Harnessing shape optimization techniques to develop novel methods to determine shear properties in PMCs

2021 ◽  
Vol 200 ◽  
pp. 110782
Author(s):  
Luke Geise ◽  
Ryan Seifert ◽  
Andrew Abbott ◽  
Daniel Rapking ◽  
Mark Flores
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.


1998 ◽  
Vol 4 (1) ◽  
pp. 21-42 ◽  
Author(s):  
J. N. Rajadas ◽  
A. Chattopadhyay ◽  
N. Pagaldipti ◽  
S. Zhang

A multidisciplinary optimization procedure, with the integration of aerodynamic and heat transfer criteria, has been developed for the design of gas turbine blades. Two different optimization formulations have been used. In the first formulation, the maximum temperature in the blade section is chosen as the objective function to be minimized. An upper bound constraint is imposed on the blade average temperature and a lower bound constraint is imposed on the blade tangential force coefficient. In the second formulation, the blade average and maximum temperatures are chosen as objective functions. In both formulations, bounds are imposed on the velocity gradients at several points along the surface of the airfoil to eliminate leading edge velocity spikes which deteriorate aerodynamic performance. Shape optimization is performed using the blade external and coolant path geometric parameters as design variables. Aerodynamic analysis is performed using a panel code. Heat transfer analysis is performed using the finite element method. A gradient based procedure in conjunction with an approximate analysis technique is used for optimization. The results obtained using both optimization techniques are compared with a reference geometry. Both techniques yield significant improvements with the multiobjective formulation resulting in slightly superior design.


Author(s):  
Ashraf O. Nassef ◽  
Hesham A. Hegazi ◽  
Sayed M. Metwalli

Abstract The hybridization of different optimization methods have been used to find the optimum solution of design problems. While random search techniques, such as genetic algorithms and simulated annealing, have a high probability of achieving global optimality, they usually arrive at a near optimal solution due to their random nature. On the other hand direct search methods are efficient optimization techniques but linger in local minima if the objective function is multi-modal. This paper presents the optimization of C-frame cross-section using a hybrid optimization algorithm. Real coded genetic algorithms are used as a random search method, while Nelder-Mead is used as a direct search method, where the result of the genetic algorithm search is used as the starting point of direct search. Traditionally, the cross-section of C-frame belonged to a set of primitive shapes, which included I, T, trapezoidal, circular and rectangular sections. The cross-sectional shape is represented by a non-uniform rational B-Splines (NURBS) in order to give it a kind of shape flexibility. The results showed that the use of Nelder-Mead with Real coded Genetic Algorithms has been very significant in improving the optimum shape of a solid C-frame cross-section subjected to a combined tension and bending stresses. The hybrid optimization method could be extended to more complex shape optimization problems.


Author(s):  
Ki-Don Lee ◽  
Kwang-Yong Kim

Shape optimization of a laidback fan-shaped film-cooling hole has been performed by surrogate-based optimization techniques using three-dimensional Reynolds-averaged Navier-Stokes analysis. Spatially-averaged film-cooling effectiveness has been maximized for the optimization. The injection angle of the hole, the lateral expansion angle of the diffuser, the forward expansion angle of the hole, and the ratio of the length to the diameter of the hole are chosen as design variables, and thirty-five experimental points within design space are selected by Latin hypercube sampling. Basic surrogate models, such as second-order polynomial response approximation (RSA), Kriging meta-modeling technique, radial basis neural network (RBNN), are constructed using the analysis results, and the PBA model is composed from these basic surrogate models with the weights being calculated for each basic surrogate. The optimal points are searched from the above constructed surrogates by sequential programming (SQP). It is shown that use of multiple surrogates increases the robustness in prediction of better design with minimum computational cost.


1999 ◽  
Vol 121 (2) ◽  
pp. 229-234 ◽  
Author(s):  
J. A. Hetrick ◽  
S. Kota

Compliant mechanisms are jointless mechanical devices that take advantage of elastic deformation to achieve a force or motion transformation. An important step toward automated design of compliant mechanisms has been the development of topology optimization techniques. The next logical step is to incorporate size and shape optimization to perform dimensional synthesis of the mechanism while simultaneously considering practical design specifications such as kinematic and stress constraints. An improved objective formulation based on maximizing the energy throughput of a linear static compliant mechanism is developed considering specific force and displacement operational requirements. Parametric finite element beam models are used to perform the size and shape optimization. This technique allows stress constraints to limit the maximum stress in the mechanism. In addition, constraints which restrict the kinematics of the mechanism are successfully applied to the optimization problem. Resulting optimized mechanisms exhibit efficient mechanical transmission and meet kinematic and stress requirements. Several examples are given to demonstrate the effectiveness of the optimization procedure.


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):  
Piotr Fulmański ◽  
Antoine Laurain ◽  
Jean-Francois Scheid ◽  
Jan Sokołowski

A Level Set Method in Shape and Topology Optimization for Variational InequalitiesThe level set method is used for shape optimization of the energy functional for the Signorini problem. The boundary variations technique is used in order to derive the shape gradients of the energy functional. The conical differentiability of solutions with respect to the boundary variations is exploited. The topology modifications during the optimization process are identified by means of an asymptotic analysis. The topological derivatives of the energy shape functional are employed for the topology variations in the form of small holes. The derivation of topological derivatives is performed within the framework proposed in (Sokołowski and Żochowski, 2003). Numerical results confirm that the method is efficient and gives better results compared with the classical shape optimization techniques.


Author(s):  
Andre´s Tovar ◽  
Shawn E. Gano ◽  
John E. Renaud ◽  
James J. Mason

The goal of this research is to obtain the optimum design of a new interbody fusion implant for use in lumbar spine fixation. A new minimally invasive surgical technique for interbody fusion is currently in development. The procedure makes use of an interbody implant that is inserted between two vertebral bodies. The implant is packed with bone graft material that fuses the motion segment. The implant must be capable of retaining bone graft and supporting spinal loads while fusion occurs. Finite element-based optimization techniques are used to drive the design. The optimization process is performed in two stages: topology optimization and then shape optimization. The different load conditions analyzed include: flexion, extension, and lateral bending.


Author(s):  
Najib Mahdi ◽  
Stephane Bila ◽  
Serge Verdeyme ◽  
Michel Aubourg ◽  
Khaled Khoder ◽  
...  

This paper outlines an original shape optimization library backed by a three dimensional (3D) full-wave electromagnetic (EM) simulator, combining several efficient structural optimization techniques and suitable for viable computer-aided design (CAD) of complex microwave components. The microwave components are modeled by finite element method (FEM) and their dimensions and shape are optimized using four techniques: design of experiments (DOE), level-set method (LS), topology gradient (TG) method, and genetic algorithm (GA). The various methods allow determining the optimal geometry, shape or topology of 2D or 3D objects within the microwave device, by minimizing iteratively a cost function related to the desired specifications. Typical demonstration illustrates the versatility of the proposed library based on the design of a dual mode dielectric resonator filter in order to improve its unloaded quality factor by keeping the same frequency isolation, their accuracy and efficiency are verified by the available measured results.


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