冯夏庭博士引用率最高的10篇SCI|论文写作与文献 - 领先的岩土技术社区，岩土领域的媒体、社区与应用平台！

离线huangwg08

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[color=#ff0000] Effects of water chemistry on microcracking and compressive strength of granite.pdf (690 K) 下载次数:229
International Journal of Rock Mechanics & Mining Sciences 38 (2001) 557–568
Technical Note
Effects of water chemistry on microcracking and compressive
strength of granite
Xia-Ting Fenga,b,*, Sili Chenb, Shaojun Lia
a Institute of Rock and Soil Mechanics, The Chinese Academy of Sciences, Wuhan 430071, People’s Republic of China
b College of Resources and Civil Engineering, Northeastern University, Shenyang 110006, People’s Republic of China
Accepted 9 March 2001
        [b]冯夏庭教授，1964年9月出生于安徽省潜山县。1982-1986年在东北工学院采矿工程专业读本科，获得学士学位。1986-1992年在东北工学院（现东北大学）岩石力学专业读研究生，获博士学位。1998至今受聘于中科院武汉岩土力学研究所工作，研究员、博导，岩土力学与工程国家重点实验室主任。
       冯夏庭教授2009年5月当选国际岩石力学学会主席，现兼任国际岩石力学学会副主席、国际岩石力学学会岩石工程设计方法委员会主席、《International Journal of Rock Mechanics and Mining Sciences》和《Geomechanics and Tunneling》编委、《International Journal of Analytic and Numerical Methods in Geomechanics》顾问编委等职。
      冯夏庭教授先后获得多项学术奖励和荣誉称号，1996年被国务院批准享受政府特殊津贴，1997年获中国科学院“百人计划”入选者，1999年获霍英东教育基金会青年教师基金”资助，2000年获国家教育部 “首届教育部优秀青年教师奖”，2001年获"中国青年科技奖"，2002年被国家科技部聘为973项目首席科学家，并应邀担任法国里尔科技大学一博士论文的第1主审人，2003年获“国家杰出青年科学基金”资助，2004年获“首批新世纪百千万人才工程国家级人选”、“中国科学院十大杰出青年”、“湖北省十大杰出青年”和“湖北省五一劳动奖章”荣誉称号，2006年获“湖北杰出专业技术人才”称号，2008年获“光华工程科技奖青年奖” 称号，2009年获得“湖北省劳动模范”称号。

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离线huangwg08

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Genetic evolution of nonlinear material constitutive models.pdf (357 K) 下载次数:126

图片:截图1304301353.jpg

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离线huangwg08

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Hybrid intelligent method optimization of a soft rock replacement scheme for a large cavern excavated in alternate hard and soft rock strata.pdf (757 K) 下载次数:119

Hybrid intelligent method optimization of a soft rock replacement scheme for a large cavern excavated in alternate hard and soft rock strata
Xia-Ting Feng*, Honggang An
Key Laboratory of Rock and Soil Mechanics, Institute of Rock and Soil Mechanics, the Chinese Academy of Sciences,Wuhan 430071, People’s Republic of China
Accepted 9 January 2004

[b]Abstract:
Optimization of a soft rock replacement scheme for a large cavern excavated in alternating hard and soft rock strata is a complicated non-linear mechanical problem having a large parameter search space. Obtaining a global optimum solution is the key to the problem. A hybrid intelligent method is proposed for this purpose. It is an integration of an evolutionary neural network and finite element analysis using a genetic algorithm. The non-linear relation of the soft rock replacement scheme with the displacement and damage zone of the cavern due to excavation in the given geological conditions is learnt and represented by a forward neural network whose structure and connection weights are global optimally recognized by using the genetic algorithm. The learning samples are obtained from finite element calculations. The optimal soft rock replacement scheme, having the minimal displacement and damage volume induced by cavern excavation, is searched in a global space using the genetic algorithm. The new methodology is used to evaluate soft rock replacement schemes for the Shuibuya cavern in China excavated in strata consisting of alternating soft and hard rocks. The results indicate that the new methodology can recognize the optimal soft rock replacement scheme for a large cavern in such complicated geological conditions and the neural network model can provide a solution which is close to the finite element analysis for the same geological and construction conditions.
2004 Elsevier Ltd. All rights reserved.

