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Sadhana
Article . 2012 . Peer-reviewed
License: Springer TDM
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Simulation–optimization model for groundwater contamination remediation using meshfree point collocation method and particle swarm optimization

Authors: MATEGAONKAR MEENAL; T I ELDHO;

Simulation–optimization model for groundwater contamination remediation using meshfree point collocation method and particle swarm optimization

Abstract

Remediation of the groundwater contamination problem is a tedious, time consuming and expensive process. Pump and treat (PAT) is one of the commonly used techniques for groundwater remediation in which the contaminated groundwater is pumped, treated and put back to the aquifer system or other sources. Developing simulation-optimization (S/O) model proved to be very useful in the design process of an effective PAT system. Simulation models help in predicting the spatial and temporal variation of the contamination plume while optimization models help in minimizing the cost of pumping. Generally, grid or mesh based models such as Finite Difference Method (FDM) or Finite Element Methods (FEM) is used for the groundwater flow and transport simulation. But it is found that grid/mesh generation is a time consuming process. Therefore, recently Meshfree (MFree) based numerical models are developed to avoid this difficulty of meshing and remeshing. MFree Point Collocation Method (PCM) is a simple meshfree method used for the simulation of coupled groundwater flow and contaminant transport. For groundwater optimization problems, even though number of methods such as linear programming, nonlinear programming, etc. are available, evolutionary algorithm based techniques such as genetic algorithm (GA) and particle swarm optimization (PSO) are found to be very effective.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Top 10%
Average
gold