About the Journal

Abbreviated key title: J. Intell. Geotech. Eng. Found.
ISSN (online): 3083-3590
Publisher: Open Horizon Global
Publication Access: Open Access

Journal of Intelligent Geotechnical Engineering and Foundations is an international, peer-reviewed scholarly journal devoted to advancing research, innovation, and practice in geotechnical engineering through the integration of intelligent technologies and data-driven methodologies. The Journal provides a multidisciplinary forum for research that combines geotechnical principles with artificial intelligence, machine learning, computational modelling, sensing technologies, automation, digital methods, and advanced numerical techniques. It welcomes theoretical, experimental, computational, and field-based studies that contribute to the understanding, design, monitoring, and management of geotechnical systems and foundations. Particular emphasis is placed on innovative approaches that improve the reliability, efficiency, sustainability, resilience, and predictive capability of geotechnical engineering.

Scope

The Journal covers a broad range of applications, including foundation engineering, soil and rock mechanics, ground improvement, underground construction, tunneling, excavation, slope stability, geohazards, geotechnical earthquake engineering, infrastructure monitoring, and performance assessment. It also encourages research addressing emerging areas such as digital twins, intelligent sensing and monitoring, predictive modelling, autonomous and robotic systems, data-driven site characterization, and AI-assisted geotechnical decision-making. Through the dissemination of rigorous and practically relevant research, the Journal seeks to strengthen connections between fundamental geotechnical science, computational innovation, and engineering practice.

Articles related to the following areas are welcome, though this is not an exhaustive list:

  • Intelligent analysis, modeling, and simulation in geotechnical engineering
  • AI, machine learning, and data-driven methods for geotechnical applications
  • Offshore foundation design, analysis, and monitoring
  • Pile foundations: behavior, design innovation, and construction technologies
  • Excavation engineering and ground stabilization techniques
  • Tunneling engineering: intelligent monitoring, prediction, and control
  • Numerical modeling, finite element methods (FEM), and analytical approaches in soil-structure interaction
  • Risk assessment, optimization, and decision-making in geotechnical projects
  • Smart sensors, real-time monitoring systems, and health diagnostics for underground and foundation structures
  • Applications of digital twin technology in geotechnical engineering
  • Intelligent geotechnical modeling, sustainable ground improvement, subgrade/foundation layers, and geosynthetic-reinforced infrastructure

Target Readership

Journal of Intelligent Geotechnical Engineering and Foundations is intended for researchers, academics, engineers, consultants, practitioners, and professionals working in geotechnical engineering, foundation engineering, soil and rock mechanics, geological engineering, underground construction, and related infrastructure disciplines. It is also relevant to specialists in artificial intelligence, machine learning, computational mechanics, numerical modelling, sensing and monitoring, data science, robotics, and digital engineering whose work addresses geotechnical applications. The Journal may also serve graduate students, research institutions, engineering organizations, infrastructure developers, and policymakers seeking contemporary research and intelligent approaches for the analysis, design, monitoring, and management of geotechnical systems.