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Inverse Design (inverse + design)

Distribution by Scientific Domains

Engineering	100%

Selected Abstracts

Inverse design of directional solidification processes in the presence of a strong external magnetic field

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 11 2001
Rajiv Sampath
Abstract A computational method for the design of directional alloy solidification processes is addressed such that a desired growth velocity ,f under stable growth conditions is achieved. An externally imposed magnetic field is introduced to facilitate the design process and to reduce macrosegregation by the damping of melt flow. The design problem is posed as a functional optimization problem. The unknowns of the design problem are the thermal boundary conditions. The cost functional is taken as the square of the L2 norm of an expression representing the deviation of the freezing interface thermal conditions from the conditions corresponding to local thermodynamic equilibrium. The adjoint method for the inverse design of continuum processes is adopted in this work. A continuum adjoint system is derived to calculate the adjoint temperature, concentration, velocity and electric potential fields such that the gradient of the L2 cost functional can be expressed analytically. The cost functional minimization process is realized by the conjugate gradient method via the FE solutions of the continuum direct, sensitivity and adjoint problems. The developed formulation is demonstrated with an example of designing the boundary thermal fluxes for the directional growth of a germanium melt with dopant impurities in the presence of an externally applied magnetic field. The design is shown to achieve a stable interface growth at a prescribed desired growth rate. Copyright © 2001 John Wiley & Sons, Ltd. [source]

CFD-based optimization of aerofoils using radial basis functions for domain element parameterization and mesh deformation

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 8 2008
A. M. Morris
Abstract A novel domain element shape parameterization method is presented for computational fluid dynamics-based shape optimization. The method is to achieve two aims: (1) provide a generic ,wrap-around' optimization tool that is independent of both flow solver and grid generation package and (2) provide a method that allows high-fidelity aerodynamic optimization of two- and three-dimensional bodies with a low number of design variables. The parameterization technique uses radial basis functions to transfer domain element movements into deformations of the design surface and corresponding aerodynamic mesh, thus allowing total independence from the grid generation package (structured or unstructured). Independence from the flow solver (either inviscid, viscous, aeroelastic) is achieved by obtaining sensitivity information for an advanced gradient-based optimizer (feasible sequential quadratic programming) by finite-differences. Results are presented for two-dimensional aerofoil inverse design and drag optimization problems. Inverse design results demonstrate that a large proportion of the design space is feasible with a relatively low number of design variables using the domain element parameterization. Heavily constrained (in lift, volume, and moment) two-dimensional aerofoil drag optimization has shown that significant improvements over existing designs can be achieved using this method, through the use of various objective functions. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Progressive optimization on unstructured grids using multigrid-aided finite-difference sensitivities

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 10-11 2005
L. A. Catalano
Abstract This paper proposes an efficient and robust progressive-optimization procedure, employing cheap, flexible and easy-to-program multigrid-aided finite-differences for the computation of the sensitivity derivatives. The entire approach is combined with an upwind finite-volume method for the Euler and the Navier,Stokes equations on cell-vertex unstructured (triangular) grids, and validated versus the inverse design of an airfoil, under inviscid (subsonic and transonic) and laminar flow conditions. The methodology turns out to be robust and highly efficient, the converged design optimization being obtained in a computational time equal to that required by 11,17 (depending on the application) multigrid flow analyses on the finest grid. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Inexact information aided, low-cost, distributed genetic algorithms for aerodynamic shape optimization

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 10-11 2003
Marios K. Karakasis
Abstract Despite its robustness, the design and optimization of aerodynamic shapes using genetic algorithms suffers from high computing cost requirements, due to excessive calls to Computational Fluid Dynamics tools for the evaluation of candidate solutions. To alleviate this problem, either the use of distributed genetic algorithms or the implementation of surrogate evaluation models have separately been proposed in the past. A distributed genetic algorithm relies on the handling of population subsets that evolve in a semi-isolated manner by regularly exchanging their best individuals. It is known that distributed schemes generally outperform single-population ones. On the other hand, the implementation of less costly surrogate evaluation tools, such as the autocatalytic radial basis function networks developed by the authors for the purpose of getting rid of most of the ,useless' exact evaluations, reduces considerably the computational cost. The aim of the present paper is to employ a surrogate evaluation model in the context of a distributed genetic algorithm and to demonstrate that the combination of both results in maximum economy in CPU cost. In addition, whenever a multiprocessor system is available, the gain is much more pronounced, since the new optimization method maximizes parallel efficiency. The proposed method is used to solve inverse design and optimization problems in aeronautics and turbomachinery. Copyright © 2003 John Wiley & Sons, Ltd. [source]