature constraints. The optimization is based on a new two-point approximation method for the function. The coupling between thermal and structural sensitivities is taken into account to ensure the convergence. The direct or adjoint method is used for the sensitivity analysis. The two-point approximation is the incomplete second order Taylor series expansion in terms of the intervening variables. The exponent of each design variable and the unknown constant in the second order terms can be obtained in a closed form. This two-point approximation is used for temperature, displacement and internal force approximations. Stress constraints are calculated by using approximated internal forces. Finally, the optimization procedure is demonstrated by two examples: the first example is the design of a titanium plate with aluminum bars and the second example is a structural wing box. These examples are subjected to external heating and mechanical loads, with temperature, strength and minimum gauge constraints.