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Books in Geotechnical engineering engineering geology

Providing insights into soil and rock behavior, slope stability, and foundation engineering, this portfolio supports civil engineers, geologists, and infrastructure planners. Featuring practical case studies, laboratory techniques, and innovative solutions, these resources address challenges related to construction, natural hazards, and environmental remediation, promoting safe, sustainable development in diverse geological settings.

  • Sustainability in Geology and Mining

    Cutting-Edge Methods and Technologies
    • 1st Edition
    • Hoang Nguyen + 6 more
    • English
    Sustainability in Geology and Mining: Cutting-Edge Methods and Technologies offers the latest thinking on sustainable and responsible mining practices, including environmental impact assessments and ethical mining regulations. Chapters explore a comprehensive range of topics, including geological exploration techniques and innovative prospecting technologies such as satellite imaging and artificial intelligence. Applications such as mineral resource assessment and estimation methods, various mining techniques, and mineral processing and extraction processes are covered. Discussions on environmental and social considerations, regulatory frameworks, and future trends and challenges offer diverse perspectives and in-depth insights.Readers will find an impressive collection of expert contributing authors who reflect on the industry's growing commitment to ethical and eco-conscious approaches. Practitioners in geology and mining will find a great deal to explore and further consider in this fascinating look at the opportunities for sustainability in mining.

  • Ground Penetrating Radar

    Theory and Practice
    • 2nd Edition
    • Erica Carrick Utsi
    • English
    Ground Penetrating Radar: Theory and Practice, Second Edition provides well-thought-out, fully updated, and expanded coverage of this NDT, trenchless technique for investigating the subsurface. Written by a recognized field specialist, the volume clearly explains not only how the technology works with introductions to the underlying physics and formation of signal patterning, but also spotlights how it can be successfully applied, including experiential insights into how parameters such as wavelength, attenuation (loss), environment, target size, and depth need proper consideration in any sampling strategy to obtain good survey results.Additional chapters explore a variety of methods for velocity calibration and suggest where they may be useful, review data processing, and address signal loss in challenging soil conditions and potential problem environments with a suite of useful resolution best practices. New to this edition are discussions on specialist GPR applications and state-of-the-art innovations (e.g., data digitization tools; machine learning, deep learning, artificial intelligence to improve detection and reliability in data interpretation; and robotization).

  • Rock Fracture

    Theories, Modeling Methods, and Engineering Applications
    • 1st Edition
    • Shibin Tang + 1 more
    • English
    Rock Fracture: Theories, Modeling Methods, and Engineering Applications provides an in-depth exploration of the fundamental principles and advanced techniques used to understand and predict rock fracture behavior. The book begins with the theoretical framework of fracture mechanics, examining how factors like T-stress influence brittle rock failure under various loading conditions, including compression and tension. It then discusses various modeling approaches for crack propagation, such as fracture mechanics criteria, localized stress models, and their applications to different rock specimens and fault configurations. The text covers hydraulic fracturing theories, including numerical models for fracture initiation and propagation around boreholes, as well as the effects of end friction and jointed rock mass failure. Additionally, it investigates the progressive failure of rock slopes, emphasizing the importance of numerical simulations to anticipate failure modes like toppling and shear failure. This comprehensive treatment underscores the importance of combining theoretical understanding with modeling techniques to optimize engineering practices. Ultimately, this book offers valuable insights for researchers and engineers committed to safer and more efficient rock engineering solutions.

  • Reshaping Geotechnical Engineering with Machine Learning

    Theory, Applications, and Innovations
    • 1st Edition
    • Divesh Ranjan Kumar + 3 more
    • English
    Reshaping Geotechnical Engineering with Machine Learning: Theory, Applications, and Innovations explores the transformative impact of machine learning (ML) on the field of geotechnical engineering. The book begins by examining the broad applications of ML in key areas such as foundation engineering and slope stability, demonstrating how advanced algorithms can enhance predictive accuracy and decision-making. It emphasizes the importance of robust data acquisition and preprocessing techniques, which are critical for the successful implementation of ML models in geotechnical contexts. The text examines the use of machine learning for predicting soil behavior, a complex challenge in geotechnical engineering, and highlights its role in risk assessment and management. It also addresses the integration of ML with finite element modeling to improve the analysis of tunnel and underground stability. The applications of machine learning in understanding geotechnical materials further showcase the versatility of these techniques. Through detailed case studies, the book illustrates practical implementations of machine learning, bridging theory and real-world problem-solving. It also covers experimental investigations, including laboratory and field studies, which provide essential data for model training and validation. Additionally, the book discusses failure diagnosis of rock slopes by combining discontinuity analysis with numerical modeling, underscoring the potential of ML to enhance safety and reliability in geotechnical projects. This comprehensive resource highlights how machine learning is revolutionizing geotechnical engineering, offering innovative tools and methodologies that improve efficiency, accuracy, and safety in the discipline.

  • Harnessing Earth Observation for Coastal Engineering

    • 1st Edition
    • Debashis Mitra + 3 more
    • English
    Harnessing Earth Observation for Coastal Engineering addresses the intersection of cutting-edge geoinformatics technologies and coastal engineering to tackle challenges in coastal processes and natural hazards. By offering robust methodologies and algorithms, the book equips students, researchers, and engineers with practical tools for immediate application. The global, real-world case studies provide insights into diverse decision-making tools and global perspectives on geoinformatics in coastal engineering and examples of the methodology in action. It goes on to promote protection and resilience by integrating geoinformatics seamlessly into coastal engineering practices, advancing knowledge and practice in the field.Users will find a great resource that not only addresses the pressing need for leveraging modern remote sensing and GIS technologies but also provides a blend of research insights and practical applications exploring advanced algorithms and techniques, allowing readers to effectively utilize new sensor data, extract vital information, and implement sustainable solutions in coastal zones worldwide.

