scholarly journals A Case Study of Damage Energy Analysis and an Early Warning by Microseismic Monitoring for Large Area Roof Caving in Shallow Depth Seams

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Like Wei ◽  
Qingxin Qi ◽  
Hongyan Li ◽  
Bin Zhang ◽  
Yongren Wang ◽  
...  
Keyword(s):  
Early Warning ◽  
Damage Mechanics ◽  
Coal Pillar ◽  
Microseismic Monitoring ◽  
Energy Model ◽  
Field Application ◽  
Shallow Depth ◽  
Large Area ◽  
Cumulative Energy ◽  
Damage Level

Shallow depth coal seams are widely spread in Shendong mining area, which is located in the Northwestern region of China. When working face is advanced out of concentrated coal pillar in upper room and pillar goaf, strong strata behaviors often cause support crushing accidents, and potentially induce large area residual pillars instability and even wind blast disaster. In order to predict the precise time when the accident happens, guaranteeing life-safety of miner, microseismic monitoring system was for the first time applied in shallow coal seam. Based on damage mechanics correlation theory, the damage energy model is established to describe relationship between damage level and cumulative energy of microseismic events. According to microseismic monitoring data of two support crushing accidents, the damage energy model is verified and an effective early warning method of these accidents is proposed. The field application showed that the early warning method had avoided miners suffering from all support crushing accidents in Shigetai coal mine.

Elastic–plastic-damage model of nano-indentation of the ion-irradiated 6061 aluminium alloy

2020 ◽  
Vol 29 (8) ◽  
pp. 1271-1305
Author(s):  
A Ustrzycka ◽  
B Skoczeń ◽  
M Nowak ◽  
Ł Kurpaska ◽  
E Wyszkowska ◽  
...  
Keyword(s):  
Damage Evolution ◽  
Damage Mechanics ◽  
Ion Irradiation ◽  
Damage Model ◽  
Indentation Test ◽  
Gtn Model ◽  
Damage Level ◽  
Nano Indentation ◽  
Wide Range ◽  
Radiation Induced

The paper presents experimental and numerical characterization of damage evolution for ion-irradiated materials subjected to plastic deformation during nano-indentation. Ion irradiation technique belongs to the methods where creation of radiation-induced defects is controlled with a high accuracy (including both, concentration and depth distribution control), and allows to obtain materials having a wide range of damage level, usually expressed in terms of displacements per atom (dpa) scale. Ion affected layers are usually thin, typically less than 1 micrometer thick. Such a low thickness requires to use nano-indentation technique to measure the mechanical properties of the irradiated layers. The He or Ar ion penetration depth reaches approximately 150 nm, which is sufficient to perform several loading-partial-unloading cycles at increasing forces. Damage evolution is reflected by the force-displacement diagram, that is backed by the stress–strain relation including damage. In this work the following approach is applied: dpa is obtained from physics (irradiation mechanisms), afterwards, the radiation-induced damage is defined in the framework of continuum damage mechanics to solve the problem of further evolution of damage fields under mechanical loads. The nature of radiation-induced damage is close to porosity because of formation of clusters of vacancies. The new mathematical relation between radiation damage (dpa) and porosity parameter is proposed. Deformation process experienced by the ion irradiated materials during the nano-indentation test is then numerically simulated by using extended Gurson–Tvergaard–Needleman (GTN) model, that accounts for the damage effects. The corresponding numerical results are validated by means of the experimental measurements. It turns out, that the GTN model quite successfully reflects closure of voids, and increase of material density during the nano-indentation.

scholarly journals Development and Optimization of NoSQL Database in Food Insecurity Early Warning System Based on Local Community Participation

2020 ◽  
pp. 161-168
Author(s):  
Yani Nurhadryani ◽  
Wiradani Ramadhan ◽  
Auzi Asfarian
Keyword(s):  
Response Time ◽  
Food Insecurity ◽  
Early Warning ◽  
Early Warning System ◽  
Local Community ◽  
Warning System ◽  
Large Area ◽  
Nosql Database ◽  
Before And After ◽  
Database Service

As a part of the food insecurity early warning system based on local participation, a robust and scalable database service is required. This necessity caused by the large area of services which include 34 provinces, 416 districts, 7,215 sub-districts and 80,534 villages in Indonesia. The abundant number of the expected daily transaction might not be handled properly using the traditional model. In this research, we design, implement, and optimize the NoSQL database to create scalable, dynamic, and flexible database service for the early warning system. The cohesion of the model is then measured, resulting in 5 entities with high cohesion, 16 with moderate cohesion, and 3 with low cohesion. After refactoring, we reduced the number of the low-cohesion entity into one and increased the average cohesion from 0.62 to 0.67. An empirical experiment was conducted to compare the response time before and after the refactoring. As the results, the average response time is decreased from 11.0 ms to 7.99 ms or equal to 1.38 in speedup. The experiment results suggest there is an impact of the logical data model improvement, by increasing their cohesion, to the performance of the NoSQL database.

