Optimization of Pipeline Flow of Fine Particles Slurry Using Genetic Algorithms

Sanjay Kumar Srivastava*, Rajesh Kumar**, Prabhat Kumar Singh Dikshit***
*Ph. D. Scholar, Department of Civil Engineering, IIT (BHU), Varanasi, India.
** Associate Professor, Department of Civil Engineering, IIT (BHU), Varanasi, India.
*** Professor, Department of Civil Engineering, IIT (BHU), Varanasi, India.
Periodicity:December - February'2015
DOI : https://doi.org/10.26634/jce.5.1.3140


Liquid and solid are two phase flows, stated to as slurries. Slurry particle less than 40 μm (fine particles) in turbulent flow behave in a homogeneous manner. They are referred to as non-setting slurry. The particles’ concentrations are almost similar across the cross section of pipe. The characteristics of slurry such as unsteady flow rate, complicated ingredients, high concentration and viscosity of liquid carrier are subjected to pipeline blockage and high energy consumption. The pressure drop is a key parameter in the design of slurry pipelines, as it delivers evidence on the power required to continue a flow rate above the critical deposition velocity. As the pressure drop in pipeline is directly proportional to the energy consumption, to minimize the pumping cost of slurry, the pressure drop must be minimum. This paper presents an overview on the head losses in pipeline for slurry flows. The minimization of the head loss is considered as the objective function. Genetic algorithm is used as the optimization technique and code is developed in MATLAB.


Pipe Network, Optimization, Genetic Algorithm.

How to Cite this Article?

Srivastava,S,K., Kumar,R., and Dikshit,P,K,S. (2015). Optimization of Pipeline Flow of Fine Particles Slurry Using Genetic Algorithms. i-manager’s Journal on Civil Engineering, 5(1), 33-37. https://doi.org/10.26634/jce.5.1.3140


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