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离线huangwg08

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Identification of visco-elastic models for rocks using genetic programming coupled with the modified particle swarm optimization algorithm.pdf (352 K) 下载次数:117

International Journal of Rock Mechanics & Mining Sciences 43 (2006) 789–801
Identification of visco-elastic models for rocks using genetic programming coupled with the modified
particle swarm optimization algorithm
Xia-Ting Fenga,b,_, Bing-Rui Chenb, Chengxiang Yangb, Hui Zhoua, Xiuli Dingc
aInstitute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China
bSchool of Resources and Civil Engineering, Northeastern University, Shenyang 110004, China
cYangtze River Scientific Research Institute, Wuhan 430010, China
Accepted 27 December 2005
Available online 15 February 2006[/align][size=3]Abstract:
The response of rocks to stress can be highly non-linear, so sometimes it is difficult to establish a suitable constitutive model using traditional mechanics methods. It is appropriate, therefore, to consider modeling methods developed in other fields in order to provide adequate models for rock behavior, and this particularly applies to the time-dependent behavior of rock. Accordingly, a new system identification method, based on a hybrid genetic programming with the improved particle swarm optimization (PSO) algorithm, for the simultaneous establishment of a visco-elastic rock material model structure and the related parameters is proposed. The method searches for the optimal model, not among several known models as in previous methods proposed in the literatures, but in the whole model space made up of elastic and viscous elementary components. Genetic programming is used for exploring the model’s structure and the modified PSO is used to identify parameters (coefficients) in the provisional model. The evolution of the provisional models (individuals) is driven by the fitness based on the residual sum of squares of the behavior predicted by the model and the actual behavior of the rock given by a set of mechanical experiments. Using this proposed algorithm, visco-elastic models for the celadon argillaceous rock and fuchsia argillaceous rock in the Goupitan hydroelectric power station, China, are identified. The results show that the algorithm is feasible for rock mechanics use and has a useful ability in finding potential models. The algorithm enables the identification of models and parameters simultaneously and provides a new method for studying the mechanical characteristics of visco-elastic rocks.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Visco-elastic models; Rock; Evolutionary algorithm; Genetic programming; Particle swarm optimization

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离线huangwg08

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[color=#ff0000] Modeling non-linear displacement time series of geo-materials using evolutionary support vector machines.pdf (796 K) 下载次数:119
International Journal of Rock Mechanics & Mining Sciences 41 (2004) 1087–1107
Modeling non-linear displacement time series of geo-materials using evolutionary support vector machines
Xia-Ting Feng*, Hongbo Zhao, Shaojun Li
Institute of Rock and Soil Mechanics, The Chinese Academy of Sciences, Wuhan 430071, People’s Republic of China
Accepted 19 April 2004Available online 17 June 2004
Abstract:
Evaluation of the non-linear deformation behavior of geo-materials is an important aspect of the safety assessment for geotechnical engineering in complex conditions. This paper presents a novel machine learning method, termed support vector machine (SVM), to obtain a global optimization model in conditions of large project dimensions, small sample sizes and nonlinearity.A new idea is put forward to combine the SVM with a genetic algorithm. The method has been used in the analysis of the high rock slope of the permanent shiplock of the Three Gorges Project and the horizontal deformation at depth in the Bachimen landslide in Fujian Province, China. The 92 non-linear SVMs in total were constructed with their kernel functions and the parameters were recognized using a genetic algorithm. The results indicate that the established SVMs can appropriately describe the evolutionary law of deformation of geo-materials at depth and provide predictions for the future 6–10 time steps with acceptable accuracy and confidence.
r 2004 Elsevier Ltd. All rights reserved.
Keywords: Evolutionary support vector machine; Genetic algorithm; Slope; Tunnel; Non-linear time series; Displacement