  • Mechanical Anisotropy of Tropical Residual Soil

    • 1st Edition
    • Xinyu Liu + 1 more
    • English
    Mechanical Anisotropy of Tropical Residual Soil provides an in-depth exploration of the directional dependence of mechanical properties in tropical residual soils, a critical factor influencing geotechnical behavior and engineering applications in tropical regions. The book begins by outlining the fundamental geotechnical properties unique to tropical residual soils, setting the stage for a focused investigation into their mechanical anisotropy. It presents a comprehensive experimental framework designed to analyze anisotropic behavior, emphasizing both shear strength and stiffness variations with direction. Sections explore the soil’s response to principal stress rotation, highlighting how stress orientation affects soil performance and structural stability.The book further examines the origins of mechanical anisotropy, discussing the microstructural and geological factors that contribute to this phenomenon. Throughout, the book integrates experimental findings with theoretical insights to provide a holistic understanding of anisotropic characteristics. Concluding with a summary and future outlook, the work identifies gaps in current knowledge and suggests directions for further research, aiming to improve predictive models and practical design approaches for tropical residual soils.

  • Introduction and Applications of Machine Learning in Geotechnics

    • 1st Edition
    • Zong Woo Geem + 5 more
    • English
    Introduction and Applications of Machine Learning in Geotechnics offers a comprehensive exploration of machine learning methodologies and their diverse applications in geotechnical engineering. The book begins with a detailed review of machine learning methods tailored for geotechnical applications, setting the foundation for subsequent chapters. Regression models are utilized to predict shear wave velocities while optimization-based approaches are employed to determine the optimal dimensions of reinforced concrete (RC) retaining walls. The book further explores the identification of gravelly soil through optimized machine learning models and predicts stress-strain responses using data from simple shear tests.Additionally, it outlines the forecasting of liquefaction events triggered by seismic activities and estimates the uniaxial compressive strength of soil using machine learning techniques. The prediction of vertical effective stress and specific penetration resistance is examined to enhance soil characterization and geotechnical analyses. The authors' provide valuable insights for geotechnical engineers and researchers seeking to leverage advanced computational tools for enhanced geotechnical assessments and design processes.

  • Environmental and Health Issues in Unconventional Oil and Gas Development

    • 2nd Edition
    • Debra A Kaden + 1 more
    • English
    Environmental and Health Issues in Unconventional Oil and Gas Development, Second Edition presents a non-partisan perspective on directional drilling and hydraulic fracturing, addressing implications for various stakeholders. The book reviews the transformations in UOGD practices, advancement in monitoring technologies, and the new issues identified by both governmental and non-governmental entities. Key topics include the economics of hydraulic fracturing, methane emissions, decarbonization, and responsibly sourced gas, along with climate risk and mitigation. Water quality and waste impacts are examined, followed by discussions on occupational health, public health, and risk communication. The book also covers environmental justice and corporate governance.

  • Advances in Computational Geomechanics

    Advanced Computational Techniques and Methodologies in Geotechnical Engineering
    • 1st Edition
    • Mohamed Shahin + 1 more
    • English
    Advances in Computational Geomechanics: Advanced Computational Techniques and Methodologies in Geotechnical Engineering provides a comprehensive overview of cutting-edge computational methodologies in geotechnical engineering. The first part examines stochastic, probabilistic, and reliability analyses in geotechnical engineering, covering stochastic methods, probabilistic approaches to soil characterization, reliability analysis in geotechnical design, and risk assessment and management in geotechnical projects. The second part delves into artificial intelligence (AI) and machine learning applications in geotechnical engineering, including machine learning algorithms for geotechnical data analysis, AI-based predictive models for soil behavior and properties, AI in geotechnical risk and decision-making, and data-driven approaches for soil classification and site characterization. The third part focuses on numerical modeling and analysis techniques, such as the Finite Element Method (FEM), Finite Difference Method (FDM), Discrete Element Method (DEM), and explores hybrid numerical methods and future directions in computational geomechanics. This book serves as a valuable resource for geotechnical engineers, researchers, and practitioners seeking to leverage advanced computational tools for geomechanical analyses and design.

  • Introduction to Mining Geostatistics

    Intuitive Applications With Excel and R
    • 1st Edition
    • Konstantinos Modis + 1 more
    • English
    Introduction to Mining Geostatistics: Intuitive Applications with Excel and R is a practical and accessible guide to geostatistical techniques in mineral exploration, with a strong focus on reserves estimation. Designed for students, researchers, and industry professionals, this book blends fundamental concepts of theory with hands-on applications, using Excel and R to simplify complex analyses.Key topics include:Essential Statistical Foundations – Master core data analysis techniques for ore reserves estimation.Sampling Strategies & Error Analysis – Minimize uncertainty and improve data reliability.Spatial Analysis & Kriging – Use variograms, covariance functions, and Kriging algorithms to estimate unknown values from borehole data.Multivariate Geostatistics – Model interdependent variables to enhance accuracy and predictive power.Stochastic Simulation – Explore alternative estimation methods for risk assessment and scenario analysis.Reserve Classification & Reporting – Understand global classification systems and key reserve estimation parameters.Filled with real-world case studies and practical examples, this book bridges theory and application, making geostatistics intuitive and approachable. Whether you're optimizing exploration projects, improving resource estimates, or conducting economic risk assessments, this guide equips you with the tools to make informed decisions.

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