本文關(guān)鍵詞：土工強(qiáng)度參數(shù)變異特征及邊坡可靠度分析中合理樣本數(shù)目研究　出處：《西南交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 邊坡可靠度分析 參數(shù)不確定性 隨機(jī)場(chǎng)理論 空間變異性 隨機(jī)抽樣 樣本數(shù)目

【摘要】：邊坡穩(wěn)定分析中,以概率理論為基礎(chǔ)、考慮各種不確定性影響的可靠度設(shè)計(jì)方法已進(jìn)入實(shí)用階段。該方法主要需要明確巖土設(shè)計(jì)參數(shù)的各種不確定性,根據(jù)不確定性來(lái)源可歸納為巖土體固有的參數(shù)變異性以及統(tǒng)計(jì)不確定性。傳統(tǒng)上,在假設(shè)土體空間是均質(zhì)的基礎(chǔ)上,采用隨機(jī)變量模型描述土體參數(shù)的變異性,但實(shí)際上由于土體的沉積過程以及應(yīng)力歷史不同,導(dǎo)致土體參數(shù)在空間上存在一定的變異性,單純利用傳統(tǒng)概率統(tǒng)計(jì)的方法忽略了土體空間不同點(diǎn)物理力學(xué)性質(zhì)的差異,已無(wú)法滿足對(duì)土體參數(shù)空間變異性做出客觀分析與評(píng)價(jià)的需要;工程中通過勘察取樣試驗(yàn)獲取有限樣本,利用小樣本下的統(tǒng)計(jì)值對(duì)參數(shù)真值進(jìn)行估計(jì)推斷,但是選取多大的巖土樣本抽樣數(shù)量才能最大程度反映總體統(tǒng)計(jì)值仍沒有具體的標(biāo)準(zhǔn),樣本數(shù)目的差異將影響統(tǒng)計(jì)不確定性的大小�；阼F路工程勘察資料,選取了5個(gè)以黏土為主的工程地質(zhì)單元,分別采用概率統(tǒng)計(jì)方法和隨機(jī)場(chǎng)理論分析了土體抗剪強(qiáng)度指標(biāo)c、φ的點(diǎn)變異與空間變異特征,比較了兩種理論分析結(jié)果的差異,討論了考慮參數(shù)c、φ空間自相關(guān)的必要性,并基于灰色關(guān)聯(lián)度研究了 c、φ空間變異性與其他物理力學(xué)指標(biāo)的關(guān)聯(lián)特征;以計(jì)算機(jī)隨機(jī)抽樣方法模擬實(shí)際工程勘探取樣試驗(yàn),分別構(gòu)建較為完備的土工參數(shù)的樣本統(tǒng)計(jì)值空間及對(duì)應(yīng)的可靠度指標(biāo)結(jié)果空間,對(duì)比分析不同樣本容量對(duì)可靠指標(biāo)離散性的影響,探討了大、中、小3種參數(shù)變異水平下樣本數(shù)目的合理取值問題。論文研究主要取得了如下成果:(1)以傳統(tǒng)概率統(tǒng)計(jì)方法和隨機(jī)場(chǎng)理論為研究手段,分別計(jì)算了黏性土 c、φ參數(shù)的點(diǎn)變異和空間變異系數(shù)。研究表明,兩參數(shù)的點(diǎn)變異系數(shù)與空間變異系數(shù)差異性較大,相較于點(diǎn)變異系數(shù),c、φ值的空間變異系數(shù)折減率分別可達(dá)25%和15%。隨機(jī)場(chǎng)理論通過方差折減的方法對(duì)強(qiáng)度參數(shù)的點(diǎn)方差進(jìn)行折減,得到土體的空間方差,從而將點(diǎn)變異系數(shù)轉(zhuǎn)化為空間變異系數(shù),更真實(shí)地反映了參數(shù)的變異特征。(2)基于灰色關(guān)聯(lián)理論探討了液性指數(shù)IL、標(biāo)準(zhǔn)壓縮系數(shù)a1-2、含水率w、天然孔隙比e和塑性指數(shù)IP等主要物理力學(xué)參數(shù)對(duì)抗剪強(qiáng)度指標(biāo)空間變異程度影響的排序規(guī)律。分析表明,液性指數(shù)IL與c、φ參數(shù)的空間變異性關(guān)聯(lián)程度最大,其次為結(jié)構(gòu)性指標(biāo)a1-2和含水性指標(biāo)w。(3)針對(duì)樣本數(shù)目與土工參數(shù)變異性影響可靠度分析結(jié)果離散程度的問題,提出了以控制可靠度分析結(jié)果空間變異程度反推樣本數(shù)目的方法,探討了不同土工參數(shù)變異水平下對(duì)應(yīng)的合理取樣數(shù)目。結(jié)果表明,可靠指標(biāo)結(jié)果空間變系數(shù)取0.30、0.25、0.20時(shí),對(duì)應(yīng)于參數(shù)呈小變異水平的樣本數(shù)為6、9、15,中、大變異水平時(shí)樣本數(shù)目宜分別提高至 11、15、20 和 18、20、30。
[Abstract]:The slope stability analysis, based on probability theory, the reliability design method considering the influence of uncertainties has entered the practical stage. The main method to clear the geotechnical design parameter uncertainty, according to the sources of uncertainty can be summarized as parameter variability and statistical uncertainty inherent in rock and soil. Traditionally, in the assumption that the soil space is homogeneous on the basis of the stochastic variable model to describe variability of soil parameters, but in fact due to the deposition process of soil and the stress history of different soil parameters, cause there is variability in space, ignoring the differences of soil spatial differences of physical and mechanical properties of the simple use of traditional methods of probability statistics. Has been unable to meet the need to make objective analysis and evaluation of parameters of soil spatial variability; engineering survey by sampling test samples with limited access. Statistical small sample values for the true value of the parameters for