Topology optimization of flow domains using the lattice Boltzmann method

Pingen, Georg; Evgrafov, Anton; Maute, Kurt

doi:10.1007/s00158-007-0105-7

Cited by 102 publications

(71 citation statements)

References 39 publications

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“…The method is attractive because it is algorithmically simple, lends itself well to parallel implementation, and is relatively easy to extend to more complicated physics, such as porous media [11][12][13], or multiphase flows [14,15]. The use of the LBM for topology optimization was pioneered by Pingen et al [16], who used the density approach to topology optimization. The work is extended to multiphase flow problems by Makhija et al [8].…”

Section: Introductionmentioning

confidence: 99%

Topology optimization of unsteady flow problems using the lattice Boltzmann method

Nørgaard

Sigmund

Lazarov

2016

Journal of Computational Physics

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This article demonstrates and discusses topology optimization for unsteady incompressible fluid flows. The fluid flows are simulated using the lattice Boltzmann method, and a partial bounceback model is implemented to model the transition between fluid and solid phases in the optimization problems. The optimization problem is solved with a gradient based method, and the design sensitivities are computed by solving the discrete adjoint problem. For moderate Reynolds number flows, it is demonstrated that topology optimization can successfully account for unsteady effects such as vortex shedding and time-varying boundary conditions. Such effects are relevant in several engineering applications, i.e. fluid pumps and control valves.

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Section: Introductionmentioning

confidence: 99%

Topology optimization of unsteady flow problems using the lattice Boltzmann method

Nørgaard

Sigmund

Lazarov

2016

Journal of Computational Physics

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“…The optimization method has recently been extended to transient and dynamic flow problems (Kreissl et al, 2011;Deng et al, 2011) though still limited to laminar flows. Traditionally the finite element method has been used for the modeling of topology optimization problems; however, fluid flow problems have also been optimized using the finite volume method (Othmer, 2008), the Lattice-Boltzmann method (Pingen et al, 2007) and kinetic gas theory (Evgrafov et al, 2008). A few works on flow components that are able to pump a fluid and have been designed by topology optimization have been promoted.…”

Section: Primary Inflow Outflowmentioning

confidence: 99%

Topology optimization of inertia driven dosing units

Andreasen

2016

Struct Multidisc Optim

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This paper presents a methodology for optimizing inertia driven dosing units, sometimes referred to as eductors, for use in small scale flow applications. The unit is assumed to operate at low to moderate Reynolds numbers and under steady state conditions. By applying topology optimization to the Brinkman penalized Navier-Stokes equation the design of the dosing units can be optimized with respect to dosing capability without initial design assumptions. The influence of flow resistance and speed is investigated to assess design performance under varying operating conditions.

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“…Since we do not model the vertical dimension of Ω, we omit the Boussinesqapproximation buoyancy term proportional to T e , which is typically included on the right-hand side of (2). We modify κ and α to model obstacles to heat and air flow in Ω, such as walls, doors, and windows, as described in [30], [31]. In particular, when the point x corresponds to a material that blocks air, we choose α(x) u(x), which results in u(x) ≈ 0, and when the point x corresponds to air then we choose α(x) = 0.…”

Section: A Cfd Modelmentioning

confidence: 99%

Zoned HVAC control via PDE-constrained optimization

González

2016

2016 American Control Conference (ACC)

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Abstract-Efficiency, comfort, and convenience are three major aspects in the design of control systems for residential Heating, Ventilation, and Air Conditioning (HVAC) units. In this paper we propose an optimization-based algorithm for HVAC control that minimizes energy consumption while maintaining a desired temperature in a room. Our algorithm uses a Computer Fluid Dynamics model, mathematically formulated using Partial Differential Equations (PDEs), to describe the interactions between temperature, pressure, and air flow. Our model allows us to naturally formulate problems such as controlling the temperature of a small region of interest within a room, or to control the speed of the air flow at the vents, which are hard to describe using finite-dimensional Ordinary Partial Differential (ODE) models. Our results show that our algorithm produces significant energy savings without a decrease in comfort.

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Topology optimization of flow domains using the lattice Boltzmann method

Cited by 102 publications

References 39 publications

Topology optimization of unsteady flow problems using the lattice Boltzmann method

Topology optimization of unsteady flow problems using the lattice Boltzmann method

Topology optimization of inertia driven dosing units

Zoned HVAC control via PDE-constrained optimization

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