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101.
Reliability analysis is inseparably connected with the formulation of failure scenarios, and common test statistics are based on specific assumptions. This is easily overlooked when processing observation differences. Poor failure identification performance and misleading pre-analysis results, mainly meaningless minimum detectable biases and external reliability measures, are the consequence. A reasonable failure scenario for use with differenced GNSS observations is formulated which takes into account that individual outliers in the original data affect more than one processed observation. The proper test statistics and reliability indicators are given for use with correlated observations and both batch processing and Kalman filtering. It is also shown that standardized residuals and redundancy numbers fail completely when used with double differenced observations.
相似文献
Andreas WieserEmail: Phone: +43-316-8736323Fax: +43-316-8736820 |
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岩溶区桩基下溶洞顶板稳定性影响因素取值的不确定性及其样本数量的有限性,给桩基下溶洞顶板稳定性的评价带来了一定困难。根据现有研究成果,建立桩基下溶洞顶板抗冲切、抗剪切和抗弯力学简化模型,并从理论上推导相应的稳定性验算公式。在此基础上,结合区间分析理论和结构非概率可靠性度量方法,提出了基于区间非概率可靠性方法的桩基下溶洞顶板稳定性评价方法。该方法采用MATLAB中的INTLAB工具箱进行区间运算,并运用截断法消除运算过程中的区间扩展现象,最后通过比较溶洞顶板体系的非概率可靠性指标η与1的大小来判断桩基下溶洞顶板稳定性。以丹霞高速互通中D匝道2#桩基下溶洞为例,计算出该桩基下溶洞顶板体系的非概率可靠性指标η=7.95,该值大于1说明该桩基下溶洞顶板处于稳定状态,且评价结果与工程实际相符,表明了该方法的合理性与可行性。分别以3种功能函数为单位,研究当区间变量的变异系数C不同时(C从0.01递增至0.1),对应非概率可靠性指标η的变化规律。研究表明,随各区间变量变异系数C的增大,相应非概率可靠性指标呈不同程度的降低,其中溶洞顶板厚度h的变异性对评价结果影响最大,其次为桩端阻力分担比T,桩顶反力F的影响相对最小。 相似文献
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为了能够真实反映砭家沟尾矿库的稳定特性,运用Monte Carlo试验原理,考虑库区砂层的空间变异特性,利用Slope/W软件对尾矿库进行了概率分析与敏感性分析。分析表明,抽样方式的不同,使尾矿坝体失稳概率和可靠性指标发生了大幅波动,但是并没有使安全系数产生明显变化,也验证了仅将安全系数作为衡量尾矿坝体稳定性的唯一标准是不合适的;敏感性分析也表明了砂层主要参数对安全系数影响的敏感程度,同时也表明黏聚力是影响库区稳定的主要砂层因素。通过研究,为尾矿库今后的运行与管理提供了理论依据,具有一定的指导意义。 相似文献
108.
Mahdi Shadab Far Yuan Wang Yousif A. H. Dallo 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2019,13(1):82-98
Rock explosion has always been a complex problem because neither rock characteristics nor explosion waves could be accurately estimated. As such, this imposes a high uncertainty on deterministic methodologies available for damage prediction. In this paper, by defining two damage zones around the blast hole, including crushed and cracked zones, a first-order reliability analysis (FORM) was adopted to address this issue. For this purpose, FORM was used in a double-loop algorithm, where the inner loop was responsible for converging the FORM, and the outer loop was assigned to feed the inner loop with new cases. Using such nested-loop algorithm, the probability of exceedance was calculated for any desired damage zone radius. The maximum effect of the involved parameters on the failure probability induced around the blast hole was additionally studied using a parametric reliability analysis. The results showed that the radii for crushed and cracked zones are limited to 0.5 and 4.2?m, respectively, so that the probability of going beyond these limits is less than 1%. Moreover, the analyses of decoupled explosions showed that increasing the gap between the explosion charge and wall of the borehole could severely reduce the failure probability; however, the maximum effect of decoupling ratio occurs in the small range of radii between 0.3?mm and 2.35?m. 相似文献
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Toshiaki Nanazawa Tetsuya Kouno Gaku Sakashita Takashi Nakaura 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2019,13(3):176-184
ABSTRACTThis paper describes the development of a partial factor design method on the bending strength of piles for the Japanese Specifications for Highway Bridges. First, uncertainties in mobilised bending moments and yield bending moments were evaluated by Monte Carlo simulations. Second, the reliability of piles designed by the previous specifications were evaluated on the basis of reliability analysis considering uncertainties in the mobilised bending moments, yield bending moments, and other factors. Finally, a partial factor design method utilising a survey subsurface investigation method and ground type was developed to reach target reliability levels determined by the Standards. 相似文献
110.
Polynomial chaos expansions (PCEs) have been widely employed to estimate failure probabilities in geotechnical engineering. However, PCEs suffer from two deficiencies: (a) PCE coefficients are solved by the least-square minimization method which easily causes overfitting issues; (b) building a high order PCE is often computationally expensive. In order to overcome the aforementioned drawbacks, the Bayesian regression technique is employed to evaluate PCE coefficients, which not only provides a sparse solution but also avoids overfitting. With the aid of the predictive means and variances given by Bayesian analysis, a learning function is proposed to sequentially select the most informative samples that are critical to build a PCE. This sequential learning scheme can highly enhance the computational efficiency of PCEs. Besides, importance sampling (IS) is incorporated into the sequential learning (SL)-PCEs to deal with geotechnical problems with small failure probabilities. The proposed method of SL-PCE-IS is applied to three illustrative examples, which shows that the improved PCE method is more effective and efficient than the common PCEs method, leading to accurate estimations of small failure probabilities using fewer training samples. 相似文献