Multi-objective Topology Optimization Using Simulated Annealing Method

Najafabadi, Hossein R.; Goto, Tiago G.; Martins, Thiago C.; Barari, Ahmad; Tsuzuki, Marcos de Sales Guerra

doi:10.1007/978-3-030-63403-2_31

Cited by 9 publications

(5 citation statements)

References 27 publications

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“…The Metropolis algorithm dictates that the probability of accepting a new solution is related to the annealing temperature, which is given by eq . This equation shows that the probability of acceptance increases at higher temperatures, while at lower temperatures, the solution tends to remain unchanged. , P i j = { true 1 , E j < E i exp true( prefix− E j − E i T true) , E j ≥ E i …”

Section: Electrochemical Behavior Prediction Of Pseudocapacitor Elect...mentioning

confidence: 99%

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Optimizing the Ultrashort Laser Pulses for In Situ Nanostructure Generation Technique for High-Performance Supercapacitor Electrodes Using Artificial Neural Networks and Simulated Annealing Algorithms

Khosravinia

Kiani

2023

ACS Omega

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Transition metals (TMs) are being investigated as electrodes for pseudocapacitors, where an oxide layer is necessary to allow for rapid redox reactions. In this work, we utilized an in situ, rapid, binder-free, and green method for the fast fabrication of pseudocapacitor electrodes called ultrashort laser pulses for in situ nanostructure generation (ULPING) to form oxide layers on a titanium sheet. By utilizing this fabrication technique on a titanium sheet, a specific areal capacitance of 0.3579 mF cm −2 was achieved at a current density of 0.25 mA cm −2 . However, the laser fabrication parameters were selected experimentally and resulted in low performance of pseudocapacitors. Therefore, one of the main objectives of this study was to find the optimal laser fabrication parameters to achieve the highest specific areal capacitance. A large dataset was generated to find the relationship between the laser fabrication parameters and the electrochemical behavior performance (impedance and specific areal capacitance) of the fabricated electrodes by using an artificial neural network (ANN). We used an optimization algorithm (simulated annealing-SA) to overlook the trained ANN model as a black box and try to maximize the objective function, which in our case is a specific capacitance value, to find the most optimal laser fabrication parameters. Using SA, optimal laser fabrication parameters were found, which increased the specific areal capacitance to 0.9999 mF cm −2 at a current density of 0.25 mA cm −2 . The results demonstrated that the conducted study has the potential to introduce effective techniques for utilizing ULPING to produce nanoscale structures on TMs. These structures have the potential to be employed as electrodes in pseudocapacitors. Additionally, the research underscores the significance of employing data-driven approaches in electrode design procedures.

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Section: Electrochemical Behavior Prediction Of Pseudocapacitor Elect...mentioning

confidence: 99%

“… 45 This equation shows that the probability of acceptance increases at higher temperatures, while at lower temperatures, the solution tends to remain unchanged. 45 , 46 …”

Section: Electrochemical Behavior Prediction Of Pseudocapacitor Elect...mentioning

confidence: 99%

Optimizing the Ultrashort Laser Pulses for In Situ Nanostructure Generation Technique for High-Performance Supercapacitor Electrodes Using Artificial Neural Networks and Simulated Annealing Algorithms

Khosravinia

Kiani

2023

ACS Omega

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“…Other metaheuristic techniques have been applied without hybridising. Such are the cases of artificial immune algorithms [191][192][193], ant colonies [194][195][196][197], particle swarms [198][199][200], simulated annealing [201][202][203][204], harmony search [205][206][207][208], and differential evolution [209,210].…”

Section: Other Metaheuristic Approachesmentioning

confidence: 99%

On Topology Optimisation Methods and Additive Manufacture for Satellite Structures: A Review

Hurtado-Pérez,

Pablo-Sotelo,

Ramírez-López

et al. 2023

Aerospace

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Launching satellites into the Earth’s orbit is a critical area of research, and very demanding satellite services increase exponentially as modern society takes shape. At the same time, the costs of developing and launching satellite missions with shorter development times increase the requirements of novel approaches in the several engineering areas required to build, test, launch, and operate satellites in the Earth’s orbit, as well as in orbits around other celestial bodies. One area with the potential to save launching costs is that of the structural integrity of satellites, particularly in the launching phase where the largest vibrations due to the rocket motion and subsequent stresses could impact the survival ability of the satellite. To address this problem, two important areas of engineering join together to provide novel, complete, and competitive solutions: topology optimisation methods and additive manufacturing. On one side, topology optimisation methods are mathematical methods that allow iteratively optimising structures (usually by decreasing mass) while improving some structural properties depending on the application (load capacity, for instance), through the maximisation or minimisation of a uni- or multi-objective function and multiple types of algorithms. This area has been widely active in general for the last 30 years and has two main core types of algorithms: continuum methods that modify continuous parameters such as density, and discrete methods that work by adding and deleting material elements in a meshing context. On the other side, additive manufacturing techniques are more recent manufacturing processes aimed at revolutionising manufacturing and supply chains. The main exponents of additive manufacturing are Selective Laser Melting (SLM) (3D printing) as well as Electron Beam Melting (EBM). Recent trends show that topology-optimised structures built with novel materials through additive manufacturing processes may provide cheaper state-of-the-art structures that are fully optimised to better perform in the outer-space environment, particularly as part of the structure subsystem of novel satellite systems. This work aims to present an extended review of the main methods of structural topology optimisation as well as additive manufacture in the aerospace field, with a particular focus on satellite structures, which may set the arena for the development of future satellite structures in the next five to ten years.

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“…Furthermore, in discrete structural optimization problems, such as truss assembly design, probabilistic methods have demonstrated the capability to attain the optimum solution [9]. Non-gradient based methods have demonstrated success in a wide range of optimization problems [10]. Nevertheless, they are still evolving and require further development to address diverse design challenges.…”

Section: Introductionmentioning

confidence: 99%

Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization

Rostami Najafabadi,

Martins,

Tsuzuki

et al. 2023

Machines

Self Cite

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This paper explores implementation of self-weight and inertial loading in topology optimization (TO) employing the Simulated Annealing (SA) algorithm as a non-gradient-based technique. This method can be applied to find optimum design of structures with no need for gradient information. To enhance the convergence of the SA algorithm, a novel approach incorporating the crystallization factor is introduced. The method is applied in a benchmark problem of a cantilever beam. The study systematically examines multiple scenarios, including cases with and without self-weight effects, as well as varying point loads. Compliance values are calculated and compared to those reported in existing literature to validate the accuracy of the optimization results. The findings highlight the versatility and effectiveness of the SA-based TO methodology in addressing complex design challenges with considerable self-weight or inertial effect. This work can contribute to structural design of systems where only the objective value is available with no gradient information to use sensitivity-based algorithms.

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Multi-objective Topology Optimization Using Simulated Annealing Method

Cited by 9 publications

References 27 publications

Optimizing the Ultrashort Laser Pulses for In Situ Nanostructure Generation Technique for High-Performance Supercapacitor Electrodes Using Artificial Neural Networks and Simulated Annealing Algorithms

Optimizing the Ultrashort Laser Pulses for In Situ Nanostructure Generation Technique for High-Performance Supercapacitor Electrodes Using Artificial Neural Networks and Simulated Annealing Algorithms

On Topology Optimisation Methods and Additive Manufacture for Satellite Structures: A Review

Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization

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