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81.
This paper is dedicated to the identification of constitutive parameters of elasto‐viscoplastic constitutive law from measurements performed on deep underground cavities (typically tunnels). This inverse problem is solved by the minimization of a cost functional of least‐squares type. The exact gradient is computed by the direct differentiation method and the descent is done using the Levenberg–Marquardt algorithm. The method is presented for lined or unlined structures and is applied for an elastoviscoplastic constitutive law of the Perzyna class. Several identification problems are presented in one and two dimensions for different tunnel geometries. The used measurements have been obtained by a preliminary numerical simulation and perturbed with a white noise. The identified responses match the measurements. We also discuss the usage of the sensitivity analysis of the system, provided by the direct differentiation method, for the optimization of in situ monitoring. The sensitivity distribution in space and time assess the location of the measurements points as well as the time of observation needed for reliable identification. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
82.
One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively. 相似文献
83.
Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach. 相似文献
84.
85.
从江县翁浪金矿床容矿岩石与围岩蚀变及其找矿标志 总被引:1,自引:7,他引:1
文章简单介绍了构造蚀变岩型金矿翁浪金矿床的容矿岩石和围岩蚀变特征,指出该类矿床的找矿标志,对进一步寻找此类矿床有一定的意义。 相似文献
86.
以大平山铜矿、天台山黄铁矿矿为例,阐述了该区的矿区、矿床地质及火山机构特征,并从成矿时间、空间及成因三个方面论述了矿床成矿与古火山机构的关系。 相似文献
87.
88.
阿尔泰可可塔勒铅锌矿床围岩蚀变及成因 总被引:2,自引:3,他引:2
可可塔勒铅锌矿床受火山喷发中心和沉积洼地控制,铅锌沉淀于海进阶段的局限还原卤水池中;矿下存在大型蚀变带,构成成矿流体对流循环过程中的水-岩作用带;后期造山挤压过程使地层和矿体倒转,矿床最终定位于麦兹倒转向斜之北东倒转翼的东南近转折部位。指出该矿床属海底火山喷流沉积改造型块状硫化物铅锌矿床。 相似文献
89.
层控夕卡岩型矿床成矿系统的元素活动性及质量迁移--以铜陵冬瓜山铜矿床为例 总被引:7,自引:0,他引:7
应用改善了的质量平衡方程研究冬瓜山层控夕卡岩型铜矿床成矿系统的元素活动性及质量迁移,结果表明:系统中Zr,Hf,Y和Nb为不活动元素,其余均为活动元素。主量元素中仅CaO为迁出组分,其质量迁移量为84%,其余均为带入组分,带入量最大的SiO2的质量迁移量高达2384%;稀土元素均为带入组分,其中,中稀土较轻稀土和重稀土的活动性更强;其它微量元素中,带入序列由强到弱为:Cr→Ta→Sn→Th,迁出序列由强至弱依次为:U→Sb→Ni—Sr→Ba→Bb→Co→W;成矿元素Cu和Ag为带入组分,其中Cu的带入量最大,质量迁移量高达1200%。本文还得出两点具普适性认识:①稀土元素较其它微量元素对体系条件的变化更为敏感,且往往表现出明显的规律性变化,能更好地示踪地质地球化学过程。②不同元素在不同体系中的行为特征差异极大,仅凭经验判定某一元素为不活动元素往往不可靠。因此,在开展质量平衡研究时,首先采用适当方法确认体系的不活动元素是一项不可或缺的前提工作。 相似文献
90.
小西弓金矿产于敦煌岩群的低绿片岩相变质岩层中,受NWW向脆韧性剪切带控制。二云母征岩不仅是矿源层,而且还是赋矿围岩。成矿流体主要是印支期岩浆期后含金热液,还包括少量变质水和大气降水,淋滤韧性剪切带内岩石中的Au元素并在有利的部位成矿。 相似文献