scholarly journals A Modified Shuffled Frog Leaping Algorithm for the Topology Optimization of Electromagnet Devices

2020 ◽  
Vol 10 (18) ◽  
pp. 6186
Author(s):  
Wenjia Yang ◽  
Siu Lau Ho ◽  
Weinong Fu
Keyword(s):  
Topology Optimization ◽  
Local Search ◽  
Three Dimensional ◽  
Optimization Method ◽  
Memetic Algorithms ◽  
Local Optimum ◽  
Shuffled Frog Leaping Algorithm ◽  
Electromagnetic Problems ◽  
Electromagnetic Devices ◽  
Shuffled Frog Leaping

The memetic algorithms which employ population information spreading mechanism have shown great potentials in solving complex three-dimensional black-box problems. In this paper, a newly developed memetic meta-heuristic optimization method, known as shuffled frog leaping algorithm (SFLA), is modified and applied to topology optimization of electromagnetic problems. Compared to the conventional SFLA, the proposed algorithm has an extra local search step, which allows it to escape from the local optimum, and hence avoid the problem of premature convergence to continue its search for more accurate results. To validate the performance of the proposed method, it was applied to solving the topology optimization of an interior permanent magnet motor. Two other EAs, namely the conventional SFLA and local-search genetic algorithm, were applied to study the same problem and their performances were compared with that of the proposed algorithm. The results indicate that the proposed algorithm has the best trade-off between the results of objective values and optimization time, and hence is more efficient in topology optimization of electromagnetic devices.

scholarly journals Multiscale, thermomechanical topology optimization of self-supporting cellular structures for porous injection molds

2019 ◽  
Vol 25 (9) ◽  
pp. 1482-1492
Author(s):  
Tong Wu ◽  
Andres Tovar
Keyword(s):  
Topology Optimization ◽  
Mechanical Performance ◽  
Mechanical Load ◽  
Design Method ◽  
Three Dimensional ◽  
Optimization Method ◽  
Cellular Structures ◽  
Injection Mold ◽  
Computationally Efficient ◽  
Content Type

Purpose This paper aims to establish a multiscale topology optimization method for the optimal design of non-periodic, self-supporting cellular structures subjected to thermo-mechanical loads. The result is a hierarchically complex design that is thermally efficient, mechanically stable and suitable for additive manufacturing (AM). Design/methodology/approach The proposed method seeks to maximize thermo-mechanical performance at the macroscale in a conceptual design while obtaining maximum shear modulus for each unit cell at the mesoscale. Then, the macroscale performance is re-estimated, and the mesoscale design is updated until the macroscale performance is satisfied. Findings A two-dimensional Messerschmitt Bolkow Bolhm (MBB) beam withstanding thermo-mechanical load is presented to illustrate the proposed design method. Furthermore, the method is implemented to optimize a three-dimensional injection mold, which is successfully prototyped using 420 stainless steel infiltrated with bronze. Originality/value By developing a computationally efficient and manufacturing friendly inverse homogenization approach, the novel multiscale design could generate porous molds which can save up to 30 per cent material compared to their solid counterpart without decreasing thermo-mechanical performance. Practical implications This study is a useful tool for the designer in molding industries to reduce the cost of the injection mold and take full advantage of AM.

scholarly journals Enhanced shuffled frog leaping algorithm with improved local exploration and energy-biased load reduction phase for load balancing of gateways in WSNs

2021 ◽  
Vol 11 (1) ◽  
pp. 437-460
Author(s):  
Amol Adamuthe ◽  
Abdulhameed Pathan
Keyword(s):  
Load Balancing ◽  
Convergence Rate ◽  
Local Search ◽  
Heuristic Algorithm ◽  
Information Exchange ◽  
Load Reduction ◽  
Deterministic Approach ◽  
Shuffled Frog Leaping Algorithm ◽  
Shuffled Frog Leaping ◽  
Search Capability

