锦屏电站地下厂房卸荷岩体参数研究

It is a basic work to ascertain the parameters of rock mass for evaluation about stability of the engineering. Anisotropism、inhomogeneity and discontinuity characters of the rock mass arise from the existing of the structural plane. Subjected to water、weathering effect、off-loading, mechanical characters of the rock mass are greatly different from rock itself, Determining mechanical parameters of the rock mass becomes so difficult because of structure effect、dimension effect、rheological character, ‘Can’t give a proper parameter’ becomes one of big problems for theoretic analysis and numerical simulation. With the increment of project scale, appraising the project rock mass and ascertaining the parameters of rock mass becomes more and more important and strict. Consequently, researching the parameters of rock mass has important theoretical significance and actual meaning. The Jin-ping hydroelectric station is the first highest hyperbolic arch dam in the world under construction, the height of the dam is about 305m, it is the biggest hydroelectric station at lower reaches of Yalong river. The length of underground factory building is 204.52m, the total height of it is 68.83m, the maximum of span clearance is 28.90m. Large-scale excavation in the underground factory of Jin-ping hydroelectric station has brought many kinds of destructive phenomenon, such as relaxation、spilling, providing a precious chance for study of unloading parameter about rock mass. As we all know, Southwest is the most important hydroelectric power base in China, the construction of the hydroelectric station mostly concentrate at high mountain and gorge area, basically and importantly, we must be familiar with the physical and mechanical character of the rock mass to guarantee to exploit safely、efficiently、quickly, in other words, we must understand the strength and deformation character of the rock mass. Based on enough fieldwork of geological investigation, we study the parameter of unloading rock mass on condition that we obtain abundant information, which is not only important for the construction of Jin-ping hydroelectric station, but also for the construction of other big hydroelectric station similar with Jin-ping. This paper adopt geological analysis、test data analysis、experience analysis、theory research and Artificial Neural Networks （ANN） brainpower analysis to evaluate the mechanical parameter, the major production is as follows: (1)Through the excavation of upper 5-layer of the underground powerhouse and the statistical classification of the main joints fractures exposed, We believe that there are three sets of joints, the first group is lay fracture, the second group and the fourth group are steep fracture. These provide a strong foundation for the following calculation of and analysis; (2)According to the in-situ measurement about sound wave velocity、displacement and anchor stress, we analyses the effects of rock unloading effect，the results show a obvious time-related character and localization features of rock deformation. We determine the depth of excavation unloading of underground factory wall based on this. Determining the rock mass parameters according to the measurement about sound wave velocity with characters of low- disturbing、dynamic on the spot, the result can really reflect the original state, this chapter approximately the mechanical parameters about rock mass at each unloading area; (3)Based on Hoek-Brown experienced formula with geological strength index GSI and RMR method to evaluate the mechanical parameters of different degree weathering and unloading rock mass about underground factory, Both of evaluation result are more satisfied; (4)From the perspective of far-field stress, based on the stress field distribution ideas of two-crack at any load conditions proposed by Fazil Erdogan (1962)，using the strain energy density factor criterion (S criterion) proposed by Xue changming(1972)，we establish the corresponding relationship between far-field stress and crack tip stress field, derive the integrated intensity criterion formula under the conditions of pure tensile stress among two line coplanar intermittent jointed rock，and establish the corresponding intensity criterion for the exploratory attempt; (5)With artificial neural network, the paper focuses on the mechanical parameters of rock mass that we concerned about and the whole process of prediction of deformation parameters, discusses the prospect of applying in assessment about the parameters of rock mass，and rely on the catalog information of underground powerhouse of Jinping I Hydropower Station, identifying the rock mechanics parameters intellectually，discusses the sample selection, network design, values of basic parameters and error analysis comprehensively. There is a certain significance for us to set up a set of parameters evaluation system，which is in construction of large-scale hydropower among a group of marble mass.

大城市内部商业环境满意度评价与消费区位决策研究-以北京市西城区和海淀区为例

Since 1990s, commercial conditions in China including commercial environment, retail types, scale of retail enterprises, spatial structure of retail and shopping decision making factors have changed. In order to keep up with these changes, commercial geography should set up new perspectives, theories and methods to analyze its internal mechanism and changing rules, and thus provide reasonable and practical scientific basis to commercial planning, location decision of retail enterprises and commercial environment construction. Taking Xicheng and Haidian District of Beijing as research case, which is a sector region from city center to rural region, this paper selects 12 commercial centers as most important study objects of this sector. This paper mainly makes use of the methods of Modeling, Pearson Bivaiiate Correlations Analysis, Factor Analysis and Logit model. Based on 1300 questionnaires and fieldwork, this paper focuses on modeling of Consumer Satisfaction of Commercial Environment (CSCE), evaluation of commercial environment and driving factors of consumers' shopping location decision. Firstly, this paper discusses the development of commercial geography and commercial environment evaluation, the new characteristics and trends of commercial development in Beijing and physical commercial environment of Xicheng and Haidian District of Beijing from chapter 1 to chapter 4. Secondly, this paper summarizes characteristics of residents' shopping behavior in chapter 5. Thirdly, this paper sets up an evaluative model of CSCE, and analyzes consumer satisfaction indexes of commercial environment and their spatial features in chapter 6. Fourthly, this paper infers how residents' attributes and shopping behaviors affect their preferences of shopping location and what are residents' shopping location decisions and their influencing factors in chapter 7. Fifthly, this paper constructs a significant index model and a pyramidal framework of CSCE, and further analyzes the diversity and competitive advantage of commercial environment in chapter 8. Finally, some conclusions are drawn as follows: 1. Characteristics of residents' shopping behavior mostly embody residents' time distance preference, commodity consumption preference, shopping time distribution and shopping activity characteristics. The important factors that influence shopping location choice of residents are distance, transportation, commodity price, commodity types and commodity quality. However, the important factors, which influence shopping location re-choice of residents, are commodity price, commodity quality, commodity types and transportation. 2. CSCE indexes of 12 commercial centers show us significant spatial characteristics, such as spatial differences of "Center-fringe region", spatial characteristics of axes, spatial diversity of ring roads and so on. 3. Influencing factors including factor endowments, relative establishment factor and location and transportation factor of commercial environment are of importance for CSCE. 4. Logit model 1 indicates that shopping behavior of residents is significantly and positively related to working in high-tech companies, high income and by car and positively related to high school diploma, by bus and subway. 5. Logit model 2 indicates that residents' shopping location decision is significantly and positively related to leisure establishment and relative restaurant and entertainment establishment and negatively related to commercial location, commodity price, service quality, parking site. 6. The significant index model and the pyramidal framework of CSCE indicate competitive advantages are crucial to attractive capability of commercial center, and competitive weakness limits development of commercial centers, in particular the weakness of service quality and parking site now is the chief factors restricting development of commercial centers