The mine blast algorithm for the structural optimization of electrical vehicle components

2020 ◽  
Vol 62 (5) ◽  
pp. 497-502 ◽  
Author(s):  
B. S. Yıldız
Keyword(s):  
Shape Optimization ◽  
Optimization Problems ◽  
Element Analysis ◽  
Mine Blast Algorithm ◽  
Component Design ◽  
Derivative Free ◽  
Door Hinge ◽  
Electrical Vehicles ◽  
Electrical Vehicle ◽  
Vehicle Components

Abstract The shape optimization of mechanical and automotive component plays a crucial role in the development of automotive technology. Presently, the use of derivative-free metaheuristics in combination with finite element analysis for mechanical component design is one of the most focused on topics due to its simplicity and effectiveness. In this research paper, the mine blast algorithm (MBA) is used to solve the problem of shape optimization for a vehicle door hinge to prove how the MBA can be used for solving shape optimization problems in designing electrical vehicles. The results show the advantage of the MBA for designing optimal components in the automotive industry.

Design Innovation Size and Shape Optimization of a 1.0mm Multifunctional Forceps-Scissors Surgical Instrument

2008 ◽  
Vol 2 (1) ◽  
Author(s):  
Milton E. Aguirre ◽  
Mary Frecker
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Shape Optimization ◽  
Optimization Problems ◽  
Cross Sectional Area ◽  
Sectional Area ◽  
Element Analysis ◽  
Cross Sectional ◽  
Size And Shape ◽  
The Cross

A size and shape optimization routine is developed for a 1.0mm diameter multifunctional instrument for minimally invasive surgery. The instrument is a compliant mechanism capable of both grasping and cutting. Multifunctional instruments are expected to be beneficial in the operating room because of their ability to perform multiple surgical tasks, thereby decreasing the total number of instrument exchanges in a single procedure. With fewer instrument exchanges, the risk of inadvertent tissue trauma as well as overall surgical time and costs are reduced. The focus of this paper is to investigate the performance effects of allowing the cross-sectional area along the length of the device to vary. This investigation is accomplished by defining various cross-sectional segments in terms of parametric variables and optimizing the dimensions of the instrument to provide a sufficient opening of the forceps jaws while maintaining adequate cutting and grasping forces. Two optimization problems are considered. First, all parametric segments are set equal to one another to achieve size optimization. Second, each segment is allowed to vary independently, thereby achieving shape optimization. Large deformation finite element analysis and optimization are conducted using ANSYS®. Finally, prototypes are fabricated using wire EMD and experiments are conducted to evaluate the instrument performance. As a result of allowing the cross-sectional area to vary, i.e., conducting shape optimization, the forceps and scissors blocked forces increased by as much as 83.2% and 87%, respectively. During prototype evaluations, it is found that the finite element analysis predictions were within 10% of the measured tool performance. Therefore, for this application, it is concluded that performing shape optimization does significantly influence the performance of the instrument.

A New Methodology for an Optimal Shape Design

2011 ◽  
Vol 61 ◽  
pp. 43-54 ◽  
Author(s):  
W. El Alem ◽  
A. El Hami ◽  
Rachid Ellaia
Keyword(s):  
Structural Optimization ◽  
Shape Optimization ◽  
Geometric Modeling ◽  
High Performance ◽  
Optimization Problems ◽  
Continuous Optimization ◽  
Element Analysis ◽  
The Finite Element Analysis ◽  
Optimization Methodology ◽  
Continuous Optimization Problems

The aim of this paper is to study the implementation of an efficient and reliable methodology for shape optimization problems where the objective function and constraints are not known explicitly and are dependent on the Finite Element Analysis (FEA). It is based on the Simultaneous Perturbation Stochastic Approximation (SPSA) method for solving unconstrained continuous optimization problems. We also propose Penalty SPSA (PSPSA) for solving constrained optimization problems, the constraints are handled using exterior point penalty functions within an algorithm that combines SPSA and exact penalty transformations. This paper presents a new structural optimization methodology that combines shape optimization, geometric modeling, FEA and PSPSA method to successfully optimize structural optimization problems. Several tests have been performed on some well known benchmark functions to demonstrate the robustness and high performance of the suggested methodology. In addition, an illustrative two-dimensional structural problem has been solved in a very efficient way. The numerical results demonstrate the robustness and high performance of the suggested methodology for structural optimization problems.