estimation, but the selection of samples of rock and soil in order to maximize the number of sampling statistics reflect the overall value is still no specific standard, different sample number will affect the statistical uncertainty. Based on survey data of railway engineering, selected 5 in clay engineering geological unit, using probability statistics method and random field theory of soil shear strength index C, feature point variability and spatial variability of phi, compared the analysis results of the two theories, discussed by considering the parameters of C, with the necessary spatial correlation, and based on the grey correlation degree of C association with characteristics of spatial variability and other physical and mechanical indexes; computer simulation method of random sampling sampling test of the practical exploration, the sample statistics of geotechnical parameters of complete construction of value space The results of the reliability index and the corresponding space, comparative analysis of the influence of different sample size on discrete reliability index, are discussed, in the number of samples to the reasonable value problem of small 3 parameter variation level. This thesis mainly achieved the following results: (1) based on the traditional statistical method and random field theory research means of cohesive soil were calculated for C, coefficient of variation and spatial variation with parameters. The results show that the two parameter difference coefficient of variation and spatial variation coefficient is larger, compared to the variation coefficients, C, spatial variation of the value number reduction method rate can reach 25% and 15%. respectively by random field theory variance reduction of strength parameters of variance reduction, spatial variance of soil, and the variation coefficients into spatial variation coefficient to reflect the variation of parameters. (2) based on Grey Relational Theory To investigate the liquidity index IL, standard compression coefficient A1-2, w water content, natural void ratio e and the main physical and mechanical parameters such as plasticity index of IP against order of shear strength index spatial variability effects. The analysis shows that the liquidity index of IL and C, the spatial variability of correlation parameters followed by the maximum diameter. The structural index A1-2 and water content index of W. (3) according to the number of samples and the effect of soil parameter variability results of reliability analysis of discrete degree of the problem, put forward to control the results of reliability analysis of spatial variability of the sample number of backstepping method, discussed the rational sampling number of soil parameter variation under different level of the corresponding results. The results show that the reliability index of space variable coefficient 0.30,0.25,0.20, corresponding to a number of small sample parameter variation level is 6,9,15, when the number of samples should be large variation levels were increased to 11,15,20 and 18,20,30.

【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TU43

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