The Experts below are selected from a list of 789 Experts worldwide ranked by ideXlab platform

A Jahangirian - One of the best experts on this subject based on the ideXlab platform.

  • Aerodynamic Optimization of Airfoils Using Adaptive Parameterization and Genetic Algorithm
    Journal of Optimization Theory and Applications, 2014
    Co-Authors: M. Ebrahimi, A Jahangirian
    Abstract:

    A new method for airfoil Shape Parameterization is presented, and its influences on the optimum design and convergence of the evolutionary optimization process are investigated. An online adaptive method is used that alters the airfoil parametric function during the process of optimization. A geometric inverse design is carried out, and the capability of the method for producing general airfoil Shapes is assessed. The performance of the method is then evaluated by aerodynamic Shape optimization. The result indicates that the proposed method improves the optimum design airfoil significantly. In addition, it reduces the total number of flow solver calls, which consequently reduces the required computational time.

  • Inverse design of transonic airfoils using genetic algorithm and a new parametric Shape method
    Inverse Problems in Science and Engineering, 2009
    Co-Authors: A Jahangirian, Ava Shahrokhi
    Abstract:

    The inverse design of transonic airfoils is carried out using genetic algorithm and different Shape Parameterization methods. A new technique for airfoil Shape Parameterization is presented considering the features of the transonic flow. The method is then applied to several airfoil inverse design problems with defined geometry or surface pressure distributions. The influence of parametric Shape methods on the accuracy and computational cost of the design process are investigated for inviscid and viscous flow problems. The fitness function evaluation is carried out using an unstructured grid finite volume flow solver. It is shown that the new Shape Parameterization method is able to reduce the total computational time by about 50% in the inverse design of transonic airfoils, particularly when viscous flow calculations are concerned.

  • airfoil Shape Parameterization for optimum navier stokes design with genetic algorithm
    Aerospace Science and Technology, 2007
    Co-Authors: Ava Shahrokhi, A Jahangirian
    Abstract:

    Abstract The effect of airfoil Shape Parameterization on optimum design and its influence on the convergence of the optimization process are investigated. A new method for airfoil Shape Parameterization is presented which takes into consideration the characteristics of viscous transonic flow particularly around the trailing edge. The method is then applied to airfoil Shape optimization at high Reynolds number turbulent flow conditions using a Genetic Algorithm. An unstructured grid Navier–Stokes flow solver with a two-equation K − e turbulence model is used to evaluate the fitness function. The aerodynamic characteristics of the optimum airfoil obtained from the proposed parametric method are compared with those from alternative methods. It is concluded that the new method is capable of finding efficient and optimum airfoils in fewer number of generations.

  • Airfoil Shape Parameterization for optimum Navier–Stokes design with genetic algorithm
    Aerospace Science and Technology, 2007
    Co-Authors: Ava Shahrokhi, A Jahangirian
    Abstract:

    Abstract The effect of airfoil Shape Parameterization on optimum design and its influence on the convergence of the optimization process are investigated. A new method for airfoil Shape Parameterization is presented which takes into consideration the characteristics of viscous transonic flow particularly around the trailing edge. The method is then applied to airfoil Shape optimization at high Reynolds number turbulent flow conditions using a Genetic Algorithm. An unstructured grid Navier–Stokes flow solver with a two-equation K − e turbulence model is used to evaluate the fitness function. The aerodynamic characteristics of the optimum airfoil obtained from the proposed parametric method are compared with those from alternative methods. It is concluded that the new method is capable of finding efficient and optimum airfoils in fewer number of generations.

M. Shimoda - One of the best experts on this subject based on the ideXlab platform.

  • A numerical form-finding method for the minimal surface of membrane structures
    Structural and Multidisciplinary Optimization, 2015
    Co-Authors: M. Shimoda, K. Yamane
    Abstract:

    This paper proposes a convenient numerical form-finding method for designing the minimal surface, or the equally tensioned surface of membrane structures with specified arbitrary boundaries. Area minimization problems are formulated as a distributed-parameter Shape optimization problem. The internal volume or the perimeter is added as a constraint according to the structure type such as a pneumatic or a suspension membrane. It is assumed that the membrane is varied in the out-of-plane and/or the in-plane direction to the surface. The Shape sensitivity function for each problem is derived using the material derivative method. The minimal surface is determined without Shape Parameterization by the free-form optimization method, a gradient method in the Hilbert space, where the Shape is varied by the traction force in proportion to the sensitivity function under the Robin boundary condition. The calculated results show the effectiveness and practical utility of the proposed method for optimal form-finding of membrane structures.

