China
Africa
Explore chapters and articles related to this topic
Prediction of the stability and supporting decision in underground engineering based on non-linear rock intelligence system thinking
Published in Heping Xie, Yuehan Wang, Yaodong Jiang, Computer Applications in the Mineral Industries, 2020
Xingping Lai, Yongping Wu, Pingwu Shi, Meifeng Cai
Lately, the field and situation and physical simulation have been indicated that the phenomenon of the day-displacement changing are not very obvious in application prediction of the stability and supporting decision in underground soft-rock roadway. In order to avoid “bottle-neck” question in the artificial intelligence. The basic principle and algorithm of FLAC[6] is similar to that of the distinct element method. Large deformation of continua can be analyzed with the non-linear finite difference model in which the node displacement is continuous. The relative displacement of elements may be obtained by using the software according to the speeds of the nodes and time, and the element strain and stress may be solved. In Figure5 one of phenomenon of the numerical simulation [7] is shown.
FLAC3D
Published in Christine Detournay, Roger Hart, FLAC and Numerical Modeling in Geomechanics, 2020
The topic of this paper is the numerical implementation in FLAC3D of the explicit algorithm for transient unsaturated fluid flow developed for FLAC in 1989 (see Itasca, 1999a). The method of solution is applicable to coarse material and it is assumed that the air phase pressure is constant, the fluid is compressible and that there exists a semi-saturated transition zone between the air phase and saturated fluid phase in which capillary pressure is neglected. The paper outlines the principal features of the method and compares the results of numerical fluid flow simulations with analytic sharp-interface solutions in one, two and three dimensions. The first problem consists of one dimensional fluid injection in a porous medium and compares the propagation of the wetting front with the analytical solution of Voller et al. (1996). The second problem analyses two-dimensional steady state flow through a dam. The length of the seepage face and total discharge through the dam are compared to the exact solutions of Polubarinova-Kochina (1962). The third problem models the three dimensional spreading of a ground water mound in a dry porous medium. The transient shape of the mound is compared to the self-similar solution of Kochina et al (1983).
Knowledge Structures for Encoding, Formatting, and Packaging
Published in Denise Bedford, Knowledge Architectures, 2020
We must also understand format compression because we are concerned about being able to access the knowledge kernel – whether it is a recorded interview, speech or memorandum, or a cultural performance funded by a community organization. Compression is essential to all kinds of formats, but mainly to audio file formats because it is a way to manage file size. Compression choices are typically made by network and technology architects to conserve storage space. Their decisions, though, can impact the knowledge architect’s ability to provide continuous availability to digital assets well into the future. Knowledge architects should understand the three types of compression, including (1) uncompressed audio (WAV, AIFF, AU or raw header-less PCM); (2) lossless compression files (FLAC, WavPack, TTA, ATRAC, ALAC, PGEG-4, MPEG-4ALS, MPEG-4DST, Windows Media Audio Lossless) and (3) lossy compression (i.e., Opus, MP3, Vorbis, Musepack, AAC, ATRAC, Windows Media Audio Lossy). Uncompressed audio is an audio file with no compression applied to it – the sound remains the same as when it was recorded. Lossless formats use compression algorithms that preserve audio data, so the audio is the same as the source. The lossy audio produces a lower-quality sound and has a smaller file size. Lossy compression produces a smaller file size and has a lower quality sound. It is called lossy because this approach to compression is not reversible – it is impossible to rebuild any elements that were stripped away. The encoding standards you choose will impact what is and is not available in the knowledge asset as you transform or map it for use in new applications.
Necessity of applying the concept of the steady state on the numerical analyses of excavation issues: laboratory, field and numerical investigations
Published in Geomechanics and Geoengineering, 2022
Heisam Heidarzadeh, Reza Kamgar
In order to add different constitutive models in the FLAC software and to analyse geotechnical problems with them, a programming language named FISH is embedded in it. Therefore, it is possible to prepare the intended constitutive model based on this programming language (FISH) and apply it in the numerical analyses. The constitutive model should be written as strain control. It means that the incremental strain tensor will be set by the internal codes (internal process) of the FLAC software. Hence, the constitutive model should be written as the stress tensor to be calculated according to the current conditions of the medium (soil) and the incremental strain tensor. In the following, the algorithm of the HMC constitutive model implemented in FLAC by FISH programming is presented step by step.
An overview on advances in computational fracture mechanics of rock
Published in Geosystem Engineering, 2021
Mojtaba Mohammadnejad, Hongyuan Liu, Andrew Chan, Sevda Dehkhoda, Daisuke Fukuda
FDM is a continuum-based method similar to FEM that differs in using a grid of nodes instead of elements for approximating. However, the conventional FDM suffers from the use of regular grid system for the description of material heterogeneity, complex boundary conditions and fractures (Elmo, 2006; Jing & Hudson, 2002). To overcome these shortcomings, the general FDM has been improved particularly thanks to the development of finite volume methods, which make it capable of using irregular quadrilateral, triangular and Voronoi grids (Figure 6) (Nikolic et al., 2016). The commercial FLAC code is the most common FDM tool for stress analysis in geomechanics problems. Konietzky, Heftenberger, and Feige (2009) developed and implemented an algorithm based on LEFM approach in FLAC 2D code. According to the algorithm, each element comprises a microcrack with a random length that propagates when the critical value is satisfied by the stress intensity factors. Based on this method, two new crack propagation schemes were proposed by Li and Konietzky (2015). Venticinque and Nemcik (2014) developed a new constitutive model based on FDM to simulate dynamic fracturing in coal. Li and Konietzky (2015) studied time-rock utilising the FDM. Li, Zhou, Zhu, Li, and Liu (2015) investigated three-dimensional crack propagation in brittle rock mass using FLAC 3D.
Evaluation of modified Cam-Clay constitutive model in FLAC and its development by FISH programming
Published in European Journal of Environmental and Civil Engineering, 2021
Jeon and Yang (2004) using FLAC has developed a back analysis algorithm to determine the main parameters for tunnel design. Kamash and Han (2014) has employed the Modified Cam-Clay into FLAC to model an embankment made of soft clay. A numerical model of the stabilised slope with piles has been constructed in FLAC using the Mohr–Coulomb constitutive model by He, Hazarika, Yasufuku, and Han (2015). A number of numerical analyses have been carried out by using the finite difference code FLAC with different constitutive models for the clayey soil layers (Delia, Miliziano, Soccodato, & Tamagnini, 1999). Cai (2008) investigated tunnels excavation methods by the means of FLAC.