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离线huangwg08

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Numerical simulations of Class I and Class II uniaxial compression curves using an elasto-plastic cellular automaton and a linear combination of stress and strain as the control method.pdf (243 K) 下载次数:113
International Journal of Rock Mechanics & Mining Sciences 43 (2006) 1109–1117
Numerical simulations of Class I and Class II uniaxial compression curves using an elasto-plastic cellular automaton and a linear combination of stress and strain as the control method
Peng-Zhi Pana, Xia-Ting Fenga, , J.A. Hudsonb
aInstitute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China
bImperial College and Rock Engineering Consultants, 7 The Quadrangle ,Welwyn Garden City, Herts AL8 6SG, UK
Accepted 22 February 2006
Available online 18 April 2006
[size=3]Abstract:
Class I and Class II behavior of the rock failure process under uniaxial compression has been numerically simulated using an elastoplastic cellular automaton (EPCA). A linear combination of stress and strain was used as the feedback signal to control the loading process in the numerical model. Uniaxial compressive simulations of heterogeneous rock failure were made using this control method and by considering different homogeneity indices and different linear combinations of parameters, as well as different yield criteria. The results indicate that Class II behavior can be numerically simulated in a complementary way to the laboratory testing method utilized in a servo-controlled testing machine. Whether the rock behaves in a Class I or Class II manner depends on the homogeneity of the rock sample, the linear combination parameters and the yield criterion selected.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Class II; Complete stress–strain curve; Elasto-plastic; Cellular automaton; Rock failure process

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[align=center] Real-time computerized tomography (CT) experiments on sandstone damage evolution during triaxial compression with chemical corrosion.pdf (643 K) 下载次数:119
International Journal of Rock Mechanics & Mining Sciences 41 (2004) 181–192
Real-time computerized tomography (CT) experiments on sandstone damage evolution during triaxial compression with chemical corrosion
Xia-Ting Fenga,b,*, Sili Chenb,c, Hui Zhoua
aKey Laboratory of Rock and Soil Mechanics, Institute of Rock and Soil Mechanics, the Chinese Academy of Sciences,
Wuhan 430071, People’s Republic of China
b College of Resources and Civil Engineering, Northeastern University, Shenyang 110006, People’s Republic of China
cDepartment of Civil Engineering, Shenyang University of Technology, Shenyang 110023, People’s Republic of China
Accepted 3 April 2003

[size=4]Abstract:
The computerized tomography (CT) images and CT values for the process of compression, micro-cracking, and dilation up to the failure of sandstone specimens under different loading levels have been obtained using the real-time CT technique for triaxial loading of sandstone subjected to chemical corrosion. Clear CT images and CT value of the stages from compression of microcavities-emergence of micro-cracks-bifurcation-development-fracture-collapse-unloading can be observed. The CT value, equivalent to rock density at the CT scan layer, is the most important parameter describing the damage evolution process of rock. The paper also presents results of the corrosive influence of chemical solutions with different pH values and ionic concentrations on the sandstone strength. Stronger acidity (pHo7) or causticity (pH>7) has a stronger effect on the rock micro-fracturing evolution.The mechanism of damage evolution of sandstone is analyzed and a damage model based on the chemical corrosive influence and CT values is proposed.
2003 Elsevier Ltd. All rights reserved.

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[color=#ff0000]
Simulation of the rock microfracturing process under uniaxial compression using an elasto-plastic cellular automaton.pdf (1367 K) 下载次数:148
International Journal of Rock Mechanics & Mining Sciences 43 (2006) 1091–1108
Simulation of the rock microfracturing process under uniaxial compression using an elasto-plastic cellular automaton
Xia-Ting Feng , Peng-Zhi Pan, Hui Zhou
Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, PR China
Accepted 22 February 2006
Available online 18 April 2006
[[/color]Abstract:
In this paper, an elasto-plastic cellular automaton (EPCA) with the associated code was developed to simulate the non-linear fracturing process of rocks under uniaxial compression. It is a useful method for simulating the process of self-organization of the complex system using simple rules. It has the advantages of localization, parallelization, and being able to consider the heterogeneity of rocks. By this means, the fracturing processes, stress–strain curves, acoustic emissions, and compressive strength of 2-D heterogeneous rock specimens under uniaxial compression were numerically investigated using the EPCA code for different cases such as: (1) the influence of the cyclic load; (2) the influence of inhomogeneity; (3) the effect of different softening coefficients; (4) the effect of specimen sizes and height/width ratios; (5) the effect of different spatial distributions of material parameters; (6) the influence of different yield criteria; and (7) the influence of the residual strength coefficient. The results indicate that the numerical simulation reproduced some of the well-known phenomena observed by previous researchers in uniaxial compression tests.
2006 Elsevier Ltd. All rights reserved.
Keywords: Cellular automaton; Fracturing process of rock; Complete stress–strain curve; Cyclic loading; Acoustic emission; Elasto-brittle-plasticity

