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Advances in Materials Science and Engineering
Volume 2015, Article ID 959726, 10 pages
http://dx.doi.org/10.1155/2015/959726
Research Article

Research on Dynamic Dissolving Model and Experiment for Rock Salt under Different Flow Conditions

1College of Civil Engineering, Chongqing University, Chongqing 400045, China
2Key Laboratory of New Technology for Construction of Cities in Mountain Area (Chongqing University), Ministry of Education, Chongqing 400030, China
3College of Civil Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China
4College of Civil Engineering, Fuzhou University, Fuzhou 350108, China

Received 8 December 2014; Accepted 19 January 2015

Academic Editor: João M. P. Q. Delgado

Copyright © 2015 Xinrong Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Utilizing deep rock salt cavern is not only a widely recognized energy reserve method but also a key development direction for implementing the energy strategic reserve plan. And rock salt cavern adopts solution mining techniques to realize building cavity. In view of this, the paper, based on the dissolving properties of rock salt, being simplified and hypothesized the dynamic dissolving process of rock salt, combined conditions between dissolution effect and seepage effect in establishing dynamic dissolving models of rock salt under different flow quantities. Devices were also designed to test the dynamic dissolving process for rock salt samples under different flow quantities and then utilized the finite-difference method to find the numerical solution of the dynamic dissolving model. The artificial intelligence algorithm, Particle Swarm Optimization algorithm (PSO), was finally introduced to conduct inverse analysis of parameters on the established model, whose calculation results coincide with the experimental data.