Multi-objective Topology Optimization of the Temperature Field Considering the Material Nonlinearities

Free-mounted cooling plate multi-objective topology optimization method towards precision machine tool heat dissipation: An experimental and numerical study

Multi-objective topology optimization method for multi-axis random vibration based on hybrid cellular automata

To optimize the frame of a sightseeing vehicle, this paper proposes a multi-objective topology optimization method combining Analytic Hierarchy Process (AHP) and topology optimization. Firstly, the edges of the unmanned sightseeing car are statically analyzed. The rectangular steel frame structure of the original frame is replaced with square plates, the basic model of the unmanned sightseeing car frame is established, and a single-objective topology optimization mathematical model of the frame is established to optimize the topology design of the frame. Then, in order to design a frame structure that meets all the working conditions at the same time, a mathematical model of multi-working condition topology optimization is established, and the weights of each working condition are determined by using AHP, and the multi-working condition topology optimization design of the frame is carried out. Finally, a comparison of the comprehensive performance of the frame before and after optimization shows that the proposed method enables the optimized frame to meet the strength requirements under various working conditions, resulting in a weight reduction of 16.5 kg.

Multi-objective topology optimization and thermal performance of liquid-cooled microchannel heat sinks with pin fins

Aiming at the multiobjective topology optimization design of the structure, this paper proposes a method to establish the comprehensive objective function based on the normalized subobjective of the compromise programming method and to determine the weight coefficient of the subobjective of the comprehensive objective function by the analytic hierarchy process (AHP). By using statistical analysis and modal analysis, the static and dynamic characteristics of the gear can be obtained. The single objective topology optimization is used to reduce the compliance of the gear and elevate the low-order natural frequency, and the frequency weighting method is used to suppress the oscillation phenomenon in the frequency-single-objective optimization. AHP was used to determine the weight coefficient of each subtarget. The compromise programming method is used for multiobjective topology optimization, and the gear design is improved according to the optimization results. By analyzing the improved gear structure, the weight of the optimized gear is reduced by 25.3%. The overall stiffness performance and strength performance are enhanced, and the natural frequencies of each order are improved to different degrees.

Multi-objective topology optimization and structural analysis of periodic spaceframe structures

Multi-objective topology optimization of cold plates featuring branched and streamlined mini-channels for thermal management system of lithium-ion battery module

This letter presents an application of multiobjective topology optimization to ultrawideband (UWB) antenna design. The design of UWB antennas is very challenging because it involves multiple design goals including miniaturization, a wide impedance bandwidth, uniform gain variation, and enhanced time-domain pulse preservation. Although topology optimization has been a popular approach for UWB antenna design, a multiobjective version that systematically copes with all the design details is critically lacking, and the early attempts have not been very successful. In this letter, we propose a Pareto-based technique for multiobjective topology optimization, showing that the proposed methodology facilitates the development of a UWB antenna with compact size, a wide bandwidth, uniform gain variation, and high fidelity factors. The optimized UWB antenna occupies a small area of $15 \times 15~\hbox{mm}^2$ , showing excellent impedance matching and stable broadside gains throughout 3.1–10.6 GHz. In addition, the variation of group delay drops dramatically from 0.94 to 0.40 ns, and the fidelity factor is enhanced from around 0.80 to 0.92. The simulated and measured results are exhibited, confirming the validity of multiobjective topology optimization.

To enhance the efficiency and machining precision of the TX1600G complex boring and milling machining center, a study was conducted on the structure of its gantry milling system. This study aimed to mitigate the influence of factors such as structural quality, natural frequency, and stiffness. The approach employed for this investigation involved mechanism topology optimization. To initiate this process, a finite element model of the gantry milling system structure was established. Subsequently, an objective function, comprising strain energy and modal eigenvalues, was synthesized. This objective function was optimized through multi-objective topology optimization, taking into account certain mass fraction constraints and considering various factors, including processing technology. The ultimate goal of this optimization was to create a gantry milling structure that exhibited high levels of dynamic and static stiffness, a superior natural frequency, and reduced mass. To validate the effectiveness of these topology optimization results, a comparison was made between the new and previous structures. The findings of this study serve as a valuable reference for optimizing the structure of other components within the machining center.

This article deals with the comparative performance of some established multi-objective evolutionary algorithms (MOEAs) for structural topology optimization. Four multi-objective problems, having design objectives like structural compliance, natural frequency and mass, and subjected to constraints on stress, etc., are posed for performance testing. The MOEAs include Pareto archive evolution strategy (PAES), population-based incremental learning (PBIL), non-dominated sorting genetic algorithm (NSGA), strength Pareto evolutionary algorithm (SPEA), and multi-objective particle swarm optimization (MPSO). The various MOEAs are implemented to solve the problems. The ground element filtering (GEF) technique is used to suppress checkerboard patterns on topologies. The results obtained from the various optimizers are illustrated and compared. It is shown that PBIL is far superior to the others. The optimal topologies from using PBIL can be compared with those obtained by employing the classical gradient-based approach. It can be considered as a powerful tool for structural topological design.

