• Tunnel and Underground Space
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• v.17 no.6
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• pp.438-447
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• 2007

This technical report is to introduce the research on SRM (Synthetic Rock Mass) which was presented in 2007 ISRM Congress at Lisbon by Prof, Fairhurst who speak with emphasis on its importance and potential in rock engineering. The Synthetic Rock Mass approach to jointed rock mass characterization (Pierce et al. 2007) is reviewed relative to existing empirical approaches and current understanding of jointed rock mass behaviour. The review illustrates how the key factors affecting the mechanical behaviour of jointed rock masses may be considered and demonstrates that the SRM approach constitutes a significant step forward in this field. This technique, based on two well-established methods, Bonded Particle Modelling in PFC-3D (Potyondy and Cundall, 2004) and Discrete Fracture Network simulation, employs a new sliding joint model that allows for large rock volumes containing thousands of pre-existing joints to be subjected to any non-trivial stress path. Output from SRM testing includes rock mass brittleness and strength, evolution of the full compliance matrix and primary fragmentation.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.131-143
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• 2022

The lunar exploration autonomous vehicle operates based on the lunar topography information obtained from real-time image characterization. For highly accurate topography characterization, a large number of training images with various background conditions are required. Since the real lunar topography images are difficult to obtain, it should be helpful to be able to generate mimic lunar image data artificially on the basis of the planetary analogs site images and real lunar images available. In this study, we aim to artificially create lunar topography images by using the location information-based style transfer algorithm known as Wavelet Correct Transform (WCT2). We conducted comparative experiments using lunar analog site images and real lunar topography images taken during China's and America's lunar-exploring projects (i.e., Chang'e and Apollo) to assess the efficacy of our suggested approach. The results show that the proposed techniques can create realistic images, which preserve the topography information of the analog site image while still showing the same condition as an image taken on lunar surface. The proposed algorithm also outperforms a conventional algorithm, Deep Photo Style Transfer (DPST) in terms of temporal and visual aspects. For future work, we intend to use the generated styled image data in combination with real image data for training lunar topography objects to be applied for topographic detection and segmentation. It is expected that this approach can significantly improve the performance of detection and segmentation models on real lunar topography images.