Back-analysis of rock mass strength parameters using AE monitoring data

• Published in: International journal of rock mechanics and mining sciences (Oxford, England : 1997) Vol. 44; no. 4; pp. 538 - 549
• Main Authors: Cai, M., Morioka, H., Kaiser, P.K., Tasaka, Y., Kurose, H., Minami, M., Maejima, T.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-06-2007; Elsevier Science
• Subjects: Applied sciences; Back analysis; Buildings. Public works; Crack initiation; Exact sciences and technology; Geotechnics; Rock mass strength; Soil investigations. Testing; Soil mechanics. Rocks mechanics; Asia; Japan; AE; Back analysis; Rock mass strength; Crack initiation; Rock mechanics; Pumping station; Rock mass; Excavating; Failure analysis; Underground construction; Acoustic emission; Application; Monitoring; Strength
• ISSN: 1365-1609; 1873-4545
• DOI: 10.1016/j.ijrmms.2006.09.012

Most back-analyses in geotechnical engineering are based on methods that utilize field displacement monitoring data. In the present study, a novel method is developed to back-calculate rock mass strength parameters from AE (acoustic emission) monitoring data in combination with FEM stress analysis. The method is based on the important concept of generalized AE initiation threshold of rock masses, established from comprehensive data analysis of laboratory test and underground monitoring programs using AE and microseismic (MS) techniques. An easy-to-use Wizard is developed in Microsoft Excel™ to assist site engineers to perform the back-analysis. The efficient solver in Excel is utilized to reach the optimization solution of an objective function with constraints. The Wizard allows the user to complete the analysis process in an interactive fashion. One example is given to demonstrate the back-analysis process using AE monitoring data recorded from a cavern site. The rock mass strength parameters identified from this approach compare well with field test data, suggesting that the tool can be used effectively to back-calculate rock mass strength parameters from AE monitoring data.