The topology of mechanical parts has a crucial effect on their performance, and many methods have been already presented to optimize the topology of different structures. In this paper, Coannealing algorithm was used for topology optimization problems with more than one objective function. This algorithm took many concepts from archived multi-objective simulated annealing (AMOSA); however, the acceptance criterion of the new solution is less complex. Also, a filtering technique has been used to limit the search area, thereby decreasing computation costs and improving the resolution of the final material distribution. The results were validated using the same input values and the results in the literature with a maximum error of 2.7%. The viable solutions in the Pareto front curve from this method can be used to select the most suitable one.

The Soft-Kill-Option method (SKO) is an evolutionary approach for topology optimization. The objective of the optimization is to determine a uniformly stressed topology for a given loading. Thus, a structure with optimal material layout can be achieved. Ordinary applications of the SKO method consider only the stress objective. Within the present study, an extension of this method is investigated, which allows the optimization of two objectives at the same time. As the second objective, heat flux is chosen. Besides thermal and mechanical induced stresses, this parameter has a large impact on the lifetime of thermal highly loaded components. The present study first explains the single objective optimization approach. Thereby, the relevant SKO parameters are also investigated. Building up on these results, a method for combining two objectives by superposition is investigated. The implementation of the developed procedure is explained, and two examples are evaluated. For the implementation of the algorithm, the scripting language python is used. The algorithm is executed with the commercial software ABAQUS.

Topology optimization method is a novel design method for MEMS actuators. In this paper, a multi-objective design method is introduced into topology optimization for MEMS actuators. Some important factors for multi-objective design of MEMS actuators are deeply researched. A multi-objective topology optimization method based on minimal structural compliance and maximal structural output displacement of MEMS actuators is proposed and the corresponding governing equation for topology optimization is established. A sensitivity analysis of adjoint method is proposed to analyze topology optimization design of multi-objective MEMS actuators. Meanwhile, GCMMA (globally convergent version of the method of moving asymptotes) algorithm is used in optimization. Two numerical examples of MEMS actuators verified the effectiveness of above theory and algorithm.

Topology optimization modifies the material distribution in the design domain to produce micro-channel structure with improved thermal performance. In this work, five heat dissipation micro-channel structures with various design domain aspect ratios are optimally designed based on the bi-objective topology optimization method. The optimal design variable fields, temperature fields, and pressure fields are subsequently obtained for each operating condition, and the flow heat transfer effect and the enhanced heat transfer mechanism are investigated under various working conditions. On this basis, the flow heat transfer impact of micro-channels under various operating situations is optimized and studied by combining the field synergy concept and entransy dissipation theory. The findings show that when the Reynolds number rises in the laminar flow region, the complexity of the topological flow channels also rises. The average temperature, Tave,decreases, Nusselt number rises, the inlet and outlet pressure drop, ?P, gradually increases, the integrated enhanced heat transfer factor PEC gradually decreases, the field synergy number, Fc, increases, the pressure drop synergy angle, ?, gradually increases, the entransy dissipation, Evh, increases, and the flow heat transfer performance of each heat dissipation channel is also enhanced due to the complex channels and high Reynolds number in the domain. The investigation of micro-channels with various topologies revealed that the micro-channels with the same boundary conditions and a design domain aspect ratio of 25/64 had the best synergy effects of velocity-pressure gradient and velocity-temperature gradient, the best heat transfer effect, and the best flow characteristics.

Aiming at the problems such as low computational efficiency and long process in dynamic topology optimization, combined with bi-directional evolutional structure optimization, the dynamic optimization problem is transformed into the static optimization problem in multiple load cases. Newmark method is used to analyze the structure dynamics load. The topology optimization model based on equivalent static load is established. On the basis of the equivalent static load, multi-objective dynamics evolutionary structure optimization is studied. And the mathematical model of the dynamic stiffness and natural frequency about the multi-objective optimization is established. The mathematical formula of the sensitivity is deduced. Then a complete optimization iterative process is given. The numerical example illustrates that it is feasible to solve the multi-objective dynamic topology optimization with equivalent static loads. Modal tracking technique is introduced to the multi-objective dynamic topology optimization. The numerical example shows that modal tracking technology can track the required modal in the optimization process.