Development of Rock Engineering Systems-Based Models for Flyrock Risk Analysis and Prediction of Flyrock Distance in Surface Blasting

The environmental effects of blasting must be controlled in order to comply with regulatory limits. Because of safety concerns and risk of damage to infrastructures, equipment, and property, and also having a good fragmentation, flyrock control is crucial in blasting operations. If measures to decrease flyrock are taken, then the flyrock distance would be limited, and, in return, the risk of damage can be reduced or eliminated. This paper deals with modeling the level of risk associated with flyrock and, also, flyrock distance prediction based on the rock engineering systems (RES) methodology. In the proposed models, 13 effective parameters on flyrock due to blasting are considered as inputs, and the flyrock distance and associated level of risks as outputs. In selecting input data, the simplicity of measuring input data was taken into account as well. The data for 47 blasts, carried out at the Sungun copper mine, western Iran, were used to predict the level of risk and flyrock distance corresponding to each blast. The obtained results showed that, for the 47 blasts carried out at the Sungun copper mine, the level of estimated risks are mostly in accordance with the measured flyrock distances. Furthermore, a comparison was made between the results of the flyrock distance predictive RES-based model, the multivariate regression analysis model (MVRM), and, also, the dimensional analysis model. For the RES-based model, R ² and root mean square error (RMSE) are equal to 0.86 and 10.01, respectively, whereas for the MVRM and dimensional analysis, R ² and RMSE are equal to (0.84 and 12.20) and (0.76 and 13.75), respectively. These achievements confirm the better performance of the RES-based model over the other proposed models.     

Prediction of Flyrock Distance in Open Pit Blasting Using Surface Response Analysis

Flyrock is a rock thrown to greater distance than desired and is a dangerous and unwanted phenomenon in surface mines, particularly, when blasting is proceeding close to human occupation and dwellings. The prediction of flyrock distance is critical in defining the statutory danger zone of blasting and has evaded blasters for quite some time. Control of flyrock with its distance prediction involves identification of key variables and understanding their influence. Theoretical models though provide a good understanding of the phenomenon, the confidence that can be assigned to such models is still very less. This study presents novel method to identify, merge and consolidate independent variables into a simplified equation for flyrock distance prediction without compromising on the actual field applications. Field investigations were carried out in several mines and relevant data were generated relating to flyrock. The key parameters, namely, explosive, blast design and rock mass nature were characterized and analysed. An empirical model involving the key contributors for flyrock generation and distance prediction were assimilated and a new equation was developed based on actual data collected by employing surface response analysis. The developed model was found to be statistically significant and validated. Sensitivity analysis was conducted to ascertain the role of independent factors on flyrock distance.     

用蒙特卡洛模拟法计算正交最小二乘法拟合参数的标准偏差

介绍了一种计算正交最小二乘法拟合参数标准偏差的新方法－蒙特卡洛模拟法,并以电子探针微区分析技术分析环境样品的数据为例,对用于计算经典最小二乘法回归系数标准偏差的公式法和蒙特卡洛模拟法进行了比较。计算结果表明,两者完全相符,蒙特卡洛模拟法的计算结果正确、可靠。考察了模拟次数对计算结果的影响。模拟次数大于500时,计算结果趋于稳定,计算所需时间在1min以内。拟合方差与回归系数标准偏差存在明显的相关关系。线性模型能解释的方差越大,回归系数标准偏差越小。蒙特卡洛模拟法特别适合于非线性模型拟合参数标准偏差的计算。     

An RES-Based Model for Risk Assessment and Prediction of Backbreak in Bench Blasting

Most blasting operations are associated with various forms of energy loss, emerging as environmental side effects of rock blasting, such as flyrock, vibration, airblast, and backbreak. Backbreak is an adverse phenomenon in rock blasting operations, which imposes risk and increases operation expenses because of safety reduction due to the instability of walls, poor fragmentation, and uneven burden in subsequent blasts. In this paper, based on the basic concepts of a rock engineering systems (RES) approach, a new model for the prediction of backbreak and the risk associated with a blast is presented. The newly suggested model involves 16 effective parameters on backbreak due to blasting, while retaining simplicity as well. The data for 30 blasts, carried out at Sungun copper mine, western Iran, were used to predict backbreak and the level of risk corresponding to each blast by the RES-based model. The results obtained were compared with the backbreak measured for each blast, which showed that the level of risk achieved is in consistence with the backbreak measured. The maximum level of risk [vulnerability index (VI) = 60] was associated with blast No. 2, for which the corresponding average backbreak was the highest achieved (9.25 m). Also, for blasts with levels of risk under 40, the minimum average backbreaks (<4 m) were observed. Furthermore, to evaluate the model performance for backbreak prediction, the coefficient of correlation (R ²) and root mean square error (RMSE) of the model were calculated (R ² = 0.8; RMSE = 1.07), indicating the good performance of the model.     

