Hadi Fattahi, Hossein Ghaedi, Danial Jahed Armaghani
{"title":"Increasing accuracy in predicting mode I fracture toughness of rock structures: a comparative analysis of the rock engineering system method","authors":"Hadi Fattahi, Hossein Ghaedi, Danial Jahed Armaghani","doi":"10.1007/s10064-024-03975-5","DOIUrl":null,"url":null,"abstract":"<div><p>The investigation of crack initiation and expansion is vital for the stability of structures. The Mode I fracture toughness (<i>K</i><sub><i>Ic</i></sub>) of rocks is a key property used to predict crack propagation in tension and hydraulic fracturing. Various methods have been introduced to determine <i>K</i><sub><i>Ic</i></sub>, but results differ due to factors like sample dimensions, crack geometry, groove type, and loading conditions. The cracked chevron notched Brazilian disc (CCNBD) sample is commonly used in laboratory tests for its easy preparation. This study employs the rock engineering system (RES) technique to overcome the challenges of time-consuming and costly laboratory tests and the uncertainty in traditional methods (analytical, numerical, experimental, laboratory, regression). Using 88 CCNBD rock samples proposed by ISRM, input parameters include thickness of the disc specimen (<i>B</i>), uniaxial tensile strength (<i>σ</i><sub><i>t</i></sub>), initial crack length (<i>α</i><sub><i>0</i></sub>), radius of the disc specimen (R), crack length (<i>α</i><sub><i>B</i></sub>), and the length of the final crack (<i>α</i><sub><i>1</i></sub>). The RES-based model used 70 data points (80% of the dataset) for development, and 18 data points (20%) for evaluation. Regression analysis compared the performance of the RES method, using statistical indicators such as squared correlation coefficient (R<sup>2</sup>), mean square error (MSE), and root mean square error (RMSE) to measure accuracy. The RES-based method outperformed other regression techniques, demonstrating significantly enhanced accuracy. This highlights the effectiveness and superior performance of the RES method in estimating fracture toughness, particularly for CCNBD samples, showcasing its potential as a robust analytical tool.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"83 12","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10064-024-03975-5.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of Engineering Geology and the Environment","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s10064-024-03975-5","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
The investigation of crack initiation and expansion is vital for the stability of structures. The Mode I fracture toughness (KIc) of rocks is a key property used to predict crack propagation in tension and hydraulic fracturing. Various methods have been introduced to determine KIc, but results differ due to factors like sample dimensions, crack geometry, groove type, and loading conditions. The cracked chevron notched Brazilian disc (CCNBD) sample is commonly used in laboratory tests for its easy preparation. This study employs the rock engineering system (RES) technique to overcome the challenges of time-consuming and costly laboratory tests and the uncertainty in traditional methods (analytical, numerical, experimental, laboratory, regression). Using 88 CCNBD rock samples proposed by ISRM, input parameters include thickness of the disc specimen (B), uniaxial tensile strength (σt), initial crack length (α0), radius of the disc specimen (R), crack length (αB), and the length of the final crack (α1). The RES-based model used 70 data points (80% of the dataset) for development, and 18 data points (20%) for evaluation. Regression analysis compared the performance of the RES method, using statistical indicators such as squared correlation coefficient (R2), mean square error (MSE), and root mean square error (RMSE) to measure accuracy. The RES-based method outperformed other regression techniques, demonstrating significantly enhanced accuracy. This highlights the effectiveness and superior performance of the RES method in estimating fracture toughness, particularly for CCNBD samples, showcasing its potential as a robust analytical tool.
期刊介绍:
Engineering geology is defined in the statutes of the IAEG as the science devoted to the investigation, study and solution of engineering and environmental problems which may arise as the result of the interaction between geology and the works or activities of man, as well as of the prediction of and development of measures for the prevention or remediation of geological hazards. Engineering geology embraces:
• the applications/implications of the geomorphology, structural geology, and hydrogeological conditions of geological formations;
• the characterisation of the mineralogical, physico-geomechanical, chemical and hydraulic properties of all earth materials involved in construction, resource recovery and environmental change;
• the assessment of the mechanical and hydrological behaviour of soil and rock masses;
• the prediction of changes to the above properties with time;
• the determination of the parameters to be considered in the stability analysis of engineering works and earth masses.