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

2014 ◽  
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.

scholarly journals Size and Topology Optimization for Trusses with Discrete Design Variables by Improved Firefly Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yue Wu ◽  
Qingpeng Li ◽  
Qingjie Hu ◽  
Andrew Borgart
Keyword(s):  
Topology Optimization ◽  
Firefly Algorithm ◽  
Optimization Problems ◽  
Optimization Method ◽  
Structural Topology ◽  
Discrete Variables ◽  
And Topology ◽  
Design Variables ◽  
Improved Firefly Algorithm ◽  
Discrete Design Variables

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.

Topology Optimization of Upper Turntable of General Vertical Rocket Rivet Fixture

2014 ◽  
Vol 607 ◽  
pp. 250-256
Author(s):  
Yong Hong Zhang ◽  
Chao Sun ◽  
Wen Tao Gu
Keyword(s):  
Finite Element ◽  
Topology Optimization ◽  
Finite Element Methods ◽  
Optimization Design ◽  
Variable Density ◽  
Paper Analysis ◽  
Analysis And Design ◽  
And Topology ◽  
Optimized Model ◽  
Set Up

In this paper, analysis and design of an upper turntable of general vertical rocket rivet fixture are presented by employing the finite element methods and topology optimization design which are based on the variable density method, in order to reduce the mass and volume of the turntable of general vertical rocket rivet fixture and improve rivet precision. During the design the loadcase is considered: constant force and torque, which is simplified and closer to actual working conditions. From static analysis of the original turntable, a topology optimization model was set up. By using topology optimization calculations a new turntable model was built and the analysis of it using finite element methods was carried out. Comparison between the optimized model and original was conducted and the results show that the stiffness was remarkably improved, the stress was well-distributed and the displacement was reduced after optimization. For designing other complicated structures this method can also provide reference and guidance.

Vertical Tail Topology Optimization Design Based on the Variable Density Method with Constraint Factor

2013 ◽  
Vol 300-301 ◽  
pp. 280-284 ◽  
Author(s):  
Fu Sheng Qiu ◽  
Wu Qiang Ji ◽  
Hou Chao Xu
Keyword(s):  
Topology Optimization ◽  
Optimization Design ◽  
Optimization Method ◽  
Optimality Criteria ◽  
Variable Density ◽  
Structural Constraints ◽  
Structural Topology ◽  
Interpolation Model ◽  
Constraint Factor ◽  
Density Method

The topology optimization design problem with multiple constraints for the complex vertical tail structure is studied in this paper. The variable density structural topology optimization method is improved by introducing a constraint factor. According to the different structural constraints and design requirements, variable factors and element pseudo density are initialized via finite element method. This method is controlled by the constraint factors, and the improved method combining with Rational Approximation of Material Properties (RAMP) density-stiffness interpolation model with optimality criteria methods (OC), the vertical tail’s stiffness optimization has been finished. The density-stiffness interpolation model, the mathematical model of variable density method with constraint factor, the structural optimization model, the solution model of the OC method, the design variables iterative format, are given in this paper and the algorithm with Matlab program is realized. Lastly, a sample vertical tail case is introduced to validate the feasibility of the algorithm by operating the results and analyzing the data.

A Kriging-Interpolated Level-Set Approach for Structural Topology Optimization

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Karim Hamza ◽  
Mohamed Aly ◽  
Hesham Hegazi
Keyword(s):  
Topology Optimization ◽  
Level Set ◽  
Best Practice ◽  
Hybrid Genetic Algorithm ◽  
Mesh Size ◽  
Test Problems ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Level Set Function ◽  
Design Variables

Level-set approaches are a family of domain classification techniques that rely on defining a scalar level-set function (LSF), then carrying out the classification based on the value of the function relative to one or more thresholds. Most continuum topology optimization formulations are at heart, a classification problem of the design domain into structural materials and void. As such, level-set approaches are gaining acceptance and popularity in structural topology optimization. In conventional level set approaches, finding an optimum LSF involves solution of a Hamilton-Jacobi system of partial differential equations with a large number of degrees of freedom, which in turn, cannot be accomplished without gradients information of the objective being optimized. A new approach is proposed in this paper where design variables are defined as the values of the LSF at knot points, then a Kriging model is used sto interpolate the LSF values within the rest of the domain so that classification into material or void can be performed. Perceived advantages of the Kriging-interpolated level-set (KLS) approach include alleviating the need for gradients of objectives and constraints, while maintaining a reasonable number of design variables that is independent from the mesh size. A hybrid genetic algorithm (GA) is then used for solving the optimization problem(s). An example problem of a short cantilever is studied under various settings of the KLS parameters in order to infer the best practice recommendations for tuning the approach. Capabilities of the approach are then further demonstrated by exploring its performance on several test problems.

A New Approach for Simultaneous Shape and Topology Optimization Based on Implicit Topology Description Functions

2004 ◽  
Author(s):  
Xu Guo ◽  
Kang Zhao ◽  
Michael Yu Wang
Keyword(s):  
Topology Optimization ◽  
Numerical Experiments ◽  
Shape Derivative ◽  
Structural Topology ◽  
Numerical Instability ◽  
New Approach ◽  
Shape And Topology Optimization ◽  
Topology Description Function ◽  
And Topology ◽  
Non Local

In the present paper, a new approach for structural topology optimization based on implicit topology description function (TDF) is proposed. TDF is used to describe the shape/topology of a structure, which is approximated in terms of the nodal values. Then a relationship is established between the element stiffness and the values of the topology description function on its four nodes. In this way and with some non-local treatments of the design sensitivities, not only the shape derivative but also the topological derivative of the optimal design can be incorporated in the numerical algorithm in a unified way. Numerical experiments demonstrate that by employing this approach, the computational efforts associated with TDF (and level set) based algorithms can be saved. Clear optimal topologies and smooth structural boundaries free from any sign of numerical instability can be obtained simultaneously and efficiently.

