scholarly journals Warning Model of the Ionic Rare Earth Mine Slope Based on Creep Deformation Time Series

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Dan Wang ◽  
Yun-zhang Rao ◽  
Min Han ◽  
Liang Shi ◽  
Li Liu ◽  
...  
Keyword(s):  
Rare Earth ◽  
Large Scale ◽  
Warning System ◽  
Deformation Stage ◽  
Initial Stage ◽  
Deformation Velocity ◽  
Safe State ◽  
Mine Slope ◽  
Warning Model ◽  
Rare Earth Mine

This paper takes the actual working conditions of leaching mining, with the Xikeng Rare Earth Mine in Anyuan County as the research object. The slope surface monitoring as a technical means is used to analyze the deformation characteristics, including cumulative displacement, velocity, and acceleration, and the leaching slope and establish an early warning system to assist with leaching production. The study shows that there are three stages in the process of ionic rare earth mine slope deformation, i.e., the initial stage with deformation velocity in 0.15 to 0.30 mm∙h-1, the speed of the uniform deformation stage fluctuating but maintaining at -0.15 to 0.15 mm∙h-1, and the accelerated deformation stage when the velocity and acceleration are 3 to 10 times or more than those of the initial deformation stage. The practice had proved that the monitoring system responded positively when an alarm based on the Local Outlier Factor (LOF) was issued so that the production process was in a safe state and no large-scale landslide disaster occurred. This study will provide theoretical and technical support for the safe and efficient mining of rare earth in situ leaching.

scholarly journals The Level of Public Acceptance to the Development of a Coastal Flooding Early Warning System in Jakarta

2021 ◽  
Vol 13 (2) ◽  
pp. 566
Author(s):  
Nelly Florida Riama ◽  
Riri Fitri Sari ◽  
Henita Rahmayanti ◽  
Widada Sulistya ◽  
Mohamad Husein Nurrahmat
Keyword(s):  
Path Analysis ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Coastal Flooding ◽  
Coastal Areas ◽  
Public Acceptance ◽  
Community Attitudes ◽  
Early Warning Model ◽  
Warning Model

Coastal flooding is a natural disaster that often occurs in coastal areas. Jakarta is an example of a location that is highly vulnerable to coastal flooding. Coastal flooding can result in economic and human life losses. Thus, there is a need for a coastal flooding early warning system in vulnerable locations to reduce the threat to the community and strengthen its resilience to coastal flooding disasters. This study aimed to measure the level of public acceptance toward the development of a coastal flooding early warning system of people who live in a coastal region in Jakarta. This knowledge is essential to ensure that the early warning system can be implemented successfully. A survey was conducted by distributing questionnaires to people in the coastal areas of Jakarta. The questionnaire results were analyzed using cross-tabulation and path analysis based on the variables of knowledge, perceptions, and community attitudes towards the development of a coastal flooding early warning system. The survey result shows that the level of public acceptance is excellent, as proven by the average score of the respondents’ attitude by 4.15 in agreeing with the establishment of an early warning system to manage coastal flooding. Thus, path analysis shows that knowledge and perception have a weak relationship with community attitudes when responding to the coastal flooding early warning model. The results show that only 23% of the community’s responses toward the coastal flooding early warning model can be explained by the community’s knowledge and perceptions. This research is expected to be useful in implementing a coastal flooding early warning system by considering the level of public acceptance.

The effect of combined ecological remediation (plant microorganism modifier) on rare earth mine wasteland

2020 ◽  
Vol 27 (12) ◽  
pp. 13679-13691
Author(s):  
Qiao Yang ◽  
Zhongqiu Zhao ◽  
Hong Hou ◽  
Zhongke Bai ◽  
Ye Yuan ◽  
...  
Keyword(s):  
Rare Earth ◽  
Ecological Remediation ◽  
Rare Earth Mine

Restoration of rare earth mine areas: organic amendments and phytoremediation

2015 ◽  
Vol 22 (21) ◽  
pp. 17151-17160 ◽  
Author(s):  
Lingyan Zhou ◽  
Zhaolong Li ◽  
Wen Liu ◽  
Shenghong Liu ◽  
Limin Zhang ◽  
...  
Keyword(s):  
Rare Earth ◽  
Organic Amendments ◽  
Rare Earth Mine

Optical temperature sensing of rare-earth ion doped phosphors

RSC Advances ◽  
2015 ◽  
Vol 5 (105) ◽  
pp. 86219-86236 ◽  
Author(s):  
Xiangfu Wang ◽  
Qing Liu ◽  
Yanyan Bu ◽  
Chun-Sheng Liu ◽  
Tao Liu ◽  
...  
Keyword(s):  
Rare Earth ◽  
Temperature Measurement ◽  
Large Scale ◽  
Temperature Sensing ◽  
Rare Earth Ions ◽  
Promising Method ◽  
Current Status ◽  
Rare Earth Ion ◽  
Optical Thermometry

Optical temperature sensing is a promising method to achieve the contactless temperature measurement and large-scale imaging. The current status of optical thermometry of rare-earth ions doped phosphors is reviewed in detail.

Early-Warning Model for TECC Based on Gray Neural Network - Taking Laolongtou Scenic Area as an Example

2013 ◽  
Vol 397-400 ◽  
pp. 2435-2438
Author(s):  
Xiu Ping Yang ◽  
Er Chao Li
Keyword(s):  
Neural Network ◽  
Early Warning ◽  
Early Warning System ◽  
Historical Data ◽  
Fuzzy Inference ◽  
Warning System ◽  
Forecasting Model ◽  
Error Signal ◽  
Single Feature ◽  
Warning Model

Based on fuzzy inference and gray neural network, indexes of early-warning system of carrying capacity in scenic spots is established and extract fuzzy rules based on historical data, simulate the early-warning system based on fuzzy inference, gray forecasting model is built for single feature index respectively, add a compensated error based on neural network. The prediction value equals to the output value of grey neural network model plus the compensated error signal. At last, takes Laolongtou scenic area as an example.

Development of early warning system for linear engineering - a case study on highway in Sichuan, China

2020 ◽  
Author(s):  
Ruihua Xiao
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
Highway Safety ◽  
Warning Systems ◽  
Safety Control ◽  
Early Warning Model ◽  
Landslide Early Warning ◽  
Warning Model

<p>For the recent years, highway safety control under extreme natural hazards in China has been facing critical challenges because of the latest extreme climates. Highway is a typical linear project, and neither the traditional single landslide monitoring and early warning model entirely dependent on displacement data, nor the regional meteorological early warning model entirely dependent on rainfall intensity and duration are suitable for it. In order to develop an efficient early warning system for highway safety, the authors have developed an early warning method based on both monitoring data obtained by GNSS and Crack meter, and meteorological data obtained by Radar. This early-warning system is not each of the local landslide early warning systems (Lo-LEWSs) or the territorial landslide early warning systems (Te-LEWSs), but a new system combining both of them. In this system, the minimum warning element is defined as the slope unit which can connect a single slope to the regional ones. By mapping the regional meteorological warning results to each of the slope units, and extending the warning results of the single landslides to the similar slope units, we can realize the organic combination of the two warning methods. It is hopeful to improve the hazard prevention and safety control for highway facilities during critical natural hazards with the progress of this study.</p>

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