Abstract Wireless sensor networks (WSNs) have grown widely due to their application in various domains, such as surveillance, healthcare, telecommunication, etc. In WSNs, there is a necessity to design energy-efficient algorithms for different purposes. Load balancing of gateways in cluster-based WSNs is necessary to maximize the lifetime of a network. Shuffled frog leaping algorithm (SFLA) is a popular heuristic algorithm that incorporates a deterministic approach. Performance of any heuristic algorithm depends on its exploration and exploitation capability. The main contribution of this article is an enhanced SFLA with improved local search capability. Three strategies are tested to enhance the local search capability of SFLA to improve the load balancing of gateways in WSNs. The first proposed approach is deterministic in which the participation of the global best solution in information exchange is increased. The next two variations reduces the deterministic approach in the local search component of SFLA by introducing probability-based selection of frogs for information exchange. All three strategies improved the success of local search. Second contribution of article is increased lifetime of gateways in WSNs with a novel energy-biased load reduction phase introduced after the information exchange step. The proposed algorithm is tested with 15 datasets of varying areas of deployment, number of sensors and number of gateways. Proposed ESFLA-RW variation shows significant improvement over other variations in terms of successful local explorations, best fitness values, average fitness values and convergence rate for all datasets. Obtained results of proposed ESFLA-RW are significantly better in terms of network energy consumption, load balancing, first gateway die and network life. The proposed variations are tested to check the effect of various algorithm-specific parameters namely frog population size, probability of information exchange and probability of energy-biased load reduction phase. Higher population size and probabilities give better solutions and convergence rate.

Large-scale three-dimensional anisotropic topology optimization of variable-axial lightweight composite structures

2021 ◽  
pp. 1-15
Author(s):  
Yuqing Zhou ◽  
Tsuyoshi Nomura ◽  
Enpei Zhao ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Composite Structures ◽  
Large Scale ◽  
Volume Fraction ◽  
Three Dimensional ◽  
Optimization Method ◽  
Optimized Design ◽  
Adaptive Meshing ◽  
Design Synthesis ◽  
Fiber Placement

Abstract Variable-axial fiber-reinforced composites allow for local customization of fiber orientation and thicknesses. Despite their significant potential for performance improvement over the conventional multiaxial composites and metals, they pose challenges in design optimization due to the vastly increased design freedom in material orientations. This paper presents an anisotropic topology optimization method for designing large-scale, 3D variable-axial lightweight composite structures subject to multiple load cases. The computational challenges associated with large-scale 3D anisotropic topology optimization with extremely low volume fraction are addressed by a tensor-based representation of 3D orientation that would avoid the 2π periodicity of angular representations such as Euler angles, and an adaptive meshing scheme, which, in conjunction with PDE regularization of the density variables, refines the mesh where structural members appear and coarsens where there is void. The proposed method is applied to designing a heavy-duty drone frame subject to complex multi-loading conditions. Finally, the manufacturability gaps between the optimized design and the fabrication-ready design for Tailored Fiber Placement (TFP) is discussed, which motivates future work toward a fully-automated design synthesis.

Topology Optimization of Three-Dimensional Biodegradable Polymer Multi-Layer Microstructure for Implantable Drug Controlled Release

2007 ◽  
Vol 26-28 ◽  
pp. 757-760
Author(s):  
Rui Xia Yu ◽  
Hua Ling Chen ◽  
Xiang Yang Zhou
Keyword(s):  
Drug Delivery ◽  
Topology Optimization ◽  
Controlled Release ◽  
Drug Release ◽  
Biodegradable Polymer ◽  
Three Dimensional ◽  
Optimization Method ◽  
Drug Release Profile ◽  
Evolutionary Structural Optimization

Biodegradable polymer multi-layer drug delivery microstructure with micro-chambers has some unique advantages in controlled long-term drug delivery, which can enclose drug in the chambers to realize drug release in a controlled fashion. Therefore, it is necessary to obtain the optimal designs of the micro-chambers and their distributions. In this paper, topology optimization of a three-dimensional biodegradable polymer multi-layer drug delivery microstructure was carried out using the cellular automaton (CA)-based evolutionary structural optimization method. The results show that the optimized controlled release system exhibits a preferable linear drug release profile.

