Stochastic simulation and analysis of geological corrosion defects in dam foundation

Chao Wang , Sherong Zhang , Mao Yu

Transactions of Tianjin University ›› 2016, Vol. 22 ›› Issue (4) : 324 -333.

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Transactions of Tianjin University ›› 2016, Vol. 22 ›› Issue (4) : 324 -333. DOI: 10.1007/s12209-016-2653-7
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Stochastic simulation and analysis of geological corrosion defects in dam foundation

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Abstract

Uncertainty in geological structural modeling, especially geological corrosion(a kind of karst cave), is a bottleneck that restricts the development and application of geological computer modeling and effect estimation. To solve this issue, a stochastic modeling method based on the random field theory is proposed in comparison with the deterministic geometric modeling method. Then the constraint random field modeling method and the random field modeling method without constrained parameters are compared and analyzed. A case study shows that the novel stochastic simulation method is an effective tool to describe the distribution characteristics of corrosion parameters and reflect the updated geological prospecting information. The influence of geological corrosion on the dam behavior can also be better analyzed by using the stochastic simulation method. At the same time, the unconfined random field ignores the sample location information and may lead to higher variability. Therefore, the constraint random field modeling method can provide a useful reference for the numerical analysis under complex geological conditions.

Keywords

hydraulic structure / computer modeling / geological corrosion / stochastic simulation / random field theory

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Chao Wang, Sherong Zhang, Mao Yu. Stochastic simulation and analysis of geological corrosion defects in dam foundation. Transactions of Tianjin University, 2016, 22(4): 324-333 DOI:10.1007/s12209-016-2653-7

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References

[1]

Houlding S. 3D Geoscience Modeling: Computer Techniques for Geological Characterization, 1994

[2]

Mallet J L L. Geomodeling, 2002.

[3]

Zhong D H, Li M C, Song L G, et al. Enhanced NURBS modeling and visualization for large 3D geoengineering applications: An example from the Jinping first-level hydropower engineering project, China[J]. Computers & Geosciences, 2006, 32(9): 1270-1282.

[4]

Zhou J, Tang Y, Yang P, et al. Inference of creep mechanism in underground soil loss of karst conduits?. Conceptual model[J]. Natural Hazards, 2012, 62(3): 1191-1215.

[5]

Tewari P. A study on soil erosion in Pasighat Town (Arunachal Pradesh) India[J]. Natural Hazards, 2004, 32(2): 257-275.

[6]

Yan C, Wang Y, Luo G, et al. Compressive structure's control on the karst development [J]. Geological Review, 2008, 54(3): 343-347.

[7]

Vemu S, Pinnamaneni U B. Estimation of spatial patterns of soil erosion using remote sensing and GIS: A case study of Indravati catchment [J]. Natural Hazards, 2011, 59(3): 1299-1315.

[8]

Fisher T R, Wales R Q. Three Dimensional Solid Modeling of Geo-Objects Using Non-Uniform Rational B-Splines (NURBS), 1992, 85-105.

[9]

Mallet J L. Discrete modeling for natural objects [J]. Mathematical Geology, 1997, 29(2): 199-219.

[10]

de Kemp E A. Visualization of complex geological structures using 3-D Bezier construction tools[J]. Computers & Geosciences, 1999, 25(5): 581-597.

[11]

Wu Q, Xu H. An approach to computer modeling and visualization of geological faults in 3D[J]. Computers & Geosciences, 2003, 29(4): 503-509.

[12]

Zhu L, Zhuang Z. Framework system and research flow of uncertainty in 3D geological structure models [J]. Mining Science and Technology(China), 2010, 20(2): 306-311.

[13]

Zhao H, Ma F, Guo J. Regularity and formation mechanism of large-scale abrupt karst collapse in southern China in the first half of 2010[J]. Natural Hazards, 2012, 60(3): 1037-1054.

[14]

Breunig M. An approach to the integration of spatial data and systems for a 3D geo-information system[J]. Computers & Geosciences, 1999, 25(1): 39-48.

[15]

Shumilov S, Breunig M. Integration of 3D geoscientific visualization tools with help of a geo-database kernel[C]. Proceedings of the Sixth EC-GI & GIS Workshop-The Spatial Information Society-Shaping the Future, 2000, 66-76.

