Shape optimization of piecewise developable free-form grid surface using plate components

2021 ◽  
Vol 245 ◽  
pp. 112865
Author(s):  
Jinglan Cui ◽  
Yanfeng Zheng ◽  
Makoto Ohsaki ◽  
Yaozhi Luo
2021 ◽  
Vol 26 (2) ◽  
pp. 34
Author(s):  
Isaac Gibert Martínez ◽  
Frederico Afonso ◽  
Simão Rodrigues ◽  
Fernando Lau

The objective of this work is to study the coupling of two efficient optimization techniques, Aerodynamic Shape Optimization (ASO) and Topology Optimization (TO), in 2D airfoils. To achieve such goal two open-source codes, SU2 and Calculix, are employed for ASO and TO, respectively, using the Sequential Least SQuares Programming (SLSQP) and the Bi-directional Evolutionary Structural Optimization (BESO) algorithms; the latter is well-known for allowing the addition of material in the TO which constitutes, as far as our knowledge, a novelty for this kind of application. These codes are linked by means of a script capable of reading the geometry and pressure distribution obtained from the ASO and defining the boundary conditions to be applied in the TO. The Free-Form Deformation technique is chosen for the definition of the design variables to be used in the ASO, while the densities of the inner elements are defined as design variables of the TO. As a test case, a widely used benchmark transonic airfoil, the RAE2822, is chosen here with an internal geometric constraint to simulate the wing-box of a transonic wing. First, the two optimization procedures are tested separately to gain insight and then are run in a sequential way for two test cases with available experimental data: (i) Mach 0.729 at α=2.31°; and (ii) Mach 0.730 at α=2.79°. In the ASO problem, the lift is fixed and the drag is minimized; while in the TO problem, compliance minimization is set as the objective for a prescribed volume fraction. Improvements in both aerodynamic and structural performance are found, as expected: the ASO reduced the total pressure on the airfoil surface in order to minimize drag, which resulted in lower stress values experienced by the structure.


2019 ◽  
Vol 9 (15) ◽  
pp. 3168
Author(s):  
Bingbing San ◽  
Yunlong Ma ◽  
Zhi Xiao ◽  
Dongming Feng ◽  
Liwei Yin

This work investigates the natural vibration characteristics of free-form shells when considering the influence of uncertainties, including initial geometric imperfection, shell thickness deviation, and elastic modulus deviation. Herein, free-form shell models are generated while using a self-coded optimization algorithm. The Latin hypercube sampling (LHS) method is used to draw the samplings of uncertainties with respect to their stochastic probability models. ANSYS finite element (FE) software is adopted to analyze the natural vibration characteristics and compute the natural frequencies. The mean values, standard deviations, and cumulative distributions functions (CDFs) of the first three natural frequencies are obtained. The partial correlation coefficient is adopted to rank the significances of uncertainty factors. The study reveals that, for the free-form shells that were investigated in this study, the natural frequencies is a random quantity with a normal distribution; elastic modulus deviation imposes the greatest effect on natural frequencies; shell thickness ranks the second; geometrical imperfection ranks the last, with a much lower weight than the other two factors, which illustrates that the shape of the studied free-form shells is robust in term of natural vibration characteristics; when the supported edges are fixed during the shape optimization, the stochastic characteristics do not significantly change during the shape optimization process.


2013 ◽  
Vol 60 (3) ◽  
pp. 537-563 ◽  
Author(s):  
Francesco Ballarin ◽  
Andrea Manzoni ◽  
Gianluigi Rozza ◽  
Sandro Salsa

2016 ◽  
Vol 23 (1) ◽  
pp. 012702 ◽  
Author(s):  
Shaoen Jiang ◽  
Yunbao Huang ◽  
Longfei Jing ◽  
Haiyan Li ◽  
Tianxuan Huang ◽  
...  

1996 ◽  
Vol 11 (3-4) ◽  
pp. 159-169 ◽  
Author(s):  
S. Guillet ◽  
F. No�l ◽  
J. C. L�on

Author(s):  
Jiaqin Chen ◽  
Vadim Shapiro ◽  
Krishnan Suresh ◽  
Igor Tsukanov

We propose a novel approach to shape optimization that combines and retains the advantages of the earlier optimization techniques. The shapes in the design space are represented implicitly as level sets of a higher-dimensional function that is constructed using B-splines (to allow free-form deformations), and parameterized primitives combined with R-functions (to support desired parametric changes). Our approach to shape design and optimization offers great flexibility because it provides explicit parametric control of geometry and topology within a large space of freeform shapes. The resulting method is also general in that it subsumes most other types of shape optimization as special cases. We describe an implementation of the proposed technique with attractive numerical properties. The effectiveness of the method is demonstrated by several numerical examples.


Author(s):  
Stavros N. Leloudas ◽  
Georgios N. Lygidakis ◽  
Giorgos A. Strofylas ◽  
Ioannis K. Nikolos

An adaptable numerical scheme for the aerodynamic shape optimization of axisymmetric diffuser-augmented wind turbine shrouds is demonstrated in this work, using an asynchronous and parallel version of a Differential Evolution (DE) algorithm. The simulation of the incompressible flow field about each candidate geometry is succeeded by means of an in-house Computational Fluid Dynamics (CFD) solver, that has been developed based on the specially modified, by the artificial compressibility approach, Navier-Stokes equations, expressed in non-dimensional form, for 2D-axisymmetric frames of reference. The discretization of the computational domain is made with 2D hybrid unstructured meshes, composed by both triangular and quadrilateral elements, combined with a node-centered finite-volume scheme, while the Free-Form Deformation (FFD) technique is applied, for both the parameterization of the design geometry and the morphing of the computational mesh. The required data transfer between the DE algorithm and the CFD solver is accomplished with appropriate text files, while the parallel implementation is achieved utilizing the Message Passing Interface (MPI) library functions. Further acceleration of the optimization procedure is succeeded by the combination of the DE with surrogate models, in order to replace the costly CFD-based evaluations of the candidate solutions with fast, but approximate estimations of their cost function.


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