Gao / Song

Geotechnical Engineering and Intelligent Disaster Prediction

Proceedings of 2024 International Conference on Geotechnics and Hydraulic Structure

Springer

ISBN 978-3-031-85786-7

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Bibliografische Daten

Fachbuch

Buch. Softcover

2025

100 s/w-Abbildungen, 115 Farbabbildungen.

In englischer Sprache

Umfang: xii, 347 S.

Format (B x L): 15,5 x 23,5 cm

Verlag: Springer

ISBN: 978-3-031-85786-7

Produktbeschreibung

This book compiles research findings related to geotechnical engineering and intelligent disaster prediction, providing readers with targeted research experience and case analysis. Geotechnical engineering, which concerns the foundation safety of infrastructure and structures, is a crucial foundational research field within civil engineering. It offers essential base data for intelligent disaster prediction. Geotechnical engineers acquire substantial information about the properties of rocks and soils through geological surveys and soil sample tests. This information is particularly critical for addressing issues related to soil mechanics loads and structural safety in complex environments, directly impacting the normal use and safety of engineering projects. Monitoring and predicting underground structures present relatively complex challenges, but with the development of artificial intelligence, we can achieve more precise predictions and simulations. These advancements help to mitigate the dangers posed by geotechnical engineering geological problems and provide accurate and reasonable solutions. Additionally, intelligent disaster prediction offers scientific bases for decision-making in geotechnical engineering. Traditional geotechnical engineering decisions often rely on experience and limited data, whereas intelligent disaster prediction utilizes comprehensive analysis of historical data and real-time monitoring information to deliver more accurate and timely prediction results. These predictions assist geotechnical engineers in choosing more reasonable and safer engineering plans during the design and construction processes, enabling proactive disaster prevention and mitigation. Furthermore, the applications of intelligent disaster prediction in geotechnical engineering are wide-ranging. For example, in earthquake-prone areas, intelligent disaster prediction systems can monitor tectonic activity in real-time and provide early warning before an earthquake occurs, allowing engineering projects to take timely emergency measures to reduce casualties and property losses. Similarly, in areas prone to landslides, intelligent systems can monitor key parameters such as surface deformations and rainfall amounts, predicting the likelihood of landslides in advance and guiding protective measures in engineering design and construction. This book includes several papers from the 2024 International Conference on Geomechanics and Hydraulic Structures, exploring topics in geotechnical engineering and intelligent disaster prediction. Themes include, but are not limited to, geotechnical slope and soil mechanics analysis, tunnel and underground construction, failure and theory in complex environments, and the monitoring and early warning of geotechnical engineering and geological disasters. We aim to share the latest research findings with geotechnical engineers worldwide and offer more problem-solving approaches to complex engineering case challenges.

Autorinnen und Autoren

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Proposes a series of geotechnical engineering Offers a perspective with AI Summarizes the latest studies by scholars

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