scholarly journals Food Vehicle Frame Topology Optimization Based on Bi-directional Interpolation Model

2016 ◽  
Vol 10 (6) ◽  
pp. 401-404
Author(s):  
Lu Jianfeng ◽  
Li Jiachun ◽  
Chen Lunjun ◽  
LI Yugang ◽  
Han Jinjin
Keyword(s):  
Topology Optimization ◽  
Interpolation Model ◽  
Directional Interpolation

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.

scholarly journals Designing Self Supported SLM Structures via Topology Optimization

2019 ◽  
Vol 3 (3) ◽  
pp. 68 ◽  
Author(s):  
B. Barroqueiro ◽  
A. Andrade-Campos ◽  
R. A. F. Valente
Keyword(s):  
Topology Optimization ◽  
Numerical Stability ◽  
Discrete Solution ◽  
Interpolation Model ◽  
Equilibrium Equations ◽  
Feature Size ◽  
Economic Competitiveness ◽  
Material Interpolation ◽  
The Subject ◽  
Minimum Feature Size

The potential of Additive Manufacturing (AM) is high, with a whole new set of manufactured parts with unseen complexity being offered. However, the process has limitations, and for the sake of economic competitiveness, these should also be considered. Therefore, a computational methodology, capable of including the referenced limitations and providing initial solid designs for Selective Laser Melting (SLM) is the subject of the present work. The combination of Topology Optimization (TO) with the simplified fabrication model is the selected methodology. Its formulation, implementation, and integration on the classic TO algorithm is briefly discussed, being capable of addressing the minimum feature size and the overhang constraint limitations. Moreover, the performance and numerical stability of the methodology is evaluated, and numerical variables, such as the accuracy of structural equilibrium equations and the material interpolation model, are considered. A comparative study between these variables is presented. The paper then proposes an enhanced version of the selected methodology, with a better convergence towards a discrete solution.

Topology Optimization of IPM Motors using Fourier Series

2017 ◽  
Vol 137 (3) ◽  
pp. 245-253
Author(s):  
Hidenori Sasaki ◽  
Hajime Igarashi
Keyword(s):  
Fourier Series ◽  
Topology Optimization

Topology Optimization of Superconducting Electromagnets for Particle Accelerators

2019 ◽  
Vol 139 (9) ◽  
pp. 568-575
Author(s):  
Yusuke Sakamoto ◽  
Daisuke Ishizuka ◽  
Tetsuya Matsuda ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki
Keyword(s):  
Topology Optimization ◽  
Particle Accelerators

Topology Optimization using Deep Learning

2020 ◽  
Vol 140 (12) ◽  
pp. 858-865
Author(s):  
Hidenori Sasaki ◽  
Yuki Hidaka ◽  
Hajime Igarashi
Keyword(s):  
Deep Learning ◽  
Topology Optimization
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