[16]

Wu Q, Xu H, Zou X. An effective method for 3D geological modeling with multi-source data integration [J]. Computers & Geosciences, 2005, 31(1): 35-43.

[17]

de Kemp E A. 3-D visualization of structural field data: Examples from the Archean Caopatina Formation, Abitibi greenstone belt, Québec, Canada[J]. Computers & Geosciences, 2000, 26(5): 509-530.

[18]

Fisher T R, Wales R Q. 3-D solid modeling of sandstone reservoirs using NURBS: A case study of Noonen Ranch Field, Denver Basin, Colorado[J]. Geobyte(USA), 1990, 5(1): 39-41.

[19]

Pinto V, Font X, Salgot M, et al. Using 3-D structures and their virtual representation as a tool for restoring opencast mines and quarries[J]. Engineering Geology, 2002, 63(1/2): 121-129.

[20]

Jones N L, Budge T J, Lemon A M, et al. Generating MODFLOW grids from boundary representation solid models[J]. Ground Water, 2002, 40(2): 194-200.

[21]

Lemon A M, Jones N L. Building solid models from boreholes and user-defined cross-sections[J]. Computers & Geosciences, 2003, 29(5): 547-555.

[22]

Caumon G, Lepage F, Sword C H, et al. Building and editing a sealed geological model[J]. Mathematical Geology, 2004, 36(4): 405-424.

[23]

Wang C X, Bai S W. Study on integration of 3D strata information system and FEM[J]. Chinese Journal of Rock Mechanics and Engineering, 2004, 23(21): 3695-3699.

[24]

Xu N X, Wu X, Wang X G, et al. Approach to automatic hexahedron mesh generation for rock-mass with complex structure based on 3D geological modeling[J]. Chinese Journal of Geotechnical Engineering, 2006, 28(8): 957-961.

[25]

Tacher L, Pomian-Srzednicki I, Parriaux A. Geological uncertainties associated with 3-D subsurface models[J]. Computers & Geosciences, 2006, 32(2): 212-221.

[26]

Bistacchi A, Massironi M D, Piaz G V, et al. 3D fold and fault reconstruction with an uncertainty model: An example from an Alpine tunnel case study[J]. Computers & Geosciences, 2008, 34(4): 351-372.

[27]

Zhu L F, He Z, Pan X, et al. Approach to computer modeling of geological faults in 3D and an application[J]. Journal of China University of Mining and Technology, 2006, 16(4): 461-465.

[28]

Yang Y. The Mechanical Properties of Corrosion Damage and Engineering Applied Research[D], 2009, Chengdu, China: Chengdu University of Technology.

[29]

Zhang J M, Wang S J, Zeng Q B. Mathematic model design for 3D random caverns of karstified rock[J]. Journal of Engineering Geology, 2004, 12(3): 237-242.

[30]

Vanmarcke E. Random Fields: Analysis and Synthesis[M], 2010

[31]

Schuëller G I. State-of-the-art report on computational stochastic mechanics[J]. Probabilistic Engineering Mechanics, 1997, 12(4): 197-321.

[32]

Fu X, Deng Jiangang. Random field modeling for soil properties and random field discretization[J]. Industrial Construction, 2002, 32(1): 32-36.

[33]

Zhang S R, Chao W, Bo S. Stochastic simulation and influence analysis of dissolution dam foundation under Bayes constraint random field[J]. Rock & Soil Mechanics, 2013, 34(8): 2337-2346.

[34]

Engelund S, Rackwitz R. A benchmark study on importance sampling techniques in structural reliability[J]. Structural Safety, 1993, 12(4): 255-276.

[35]

Helton J C, Davis F J. Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems[J]. Reliability Engineering & System Safety, 2003, 81(1): 23-69.

[36]

Iman R L. Latin Hypercube Sampling[M]. John Wiley & Sons, Ltd, 2008.

[37]

Hu X, Tang Chun'an. Research on discretion of the random field of rock and soil mechanical parameters[J]. Chinese Journal of Geotechnical Engineering, 1999, 21(4): 450-455.

[38]

GB 50199—2013. Unified Standard for Reliability Design of Hydraulic Engineering Structures[S]. 2013.

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