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The Optimization Of The Support Thickness Of The Deep Well In Cold Areas

Posted on:2015-04-09Degree:MasterType:Thesis
Country:ChinaCandidate:H CuiFull Text:PDF
GTID:2181330431498436Subject:Mining engineering
Abstract/Summary:PDF Full Text Request
According to the features of wellbore pressure, short construction period, rockand supporting material mechanics parameter variability existed the procedure ofdesign and construction of deep wells engineering in extremely cold area, combiningwith the design of a molybdenum ore in Heilongjiang mixed well, the shaft liningthickness optimization method based on the combination reliability method andexperience method is built.The engineering rock mass structural plane investigations and rock mechanicsexperiments,using reduction parameters method to obtain parameters of rockmechanics; At the same time, the in-situ stress data obtained through hydrofracturingmeasurements were fitted to obtain the rule of horizontal stress changes with depth.Studying the interaction mechanism of the support system and surrounding rock,calculating lateral pressure on the shaft, according to the safety coefficient method,combining with the tunnel design specification, to draft preliminarily shaft liningthickness. Using Midas/gts numerical simulation software analysis, validate of thestress, strain and displacement of thickness wellbore proposed.Studying the random distribution rule of rock mass and the mechanicalparameters creating the calculation method of reliability of shaft lining thickness,according to the target reliability optimization support thickness, to calculate thereliability index and failure probability of the protective thickness drafted.Through the establishment of the optimization method of shaft support thicknessbased on the combination of empirical method, numerical simulation methodandreliability method, can be widely used in the optimization of deep shaft supportthickness in similar environment mine.
Keywords/Search Tags:rock mechanics parameters, reduction, numerical simulation, reliability, support parameter optimization
PDF Full Text Request
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