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Stability assessment of the Three-Gorges Dam foundation China using physical and numerical modeling—Part I- physical model tests.pdf (1519 K) 下载次数:157
International Journal of Rock Mechanics & Mining Sciences 40 (2003) 609–631
Stability assessment of the Three-Gorges Dam foundation, China, using physical and numerical modeling—Part I: physical model tests
Jian Liua,b,*, Xia-Ting Fenga, Xiu-Li Dingb, Jie Zhangb, Deng-Ming Yueb
a Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Xiaohongshan, Wuhan, Hubei 430071, China
b Yangtze River Scientific Research Institute, Wuhan 430019, China
Accepted 31 March 2003
[size[color=#002060]=3]
Abstract:
Foundation stability is one of the most important factors influencing the safety of a concrete dam and has been one of the key technical problems in the design of the Three-Gorges Project. The major difficulties lie in two facts. The first one is that the dam foundation consists of rock blocks, with joints and so-called ‘rock bridges’ and the gently dipping joints play a critical role in the foundation stability against sliding. The second one is that, even in the regions where the gently dipping fractures are most developed, there are no through-going sliding paths in the rock mass due to the existence of the rock bridges; so the dam could slide only if some of the rock bridges fail, so as to create at least one through-going sliding path. To date, due to unavoidable shortcomings in physical and numerical modeling techniques, there is not a single satisfactory method to solve the problem completely. For this reason, the integration of multiple methods was adopted in this study and proved to be an effective and reliable approach. This Part I paper describes work based on the results of geological investigations and mechanical tests, relating to the geological and geomechanical models of the Three-Gorges Dam, and then a systematic study procedure was developed to carry out the stability assessment project. Then, 2D and 3D physical model tests for some critical dam sections were performed. In the physical tests, based on similarity theory, various testing materials were selected to simulate the rock, concrete, fracture and rock bridge. The loading and boundary conditions were also modeled to meet the similarity requirements. The failure mechanism was derived through a progressive overloading that simulated the upstream hydrostatic pressure applied to the dam, and the factor of safety was defined as the ratio between the maximum external load inducing the start of sliding instability of the dam foundation and the upstream hydrostatic load. The experimental results indicated that the stability of the Three-Gorges Dam foundation satisfies the safety requirements. Nevertheless, further discussions demonstrated that because of the incomplete definition of factor of safety adopted in the physical model tests, it is also essential to study the stability of the Three-Gorges Dam foundation using numerical modeling, which will be presented in the companion Part II paper.
2003 Elsevier Ltd. All rights reserved.
Keywords: Dam foundation; Stability assessment; Physical model test; Gently dipping joint; Rock bridge; Three-Gorges Dam

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Estimating mechanical rock mass parameters relating to the Three Gorges Project permanent shiplock using an intelligent displacement back analysis method.pdf (903 K) 下载次数:129
International Journal of Rock Mechanics & Mining Sciences 37 (2000) 1039±1054
Estimating mechanical rock mass parameters relating to the Three Gorges Project permanent shiplock using an intelligent displacement back analysis method
Xia-Ting Fenga,*, Zhiqiang Zhangb, Qian Shengc
a Institute of Rock and Soil Mechanics, The Chinese Academy of Sciences, Wuhan 430071, People's Republic of China
b College of Resources and Civil Engineering, Northeastern University, Shenyang 110006, People's Republic of China
c Yangtze River Science Institute, Wuhan 430070, People's Republic of China
Accepted 19 April 2000

Abstract:
Establishing the mechanical rock mass parameters is one of the important tasks for the highwall stability analysis of the permanent shiplock at the Three Gorges Project in China. Existing back analysis methods are not sucient to provide the necessary accuracy and to recognize non-linear relations. The new displacement back analysis method proposed in this paper is a combination of a neural network, an evolutionary calculation, and numerical analysis techniques. The non-linear relation involving displacement and mechanical parameters is adequately recognized by the neural network techniques. The neural networks learn using an evolutionary technique, with samples created by orthogonal design and tested with new cases given by event design. With the neural network model established, the mechanical parameters are recognized using a genetic algorithm over a large search space in the global range. The predicted displacement occurring for each excavation step from January 1998 to the end of excavation and their cumulative values for 5 later excavation steps are closely characterized by the new analysis technique.
# 2000 Elsevier Science Ltd.All rights reserved.