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

被引：6
作者：
Liu, Xinrong [1 ,2 ]
Yang, Xin [1 ,2 ]
Zhong, Zuliang [1 ,2 ]
Liang, Ninghui [1 ,2 ]
Wang, Junbao [3 ]
Huang, Ming [4 ]
机构：
[1] Chongqing Univ, Coll Civil Engn, Chongqing 400045, Peoples R China
[2] Chongqing Univ, Minist Educ, Key Lab New Technol Construct Cities Mt Area, Chongqing 400030, Peoples R China
[3] Xian Univ Architecture & Technol, Coll Civil Engn, Xian 710055, Peoples R China
[4] Fuzhou Univ, Coll Civil Engn, Fuzhou 350108, Peoples R China
来源：
ADVANCES IN MATERIALS SCIENCE AND ENGINEERING | 2015年 / 2015卷
基金：
中国国家自然科学基金;
关键词：
PERMEABILITY; DISSOLUTION; DAMAGE;
D O I：
10.1155/2015/959726
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
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页数：10
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