Seagull optimization algorithm for solving real-world design optimization problems

2020 ◽  
Vol 62 (6) ◽  
pp. 640-644 ◽  
Author(s):  
Natee Panagant ◽  
Nantiwat Pholdee ◽  
Sujin Bureerat ◽  
Khon Kaen ◽  
Ali Rıza Yıldız ◽  
...  
Keyword(s):  
Shape Optimization ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Kriging Model ◽  
Stress Constraint ◽  
Constraint Function ◽  
Element Analysis ◽  
Structural Shape ◽  
Whale Optimization ◽  
Structural Mass

AbstractIn this research paper, a new surrogate-assisted metaheuristic for shape optimization is proposed. A seagull optimization algorithm (SOA) is used to solve the shape optimization of a vehicle bracket. The design problem is to find structural shape while minimizing structural mass and meeting a stress constraint. Function evaluations are carried out using finite element analysis and estimated by using a Kriging model. The results show that SOA has outstanding features just as the whale optimization algorithm and salp swarm optimization algorithm for designing optimal components in the industry.

Optimal design of automobile structures using moth-flame optimization algorithm and response surface methodology

2020 ◽  
Vol 62 (4) ◽  
pp. 371-377 ◽  
Author(s):  
Betül Sultan Yıldız
Keyword(s):  
Response Surface Methodology ◽  
Shape Optimization ◽  
Response Surface ◽  
Optimization Algorithm ◽  
Integrated Approach ◽  
Stress Constraint ◽  
Element Analysis ◽  
Component Design ◽  
Automobile Components ◽  
Moth Flame Optimization Algorithm

Abstract In order to present an integrated approach to optimal automobile component design, this research is focused on a shape optimization problem of a bracket using moth-flame optimization algorithm (MFO) and response surface methodology. First, the multiple disc clutch brake problem is optimized using the MFO. Finally, the design problem is posed for shape optimization of the bracket with a mass objective function and a stress constraint. Actual function evaluations are based on finite element analysis while the response surface method is used to obtain the equations for objective and constraint functions. Weight reduction of the bracket is 45.2 % using the MFO. The results show the ability of the MFO to optimize automobile components in the industry.

scholarly journals Relaxed gradient projection algorithm for constrained node-based shape optimization

2021 ◽  
Author(s):  
Ihar Antonau ◽  
Majid Hojjat ◽  
Kai-Uwe Bletzinger
Keyword(s):  
Shape Optimization ◽  
Optimization Problems ◽  
Gradient Projection ◽  
Projection Algorithm ◽  
Design Parameters ◽  
Active Set ◽  
Physical Constraints ◽  
Original Algorithm ◽  
Gradient Projection Algorithm ◽  
Non Linear

AbstractIn node-based shape optimization, there are a vast amount of design parameters, and the objectives, as well as the physical constraints, are non-linear in state and design. Robust optimization algorithms are required. The methods of feasible directions are widely used in practical optimization problems and know to be quite robust. A subclass of these methods is the gradient projection method. It is an active-set method, it can be used with equality and non-equality constraints, and it has gained significant popularity for its intuitive implementation. One significant issue around efficiency is that the algorithm may suffer from zigzagging behavior while it follows non-linear design boundaries. In this work, we propose a modification to Rosen’s gradient projection algorithm. It includes the efficient techniques to damp the zigzagging behavior of the original algorithm while following the non-linear design boundaries, thus improving the performance of the method.

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