Structural strength and laminate optimization of self-twisting composite hydrofoils using a Genetic Algorithm

2017 ◽  
Vol 176 ◽  
pp. 359-378 ◽  
Author(s):  
Manudha T. Herath ◽  
B. Gangadhara Prusty ◽  
Andrew W. Phillips ◽  
Nigel St. John
Keyword(s):  
Genetic Algorithm ◽  
Structural Strength ◽  
Laminate Optimization

Structural Strength and Laminate Optimization of Composite Connecting Bracket in Manned Spacecraft Using a Genetic Algorithm

2018 ◽  
Vol 26 (2) ◽  
pp. 591-604 ◽  
Author(s):  
Ke Li ◽  
Xuewen Liu ◽  
Yulong Jin ◽  
Hongzhong Qi ◽  
Xintian Liu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Structural Strength ◽  
Manned Spacecraft ◽  
Laminate Optimization

Genetic Algorithm Optimization of a Double Four-Bar Manipulator

2013 ◽  
Vol 834-836 ◽  
pp. 1323-1326
Author(s):  
Qi Jing Tang ◽  
Tie Shi Zhao
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Structural Strength ◽  
Optimization Method ◽  
Installation Space ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Transmission Angle ◽  
The Mathematical Model

In order to optimize the dimension of a manipulator, the optimization requirements are analyzed. Then the mathematical model and optimization objectives are established. Next, the lengths of the manipulator are optimized by Matlab genetic algorithm optimization toolbox. The structural strength and bearing installation space are considered at the same time. The trajectory and transmission angle are compared. Finally, the lengths which meet the use requirements are obtained. This optimization method provides a reference for similar mechanism.

Optimization of Ships’ Diagonal Ballast Water Exchange Sequence Using a Multiobjective Genetic Algorithm

2010 ◽  
Vol 54 (04) ◽  
pp. 257-267
Author(s):  
Jing Chen ◽  
Yan Lin ◽  
Junzhou Huo ◽  
Mingxia Zhang ◽  
Zhuoshang Ji
Keyword(s):  
Genetic Algorithm ◽  
Ballast Water ◽  
Structural Strength ◽  
Mathematic Model ◽  
Pareto Solutions ◽  
Sequential Method ◽  
Exchange Method ◽  
Pareto Solution ◽  
Multiobjective Genetic Algorithm ◽  
Intact Stability

Ballast water management and the method chosen to achieve it is a key issue and concerns key technologies in ship design. If the sequential exchange method is the chosen method, the sequence chosen to perform the exchange is very important and affects many aspects including ships' stability, structural strength, maneuverability, operational expenses and building cost, and so forth. In this paper, based on the multiple risk assessment criteria of the sequential method, the problem of finding a feasible and optimum exchange sequence is boiled down to a multiobjective combinatorial optimization problem with multiple nonlinear constraints. The diagonal exchange strategy was adopted, and the diagonal exchange mathematical model was built, taking into consideration the ship's intact stability, structural strength, trims, draughts, and bridge vision. In order to find a set of Pareto solutions, a multiobjective genetic algorithm (MOGA) was used. In the algorithm, a constraint-domination principle was adopted to handle the multiple constraints, and a nondominated sorting method was used to perform the selection of the Pareto solutions. Using the proposed mathematic model and the MOGA, a Pareto solution set that met all the design criteria could be efficiently and accurately obtained for the engineers to choose from within short running times. Compared with the traditional symmetrical exchanging method, the simulation results showed that the proposed method can produce more and better solutions with smaller trims, smaller bridge blind vision range, and better structural strength performances.

