CFD geometrical optimization to improve mixing performance of axial mixer

Hanada, Toshihiro; Kuroda, Kenji; Takahashi, Koji

doi:10.1016/j.ces.2016.01.029

Cited by 19 publications

(8 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Apart from delivering uniform flow at the outlet, mixers should have the smallest possible power losses to reduce energy consumption. Several published studies are dealing with the flow simulation in mixing devices [10,11] or with the problem of optimizing them, targeting mixture uniformity at the exit [12][13][14] and minimum total pressure drop within the device [15,16], though none of them uses the adjoint method, at least to the author's knowledge. In this paper, a method based on the continuous adjoint for a two-phase model is used for the optimization of a static mixing device targeting both the aforementioned objective functions.…”

Section: Introductionmentioning

confidence: 99%

Shape Optimization of a Two-Fluid Mixing Device Using Continuous Adjoint

Alexias

Giannakoglou

2020

Fluids

View full text Add to dashboard Cite

In this paper, the continuous adjoint method is used for the optimization of a static mixing device. The CFD model used is suitable for the flow simulation of the two miscible fluids that enter the device. The formulation of the adjoint equations, which allow the computation of the sensitivity derivatives is briefly demonstrated. A detailed analysis of the geometry parameterization is presented and a set of different parameterization scenarios are investigated. In detail, two different parameterizations are combined into a two-stage optimization algorithm which targets maximum mixture uniformity at the exit of the mixer and minimum total pressure losses. All parameterizations are in conformity with specific manufacturability constraints of the final shape. The non-dominated front of optimal solutions is obtained by using the weighted sum of the two objective functions and executing a set of optimization runs. The effectiveness of the proposed synthetic parameterization schemes is assessed and discussed in detail. Finally, a reduced length mixer is optimized to study the impact of the length of the tube on the device’s performance.

show abstract

Section: Introductionmentioning

confidence: 99%

Shape Optimization of a Two-Fluid Mixing Device Using Continuous Adjoint

Alexias

Giannakoglou

2020

Fluids

View full text Add to dashboard Cite

show abstract

“…The digester volume turnover time (DVTT), mixture diffusion time (MDT), and hydraulic retention time (HRT) is used to calculate the rate of mixing of step and tracers of slug injection. Toshihiro et al [4] performed experiments in a CFD geometrical optimization to improve mixing performance of axial mixer to observe the performance of the axial static mixers produces high pressure drop characteristics and wide frequency range of input disturbance cannot be filtered whereas the static Time Difference Type Mixer (TDM)" is a new practical axial mixer that reduces the intermittent variation concentration of the mixture. This TDM was modified to decrease the pressure drop and smoothen the outlet concentration profile.…”

Section: Introductionmentioning

confidence: 99%

Turbulent Flow Behavior of Mixing Process Inside a Pharmaceutical Stirred Tank

Sharan¹,

Student²,

Bhuvaneshwar³

et al. 2020

IJEAT

View full text Add to dashboard Cite

As mixing is an essential operation in many engineering fields a mixing system is designed using agitated vessels in which it is difficult to obtain accurate information on induced turbulence by the impeller where CFD can provide detailed understanding of such systems. Here the impeller is designed and tested in both single phase &multiphase. Here specifically incompressible flow is used and Multiple reference frame is used to model the motion of the impeller zone. Hence, we study the flow characteristics by comparing the velocity and temperature contour of three different rotating speed of the impeller and predict the percentage increase and decrease for varying boundary conditions.

show abstract

“…CFD provides a further benefit of tracking the evolution of the process across the volume of the vessel, which is often not practical when studying real industrial systems experimentally, due to the impermeable nature of the construction materials of the vessels and often the fluids within. In addition, it is possible to couple a CFD modelling tool with an optimisation tool, where a target can be set, for example to minimise energy consumption of the mixer, and some features of the design can be varied by the optimiser to achieve the set goal (Hanada et al, 2016;Palacz et al, 2016). For the purposes of this study Siemens STAR-CCM+ CFD package and HEEDS optimisation package were used.…”

Section: Introductionmentioning

confidence: 99%