Analytical, Numerical and Big-Data-Based Methods in Deep Rock Mechanics

ISBN 10: 303655761X / ISBN 13: 9783036557618

Published by MDPI AG, 2023

About this Item

Analytical, Numerical and Big-Data-Based Methods in Deep Rock Mechanics | Buch | Gebunden | Englisch | 2023 | MDPI AG | EAN 9783036557618 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 126508463

Bibliographic Details

• Title: Analytical, Numerical and Big-Data-Based Methods in Deep Rock Mechanics
• Publisher: MDPI AG
• Publication Date: 2023
• Language: English
• ISBN 10: 303655761X
• ISBN 13: 9783036557618
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 32D millimeters 250 millimeters width by 175 millimeters height by 32 millimeters depth
• Weight: 1279 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

With the increasing requirements for energy, resources, and space, numerous rock engineering projects (e.g., mining, tunnelling, underground storage, and geothermal and petroleum engineering) are more often being constructed and operated in large-scale, deep underground, and complex geology environments. Meanwhile, more and more unconventional rock failures and rock instabilities (e.g., rockbursts, large-scale collapses, and mine earthquakes) are occurring and severely threatening the safety of underground operations. It is well-recognized that rocks have multiscale structures from minerals, particles, fractures, fissures, joints, and stratification to faults and involve multiscale fracture processes. In the deep earth, rocks are commonly subjected to complex high-stress and strong-dynamic disturbances simultaneously. In addition, there are many multiphysics coupling processes, such as the coupled thermo-hydromechanical interaction in fractured porous rocks. It is still difficult to understand rock mechanics and to characterize rock behaviors with complex stress conditions, multiphysics processes, and multiscale changes. The primary aim of this Special Issue is to bring together original research discussing innovative efforts on analytical, numerical, and big-data-based methods in rock mechanics. It includes 25 manuscripts that illustrate the richness and challenging nature of deep rock mechanics.