scholarly journals Shape Optimization Design for a Centrifuge Structure with Multi Topological Configurations Based on the B-Spline FCM and GCMMA

2020 ◽  
Vol 10 (2) ◽  
pp. 620
Author(s):  
Xinyao Li ◽  
Liangli He
Keyword(s):  
Shape Optimization ◽  
Optimization Design ◽  
Design Method ◽  
Von Mises Stress ◽  
Design Solution ◽  
Deformation And Failure ◽  
B Spline ◽  
Geotechnical Centrifuge ◽  
Final Configuration ◽  
Deep Groove

The geotechnical centrifuge applied in various geotechnical engineering fields provides physical data for investigating mechanisms of deformation and failure and for validating analytical and numerical methods by simulating and studying the geotechnical problems. The basket, as one of the important components used to place the inspection model of centrifugal test, is designed to withstand complex loads. This paper presents an optimization design method for the basket based on the weighted B-Spline Finite Cell Method (FCM) and the globally-convergent method of moving asymptotes (GCMMA). In order to obtain a superior design solution, four topological configurations, i.e., original single web, porous dual web, open deep groove dual web, and connected closed dual web, are investigated and optimized. The mass is selected as the optimization objective, while key shape parameters and stress are regarded as design variables and the constraint, respectively. By optimization, the final masses of the four configurations are reduced greatly compared with the initial configurations, where the greatest weight loss, in case 4, is 10.6%. This indicates that the weighted B-Spline FCM and GCMMA can be well applied for shape optimization of structure in engineering design. In contrast to the final single web adopted in the traditional basket design in case 1, the final configuration in case 4, i.e., connected closed dual web, has the least mass. The final mass is reduced by 133.38 kg when the centrifuge strength requirement is met. Therefore, the final configuration in case 4, where the maximum von-Mises stress is 398.72MPa and mass is 781.82 kg, is superior to the three other configurations.

A new jig-shape optimization method for the high aspect ratio wing

2018 ◽  
Vol 91 (1) ◽  
pp. 124-133
Author(s):  
Zhe Yuan ◽  
Shihui Huo ◽  
Jianting Ren
Keyword(s):  
Aspect Ratio ◽  
Shape Optimization ◽  
High Aspect Ratio ◽  
Optimization Design ◽  
Design Method ◽  
Aircraft Design ◽  
Optimization Method ◽  
Attack Angle ◽  
Structural Deformation ◽  
Content Type

Purpose Computational efficiency is always the major concern in aircraft design. The purpose of this research is to investigate an efficient jig-shape optimization design method. A new jig-shape optimization method is presented in the current study and its application on the high aspect ratio wing is discussed. Design/methodology/approach First, the effects of bending and torsion on aerodynamic distribution were discussed. The effect of bending deformation was equivalent to the change of attack angle through a new equivalent method. The equivalent attack angle showed a linear dependence on the quadratic function of bending. Then, a new jig-shape optimization method taking integrated structural deformation into account was proposed. The method was realized by four substeps: object decomposition, optimization design, inversion and evaluation. Findings After the new jig-shape optimization design, both aerodynamic distribution and structural configuration have satisfactory results. Meanwhile, the method takes both bending and torsion deformation into account. Practical implications The new jig-shape optimization method can be well used for the high aspect ratio wing. Originality/value The new method is an innovation based on the traditional single parameter design method. It is suitable for engineering application.

3D Aided Design Solution for Integrated Pipe Network of Subway Station

2013 ◽  
Vol 368-370 ◽  
pp. 1438-1442
Author(s):  
Yong Zhang ◽  
Qian Kun Wang ◽  
Chen Bin
Keyword(s):  
Design Process ◽  
Optimization Design ◽  
3D Visualization ◽  
Design Method ◽  
Secondary Development ◽  
Design Solution ◽  
Subway Station ◽  
Pipe Network ◽  
Analysis Technique ◽  
Aided Design

Based on analysis of problems existing in the design process of integrated pip network, the authors put forward the aided design method of converting 2D design drawings to 3D visualization model. Based on the 3D aided design workflow, the solution of 3D aided design is proposed, the kernel contains include: making drawing standard and development of the plug-in, selection and secondary development of 3D platform, report of conflict analysis and optimization design. The key analysis technique is discussed in the end of this paper.