Decomposition-Based Assembly Synthesis of Multiple Structures for Minimum Manufacturing Cost

2004 ◽  
Vol 127 (4) ◽  
pp. 572-579 ◽  
Author(s):  
Onur L. Cetin ◽  
Kazuhiro Saitou
Keyword(s):  
Genetic Algorithm ◽  
Early Identification ◽  
Economies Of Scale ◽  
Structural Strength ◽  
Manufacturing Cost ◽  
Manufacturing Costs ◽  
Multiobjective Genetic Algorithm ◽  
Trade Offs ◽  
Multiple Structures

An extension of decomposition-based assembly synthesis for structural modularity is presented where the early identification of shareable components within multiple structures is posed as an outcome of the minimization of estimated manufacturing costs. The manufacturing costs of components are estimated under given production volumes considering the economies of scale. Multiple structures are simultaneously decomposed, and the types of welded joints at component interfaces are selected from a given library, in order to minimize the overall manufacturing cost and the reduction of structural strength due to the introduction of joints. A multiobjective genetic algorithm is used to allow effective examination of trade-offs between manufacturing cost and structural strength. A new joint-oriented representation of structures combined with a “direct” crossover is introduced to enhance the efficiency of the search. A preliminary case study with two simplified aluminum space frame automotive bodies is presented to demonstrate that not all types of component sharing are economically justifiable under a certain production scenario.

scholarly journals Structural Strength and Reliability Analysis of Important Parts of Marine Diesel Engine Turbocharger

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Lin Lei ◽  
Ming-ze Ding ◽  
Hong-wei Hu ◽  
Yun-xiao Gao ◽  
Hai-lin Xiong ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Diesel Engine ◽  
Multiobjective Optimization ◽  
Turbine Blade ◽  
Structural Strength ◽  
Turbine Disk ◽  
Marine Diesel Engine ◽  
Nsga Ii ◽  
Multiobjective Genetic Algorithm ◽  
Marine Diesel

Supercharging is the main method to improve the output power of marine diesel engines. Nowadays, most marine diesel engines use turbocharging technology, which increases the air pressure and density into the cylinder and the amount of fuel injected correspondingly so as to achieve the purpose of improving the power. In a marine diesel engine, the turbocharger has become an indispensable part. The performance of turbochargers in a harsh working environment of high temperature and high pressure for a long time will directly affect the performance of diesel engine. Based on the market feedback data from manufacturers, the failure modes of compressor impeller, turbine blade, and turbine disk of marine diesel turbocharger are analyzed, and the statistical model of random factors is established. Using DOE design, the structural strength simulation data of 46 compressors and 62 turbines are obtained, and the response surface model is constructed. On this basis, Monte Carlo sampling is carried out to analyze the reliability of the compressor and turbine. The reliability of the compressor is good, while that of the turbine disk is 0.943 and that of the turbine blade is 0.96, which still has the potential of reliability optimization space. Therefore, a multiobjective optimization method based on the NSGA-II genetic algorithm is proposed to obtain the multiobjective optimization scheme data with the reliability and processing cost of turbine disk and blade as the objective function. After optimization, the reliability of turbine disk and blade is 1, the stress value of turbine blade is optimized by 4.7941%, the stress value of turbine disk is optimized by 3.0136%, the machining cost of the turbine blade is reduced by 15.5087%, and the machining cost of turbine disk is reduced by 3.9907%. At the same time, it is verified by simulation, the data based on NSGA-II multiobjective genetic algorithm are more accurate and have practical engineering reference value. The optimized data based on NSGA-II multiobjective genetic algorithm are used to manufacture new turbine samples, and the accelerated test of simulation samples is carried out. The cycle life of the optimized turbine can reach 101,697 cycles and 118,687 cycles, which is 51.75% and 77.11% longer than that of the unoptimized turbine. It can be seen that the optimized turbine can meet the requirements of the reliability index while reducing the manufacturing cost.

Grillage Structural Optimization Based on Genetic Algorithm and Mechanical Direct Calculation

2014 ◽  
Vol 1061-1062 ◽  
pp. 1135-1139
Author(s):  
Xiao Ning Yao ◽  
Yu Long Zhou ◽  
Xin Sheng Zhang
Keyword(s):  
Genetic Algorithm ◽  
Structural Optimization ◽  
Optimization Design ◽  
Structural Strength ◽  
Structure Optimization ◽  
Direct Calculation ◽  
Optimization Scheme ◽  
Significant Time

In the process of using the genetic algorithm for grillage structural optimization, direct calculation was applied to grillage structural strength Check. The combination of genetic algorithm and direct calculation can save significant time in optimization design and strength check, at the same time, optimized grillage structure provides more security.And then this structure optimization scheme was programmed by VB with easy interface. The example indicates the program, being reasonable and feasible, proves the combination's superiority.

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