Parameter identification of rock mass in the time domain

A time domain rock mass parameter identification method considering the Rayleigh damping is proposed in this paper. Starting with a set of initial parameter values, the algorithm solves the finite-element (FE) equations updating the parameters in each iterative step until the result converges to a local optimum. Numerical FE analysis, displacement sensitivity analysis, and the truncated singular value decomposition method are integrated into the solution algorithm for parameter identification. The technique introduced is verified in numerical studies with in-situ experiments of rock mass structures. Our results show that the approach, compared with conventional methods, can reduce ambiguities caused by inadequate data and provide more accurate insights into the subsurface for rock mass quality evaluation.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-10-16
DOI
https://doi.org/10.1038/s41598-024-74850-2
Citations
2
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.54

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Parameter identification of rock mass in the time domain

Rui Huang, Takafumi Seiki, Satoshi Yamaoka, Ömer Aydan et al.
2 citations
Scientific Reports
Rock Mechanics and Modeling
0.54
article

Parameter identification of rock mass in the time domain

Rui Huang, Takafumi Seiki, Satoshi Yamaoka, Ömer Aydan, Qinxi Dong
article en
2 citations

Abstract

A time domain rock mass parameter identification method considering the Rayleigh damping is proposed in this paper. Starting with a set of initial parameter values, the algorithm solves the finite-element (FE) equations updating the parameters in each iterative step until the result converges to a local optimum. Numerical FE analysis, displacement sensitivity analysis, and the truncated singular value decomposition method are integrated into the solution algorithm for parameter identification. The technique introduced is verified in numerical studies with in-situ experiments of rock mass structures. Our results show that the approach, compared with conventional methods, can reduce ambiguities caused by inadequate data and provide more accurate insights into the subsurface for rock mass quality evaluation.

Scientific ReportsVol. 14(1)
Xihua University (CN), Utsunomiya University (JP), Hainan University (CN), University of the Ryukyus (JP)
State Key Laboratory of High Performance Civil Engineering Materials
Climate action
Openalex Percentile: Top 39%
Rock Mechanics and Modeling
0.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.