Geotechnical Modeling and Intelligent Systems
This open access book provides insights into research topics related to geotechnical engineering simulations. With the development of computing power and artificial intelligence, research methods in geotechnical engineering are gradually shifting from field surveys and physical experiments toward si...
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| Materialtyp: | Online |
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| Språk: | engelska |
| Utgiven: |
Springer Nature
2025
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| Ämnen: | |
| Länkar: | ONIX_20251020T130859_9789819669257_32 |
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| _version_ | 1869514745264996352 |
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| collection | Directory of Open Access Books |
| description | This open access book provides insights into research topics related to geotechnical engineering simulations. With the development of computing power and artificial intelligence, research methods in geotechnical engineering are gradually shifting from field surveys and physical experiments toward simulation and prediction. Through simulations, it is possible to infer the impact of engineering structures on soil and rock masses, as well as their response to natural disasters such as earthquakes, landslides, and debris flows, allowing for early planning of mitigation measures. Inside, readers will find cutting-edge studies on microbial soil stabilization, finite element simulations, centrifuge modeling, and machine learning applications. Topics include advanced material characterization, predictive modeling of tunnels and slopes, AI-enhanced monitoring systems, and risk mitigation strategies for deep excavations and mining subsidence. These contributions illustrate how intelligent systems are optimizing both design and safety across a wide range of geotechnical scenarios. This volume is an essential resource for researchers, engineers, and graduate students seeking to leverage intelligent technologies for more efficient, accurate, and resilient geotechnical solutions. With its integration of theory, experimentation, and smart modeling, it offers a forward-looking perspective on the future of infrastructure in a rapidly evolving technological landscape. |
| format | Online |
| id | doab-20.500.12854ir-168433 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1684332025-10-21T05:34:51Z Geotechnical Modeling and Intelligent Systems Zhao, Gao-Feng Open Access Civil Engineering Geotechnical engineering Simulation and algorithms Geotechnical mechanics Computational mechanics Load analysis thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences This open access book provides insights into research topics related to geotechnical engineering simulations. With the development of computing power and artificial intelligence, research methods in geotechnical engineering are gradually shifting from field surveys and physical experiments toward simulation and prediction. Through simulations, it is possible to infer the impact of engineering structures on soil and rock masses, as well as their response to natural disasters such as earthquakes, landslides, and debris flows, allowing for early planning of mitigation measures. Inside, readers will find cutting-edge studies on microbial soil stabilization, finite element simulations, centrifuge modeling, and machine learning applications. Topics include advanced material characterization, predictive modeling of tunnels and slopes, AI-enhanced monitoring systems, and risk mitigation strategies for deep excavations and mining subsidence. These contributions illustrate how intelligent systems are optimizing both design and safety across a wide range of geotechnical scenarios. This volume is an essential resource for researchers, engineers, and graduate students seeking to leverage intelligent technologies for more efficient, accurate, and resilient geotechnical solutions. With its integration of theory, experimentation, and smart modeling, it offers a forward-looking perspective on the future of infrastructure in a rapidly evolving technological landscape. 2025-10-21T05:34:50Z 2025-10-21T05:34:50Z 2025-10-20T11:13:58Z 2026 book ONIX_20251020T130859_9789819669257_32 https://library.oapen.org/handle/20.500.12657/107665 9789819669257 9789819669240 https://directory.doabooks.org/handle/20.500.12854/168433 eng Earth and Environmental Science; Earth and Environmental Science (R0) open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/107665/1/9789819669257.pdf Springer Nature Springer 10.1007/978-981-96-6925-7 10.1007/978-981-96-6925-7 9fa3421d-f917-4153-b9ab-fc337c396b5a 9789819669257 9789819669240 Springer 435 Singapore open access |
| spellingShingle | Open Access Civil Engineering Geotechnical engineering Simulation and algorithms Geotechnical mechanics Computational mechanics Load analysis thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences Geotechnical Modeling and Intelligent Systems |
| title | Geotechnical Modeling and Intelligent Systems |
| title_full | Geotechnical Modeling and Intelligent Systems |
| title_fullStr | Geotechnical Modeling and Intelligent Systems |
| title_full_unstemmed | Geotechnical Modeling and Intelligent Systems |
| title_short | Geotechnical Modeling and Intelligent Systems |
| title_sort | geotechnical modeling and intelligent systems |
| topic | Open Access Civil Engineering Geotechnical engineering Simulation and algorithms Geotechnical mechanics Computational mechanics Load analysis thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences |
| topic_facet | Open Access Civil Engineering Geotechnical engineering Simulation and algorithms Geotechnical mechanics Computational mechanics Load analysis thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences |
| url | ONIX_20251020T130859_9789819669257_32 |