Monte Carlo模拟法与基坑变形的可靠度分析

将Ｍｏｎｔｅ Ｃａｒｌｏ模拟法与有限元技术结合,对基坑变形的稳定怀进行了可靠度分析,并通过重构响应面来提高Ｍｏｎｔｅ Ｃａｒｌｏ模拟法的计算效率,研究表明该方法可行,计算结果较符合实际。     

随机误差传递与合成的蒙特卡罗模拟

对分析测试过程中随机误差的传递与合成进行了蒙卡罗模拟,并偏制了ＢＡＳＩＣ程序。该方法解决了当被合成误差不相互独立时泰勒级数公式所遇到的困难,当被合成误差相互独立时,与泰勒公式计算结果一致。     

加权距离判别法在泥石流危险度评价中的应用

将加权距离判别法引用到泥石流危险度分类中,建立了泥石流危险度分类模型。该模型选用了流域面积、主沟长度、流域最大相对高差、流域切割密度、主沟床弯曲系数、人口密度、泥沙补给长度比、植被覆盖率、一次泥石流（可能）最大冲出量和泥石流发生频率10项指标为建模参数,运用熵值法对这10个指标进行赋权,用已经分类的泥石流沟作为训练样本进行学习,建立了相应的判别准则。将待判泥石流沟样本代入判别准则进行判别分类,分类结果与传统分类结果100%吻合,验证了该模型的分类性能良好。该方法可以在实际工程中进行推广。     

基于Monte Carlo模拟的三维剖面地质界线不确定性分析

三维剖面地质界线是构建三维地质结构模型的重要基础数据,其不确定性会影响三维模型的几何形态和属性分布。以单一分布为假设前提的统计学不确定性分析方法掩盖了其他概率分布特征对模型的影响。突破单一误差分布条件的假设前提,本文使用Monte Carlo方法模拟了不同概率分布情况下地质剖面数据中地质界线的抽样采集,以及地质界线空间分布的不确定性;依托地质界线空间位置与地质属性的耦合关系,提出了用地质属性概率分布实现地质界线空间不确定性的定量可视化,并结合实际地质剖面探讨了多种概率分布条件下地质界线的空间不确定性。实例研究表明,基于Monte Carlo模拟的不确定性分析方法可以突破单一误差分布假设条件,结合地质属性概率可充分揭示出建模数据的内在不确定性与模型外在要素形态之间的耦合关系。     

岩土爆破工程危险源辨识、风险评价和控制

简述了岩土爆破工程按《职业健康安全管理体系一规范》（GB／T28001）进行危险源辨识、风险评价和控制的方法,辨识重大危险源,对重大危险源进行控制,减少安全风险,提高安全运行绩效。     

Prediction of the Rock Mass Diggability Index by Using Fuzzy Clustering-Based,ANN and Multiple Regression Methods

Rock mass classification systems are one of the most common ways of determining rock mass excavatability and related equipment assessment. However, the strength and weak points of such rating-based classifications have always been questionable. Such classification systems assign quantifiable values to predefined classified geotechnical parameters of rock mass. This causes particular ambiguities, leading to the misuse of such classifications in practical applications. Recently, intelligence system approaches such as artificial neural networks (ANNs) and neuro-fuzzy methods, along with multiple regression models, have been used successfully to overcome such uncertainties. The purpose of the present study is the construction of several models by using an adaptive neuro-fuzzy inference system (ANFIS) method with two data clustering approaches, including fuzzy c-means (FCM) clustering and subtractive clustering, an ANN and non-linear multiple regression to estimate the basic rock mass diggability index. A set of data from several case studies was used to obtain the real rock mass diggability index and compared to the predicted values by the constructed models. In conclusion, it was observed that ANFIS based on the FCM model shows higher accuracy and correlation with actual data compared to that of the ANN and multiple regression. As a result, one can use the assimilation of ANNs with fuzzy clustering-based models to construct such rigorous predictor tools.     

