A comprehensive review of sinkhole modeling and prediction methods

• Autorzy: Szmigiel Alicja , Tajduś Krzysztof

Identyfikatory

DOI

10.24425/ams.2025.154664

• Języki publikacji: EN

Abstrakty

EN

This article presents a comprehensive overview of the problem of sinkholes in mining and post-mining areas. It analyzes the key causes and mechanisms behind sinkhole formation, taking into account both natural factors and those resulting from human activity. Special attention is given to modeling methods and risk forecasting of sinkhole occurrence, based on a review of current scientific literature and the latest technological advancements, including advanced analytical techniques, numerical modeling and machine learning methods. The aim of this study is to expand both theoretical and practical understanding of sinkhole processes and to support the development of effective risk management strategies in regions affected by intensive mining activities.

Słowa kluczowe

EN

FEM; mining; rock mass; machine learning; sinkholes

PL

górnictwo; masyw skalny; lej krasowy

• Wydawca: Instytut Mechaniki Górotworu PAN
• Czasopismo: Archives of Mining Sciences
• Rocznik: 2025
• Tom: Vol. 70, no. 2
• Strony: 293--312
• Opis fizyczny: Bibliogr. 61 poz., rys., wykr.

Twórcy

autor

Szmigiel Alicja

• Strata Mechanics Research Institute Polish Academy of Sciences, 27 Reymonta Str., 30-059 Kraków, Poland

• https://orcid.org/0000-0001-6770-0421

autor

Tajduś Krzysztof

• AGH University of Krakow, Al. Mickiewicza 30, 30-059 Kraków, Poland

• https://orcid.org/0000-0003-2014-0900

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025)