Topology optimization of turbulent fluid flow via the TOBS method and a geometry trimming procedure

Picelli, Renato; Moscatelli, Eduardo; Yamabe, Paulo Vinícius Miyuki; Alonso, Diego Hayashi; Ranjbarzadeh, Shahin; Gioria, Rafael dos Santos; Meneghini, Júlio Romano; Silva, Emilío Carlos Nelli

doi:10.1007/s00158-021-03118-4

Cited by 24 publications

(22 citation statements)

References 33 publications

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“…They represented the turbulence with the k − and k − models under the assumption of frozen turbulence. Picelli et al (2022) used a binary topology optimization approach in combination with a geometry trimming procedure to design channels for minimum turbulent energy dissipation with the k − and k − models. Alonso et al (2022) extended the framework to the Wray-Agarwal turbulence model.…”

Section: Introductionmentioning

confidence: 99%

XFEM level set-based topology optimization for turbulent conjugate heat transfer problems

Noël

Maute

2022

Struct Multidisc Optim

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Solving conjugate heat transfer design problems is relevant for various engineering applications requiring efficient thermal management. Heat exchange between fluid and solid can be enhanced by optimizing the system layout and the shape of the flow channels. As heat is transferred at fluid/solid interfaces, it is crucial to accurately resolve the geometry and the physics responses across these interfaces. To address this challenge, this work investigates for the first time the use of an eXtended Finite Element Method (XFEM) approach to predict the physical responses of conjugate heat transfer problems considering turbulent flow. This analysis approach is integrated into a level set-based optimization framework. The design domain is immersed into a background mesh and the geometry of fluid/solid interfaces is defined implicitly by one or multiple level set functions. The level set functions are discretized by higher-order B-splines. The flow is predicted by the Reynolds Averaged Navier–Stokes equations. Turbulence is described by the Spalart–Allmaras model and the thermal energy transport by an advection–diffusion model. Finite element approximations are augmented by a generalized Heaviside enrichment strategy with the state fields being approximated by linear basis functions. Boundary and interface conditions are enforced weakly with Nitsche’s method, and the face-oriented ghost stabilization is used to mitigate numerical instabilities associated with the emergence of small integration subdomains. The proposed XFEM approach for turbulent conjugate heat transfer is validated against benchmark problems. Optimization problems are solved by gradient-based algorithms and the required sensitivity analysis is performed by the adjoint method. The proposed framework is illustrated with the design of turbulent heat exchangers in two dimensions. The optimization results show that, by tuning the shape of the fluid/solid interface to generate turbulence within the heat exchanger, the transfer of thermal energy can be increased.

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Section: Introductionmentioning

confidence: 99%

XFEM level set-based topology optimization for turbulent conjugate heat transfer problems

Noël

Maute

2022

Struct Multidisc Optim

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“…Since we perform a body‐fitted analysis of the topology, the FEA sensitivity field is exported via interpolation to the centroid of the elements from the regular mesh. This communication technique between TOBS and FEA software via the pair sensitivity and geometry was proposed recently and the details are available for turbulent flow problems 14 …”

Section: Topology Optimization Frameworkmentioning

confidence: 99%

“…Snapshots of velocity (m/s) evolution of the 2D bend pipe body‐fitted optimization with

\mathit{\operatorname{Re}}=1000

. (A) Iteration 9, (B) Iteration 18, (C) Iteration 27, (D) Iteration 36, (E) Iteration 54, (F) Iteration 63, (G) Iteration 72, (H) Iteration 90, (I) k‐

\epsilon

turbulence model (Picelli et al 14 ). …”

Section: Numerical Examplesmentioning

confidence: 99%

Body‐fitted topology optimization via integer linear programming using surface capturing techniques

