Single-step One-shot Aerodynamic Shape Optimization

Özkaya, Emre; Gauger, Nicolas R.

doi:10.1007/978-3-7643-8923-9_11

Cited by 34 publications

(12 citation statements)

References 9 publications

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“…With the one-shot method, one gets an optimization for a small multiple of the numerical effort of a flow simulation. This has been already demonstrated with the continuous adjoint method in [11] and with the discrete adjoint method by the authors for unconstrained Euler cases [15], where AD is used for the adjoint part. In this paper, we show the extension to constrained RANS case.…”

Section: Introductionmentioning

confidence: 72%

Automatic transition from simulation to one‐shot shape optimization with Navier‐Stokes equations

Özkaya

Gauger

2010

GAMM-Mitteilungen

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MSC (2000) 65K10,49M25,76D55We introduce the one-shot method and its application to aerodynamic shape optimization, where the governing equations are the incompressible Reynolds-Averaged Navier-Stokes (RANS) equations in combination with the k − ω turbulence model. We constrain the oneshot strategy to problems, where steady-state solutions are achieved by fixed-point iteration schemes. The one-shot optimization strategy pursues optimality simultaneously with the goals of primal and adjoint feasibility. To exploit the domain specific experience and expertise invested in the simulation tools, we propose to extend them in an automated fashion by the use of automatic differentiation (AD) tools. First, they are automatically augmented with an adjoint solver to obtain (reduced) derivatives and then this sensitivity information is immediately used to determine optimization corrections.

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Section: Introductionmentioning

confidence: 72%

Automatic transition from simulation to one‐shot shape optimization with Navier‐Stokes equations

Özkaya

Gauger

2010

GAMM-Mitteilungen

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“…• the optimization parameters are updated by MMA The second method is a simple descent algorithm. The optimization problem is solved simultaneously with the primal and adjoint problem using a one-shot framework [11,22]. A single iteration consists of:…”

Section: Optimizationmentioning

confidence: 99%

Adjoint Lattice Boltzmann for topology optimization on multi-GPU architecture

Łaniewski-Wołłk

Rokicki

2016

Computers & Mathematics with Applications

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In this paper we present a topology optimization technique applicable to a broad range of flow design problems. We propose also a discrete adjoint formulation effective for a wide class of Lattice Boltzmann Methods (LBM). This adjoint formulation is used to calculate sensitivity of the LBM solution to several type of parameters, both global and local. The numerical scheme for solving the adjoint problem has many properties of the original system, including locality and explicit time-stepping. Thus it is possible to integrate it with the standard LBM solver, allowing for straightforward and efficient parallelization (overcoming limitations typical for discrete adjoint solvers). This approach is successfully used for the channel flow to design a free-topology mixer and a heat exchanger. Both resulting geometries being very complex maximize their objective functions, while keeping viscous losses at acceptable level.

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“…In this paper, we apply the One-shot approach to a box model of the North Atlantic. This problem is different from the application in [6] in that the parameters enter in a nonlinear fashion resulting in so-called non-separable adjoints where the adjoint is no longer only the sum of a term on the state and a term on design.…”

Section: Introductionmentioning

confidence: 98%

“…That means that the number of One-shot iterations shall not too much exceed the number of fixed point iteration steps that are necessary for the computation of feasible states itself. Theoretical results were published in [4], [5], an engineering application was presented byÖzkaya and Gauger in [6].…”

Section: Introductionmentioning

confidence: 99%

Simultaneous model spin-up and parameter identification with the one-shot method in a climate model example

Kratzenstein

Slawig

2013

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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We investigate the One-shot Optimization strategy introduced in this form by Hamdi and Griewank for the applicability and efficiency to identify parameters in models of the earth's climate system. Parameters of a box model of the North Atlantic Thermohaline Circulation are optimized with respect to the fit of model output to data given by another model of intermediate complexity.Since the model is run into a steady state by a pseudo time-stepping, efficient techniques are necessary to avoid extensive recomputations or storing when using gradient-based local optimization algorithms. The One-shot approach simultaneously updates state, adjoint and parameter values. For the required partial derivatives, the algorithmic/automatic differentiation tool TAF was used. Numerical results are compared to results obtained by the BFGS and L-BFGS quasi-Newton method.

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Single-step One-shot Aerodynamic Shape Optimization

Cited by 34 publications

References 9 publications

Automatic transition from simulation to one‐shot shape optimization with Navier‐Stokes equations

Automatic transition from simulation to one‐shot shape optimization with Navier‐Stokes equations

Adjoint Lattice Boltzmann for topology optimization on multi-GPU architecture

Simultaneous model spin-up and parameter identification with the one-shot method in a climate model example

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