Radar Cross Section Reduction and Shape Optimization using Adjoint Method and Automatic Differentiation

2021 ◽  
Vol 36 (3) ◽  
pp. 320-335
Author(s):  
Ming Li ◽  
Junqiang Bai ◽  
Feng Qu
Keyword(s):  
Shape Optimization ◽  
Cross Section ◽  
Optimization Design ◽  
Adjoint Method ◽  
Evaluation Method ◽  
Automatic Differentiation ◽  
Design Method ◽  
Radar Cross Section ◽  
Memory Consumption ◽  
Gradient Based

An efficient Radar Cross Section (RCS) gradient evaluation method based on the adjoint method is presented. The Method of Moments is employed to solve the Combined Field Integral Equation (CFIE) and the corresponding derivatives computing routines are generated by the program transformation Automatic Differentiation (AD) technique. The differential code is developed using three kinds of AD mode: tangent mode, multidirectional tangent mode, and adjoint mode. The differential code in adjoint mode is modified and optimized by changing the “two-sweeps” architecture into the “inner-loop two-sweeps” architecture. Their efficiency and memory consumption are tested and the differential code using modified adjoint mode demonstrates the great advantages in both efficiency and memory consumption. A gradient-based shape optimization design method is established using the adjoint method and the mechanism of RCS reduction is studied. The results show that the sharp leading can avoid the specular back-scattering and the undulations of the surface could change the phases which result in a further RCS reduction.

A Parametric Structure Optimization Method for the Jack-Up Platform

2012 ◽  
Author(s):  
Yan-yun Yu ◽  
Yan Lin ◽  
Zhuo-shang Ji
Keyword(s):  
Shape Optimization ◽  
Optimization Design ◽  
Design Method ◽  
Structure Optimization ◽  
Element Model ◽  
Optimization Method ◽  
Structure Model ◽  
Strength Performance ◽  
High Efficient ◽  
Jack Up

In this paper, A parametric structure optimization method, which is called Parametric Structure Shape Optimization Method (PSSOM), is proposed in order to optimize the structure shape of the jack-up platform. According to the characteristic of the jack-up, an approach to create the Parametric Structure Model (PSM) is proposed. The projections of the main structure onto the horizontal plane are used to create the sketch, which is a 2D drawing driven by dimensions. The 3D modeling technique that based on the sketch and feature modeling is used to create the structure model of the jack-up. A meshing procedure is presented to convert PSM into finite element model automatically together with the boundary conditions and the design loads. After calling the FEM solver, the stress and strain for each structure according to any reasonable dimensions could be calculated, and this is the most important foundation of the structure shape optimization design. An optimization design method based on PSM is proposed for the structure optimization design of the jack-up. The genetic algorithm is used to get the optimum dimensions that have better structure strength performance under the premise of that all the other design requirement are satisfied. PSSOM is proved to be practical and high-efficient by the structure optimization of a 300 ft jack-up platform.

Development of an Optimization Design Method for Turbomachinery by Incorporating the Cooperative Coevolution Genetic Algorithm and Adaptive Approximate Model

2011 ◽  
Author(s):  
Peng Song ◽  
Jinju Sun ◽  
Ke Wang ◽  
Zhilong He
Keyword(s):  
Optimal Design ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Optimization Design ◽  
Design Method ◽  
Mathematical Optimization ◽  
Cryogenic Liquid ◽  
Design Solution ◽  
Cooperative Coevolution ◽  
The Real

An optimization design method is developed, which is motivated by the optimal design of a cryogenic liquid turbine (including an asymmetric volute, variable stager vane nozzles, shroud impeller and diffuser) for replacement of the Joule-Thompson throttling valve in the internal compression air-separation unit. The method involves mainly three elements: geometric parameterization, prediction of objective function, and mathematical optimization algorithm. Traditional parameterization approach is used for the geometry representation, while some novel work in the latter two aspects (i.e. objective function evaluation and optimization algorithm) is done to reduce the computing time and improve the optimization solution. A modified Cooperative Coevolution Genetic Algorithms (CCGA) is developed by incorporating a modified variable classification algorithm and some new self-adapted GA operators, which help to enhance the global search ability with an excessive number of optimization variables. Design of Experiment (DOE) is carried out to initialize the kriging approximation model, which is used to approximate the time-costly objective function. Then the CCGA is started, and once a potential superior individual is found, a decision will be made by the in-house code on whether or not it needs a updating. If required, the true objective function prediction based on the real model will be conducted and the obtained value of objective function will be used to update the kriging model. In such a way, the CCGA can complete its optimal searching with a limited number of real evaluations for objective function. All the above features are integrated into the optimization framework and encoded for the optimal turbine design. In addition, CFD software ANSYS CFX is used for the real objective function evaluations, and a well-organized batch code is developed by the authors for calling the CFD simulation which helps to promote this automation of the optimization process. For validation, the optimization method is used to solve some classical mathematical optimization problems and its effectiveness is demonstrated. The method is then used in the optimal design of the cryogenic liquid turbine stage, it is demonstrated that the optimal design method can help to reduce significantly the searching time for the optimal design and improve the design solution to the liquid turbine.

Efficient Optimization Design Method Using Kriging Model

2005 ◽  
Vol 42 (5) ◽  
pp. 1375-1375 ◽  
Author(s):  
Shinkyu Jeong ◽  
Mitsuhiro Murayama ◽  
Kazuomi Yamamoto
Keyword(s):  
Optimization Design ◽  
Design Method ◽  
Kriging Model

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

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