模糊测度模型用于爆破震动影响下山区露天矿山边坡变形分析

根据生产爆破震动对山区山坡露天矿高陡边坡稳定性影响的工程实际,本文采用非确定性方法,将爆破震动引起露天矿边坡岩体移动变形这一现象视为一模糊事件,建立了生产爆破震动影响下山区山坡露天矿边坡岩体移动变形分析的Fuzzy测度理论模型.并利用该模型对我国某露天矿边坡岩体移动变形及其稳定性进行了具体的分析预测,所获理论结果符合工程实际.     

灰色-模糊系统(GFS)方法用于预测开挖引起的山体失稳

针对山区复杂地形条件下工程开挖实际情况,利用模糊数学和灰色系统理论建立了预测山区地下开挖引起岩体及自然坡失稳的数学模型,并对具体矿山工程中岩体移动和自然坡失稳问题进行了计算和分析.提出了山区复杂地形条件下地下安全开采技术方案.     

高陡山区岩体移动分析的Fuzzy数学模型

本文利用 Fuzzy数学理论 ,针对高陡山区地下房柱法采矿所引起的岩体移动变形问题 ,建立了具体的数学模型和预测分析方法 .通过对工程实例的计算分析 ,表明本文所建立的数学模型和分析方法适用于工程实际     

模糊遗传规划方法在预测深部开采岩体移动中的应用

运用模糊(Fuzzy)系统理论,给出了地下深部开采岩体移动变形预测分析的Fuzzy模型,对岩体移动参数采用遗传规划(GP)方法进行确定,进而形成了模糊遗传规划方法.用工程实测数据对遗传规划网络进行了训练,并用测试样本对GP模型进行了测试,证明了模型的预测性能是令人满意的.通过工程实例计算分析表明,采用本文提出的模糊遗传规划方法所获结果符合工程实际.     

基于FEMLIP的全风化边坡失稳破坏全过程的数值模拟研究

边坡坡角和强度是影响边坡稳定性的重要因素,而边坡失稳往往伴随着大变形的发生,其变形从数十米至数千米不等.目前,传统有限元法在处理大变形问题时常常因网格畸变而导致计算终止.因此,为了实现边坡失稳破坏全过程的模拟,并研究边坡坡角和强度对边坡稳定性的影响,基于Lagrange(拉格朗日)积分点有限元法（FEMLIP）,采用C语言编写了能够模拟边坡失稳滑塌全过程的Ellipsis程序,并通过一个典型案例对该方法的正确性和可行性进行了验证.采用该方法分析了边坡在不同坡角和强度条件下的稳定性和滑坡过程.研究结果表明,Lagrange积分点有限元法可以较准确地模拟边坡的潜在滑移面,并且可以模拟边坡失稳后的滑坡发展过程,为边坡滑坡大变形分析提供了一种新的数值计算方法.     

Fuzzy概率理论用于研究采矿引起的岩体移动

本文运用 Fuzzy 概率理论,对矿山岩体力学中的岩体移动问题,建立了相应的Fuzzy 数学模型,并利用该模型对地下采矿导致的岩体垂直移动、水平移动、水平变形、岩体倾斜和曲率变化等指标进行了定量计算.对于山区开采导致的岩体移动问题也进行了初步探讨.最后还对几个矿山工程实例进行了计算分析,结果表明,本文提出的新方法可用于分析采矿导致的岩体移动问题.     

基于复杂网络的黏性土颗粒边坡堆积体失稳研究

对颗粒边坡堆积体模型在金属板向下持续作用时的失稳破坏过程进行了颗粒离散元模拟,得出了二维边坡堆积体土颗粒速度总矢量、边坡堆积体失稳破坏时滑移开裂面的角度以及边坡堆积体坡顶y方向的平均速度等宏观响应过程.构建了自然堆积下边坡堆积体颗粒的法向力链无向网络模型,研究其滑移面出现的位置,并与实验结果做对比.最后,用复杂网络方法对边坡堆积体坡顶颗粒接触力链网络的拓扑特征进行了分析,得到平均度、簇聚系数和平均最短路径在边坡堆积体失稳过程中的演化规律,并结合强度折减法验证其准确性.研究结果表明,平均最短路径可以对边坡堆积体失稳破坏进行较为有效的预警.采用复杂网络理论研究边坡堆积体宏观响应与其力链网络介观结构之间的相互关系,为边坡失稳研究提供了一种全新的数学分析方法.     

