Optimal Design of Two-Stage-To-Orbit Space Planes with Airbreathing Engines

2005 ◽  
Vol 42 (1) ◽  
pp. 90-97 ◽  
Author(s):  
Takeshi Tsuchiya ◽  
Takashige Mori
Keyword(s):  
Optimal Design ◽  
Orbit Space ◽  
Two Stage

Optimal design of two-stage ejector for subzero refrigeration system on fishing vessel

2021 ◽  
Vol 187 ◽  
pp. 116565
Author(s):  
Xinli Wang ◽  
Lei Wang ◽  
Yajie Song ◽  
Jie Deng ◽  
Youjie Zhan
Keyword(s):  
Optimal Design ◽  
Refrigeration System ◽  
Fishing Vessel ◽  
Two Stage

scholarly journals Solving the problem of optimal design for a two-stage reducer by using a modified evolutionary algorithm

2020 ◽  
Vol 317 ◽  
pp. 01004
Author(s):  
Oleksandr Ustynenko ◽  
Oleksiy Bondarenko ◽  
Volodymyr Serykov
Keyword(s):  
Optimal Design ◽  
Evolutionary Algorithm ◽  
Specific Problem ◽  
Functional Limitations ◽  
Evolutionary Process ◽  
Design Parameters ◽  
Initial Population ◽  
Objective Functions ◽  
Two Stage ◽  
Test Points

The work is devoted to solving the problem of selecting optimal geometric parameters of gears of a two-stage cylindrical reducer using a modified evolutionary algorithm (EA). The statement of the problem is considered, design parameters, objective functions, limitations on design parameters are determined. This allowed us to propose a modification of EA. To generate the initial test points, it was proposed to use the LP-τ sequence, this allowed us to reduce the initial population of test points and bring EA closer to a truly “random” process. The scheme of the proposed algorithm is considered, which gives an idea of the sequence of operations that are carried out with populations of test points at each stage of the evolutionary process. The solution of the specific problem of selecting optimal parameters for a serial reducer is given. The input data, numerical and functional limitations are determined, the objective functions are formed. The results of the solution are shown in several presentation formats: tabular and graphical, which allows to qualitatively interpret and analyze the results. Conclusions are made about testing the proposed algorithm for solving a specific problem of optimal design. Further ways of improving this methodology are proposed.

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