  • A non-parametric free-form optimization method for shell structures
    Structural and Multidisciplinary Optimization, 2014
    Co-Authors: M. Shimoda
    Abstract:

    This paper presents a numerical Shape optimization method for the optimum free-form design of shell structures. It is assumed that the shell is varied in the out-of-plane direction to the surface to determine the optimal free-form. A compliance minimization problem subject to a volume constraint is treated here as an example of free-form design problem of shell structures. This problem is formulated as a distributed-parameter, or non-parametric, Shape optimization problem. The Shape gradient function and the optimality conditions are theoretically derived using the material derivative formulae, the Lagrange multiplier method and the adjoint variable method. The negative Shape gradient function is applied to the shell surface as a fictitious distributed traction force to vary the shell. Mathematically, this method is a gradient method with a Laplacian smoother in the Hilbert space. Therefore, this Shape variation makes it possible both to reduce the objective functional and to maintain the mesh regularity simultaneously. With this method, the optimal smooth curvature distribution of a shell structure can be determined without Shape Parameterization. The calculated results show the effectiveness of the proposed method for the optimum free-form design of shell structures.

Jamshid A. Samareh - One of the best experts on this subject based on the ideXlab platform.

  • Geometry and Grid/Mesh Generation Issues for CFD and CSM Shape Optimization
    Optimization and Engineering, 2005
    Co-Authors: Jamshid A. Samareh
    Abstract:

    This paper discusses geometry and grid generation issues for an automated Shape optimization using computational fluid dynamics and computational structural mechanics. Special attention is given to five major steps for Shape optimization: Shape Parameterization, automation of model abstraction, automation of grid generation, calculation of analytical sensitivity, and robust grid deformation.

  • Aerodynamic Shape Optimization Based on Free-form Deformation
    10th AIAA ISSMO Multidisciplinary Analysis and Optimization Conference, 2004
    Co-Authors: Jamshid A. Samareh
    Abstract:

    This paper presents a free-form deformation technique suitable for aerodynamic Shape optimization. Because the proposed technique is independent of grid topology, we can treat structured and unstructured computational fluid dynamics grids in the same manner. The proposed technique is an alternative Shape Parameterization technique to a trivariate volume technique. It retains the flexibility and freedom of trivariate volumes for CFD Shape optimization, but it uses a bivariate surface representation. This reduces the number of design variables by an order of magnitude, and it provides much better control for surface Shape changes. The proposed technique is simple, compact, and efficient. The analytical sensitivity derivatives are independent of the design variables and are easily computed for use in a gradient-based optimization. The paper includes the complete formulation and aerodynamics Shape optimization results.

  • novel multidisciplinary Shape Parameterization approach
    Journal of Aircraft, 2001
    Co-Authors: Jamshid A. Samareh
    Abstract:

    A multidisciplinary Shape Parameterization approach is presented. The approach consists of two basic concepts: 1) parameterizing the Shape perturbations rather than the geometry itself and 2) performing the Shape deformation by means of the soft object animation algorithms used in computer graphics. Because the formulation presented is independent of grid topology, we can treat computational fluid dynamics and finite element grids in the same manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity, for example, linear aerodynamics and equivalent laminated plate structures, and high-fidelity, for example, nonlinear computational fluid dynamics and detailed finite element modeling, analysis tools. The implementation details of parameterizing for planform, twist, dihedral, thickness, camber, and free-form surface are given. Results are presented for a multidisciplinary application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module

  • Survey of Shape Parameterization Techniques for High-Fidelity Multidisciplinary Shape Optimization
    AIAA Journal, 2001
    Co-Authors: Jamshid A. Samareh
    Abstract:

    A survey is provided of Shape Parameterization techniques formultidisciplinary optimization, and some emerging ideas are highlighted. The survey focuses on the suitability of available techniques for multidisciplinary applications of complex cone gurations using high-e delity analysis tools such as computational e uid dynamics and computational structural mechanics. The suitability criteria are based on the efe ciency, effectiveness, ease of implementation, and availability of analytical sensitivities for geometry and grids. A section on sensitivity analysis, grid regeneration, and grid deformation techniques is also provided.

Damir Vucina - One of the best experts on this subject based on the ideXlab platform.

  • efficient Shape Parameterization method for multidisciplinary global optimization and application to integrated ship hull Shape optimization workflow
    Computer-aided Design, 2016
    Co-Authors: Ivo Marinickragic, Damir Vucina, Milan Curkovic
    Abstract:

