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Thermo-mechanical coupling analysis of APSE using submodels and neural networks

Thermo-mechanical coupling analysis of APSE using submodels and neural networks
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摘要 The ,Aspoe Pillar Stability Experiment (APSE) is an in situ experiment for investigating the spalling mechanism under mechanical and thermal loading conditions in a crystalline rock. In this study, the thermo-mechanical behaviors in the APSE were investigated with three models: (1) a Full model with rough meshes for calculating the influence of tunnel excavation; (2) a Submodel with fine meshes for predicting the thermo-mechanical behavior in the pillar during the borehole drilling, heating, and cool- ing phases; and (3) a Thin model for modeling the effect of slot cutting for de-stressing around the pillar. In order to import the stresses calculated from the Full model to the Submodel and to define the complex thermal boundary conditions, artificial neural networks (NNs) were utilized. From this study, it was pos- sible to conclude that the stepwise approach with the application of NNs was useful for predicting the complex response of the pillar under severe thermo-mechanical loading conditions. The ,Aspoe Pillar Stability Experiment (APSE) is an in situ experiment for investigating the spalling mechanism under mechanical and thermal loading conditions in a crystalline rock. In this study, the thermo-mechanical behaviors in the APSE were investigated with three models: (1) a Full model with rough meshes for calculating the influence of tunnel excavation; (2) a Submodel with fine meshes for predicting the thermo-mechanical behavior in the pillar during the borehole drilling, heating, and cool- ing phases; and (3) a Thin model for modeling the effect of slot cutting for de-stressing around the pillar. In order to import the stresses calculated from the Full model to the Submodel and to define the complex thermal boundary conditions, artificial neural networks (NNs) were utilized. From this study, it was pos- sible to conclude that the stepwise approach with the application of NNs was useful for predicting the complex response of the pillar under severe thermo-mechanical loading conditions.
出处 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2013年第1期32-43,共12页 岩石力学与岩土工程学报(英文版)
基金 within the context of the international DECOVALEX Project (DEvelopment of COupled models and their VALidation against EXperiments) supported by Korea Atomic Energy Research Institute (KAERI) as one of the Funding Organizations of the project,through the Nuclear Research and Development Program of KOSEF with a grant funded by MEST supported by Inha University Research Grant (INHA-44095-1) the support by Seoul National University (SNU) Swedish Nuclear Fuel and Waste Management Co. (SKB), Sweden provided by SKB through its sp Pillar Stability Experiment project
关键词 Sspoe Pillar Stability Experiment (APSE)Artificial neural network (NN)SubmodelThermo-mechanical couplingSpalling Sspoe Pillar Stability Experiment (APSE)Artificial neural network (NN)SubmodelThermo-mechanical couplingSpalling
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参考文献7

  • 1Andersson JC, Martin CD. The ,Aspo Pillar Stability Experiment: Part l--Experiment design. International Journal of Rock Mechanics and Mining Sciences 2009;46(5):865-78.
  • 2Andersson JC. Aspo, Pillar Stability Experiment (final report). Stockholm: Swedish Nuclear Fuel and Waste Management Co. (SKB); 2007.
  • 3Christiansson R, Janson T. A test of different stress measurement methods in two orthogonal bore holes in Aspo Hard Rock Laboratory (HRL), Sweden. Interna- tionalJournal of Rock Mechanics and Mining Sciences 2003;40(7/8):1161-72.
  • 4ltasca Consulting Group Inc. FLAC3D user's guide. Minneapolis, USA: Itasca Consul- ting Group lnc; 2009.
  • 5Kwon S, Lee CS, Cho SJ,Jeon SW, Cho WJ. An investigation of the excavation damaged zone at the KAERI underground research tunnel. Tunnelling and Underground Space Technology 2009;24(1 ):1-13.
  • 6LawrenceJ. Introduction to neural networks. Nevada City: California Scientific; 1993.
  • 7Martin CD, Christiansson R. Estimating the potential for spalling around a deep nuclear waste repository in crystalline rock. International Journal of Rock Mechanics and Mining Sciences 2009;46(2):219-28.

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