Identification of the governing parameters related to rock indentation depth by using similarity analysis

Autor:	Xiangchun Tan, Yi Huang, Per-Arne Lindqvist, Shaoquan Kou
Rok vydání:	1998
Předmět:	Identification (information) Artificial neural network Similarity (network science) Computer simulation Similarity analysis Computer science Rock mechanics Indentation Forensic engineering Geology Geotechnical Engineering and Engineering Geology Algorithm Similitude
Zdroj:	Engineering Geology. 49:261-269
ISSN:	0013-7952
DOI:	10.1016/s0013-7952(97)00057-4
Popis:	This paper focuses on the indentation depth in rocks caused by a hemispherical indenter. The problem is approached by a combination of similarity methods with an artificial neural network. The similarity methods offer a profound understanding of the physical problem and help to identify the most important governing parameters or factors that reflect the essence of the rock indentation events, thus simplifying the target problem. The artificial neural network provides an advanced computing model, which allows more factors to be involved. The predictions obtained using this combined approach are in better agreement with the experimental results than predictions using other methods.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3a608e22842459d56ef745fdba83bc13 https://doi.org/10.1016/s0013-7952(97)00057-4 Zobrazit plný text záznamu Full Text from ScienceDirect