scholarly journals Inversion Analysis of Seepage Parameters Based on Improved Shuffled Frog Leaping Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Li Qun Xu ◽  
Ling Li
Keyword(s):  
Inverse Analysis ◽  
Threshold Value ◽  
Local Extremum ◽  
Earth Dam ◽  
Initial Population ◽  
Local Optimum ◽  
Shuffled Frog Leaping Algorithm ◽  
Shuffled Frog Leaping ◽  
Seepage Characteristics ◽  
Inversion Analysis

Aiming at overcoming the defects such as slow searching speed and easily trapping into local extremum at anaphase of the shuffled frog leaping algorithm (SFLA), based on the Evolutionary Exploration strategy, a more effective shuffled frog leaping algorithm, Improved Shuffled Frog Leaping Algorithm (ISFLA), which can be applied to the inverse analysis of seepage parameters to dams, is proposed. With the introduction of the threshold value selection in the local search of the original initial population to improve the best frogs in memeplex, the improved algorithm overcomes the shortcomings of traditional SFLA which can easily fall into a local optimum. By comparative analysis between the laboratory test and numerical simulation, the effectiveness and accuracy of ISFLA are demonstrated by the application to the inversion analysis of seepage parameters of earth dams. Furthermore, the inversion analysis of seepage parameters to the earth dam in Lianyungang China is studied by the ISFLA. Moreover, the seepage characteristics of the dam are evaluated; thus, the suggestion that the dam should be reinforced is put forward. All the results show that ISFLA in an inverse analysis of seepage parameters of dams has excellent value to hydropower engineering.

Navigational strategy for underwater mobile robot based on adaptive neuro-fuzzy inference system model embedded with shuffled frog leaping algorithm–based hybrid learning approach

2017 ◽  
Vol 231 (4) ◽  
pp. 844-862
Author(s):  
DR Parhi ◽  
S Kundu
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Three Dimensional ◽  
Hybrid Learning ◽  
System Model ◽  
Underwater Robot ◽  
Shuffled Frog Leaping Algorithm ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Shuffled Frog Leaping

In this research article, a novel navigational approach has been introduced for underwater robot based on learning and self-adaptation ability of adaptive neuro-fuzzy inference system. For avoiding obstacles during three-dimensional navigation, two adaptive neuro-fuzzy inference system models have been coupled to find out required change in heading angles of underwater robot in horizontal and vertical planes, respectively. A new hybrid learning scheme has been proposed for adaptive neuro-fuzzy inference system. Here, memetic approach based shuffled frog leaping algorithm has been used to tune the premise parameters and consequent parameters has been estimated through recursive least square estimation. Minimization of error in output of adaptive neuro-fuzzy inference system model has been treated as major objective of evolutionary-based training algorithm. Preliminary robotic behaviors of underwater robot have been successfully executed by implementing such well-trained adaptive neuro-fuzzy inference system architecture within three-dimensional unspecified workspace. Navigational performance of adaptive neuro-fuzzy inference system trained with the proposed hybrid learning algorithm has been compared with other three-dimensional navigational approaches in simulation mode for authentication purpose. Experimental verification has also been carried out to validate the feasibility and efficiency of the proposed navigational strategy.

scholarly journals A Topology Optimization Method for Stochastic Lattice Structures

2021 ◽  
pp. 235-240
Author(s):  
Filippo Cucinotta ◽  
Marcello Raffaele ◽  
Fabio Salmeri
Keyword(s):  
Topology Optimization ◽  
3D Printing ◽  
Structural Optimization ◽  
High Performance ◽  
Three Dimensional ◽  
Optimization Method ◽  
Lattice Structures ◽  
Low Weight ◽  
Topology Optimization Method

AbstractStochastic lattice structures are very powerful solutions for filling three-dimensional spaces using a generative algorithm. They are suitable for 3D printing and are well appropriate to structural optimization and mass distribution, allowing for high-performance and low-weight structures. The paper shows a method, developed in the Rhino-Grasshopper environment, to distribute lattice structures until a goal is achieved, e.g. the reduction of the weight, the harmonization of the stresses or the limitation of the strain. As case study, a cantilever beam made of Titan alloy, by means of SLS technology has been optimized. The results of the work show the potentiality of the methodology, with a very performing structure and low computational efforts.

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