蒙特卡罗法油气资源评价软件的设计与开发

根据有关资料，对比油气资源量评价的各种方法，详细论述了蒙特卡罗法在油气资源量评价中的应用原理和特点，从算法上解决了蒙特卡罗法的关键实现技术即伪随机数产生和随机数抽样问题。利用API设计编制了程序软件，完成了程序设计、算法实现、界面开发等工作，并应用于实际地区的资源评价工作，给出了实际算例。     

Reliability Assessment of Shallow Foundation Stability Under Eccentric Load Using Monte Carlo and First Order Second Moment Method

Geotechnical and Geological Engineering - An analytical model defining soil-foundation probability of failure with respect to total system stability was developed in the present study. Soil...     

桂北某矿区硫化物尾矿重金属复合污染评价预测

对于硫化物尾矿重金属复合污染的评价采用以元素总量为主因子的单一方法(如Nemerom法)常难得到合理的结果.在桂北某矿区,运用地质累积指数、生态危害指数以及BCR酸提取等研究方法,并以近矿围岩风化壳的元素丰度作为参比值,对尾矿Pb、Zn、Cd及As复合污染进行综合评价预测.结果表明,(1)该区尾矿中Cd(生态危害性高、迁移性强)和As(污染程度高、生态危害性也较高)为主要污染因子,应重点预防和控制;而Zn(生态危害性较低)和Pb(污染程度、生态危害性及迁移性均较低)则相对次要;(2)尾矿中元素活性酸提取态分量(为产生环境效应的主因),与其元素总含量之间存在着不同程度或不一致的相关关系,这是元素总量因子评价法的问题之一.      

逻辑回归和信息量模型在山区滑坡易发性评价中适宜性的分析

以万山区为例,在区域滑坡孕灾条件的基础上,筛选工程地质岩组、斜坡结构、平均坡度、地貌、距构造距离及距河流距离共6个易发条件因子,选取逻辑回归模型和信息量模型对山区滑坡进行易发性评价。结果显示逻辑回归模型中中高易发区面积占比分别为1578%和1970%,82%的地质灾害点落在该区域内;信息量模型中中高易发区面积占比为1241%、2519%,包含了区域88%的滑坡灾害点。最后通过实际发生的灾害点在各易发区的分布情况进行检验,逻辑回归模型中灾害点落在高易发区的比例远小于信息量模型,且高易发等级中灾害点实际发生的比值较小,说明针对山区区域滑坡地质灾害易发性评价结果预测上,信息量模型的评价结果更为客观准确。     

不同降雨条件下黄土高原浅层滑坡危险性预测评价

黄土地区浅层滑坡发育非常广泛,由于其具有分布规律性差、前期变形迹象小、分布范围大、面小点多等特征,目前还无法进行有效预测,因此给黄土地区工程安全带来严重威胁。根据无限边坡模型,结合降雨入渗-土体强度衰减规律和GIS（地理信息系统）技术,构建了不同降雨条件下黄土地区浅层滑坡发育危险性评价模型,并将该评价模型应用到延河一级支流幸福川流域,预测在有效降雨量30、50、100、200 mm条件下,该流域浅层滑坡发育程度,并与当前较为流行的SINMAP模型(地形稳定性模型)进行对比。结果表明：①不稳定和潜在不稳定浅层滑坡主要分布在末级河流的两侧和源头,稳定和较稳定区域主要分布在一级河流河道两侧和塬面上;通过对比分析,SINMAP模型计算的结果与本文建立的模型在降雨强度30 mm时的计算结果较为一致。②在本文建立的模型评价结果中,随着有效降雨量的增加,F_s（稳定性系数）<1.00的不稳定区域所占比例逐渐增加,从30 mm的1.12%到200 mm的4.79%;相反,稳定区域则出现逐渐减少的趋势。③根据已发生灾害点的分布,随着有效降雨量的增加,研究区域已发生的灾害点分布在F_s<1.25的比例明显增加,从30 mm的62%到200 mm的88%,在SINMAP评价模型中,研究区域已发生的灾害点的64%分布在不稳定和潜在不稳定区域内,说明本文所建立的评价模型具有一定的精度。通过与SINMAP评价模型对比,本文建立的模型主要采用基于降雨入渗规律,而SINMAP评价模型主要基于降雨汇流过程,因此在利用过程中应根据区域特征选择利用。     

蒙特卡罗方法对TH—PPL CT屏蔽铅罐辐射防护的模拟分析

清华大学研制开发的单探头CT成像教学仪(TH-PPL CT)采用了一个10 mCi的137Cs标准放射源,该放射源由一个铅罐容器屏蔽.采用蒙特卡罗方法模拟和JB-4000型便携式智能化X-γ辐射仪实际测量相结合的方法,对TH-PPL CT教学仪放射源屏蔽铅罐周围照射量率进行模拟,证实了利用蒙特卡罗方法模拟防护铅罐这种方法的正确性.通过蒙特卡罗方法模拟距TH-PPL CT教学仪防护铅罐50cm处ICRU(国际辐射防护委员会)球的沉积能量,计算出人体在防护铅罐外所受的年剂量当量,证实了TH-PPL CT教学仪防护铅罐的防护满足要求,同时得出蒙特卡罗方法模拟可用于辐射防护分析和放射源屏蔽铅罐优化设计.     