基于最小二乘准则的滑坡位移动态权系数线性组合预测模型研究

针对固定权系数组合预测模型在滑坡监测数据多期预测预报中存在精度下降过快的问题,以最小二乘线性组合预测模型为基础,结合生物体新陈代谢过程,提出了一种基于最小二乘准则的滑坡位移动态权系数线性组合预测模型的构建方法,并引入SSE、MSE、MAE、MAPE和MSPE5种误差指标对该模型的预测精度进行评价.通过黄茨滑坡B2监测点和重庆市巫溪县物流园区长宁路边坡工程DW4监测点的监测数据进行算例验证,实验结果表明,基于最小二乘准则的滑坡位移动态权系数线性组合预测模型的预测评价指标均优于选用的单项预测模型以及普通线性组合预测模型.     

数量化理论在确定滑坡稳定性影响因素中的应用

确定滑坡稳定性的影响因素是防治滑坡之关键。本文运用数量化理论，建立了新滩滑坡位移量的预测公式，并由此确定出降雨作用、基岩面形状和滑体厚度是该滑坡稳定性的主要影响因素。此结论符合客观事实，对滑动后的新滩边坡稳定性和加固处理仍具有指导意义。     

三维岩体移动分析的Fuzzy数学模型

本文是文献[1,2,3,4]的深入研究和初步完善.文中研究了 N 维 Fuzzy 概率理论在岩体力学学科中的进一步应用.根据实际岩土工程中的岩体移动观测资料,建立了岩体移动问题的三维 Fuzzy 数学模型,并通过工程实例的计算分析论证了该模型的适用性.从而基本解决了岩体力学学科内一直未能获得解决的金属矿岩体连续移动预计这一重要课题,在岩体力学领域形成了新的理论体系——Fuzzy 数学理论体系.     

Optimal selection of a landfill disposal site using a modified fuzzy utility approach

The present paper develops an integrated fuzzy based model to select an optimal landfill site among the given alternative sites by using the concept of fuzzyutility method and multi-nomial logit theory. The suitability of different landfill sites are evaluated based on some important criteria involved in the process such as accessibility and transportation; environmental, geological and climatic conditions; socioeconomic conditions; land use pattern; and safety at the selected site. These criteria are assessed qualitatively by the decision makers based on their relative degree of importance. The importance weights and ratings of each criterion have been defined in the form of triplets of triangular fuzzy numbers by taking opinion of the decision makers. The corresponding triplets of ratings of each site are used to derive the utility value of the alternative sites. A multi-nomial logit model has been applied to calculate the probability of selection of each alternative site which can help policy makers to take appropriate decisions. Finally, the proposed methodology has been applied to allocate suitable landfill sites for disposing off municipal solid waste for Pilani town which is located in Jhunjhunu district of Rajasthan. The results evaluated by the modified fuzzy utility are also compared to the outputs of a direct method which is basically based on certain linguistic aggregation operators for group decision making. Computational results clearly demonstrate that the results obtained by the proposed method are coinciding very well and prepares a basis to adopt an overall strategy for selecting appropriate landfill site for proper solid waste disposal and its management.     

A fuzzy-robust stochastic multiobjective programming approach for petroleum waste management planning

This paper proposes a fuzzy-robust stochastic multiobjective programming (FRSMOP) approach, which integrates fuzzy-robust linear programming and stochastic linear programming into a general multiobjective programming framework. A chosen number of noninferior solutions can be generated for reflecting the decision-makers’ preferences and subjectivity. The FRSMOP method can effectively deal with the uncertainties in the parameters expressed as fuzzy membership functions and probability distribution. The robustness of the optimization processes and solutions can be significantly enhanced through dimensional enlargement of the fuzzy constraints. The developed FRSMOP was then applied to a case study of planning petroleum waste-flow-allocation options and managing the related activities in an integrated petroleum waste management system under uncertainty. Two objectives are considered: minimization of system cost and minimization of waste flows directly to landfill. Lower waste flows directly to landfill would lead to higher system costs due to high transportation and operational costs for recycling and incinerating facilities, while higher waste flows directly to landfill corresponding to lower system costs could not meet waste diversion objective environmentally. The results indicate that uncertainties and complexities can be effectively reflected, and useful information can be generated for providing decision support.     

多模式广义失效概率计算的数值模拟法及其工程应用

提出了安全与失效状态含有模糊信息时,广义失效概率计算的数值模拟,及相应的方差估算,并提出了对应的数值积分方法．当状态变量服从正态分布,且其对模糊安全域的隶属函数为正态型时,单个模式的广义失效概率具有精确解．首先利用这种特殊情况检验了所提数值模拟的精度,结果表明对于数值模拟法,随抽样次数的增加,估计值逐渐收敛于真实值．然后利用扩展原理和概率定理,提出两个及两个以上失效模式数广义失效概率的数值模拟计算方法以及相应的数值积分方法．对于工程结构问题,一般在删除次要失效模式之后,主要失效模式的数目不会太多,因此用该数值模拟与数值积分法可以得到精度较高的解．工程算例结果证明了此结论．另外还对所提的两种方法的适用范围做了讨论．     

Numerical simulation based on fuzzy stochastic analysis

In this paper mathematical methods for fuzzy stochastic analysis in engineering applications are presented. Fuzzy stochastic analysis maps uncertain input data in the form of fuzzy random variables onto fuzzy random result variables. The operator of the mapping can be any desired deterministic algorithm, e.g. the dynamic analysis of structures. Two different approaches for processing the fuzzy random input data are discussed. For these purposes two types of fuzzy probability distribution functions for describing fuzzy random variables are introduced. On the basis of these two types of fuzzy probability distribution functions two appropriate algorithms for fuzzy stochastic analysis are developed. Both algorithms are demonstrated and compared by way of an example.     

