Mixing and Refinement of Design Variables for Geometry and Topology Optimization in Aerodynamics

Firefly Algorithm (FA, for short) is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly, development of structural topology optimization method and the basic principle of standard FA are introduced in detail. Then, in order to apply the algorithm to optimization problems with discrete variables, the initial positions of fireflies and the position updating formula are discretized. By embedding the random-weight and enhancing the attractiveness, the performance of this algorithm is improved, and thus an Improved Firefly Algorithm (IFA, for short) is proposed. Furthermore, using size variables which are capable of including topology variables and size and topology optimization for trusses with discrete variables is formulated based on the Ground Structure Approach. The essential techniques of variable elastic modulus technology and geometric construction analysis are applied in the structural analysis process. Subsequently, an optimization method for the size and topological design of trusses based on the IFA is introduced. Finally, two numerical examples are shown to verify the feasibility and efficiency of the proposed method by comparing with different deterministic methods.

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Study of Parametric and Non-Parametric Optimization of a Rotor-Bearing System

Volume 7A: Structures and Dynamics ◽

10.1115/gt2014-25095 ◽

2014 ◽

Cited By ~ 2

Author(s):

Youngwon Hahn ◽

John I. Cofer

Keyword(s):

Topology Optimization ◽

Critical Speed ◽

Parametric Optimization ◽

Optimization Methods ◽

Optimization Process ◽

Support Structure ◽

And Topology ◽

Design Variables ◽

Rotor Bearing ◽

Non Parametric

The optimization techniques most widely used in various industrial fields for structural optimization generally can be placed into two categories: parametric optimization and non-parametric optimization. In parametric optimization, the parametric variables defining a geometric model are used as design variables. For example, all dimensions defining a structural shape in a CAD (Computer-Aided Design) system can be used as parameters in an optimization process to achieve a desired objective. In non-parametric optimization, an initial outer boundary of the geometry is defined and the optimization process either removes mass without changing the node locations in the calculation mesh (topology optimization) or directly manipulates the node locations (shape optimization) to achieve a desired objective. Nowadays, the combination of both parametric and non-parametric optimization methods can provide an attractive approach to satisfy the requirements of advanced levels of structural performance. While optimization methods have been widely used in many turbomachinery applications, such as turbine and compressor blading, combustors, and casings, in the rotordynamics field, relatively little work has been done to investigate methods for the overall optimization of rotor-bearing-support structures to achieve desired system behavior. In this paper, a combined parametric and non-parametric optimization method is applied to a rotor-bearing-support structure in order to achieve the desired critical speed and unbalance response. The bearing design variables are selected as parametric design variables and topology optimization is applied to the support structure. The entire optimization workflow is constructed in the commercial software Isight, and Abaqus and ATOM (Abaqus Topology Optimization Module) are used for rotordynamics analysis and topology optimization. The desired critical speed and unbalance response can be obtained with the optimized topology of the support structure.

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Structure Analysis and Topology Optimization of a Bent-Bar-Frame Piston Based on the Variable Density Approach

Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing ◽

10.1115/dscc2014-6118 ◽

2014 ◽

Cited By ~ 2

Author(s):

Jie Zhao ◽

Farong Du ◽

Wei Yao

Keyword(s):

Topology Optimization ◽

Thermal Loading ◽

Coupled Model ◽

Variable Density ◽

Structural Topology ◽

Connecting Rod ◽

And Topology ◽

Design Variables ◽

Cylinder Piston ◽

Optimized Model

The iterative algorithm of design variables for structural topology optimization is derived by using variable density approach and Finite Element Method. A coupled model of bent-bar-frame piston is built considering the contact between piston and cylinder, piston and piston pin, piston pin and connecting rod. Based on this model, the deformation and stress of piston are analyzed under each of mechanical or thermal loading. Taking structural weight as the objective function of optimization, three desired regions of piston are optimized by using variable density approach in commercial FEA software HYPERMESH and ANSYS. Finally, the deformation and temperature of the optimized model are compared with prototype by using the same loading and boundary conditions. The results show that the weight of piston is reduced by 12.5% while meeting the required specifications.