Analysis of cation distribution in the octahedral sheet of dioctahedral 2:1 phyllosilicates by using inverse Monte Carlo methods

An inverse Monte Carlo (MC) method was developed to determine the distribution of octahedral cations (Al³⁺, Fe³⁺, and Mg²⁺) in bentonite illite–smectite (I–S) samples (dioctahedral 2:1 phyllosilicates) using FT–IR and ²⁷Al MAS NMR spectroscopies. FT–IR allows determination of the nature and proportion of different cation pairs bound to OH groups measuring the intensities of OH-bending bands. ²⁷Al MAS NMR data provide information about cation configuration because ²⁷Al MAS NMR intensity depends on Fe distribution. MC calculations based on FT–IR data alone show Fe segregation by short-range ordering (Fe clusters within 9 to 15?Å from a given Fe atom). Fe segregation increases with illite proportion. MC calculations based on IR and ²⁷Al NMR simultaneously yield similar configurations in which Fe clusters are smaller. The latter calculations fail to build appropriate cation distributions for those samples with higher number of illite layers and significant Fe content, which is indicative of long-range Fe ordering that cannot be detected by FT–IR and ²⁷Al MAS NMR. The proportion of Mg–Mg pairs is negligible in all samples, and calculations, in which the number of Mg atoms, as second neighbours, is minimised, create appropriate configurations.     

Assessing Stabilization Effectiveness of Combined Cement Kiln Dust and Quarry Fines on Pavement Subgrades Dominated by Black Cotton Soil

In developing technically viable and economically sustainable methods of improving soil properties to suit the requirements of engineering structures, designers/engineers are to take into consideration the availability and cost effectiveness of materials required for such improvement scheme. In line with this, the present study evaluates stabilization effectiveness of combined quarry fines (QF) and cement kiln dust (CKD) on subgrades dominated by black cotton soil (BC soil). The experimental programme included Atterberg limits, compaction and California bearing ratio (CBR) tests on soil mixtures prepared with a representative BC soil at constant dosage of 10 % QF and 0, 4, 8, 12 and 16 % CKD. Prior to testing, soil mixtures for CBR test prepared at optimum moistures and compacted with British standard light compaction effort were soaked for 96 h after curing for 28 days. Test data show that the addition of QF and CKD together reduced the plasticity index that resulted in rapid textural changes and eventual improvement in constructability, led to an increase in the optimum moisture content and a decrease in the maximum dry unit weight. Furthermore, the coupled effects of QF and CKD resulted in substantial increase in CBR strength of the composite specimens. Overall, mixtures created using the proposed QF and CKD ratios rendered the soil physically and mechanically stable producing results that are compatible with desired values for engineering performance typically required by various user agencies for pavement subgrades. This improvement scheme is not only cost effective, but it is capable of lessening the demand on non renewable resources thereby reducing the footprint of road construction projects in the environment.     

基于离散元数值模拟的应变分析和裂缝预测技术

应变分析与裂缝预测技术在地学领域具有重要应用意义。离散元方法虽然能有效分析含有大量间断的问题,但目前在地学领域应用较少。文中尝试使用离散元方法表示符合实际性质的岩石,模拟水平挤压环境下滑脱构造的形成过程,并对变形过程中的应变分布变化与裂缝生成规律进行了分析。结果表明:在挤压环境的滑脱构造中,裂缝产生的高峰期先于断层明显活动期,局部区域内聚集的大量裂缝是产生断层的诱因;已经出现明显活动的断层中产生的裂缝较少。裂缝集中区域和应变集中区域相互重叠,裂缝越发育则应变越强烈。受同一个断层影响的裂缝首先在断面上集中出现,随后产生在断面周边区域;在受断层影响的范围内,裂缝距离断面越远则形成时间越晚。该成果还表明离散元方法在应变分析与裂缝预测研究中具有巨大潜力。