    Abstract Multidisciplinary global Shape optimization requires a geometric Parameterization method that keeps the Shape generality while lowering the number of free variables. This paper presents a reduced parameter set Parameterization method based on integral B-spline surface capable of both Shape and topology variations and suitable for global multidisciplinary optimization. The objective of the paper is to illustrate the advantages of the proposed method in comparison to standard Parameterization and to prove that the proposed method can be used in an integrated multidisciplinary workflow. Non-linear fitting is used to test the proposed Parameterization performance before the actual optimization. The Parameterization method can in this way be tested and pre-selected based on previously existing geometries. Fitting tests were conducted on three Shapes with dissimilar geometrical features, and great improvement in Shape generality while reducing the number of Shape parameters was achieved. The best results are obtained for a small number (up to 50) of optimization variables, where a classical applying of Parameterization method requires about two times as many optimization variables to obtain the same fitting capacity. The proposed Shape Parameterization method was tested in a multidisciplinary ship hull optimization workflow to confirm that it can actually be used in multiobjective optimization problems. The workflow integrates Shape Parameterization with hydrodynamic, structural and geometry analysis tools. In comparison to classical local and global optimization methods, the evolutionary algorithm allows for fully autonomous design with an ability to generate a wide Pareto front without a need for an initial solution.

  • 3d Shape acquisition and integral compact representation using optical scanning and enhanced Shape Parameterization
    Advanced Engineering Informatics, 2014
    Co-Authors: Milan Curkovic, Damir Vucina
    Abstract:

    An efficient computational methodology for Shape acquisition, processing and representation is developed. It includes 3D computer vision by applying triangulation and stereo-photogrammetry for high-accuracy 3D Shape acquisition. Resulting huge 3D point clouds are successively parameterized into mathematical surfaces to provide for compact data-set representation, yet capturing local details sufficiently. B-spline surfaces are employed as parametric entities in fitting to point clouds resulting from optical 3D scanning. Beyond the linear best-fitting algorithm with control points as fitting variables, an enhanced non-linear procedure is developed. The set of best fitting variables in minimizing the approximation error norm between the parametric surface and the 3D cloud includes the control points coordinates. However, they are augmented by the set of position parameter values which identify the respectively closest matching points on the surface for the points in the cloud. The developed algorithm is demonstrated to be efficient on demanding test cases which encompass sharp edges and slope discontinuities originating from physical damage of the 3D objects or Shape complexity.

  • Ad-hoc cluster and workflow for parallel implementation of initial-stage evolutionary optimum design
    Structural and Multidisciplinary Optimization, 2012
    Co-Authors: Damir Vucina, Željan Lozina, Igor Pehnec
    Abstract:

    Numerical optimization and especially topology and Shape optimization are typically numerically very comprehensive due to implicit models, large number of variables, high non-linearity, possible infeasibility of candidate designs and related causes. It usually has to be implemented by coupling heterogeneous program environments such as evolutionary optimizers, computer-aided geometric modeling programs and simulators such as finite-element based analysis packages. This paper develops a workflow-based numerical system that serves the purpose of integrating, harmonizing and managing these distinct components in such a way that it provides the functionality needed for the inverse problem of evolutionary initial-stage topology- and Shape synthesis. The approach based on inserting and optimizing holes is developed using chained piecewise Bezier curves and/or surfaces for Shape Parameterization. The procedure developed here employs existing off-the-shelf software packages for computer-aided design, finite element analysis and numerical optimization while building custom middle-ware programs and scripts. It also provides for parallel invoking of different and/or multiple simulators which reduces the optimization run-time by widening the critical bottle-necks in the overall process. The system is implemented inexpensively as an ad-hoc PC-based cluster where individual computers expose server programs and respective services which control locally installed simulators.

Slobodan Ilic - One of the best experts on this subject based on the ideXlab platform.

  • BMVC - Physically Valid Shape Parameterization for Monocular 3-D Deformable Surface Tracking
    Procedings of the British Machine Vision Conference 2005, 2020
    Co-Authors: Mathieu Salzmann, Slobodan Ilic
    Abstract:

    We develop a low-dimensional approximation of the set of possible deformations of smoothly deforming objects of planar topology. To this end, we propose a novel Parameterization of inextensible surfaces that allows us first to effectively sample the space of all possible deformations, which is a priori very large, and then to derive the low-dimensional model using a simple dimensionality reduction technique. We incorporate the resulting models into a monocular tracking system that we use to capture complex deformations of objects such as sheets of paper or more flexible material. We also show that, even though the model was built by sampling the set of possible deformations of inextensible surfaces, it can also handle extensible ones.

  • physically valid Shape Parameterization for monocular 3 d deformable surface tracking
    British Machine Vision Conference, 2005
    Co-Authors: Mathieu Salzmann, Slobodan Ilic
    Abstract:

    We develop a low-dimensional approximation of the set of possible deformations of smoothly deforming objects of planar topology. To this end, we propose a novel Parameterization of inextensible surfaces that allows us first to effectively sample the space of all possible deformations, which is a priori very large, and then to derive the low-dimensional model using a simple dimensionality reduction technique. We incorporate the resulting models into a monocular tracking system that we use to capture complex deformations of objects such as sheets of paper or more flexible material. We also show that, even though the model was built by sampling the set of possible deformations of inextensible surfaces, it can also handle extensible ones.