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Optimal Design of CNC Crushing Machine Steady Based on Genetic Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.397-400.1129 ◽

2013 ◽

Vol 397-400 ◽

pp. 1129-1132

Author(s):

De Xin Zhang ◽

Ming Jian Han ◽

Yang Jie Ou ◽

Guo Qing Wang ◽

Guo Qing Hao ◽

...

Keyword(s):

Genetic Algorithm ◽

Genetic Algorithms ◽

Topology Optimization ◽

Optimization Design ◽

Structure Optimization ◽

Multi Objective Optimization ◽

Shape And Topology Optimization ◽

And Topology ◽

Design Variables ◽

Starting Point

The Genetic Algorithms In engineering structure optimization design includes Truss Structure optimization, Shape and topology optimization, Composite materials optimization, layout optimization, Multi-Objective Optimization. This paper combined with engineering background , Selecting the Pressing gear of CNC crushing Machine Steady as starting point for Optimization modeling .Analyzing the simple conditions theoretical physical model of CNC Crushing Machine Steady, Reasonably selected design variables ,using Conventional Methods and genetic algorithms to optimize the Steady ,obtainning every iterative step relevant data under the two methods, and analyzing the results ,analysis the accuracy of the optimize results through the stress and displacement map .

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Vibration Reduction Design with Hybrid Structures and Topology Optimization

Polish Maritime Research ◽

10.1515/pomr-2016-0040 ◽

2016 ◽

Vol 23 (s1) ◽

pp. 10-19 ◽

Cited By ~ 4

Author(s):

Fali Huo ◽

Deqing Yang ◽

Yinzhi Zhao

Keyword(s):

Topology Optimization ◽

Weight Control ◽

Vibration Reduction ◽

Topology Design ◽

Hybrid Structures ◽

Truss Structures ◽

Materials Selection ◽

Simp Method ◽

And Topology ◽

Design Variables

Abstract The hybrid structures show excellent performance on vibration reduction for ship, aircraft and spacecraft designs. Meanwhile, the topology optimization is widely used for structure vibration reduction and weight control. The design of hybrid structures considering simultaneous materials selection and topology optimization are big challenges in theoretical study and engineering applications. In this paper, according to the proposed laminate component method (LCM) and solid isotropic microstructure with penalty (SIMP) method, the mathematical formulations are presented for concurrent materials selection and topology optimizations of hybrid structures. Thickness distributions of the plies in laminate components are defined as materials selection design variables by LCM method. Relative densities of elements in the components are defined as topology design variables by SIMP method. Design examples of hybrid 3-bar truss structures and hybrid floating raft with vibration reduction requirements verified the effectiveness of the presented optimization models.

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Anisotropic Mesh Adaptation and Topology Optimization in Three Dimensions

Journal of Mechanical Design ◽

10.1115/1.4032266 ◽

2016 ◽

Vol 138 (6) ◽

Cited By ~ 10

Author(s):

Kristian Ejlebjerg Jensen

Keyword(s):

Topology Optimization ◽

Mesh Adaptation ◽

Three Dimensions ◽

Test Cases ◽

Anisotropic Mesh ◽

Aspect Ratios ◽

And Topology ◽

Design Variables ◽

Mesh Independence ◽

Anisotropic Mesh Adaptation

Anisotropic mesh adaptation has been used to accelerate computation in several engineering fields, and we show that it can also be used for topology optimization. We use a combination of filtered continuous sensitivities and filtered design variables to drive the mesh adaptation. The filtered design variables are computed for this purpose only, while the filtered sensitivities are used as input to the optimizer. We test mesh independence for a cantilever problem and also show results for two other test cases. Finally, speedup relative to isotropic adaptation is estimated at 50 using average element aspect ratios.

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