Soares da Costa Azevêdo,

Li,

Ishida

et al. 2024

Numerical Meth Engineering

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Recent advancements in computational tools and additive manufacturing have expanded design possibilities on fluid devices and structures to also include aesthetics. However, traditional discrete density‐based topology optimization methods usually use square and cubic regular meshes, resulting in jagged contour patterns that require mesh refinement and post‐processing to numerical solution steps of complex physics problems. In this article, we propose a new isosurface boundary capture strategy for topology optimization in structural and fluid flow problems. The capture of smoothed boundaries is done via a simple strategy through element splitting and analysis domain remeshing. The smoothing procedure novelty lies on the optimizer regular mesh decomposition into smaller triangular or tetrahedral elements with a pseudo‐density nodal function that produces implicit geometry boundaries. We employ the TOBS‐GT (topology optimization of binary structures with geometry trimming) method to solve optimization problems for mean compliance and fluid flow energy dissipation, subject to a volume fraction constraint. Since, we perform discrete body‐fitted optimization, the material interpolation models are expressed in linear form without penalty factors. Our method produces a lower computational cost topology evolution with high resolution and mitigated sharp details, achieved via smooth edges and surfaces, as demonstrated through benchmark numerical examples in two‐ and three‐dimensional space. In addition, the proposed strategy facilitates the optimization of benchmark fluid flow examples for moderate Reynolds numbers.

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“…This is performed for better numerical conditioning. However, there are researches that rely on some adaptations/filterings or approach (PICELLI et al, 2021), which may be roughly described as a multi-resolution scheme, since it relies on TOBS being applied to a fixed mesh for the design variable, but the simulations being performed in post-processed meshes with smoothed contours.…”

Section: Fluid Flow Topology Optimizationmentioning

confidence: 99%

“…• Savitzky-Golay filter approach: One possibility, which has been first considered in Picelli et al (2021), is by considering the Savitzky-Golay filter (SAVITZKY; GOLAY, 1964), which is a low-pass filter capable of smoothing noisy data. It operates by considering a least-square fit with a high-order polynomial inside a set of points (window) around each value -an example is using a 2 nd order polynomial, with a window of size 9.…”

Section: 19mentioning

confidence: 99%

Topology optimization for 2D swirl flows with application in the design of a ventricular assist device.

Alonso¹

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Ventricular Assist Devices (VADs) substitute or temporarily assist the heart and blood circulation by means of a small-scale blood pump. Due to the operation with blood, their designs aim to minimize blood damage (hemolysis and thrombosis) and maximize the performance (i.e., more efficient pumping). For that, the topologies of the rotor and the volute play a major role. In this research, the rotor is based on the 2D swirl concept, which considers swirling axisymmetric flow, being represented mainly by the Tesla pump.In a Tesla pump, the boundary layer (viscous) effect pumps the fluid, which may lead to less blood damage than bladed pumps (pumping based on the variation of linear momentum). However, the obtained efficiency is normally low, which may be improved by using the topology optimization method. Therefore, in this research, the topology optimization method is implemented for the 2D swirl flow model, also considering a non-Newtonian model for blood (Carreau-Yasuda) and hemolysis/thrombosis models to quantify the blood damage. Furthermore, the 2D swirl flow topology optimization is extended to the Wray-Agarwal turbulence model (WA2018), which presents advantages from the simulation and topology optimization points-of-view. The solid material is modeled as a porous medium with permeability controlled by the topology optimization.The numerical implementation is performed mainly through the FEniCS platform, by using the dolfin-adjoint library for the automatically derived adjoint model, and also relying on the OpenFOAM ® software for considering higher-speed flows, turbulence and 3D simulations. For the optimization, the IPOPT and TOBS solvers are considered. The optimized designs are interpreted and fabricated through additive manufacturing, and then experimentally evaluated.

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Topology optimization of turbulent fluid flow via the TOBS method and a geometry trimming procedure

Cited by 24 publications

References 33 publications

XFEM level set-based topology optimization for turbulent conjugate heat transfer problems

XFEM level set-based topology optimization for turbulent conjugate heat transfer problems

Body‐fitted topology optimization via integer linear programming using surface capturing techniques

Topology optimization for 2D swirl flows with application in the design of a ventricular assist device.

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