scholarly journals A shape optimization algorithm for cellular composites

2021 ◽  
Keyword(s):  
Shape Optimization ◽  
Optimization Algorithm ◽  
Elastic Energy ◽  
Inner Product ◽  
Mesh Deformation ◽  
Multigrid Solver ◽  
Parallel Scalability ◽  
Shape Spaces ◽  
Linear Elastic ◽  
Geometric Multigrid

We propose and investigate a mesh deformation technique for PDE constrained shape optimization. Introducing a gradient penalization to the inner product for linearized shape spaces, mesh degeneration can be prevented within the optimization iteration allowing for the scalability of employed solvers. We illustrate the approach by a shape optimization for cellular composites with respect to linear elastic energy under tension. The influence of the gradient penalization is evaluated and the parallel scalability of the approach demonstrated employing a geometric multigrid solver on hierarchically distributed meshes.

scholarly journals Minimization of energy consumption by building shape optimization using an improved Manta-Ray Foraging Optimization algorithm

2021 ◽  
Vol 7 ◽  
pp. 1068-1078
Author(s):  
Jiaying Feng ◽  
Xiaoguang Luo ◽  
Mingzhe Gao ◽  
Adnan Abbas ◽  
Yi-Peng Xu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Shape Optimization ◽  
Optimization Algorithm ◽  
Building Shape ◽  
Manta Ray

An enhanced manta ray foraging optimization algorithm for shape optimization of complex CCG-Ball curves

2022 ◽  
pp. 108071
Author(s):  
Gang Hu ◽  
Min Li ◽  
Xiaofeng Wang ◽  
Guo Wei ◽  
Ching-Ter Chang
Keyword(s):  
Shape Optimization ◽  
Optimization Algorithm ◽  
Manta Ray

Concurrent Blade Aerodynamic-Aeroelastic Design Optimization With Re-Scaled Response Surface

2014 ◽  
Author(s):  
O. Valero ◽  
L. He ◽  
Y. S. Li
Keyword(s):  
Shape Optimization ◽  
Response Surface ◽  
Optimization Algorithm ◽  
Multidisciplinary Optimization ◽  
Gradient Algorithm ◽  
Optimized Design ◽  
Element Analysis ◽  
Structural Dynamic ◽  
Flow Equations ◽  
Blade Shape

Given the ever increasing demands on turbomachinery performance, various advanced blade shape optimizations have been actively developed and applied in modern blading designs. Multidisciplinary and concurrent optimizations have attracted considerable attention, offering the advantage of disciplinary interactions being included more simultaneously in a design process. This paper presents the development of a multidisciplinary optimization algorithm for the concurrent blade aerodynamic and aeromechanic shape optimization of realistic 3D turbine stages. A non-gradient algorithm is enhanced by a new re-scaled response surface (RSM) model. This meta-model is able to rescale the design space and redefine the response surface during a blade shape optimization process, leading to a much enhanced convergence compared to a standard RSM approach. The optimization algorithm is developed in conjunction with an efficient nonlinear harmonic phase solution method solving the unsteady flow equations in the frequency domain, combined with a finite element analysis (FEA) to extract the structural dynamic characteristics of the blades. The effectiveness of the concurrent method is examined for an optimized design of a realistic LP turbine stage. The optimization goals are the maximization of the isentropic stage efficiency and aeroelastic flutter stability (aero-damping). Two sets of cases are considered. In the first set, the shaping is applied only to stator blades, while for the second set, both stator and rotor blades are shaped. The concurrent cases are compared with their single-disciplinary counterparts. For both sets of the cases, the advantages of the concurrent treatment are clearly demonstrated.

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