Shape design for polymer spin packs: modeling, optimization and validation

Leithäuser, Christian; Pinnau, René; Feßler, Robert

doi:10.1186/s13362-018-0055-2

Cited by 10 publications

(6 citation statements)

References 16 publications

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“…Residence time distribution (RTD) is an important aspect of the melt in spinning pack, through which the flow characteristics of dead zone, short circuit, and circulating flow can be reflected and evaluated. Leithauser et al used a cavity with a specific wall shear stress curve to optimize the structure of spinning pack, which can lead to a short and uniform residence time of the fluid 1–3 . Hohmann et al optimized the fluid distributor in an industrial spinning pack and established a model for the RTD and pressure drop 4 .…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation and modeling of viscous fluid residence time distribution in the melt spinning pack

Zhu

et al. 2022

Asia-Pacific J Chem Eng

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Melt spinning is an important method in fiber production. The hydrodynamic performance of fluid in the melt spinning process's core device, spinning pack, can directly affect the quality of fiber products. To guarantee the uniform distribution of flow in the spinning pack, the residence time distribution (RTD) characteristics of high viscosity fluid in the spinning pack were investigated experimentally and numerically in this work. Peak and trailing of RTD curves indicate the existence of short circuit and dead zone in the spinning pack. Results show that the porous media and gland can reduce the dead zone, and baffles could reduce the short circuit. Based on the experiment and numerical simulation results, a one-dimensional axial diffusion model was established to describe the RTD characteristics of viscous fluid in the spinning pack. This work can be valuable references for the understanding and optimization of the spinning pack in melt spinning process.

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Section: Introductionmentioning

confidence: 99%

Numerical simulation and modeling of viscous fluid residence time distribution in the melt spinning pack

Zhu

et al. 2022

Asia-Pacific J Chem Eng

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“…These techniques are based on the so‐called shape derivative, which measures the sensitivity of a shape due to infinitesimal deformations, and the topological derivative, which measures the sensitivity of a geometry with respect to the insertion of an infinitesimally small hole, see, e.g., [14, 61] for shape calculus and [45] for topological sensitivity analysis. In recent years these techniques have been applied to many industrial problems, e.g., the shape design of polymer spin packs [27, 37–39], electric motors [20, 21], acoustic horns [5, 57], automobiles [18, 46, 48], aircrafts [41, 55, 56] or pipe systems [25, 28, 58]. To the best of our knowledge, the optimization of a microchannel cooling system by means of shape calculus has only been investigated in our earlier work [6], where we rigorously analyzed the theoretical aspects of this problem.…”

Section: Introductionmentioning

confidence: 99%

Model hierarchy for the shape optimization of a microchannel cooling system

2020

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We model a microchannel cooling system and consider the optimization of its shape by means of shape calculus. A three‐dimensional model covering all relevant physical effects and three reduced models are introduced. The latter are derived via a homogenization of the geometry in 3D and a transformation of the three‐dimensional models to two dimensions. A shape optimization problem based on the tracking of heat absorption by the cooler and the uniform distribution of the flow through the microchannels is formulated and adapted to all models. We present the corresponding shape derivatives and adjoint systems, which we derived with a material derivative free adjoint approach. To demonstrate the feasibility of the reduced models, the optimization problems are solved numerically with a gradient descent method. A comparison of the results shows that the reduced models perform similarly to the original one while using significantly less computational resources.

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“…Shape optimization problems constrained by partial differential equations (PDEs) and their solution based on shape calculus have received a lot of attention in recent years. They are used for many industrial applications, e.g., to optimize electric motors [15,16], polymer spin packs [26,31,32], aircrafts and automobiles [17,37], or microchannel heat exchangers [4,5]. Alternatively, such shape optimization techniques are also used to solve inverse problems, e.g., in image segmentation [11,24] or electrical impedance tomography [23,30].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Conjugate Gradient Methods for PDE Constrained Shape Optimization Based on Steklov-Poincaré-Type Metrics

Blauth

2020

Preprint

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Shape optimization based on shape calculus has received a lot of attention in recent years, particularly regarding the development, analysis, and modification of efficient optimization algorithms.In this paper we propose and investigate nonlinear conjugate gradient methods based on Steklov-Poincaré-type metrics for the solution of shape optimization problems constrained by partial differential equations. We embed these methods into a general algorithmic framework for gradient based shape optimization methods and discuss the numerical discretization of the algorithms. We numerically compare the proposed nonlinear conjugate gradient methods to established gradient based shape optimization methods on several benchmark problems. The results show that the proposed nonlinear conjugate gradient methods yield a significant improvement over the gradient descent method, and that their performance can be compared to that of the limited memory BFGS methods, making them efficient and attractive gradient based shape optimization algorithms.

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Shape design for polymer spin packs: modeling, optimization and validation

Cited by 10 publications

References 16 publications

Numerical simulation and modeling of viscous fluid residence time distribution in the melt spinning pack

Numerical simulation and modeling of viscous fluid residence time distribution in the melt spinning pack

Model hierarchy for the shape optimization of a microchannel cooling system

Nonlinear Conjugate Gradient Methods for PDE Constrained Shape Optimization Based on Steklov-Poincaré-Type Metrics

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