Font Size: a A A

Rheology Parameters Back Analysis Of Longtan Power Station's Model Experimental Cave

Posted on:2006-08-25Degree:MasterType:Thesis
Country:ChinaCandidate:G F WangFull Text:PDF
GTID:2132360155458162Subject:Mining engineering
Abstract/Summary:PDF Full Text Request
With enlargement of all kinds of geotechnical engineering and studying on the rock and its characteristic, the rheology has become a kind of important capability of the rock. Amount of locale measuring and examination indicating, for the weak rock, even the hard one, they will bring the phenomena of the rheology. If we neglect it, the calamitous results will happen. So studying the reason of the phenomena and the mechanics principium has significant meaning. In the thesis, with the background of longtan project, adopt the methods theoretic analysis and intelligent arithmetic to research and discuss. The primary tasks in this thesis are stated as followed:(1)Predigesting rock character of the model of 72# cave, taking into account the major factor of the terrane, according the geologic information, build the numerical value model. In term of uniform design method to design the data, adopt FLAC3D process to account.(2)According to the experience of engineering and test data, deal with the data beforehand. First, dividing the data of experience into different things, calculate in the FLAC3D process. Second, analyse the susceptivity of the parameter. Adjust the trend of the curve according to the practical inspect curve, confirming the bound of the parameter. The way of deal with the data beforehand, it can avoid the amount of calculating only depending on accounting to confirm the bound, as the same time, it can avoid the error only depending on experience to confirm the parameter.(3)Adopting the way of combining the Neural Network and Genetic Algorithm, making use of the accomplished 72# cave model and the data through the dealing with the data beforehand, design the calculating...
Keywords/Search Tags:Rock rheology, FLAC-3D process, Neural Network, Genetic algorithm, Parameter back analysis
PDF Full Text Request
Related items