Abstract-The seismogenic process is nonlinear and irreversible so that the response to loading is different from unloading. This difference reflects the damage of a loaded material. Based on this insight, a new parameter-load/unload response ratio (LURR) was proposed to measure quantitatively the proximity to rock failure and earthquake more than ten years ago. In the present paper, we review the fundamental concept of LURR, the validation of LURR with experimental and numerical simulation, the retrospective examination of LURR with new cases in different tectonic settings (California, USA, and Kanto region, Japan), the statistics of earthquake prediction in terms of LURR theory and the random distribution of LURR under Poisson's model. Finally we discuss LURR as a parameter to judge the closeness degree to SOC state of the system and the measurement of tidal triggering earthquake.The Load/Unload Response Ratio (LURR) theory was first proposed in 1984 (YIN, 1987). Subsequently, a series of advances were made (YIN and
Abstract-The seismogenic process is nonlinear and irreversible so that the response to loading is different from unloading. This difference reflects the damage of a loaded material. Based on this insight, a new parameter-load/unload response ratio (LURR) was proposed to measure quantitatively the proximity to rock failure and earthquake more than ten years ago. In the present paper, we review the fundamental concept of LURR, the validation of LURR with experimental and numerical simulation, the retrospective examination of LURR with new cases in different tectonic settings (California, USA, and Kanto region, Japan), the statistics of earthquake prediction in terms of LURR theory and the random distribution of LURR under Poisson's model. Finally we discuss LURR as a parameter to judge the closeness degree to SOC state of the system and the measurement of tidal triggering earthquake.The Load/Unload Response Ratio (LURR) theory was first proposed in 1984 (YIN, 1987). Subsequently, a series of advances were made (YIN and
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.