模糊密度随机变量的数学描述

研究了由于概率密度函数的模糊性而引起的模糊概率随机变量问题。给出了区间密度函数、模糊密度函数、模糊密度随机变量及其分布函数和模糊密度随机变量的模糊数学期望、模糊方差等基本概念及定义和计算方法,并证明了有关定理。     

结构的失效可能度及模糊概率计算方法

依据模糊可能性理论,系统地建立含模糊变量时结构的可靠性计算模型。旨在解决模糊结构、模糊-随机结构和模糊状态假设下结构的可靠性计算问题。所建模型可给出模糊结构失效的可能度和模糊-随机结构失效概率的可能性分布。研究表明:对同时含模糊变量和随机变量的混合可靠性计算问题,把失效概率(或可靠度)作为模糊变量,能更客观地反映系统的安全状况。算例分析说明了文中方法的合理性和有效性。     

模糊概率随机变量

研究了第二类模糊随机变量——具有清晰事件、模糊概率的随机变量的数学描述。在区间概率的基础上,利用模糊分解定理给出了概率模糊数集是可行的条件,进一步给出了具有模糊概率的随机变量及模糊概率随机变量的模糊分布函数和模糊分布列的定义和性质。提出并证明了具有模糊概率运算封闭性的模糊概率分解定理。研究了模糊概率随机变量的模糊数学期望和模糊方差的定义和性质。所有关于模糊概率随机变量的数学描述都具有模糊概率运算的封闭性,这为完善模糊概率的运算方法打下了基础。     

The role of fuzzy sets in civil engineering

Civil Engineering is an art, the practise of which requires the use of scientific knowledge as a basic tool. The engineer has to use considerable judgement in setting up and interpreting his scientific calculations and in making decisions based upon incomplete information. Because a very high safety level is required in civil engineering structures the uncertainty associated with the application of scientific calculations is very crudely and conservatively estimated using traditional methods. Current reliability theory enables a discussion of random parameter uncertainty but in civil engineering, system uncertainty and the possibility of human error is extremely important and must be included in any reliability calculations.The potential role of fuzzy sets in analysing system and human uncertainty is discussed in the paper and two numerical examples are given of the calculation of system and random uncertainty using probability measures of fuzzy sets.     

System reliability analysis of slope stability using generalized Subset Simulation

Slope failure mechanisms (e.g., why and where slope failure occurs) are usually unknown prior to slope stability analysis. Several possible failure scenarios (e.g., slope sliding along different slip surfaces) can be assumed, leading to a number of scenario failure events of slope stability. How to account rationally for various scenario failure events in slope stability reliability analysis and how to identify key failure events that have significant contributions to slope failure are critical questions in slope engineering. In this study, these questions are resolved by developing an efficient computer-based simulation method for slope system reliability analysis. The proposed approach decomposes a slope system failure event into a series of scenario failure events representing possible failure scenarios and calculates their occurrence probabilities by a single run of an advanced Monte Carlo simulation (MCS) method, called generalized Subset Simulation (GSS). Using GSS results, representative failure events (RFEs) that are considered relatively independent are identified from scenario failure events using probabilistic network evaluation technique. Their relative contributions are assessed quantitatively, based on which key failure events are determined. The proposed approach is illustrated using a soil slope example and a rock slope example. It is shown that the proposed approach provides proper estimates of occurrence probabilities of slope system failure event and scenario failure events by a single GSS run, which avoids repeatedly performing simulations for each failure event. Compared with direct MCS, the proposed approach significantly improves computational efficiency, particularly for failure events with small failure probabilities. Key failure events of slope stability are determined among scenario failure events in a cost-effective manner. Such information is valuable in making slope design decisions and remedial measures.     

单源模糊数的模糊随机有限元方程的解法

在工程实际情况下,有时候可以利用单源模糊数的运算法则,来减少模糊随机有限元方程的计算量.通过推导证明,其计算量仅相当于求解普通的随机有限元方程.为了更好地适应现代工程设计的需要,还提出用模糊随机有限元方程计算结果求结构模糊失效概率的近似方法.