4.7 Article

CFD modelling of axial mixing in the intermediate and final rinses of cleaning-in-place procedures of straight pipes

期刊

JOURNAL OF FOOD ENGINEERING
卷 221, 期 -, 页码 95-105

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jfoodeng.2017.09.017

关键词

Rinse; CFD; CIP; Axial mixing; Reducing water consumption

资金

  1. Innovation Fund Denmark (IFD) [5107-00003B]
  2. Technical University of Denmark (DTU)

向作者/读者索取更多资源

The intermediate and final rinses of straight pipes, in which water replaces a cleaning agent of similar density and viscosity, are modelled using Computational Fluid Dynamic (CFD) methods. It is anticipated that the displacement process is achieved by convective and diffusive transport. The simulated agent concentrations show good agreement with the analytical axial mixing models from literature. The displacement time, minimum water consumption, minimum generation of wastewater and minimum requirement of intermediate rinsing water are evaluated using CFD. Practical empirical equations are derived from CFD results and applied to examine if the process is operated in an efficient and economic manner. It has been found that the displacement time can be predicted from the inner pipe diameter and the mean flow velocity using a power law relationship. Changing flow velocities does not significantly influence the minimum water consumption and the minimum wastewater generation for rinsing a pipe. Controlling the rinsing step based on a downstream measurement still consumes more water than the minimum requirement to reduce contamination risks. This article presents an innovative algorithm for optimizing the rinse steps with lower water consumption based on the above observations. A case of rinsing a 24 m long straight pipe describes the promising application of the CFD study. The recovery of cleaning agent can be up to 89.3% of the volume and the saving of intermediate rinsing water can be at least 55% compared to the conventional rinse method. The work in this article presents an example showing how to deal with more complex systems in the future. (C) 2017 Elsevier Ltd. All rights reserved.

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