Energy Efficient Design of a Jet Pump by Ensemble of Surrogates and Evolutionary Approach

Abstract

Energy systems working coherently in different conditions may not have a specific design which can provide optimal performance. A system working for a longer period at lower efficiency implies higher energy consumption. In this effort, a methodology demonstrated by a jet pump design and optimization via numerical modeling for fluid dynamics and implementation of an evolutionary algorithm for the optimization shows a reduction in computational costs. The jet pump inherently has a low efficiency because of improper mixing of primary and secondary fluids, and multiple momentum and energy transfer phenomena associated with it. The high fidelity solutions were obtained through a validated numerical model to construct an approximate function through surrogate analysis. Pareto-optimal solutions for two objective functions, i.e., secondary fluid pressure head and primary fluid pressure-drop, were generated through a multi-objective genetic algorithm. For the jet pump geometry, a design space of several design variables was discretized using the Latin hypercube sampling method for the optimization. The performance analysis of the surrogate models shows that the combined surrogates perform better than a single surrogate and the optimized jet pump shows a higher performance. The approach can be implemented in other energy systems to find a better design.

Numerical Simulation of Double Surface Liquid Ejector with Flow Swirl for Centrifugal Pump

“…In JP with a flow swirl, the following positive aspects can be distinguished:  increased efficiency compared to existing JP designs [10,11];  increased coefficient of ejection. This allows to obtain pumps for large flows for the same external energy parameters;…”

An integrated modeling approach for design and optimization of ejector pumps carrying two-phase fluid

“…The jet pump was optimized numerically and the highest efficiency detected. Nevertheless, there was no experimental or industrial data supporting or verifying Husain et al [33] claims.…”

“…(Lm/Dn) is 2-3.5. Afzal Husain and his coworkers [33] introduced an improved numerical modeling and optimization approach using fluid dynamics to design energy efficient ejector pumps. In their work, optimization was conducted by applying geometrical variables by using LHS, Latin Hypercube Sampling, and method.…”