CAD‐based shape optimisation with CFD using a discrete adjoint

Xu, Shugen; Jahn, Wolfram; Müller, Jens-Dominik

doi:10.1002/fld.3844

Cited by 63 publications

(64 citation statements)

References 31 publications

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“…In addition, there is growing recognition of the benefits of coupling high fidelity CFD with systematic optimization techniques for the shape optimization of vehicles. Adjoint methods for CAD-based shape optimization have recently become viable for whole vehicle optimization [17,18] and will be used increasingly within industry to reduce aerodynamic drag. This paper addresses the aerodynamic drag reduction of vans, which are converted for use as emergency response vehicles (ERVs) to provide patient transport to hospital and within the police service in the UK.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic Drag Reduction of Emergency Response Vehicles

Ar¹,

Gn²,

Ph³

et al. 2015

Adv Automob Eng

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This paper presents the first experimental and computational investigation into the aerodynamics of emergency response vehicles and focuses on reducing the additional drag that results from the customary practice of adding light-bars onto the vehicles' roofs. A series of wind tunnel experiments demonstrate the significant increase in drag that results from the light bars and show these can be minimized by reducing the flow separation caused by them. Simple potential improvements in the aerodynamic design of the light bars are investigated by combining Computational Fluid Dynamics (CFD) with Design of Experiments and metamodelling methods. An aerofoil-based roof design concept is shown to reduce the overall aerodynamic drag by up to 20% and an analysis of its effect on overall fuel consumption indicates that it offers a significant opportunity for improving the fuel economy and reducing emissions from emergency response vehicles. These benefits are now being realised by the UK's ambulance services.

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Section: Introductionmentioning

confidence: 99%

Aerodynamic Drag Reduction of Emergency Response Vehicles

Ar¹,

Gn²,

Ph³

et al. 2015

Adv Automob Eng

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“…The whole optimisation loop for the test case is not done in this work. The reader is referred to the work of Shenren et al 21 for the result of optimisation with the application of AD in a brute-force fashion.…”

Section: B S-bend Air Ductmentioning

confidence: 99%

Fixed point discrete adjoint of SIMPLE-like solvers

Akbarzadeh

Wang

Müeller

2015

22nd AIAA Computational Fluid Dynamics Conference

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The algebraic fixed-point form of the equation of the discrete adjoint of a segregated SIMPLE-like incompressible solver is derived and an implementation using building blocks produced with automatic differentiation (AD) software tools is presented which reuses a substantial amount of code for matrix building and matrix-vector products from the original linearised flow code (primal). The approach reduces the memory requirement compared to code from 'brute-force' application of AD. Most importantly, the adjoint solution can be 'hot-started' from an earlier design iteration which is important for use in 'one-shot' design optimisation loops.

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“…A trivariate B-spline parameterization was used by [24] for the same test case that allows a rapid meshing of the domain suitable for a one-shot optimization method while the geometry maintains the link to a CAD representation. A different approach was developed by [25,26] that employs the displacements of the control points of non-uniform rational B-spline (NURBS) patches as design parameters, which are available in the STEP file standard used to exchange data in a computer-aided engineering (CAE) framework. This method is not connected to a higher-level parameterization and represents the richest design space a CAD geometry can have.…”

Section: Introductionmentioning

confidence: 99%

CAD Integrated Multipoint Adjoint-Based Optimization of a Turbocharger Radial Turbine

Mueller

Verstraete

2017

IJTPP

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Abstract:The adjoint method is considered as the most efficient approach to compute gradients with respect to an arbitrary number of design parameters. However, one major challenge of adjoint-based shape optimization methods is the integration into a computer-aided design (CAD) workflow for practical industrial cases. This paper presents an adjoint-based framework that uses a tailored shape parameterization to satisfy geometric constraints due to mechanical and manufacturing requirements while maintaining the shape in a CAD representation. The system employs a sequential quadratic programming (SQP) algorithm and in-house developed libraries for the CAD and grid generation as well as a 3D Navier-Stokes flow and adjoint solver. The developed method is applied to a multipoint optimization of a turbocharger radial turbine aiming at maximizing the total-to-static efficiency at multiple operating points while constraining the output power and the choking mass flow of the machine. The optimization converged in a few design cycles in which the total-to-static efficiency could be significantly improved over a wide operating range. Additionally, the imposed aerodynamic constraints with strict convergence tolerances are satisfied and several geometric constraints are inherently respected due to the parameterization of the turbine. In particular, radial fibered blades are used to avoid bending stresses in the turbine blades due to centrifugal forces. The methodology is a step forward towards robustness and consistency of gradient-based optimization for practical industrial cases, as it maintains the optimal shape in CAD representation. As shown in this paper, this avoids shape approximations and allows manufacturing constraints to be included.

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CAD‐based shape optimisation with CFD using a discrete adjoint

Cited by 63 publications

References 31 publications

Aerodynamic Drag Reduction of Emergency Response Vehicles

Aerodynamic Drag Reduction of Emergency Response Vehicles

Fixed point discrete adjoint of SIMPLE-like solvers

CAD Integrated Multipoint Adjoint-Based Optimization of a Turbocharger Radial Turbine

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