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

2014 ◽  
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.

Topology Optimization Design of Pre-Stressed Plane Entity Steel Structure with the Constrains of Stress and Displacement

2014 ◽  
Vol 945-949 ◽  
pp. 1216-1222 ◽  
Author(s):  
Li Yao ◽  
Yun Xia Gao ◽  
Hai Jun Yang
Keyword(s):  
Topology Optimization ◽  
Optimization Design ◽  
Mechanical Performance ◽  
Steel Structure ◽  
Structural Topology ◽  
Unit Size ◽  
Structure Topology ◽  
Design Variables ◽  
Displacement Sensitivity ◽  
Low Sensitivity

For the prestressed plane entitiy steel structure topology optimization design which design variables include the cable pretension value, unit size and the structural topology, the optimized mathematical model which objective function is the minimum structural weight is established with consideration of the constrains of stress and displacement. As for the solving method, firstly we need to determine the pretension applying to the cable according to full stress design and choose the unit size; then we need to conduct displacement sensitivity analysis to delete the low sensitivity unit to realize the structural topology optimization design. The example result is in conformity with the corresponding system of mechanical performance, and it indicates that the method proposed in this paper is effective.

Topology Optimization of Compliant Mechanisms Using Evolutionary Algorithm With Design Geometry Encoded as a Graph

2002 ◽  
Author(s):  
Shamim Akhtar ◽  
Kang Tai ◽  
Jitendra Prasad
Keyword(s):  
Topology Optimization ◽  
Evolutionary Algorithm ◽  
Optimization Problems ◽  
Compliant Mechanism ◽  
Evolutionary Process ◽  
Optimization Procedure ◽  
Structural Topology ◽  
Mutation Operators ◽  
Design Variables ◽  
Straight Line

This paper describes an intuitive way of defining geometry design variables for solving structural topology optimization problems using an evolutionary algorithm (EA). The geometry representation scheme works by defining a skeleton which represents the underlying topology/connectivity of the continuum structure. As the effectiveness of any EA is highly dependent on the chromosome encoding of the design variables, the encoding used here is a graph which reflects this underlying topology so that the genetic crossover and mutation operators of the EA can recombine and preserve any desirable geometric characteristics through succeeding generations of the evolutionary process. The overall optimization procedure is applied to design a straight-line compliant mechanism : a large displacement flexural structure that generates a vertical straight line path at some point when given a horizontal straight line input displacement at another point.

scholarly journals A Firefly Algorithm Based Hybrid Method for Structural Topology Optimization

2020 ◽  
Author(s):  
Hailu Shimels Gebremedhen ◽  
Dereje Engida Woldemichael ◽  
Fakhruldin Mohd Hashim
Keyword(s):  
Topology Optimization ◽  
Hybrid Algorithm ◽  
Firefly Algorithm ◽  
Optimization Problems ◽  
Optimality Criteria ◽  
Benchmark Problems ◽  
Material Distribution ◽  
Structural Topology ◽  
Weight Percentage ◽  
Design Variables

Abstract In this paper a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability of generating connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. Lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize firefly algorithm based section of the hybrid algorithm. Input parameters, number of fireflies and number function evaluations were determined before implementation of firefly algorithm to solve formulated problems. Since direct application of firefly algorithm cannot generate connected topologies, outputs from firefly algorithm were used as an initial input material distribution for OC method. The proposed method was validated using two-dimensional benchmark problems and the results were compared with results using OC method. Weight percentage reduction, maximum stress induced, optimal material distribution and compliance were used to compare results. Results from the proposed method showed that the proposed method can generate connected topologies and generated topologies are free from interference of end users, which only dependence on boundary conditions or the design variables. From the results, the objective function (weight of the design domain) can be further reduced in the range of 5% to 15% compared to OC method.

scholarly journals A Firefly Algorithm Based Hybrid Method for Structural Topology Optimization

2020 ◽  
Author(s):  
Hailu Shimels Gebremedhen ◽  
Dereje Engida Woldemichael ◽  
Fakhruldin Mohd Hashim
Keyword(s):  
Topology Optimization ◽  
Hybrid Algorithm ◽  
Firefly Algorithm ◽  
Optimization Problems ◽  
Optimality Criteria ◽  
Benchmark Problems ◽  
Material Distribution ◽  
Structural Topology ◽  
Weight Percentage ◽  
Design Variables

Abstract In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. Input parameters, the number of fireflies, and number function evaluations were determined before the implementation of the firefly algorithm to solve formulated problems. Since the direct application of the firefly algorithm cannot generate connected topologies, outputs from the firefly algorithm were used as an initial input material distribution for the OC method. The proposed method was validated using two-dimensional benchmark problems and the results were compared with results using the OC method. Weight percentage reduction, maximum stress-induced, optimal material distribution, and compliance were used to compare results. Results from the proposed method showed that the proposed method can generate connected topologies and generated topologies are free from the interference of end-users, which only dependence on boundary conditions or the design variables. From the results, the objective function (weight of the design domain) can be further reduced in the range of 5% to 15% compared to the OC method.

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