scholarly journals Controlling the Deformation of a Small Coal Pillar Retaining Roadway by Non-Penetrating Directional Pre-Splitting Blasting with a Deep Hole: A Case Study in Wangzhuang Coal Mine

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3084
Author(s):  
Shixing Cheng ◽  
Zhanguo Ma ◽  
Peng Gong ◽  
Kelong Li ◽  
Ning Li ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Coal Mine ◽  
High Efficiency ◽  
Longwall Mining ◽  
Coal Pillar ◽  
Field Application ◽  
Vertical Stress ◽  
Mine Pressure ◽  
Deep Hole ◽  
Fracture Length

In longwall mining of coal mines, the large deformation of small pillar retaining roadways creates difficulties for the safe and efficient retreating of the mining panel. Based on the engineering background of a small coal pillar retaining roadway in Wangzhuang coal mine, pressure relief technology for non-penetrating directional pre-splitting blasting with a deep hole ahead was proposed. The influence of the non-penetrating fracture length on the pre-splitting effect was studied by numerical simulation. The results showed that the vertical stress in the coal pillar center, the small pillar retaining roadway deformation, and the energy accumulation on the pillar decreased with an increase in the non-penetrating fracture length. The vertical stress at the working face end increased with an increase in the non-penetrating fracture length. The field application and monitoring results indicated that non-penetrating directional pre-splitting blasting could effectively control the deformation of small pillar retaining roadways. The roof-to-floor and rib-to-rib maximum convergences of the 6208 tail entry were reduced by 53.66% and 52.62%, respectively, compared to the results with no blasting. The roadway section met the demands of mining panel high-efficiency retreating, thereby demonstrating the rationality of the technical and numerical simulation results. The research results shed light on the improvement of small coal pillar retaining roadway maintenance theory and technology.

scholarly journals Microseismic monitoring, analysis and early warning of rockburst

2021 ◽  
Vol 12 (1) ◽  
pp. 2956-2983
Author(s):  
Tian-hui Ma ◽  
Chun-an Tang ◽  
Fei Liu ◽  
Shi-chao Zhang ◽  
Zhi-qiang Feng
Keyword(s):  
Early Warning ◽  
Microseismic Monitoring

scholarly journals Inverse modeling of turbidity currents using artificial neural network: verification for field application

2020 ◽  
Author(s):  
Hajime Naruse ◽  
Kento Nakao
Keyword(s):  
Neural Network ◽  
Inverse Modeling ◽  
Field Application ◽  
Inverse Model ◽  
Turbidity Currents ◽  
Random Errors ◽  
Large Area ◽  
Initial Flow ◽  
Hydraulic Conditions ◽  
Input Parameters

Abstract. Although in situ measurements observed on modern frequently occurring turbidity currents have been performed, the flow characteristics of turbidity currents that occur only once every hundreds of years and deposit turbidites over a large area have not yet been elucidated. In this study, we propose a method for estimating the paleo-hydraulic conditions of turbidity currents from ancient turbidites by using machine learning. In this method, we hypothesize that turbidity currents result from suspended sediment clouds that flow down a steep slope in a submarine canyon and into a gently sloping basin plain. Using inverse modeling, we reconstruct seven model input parameters including the initial flow depth, the sediment concentration and the basin slope. Repeated numerical simulation using one-dimensional shallow water equations under various input parameters generates a dataset of the characteristic features of turbidites. This artificial dataset is then used for supervised training of a deep learning neural network (NN) to produce an inverse model capable of estimating paleo-hydraulic conditions from data of the ancient turbidites. Only 3,500 datasets are needed to train this inverse model. The performance of the inverse model is tested using independently generated datasets. Consequently, the NN successfully reconstructs the flow conditions of the test datasets. In addition, the proposed inverse model is quite robust to random errors in the input data. Judging from the results of subsampling tests, inversion of turbidity currents can be conducted if an individual turbidite can be correlated over 10 km at approximately 1 km intervals. These results suggest that the proposed method can sufficiently analyze field-scale turbidity currents.

scholarly journals Research on Low-density Cross-border Support Technology For Large-section Coal Roadway in Shallow-buried Thick Coal Seam

2021 ◽  
Author(s):  
Shiping Yan ◽  
feng guo ◽  
Fei Chen ◽  
Yuxiang Cao ◽  
Zhe He
Keyword(s):  
Large Scale ◽  
Coal Pillar ◽  
Peak Stress ◽  
Field Application ◽  
Efficient Production ◽  
Low Density ◽  
Control Effect ◽  
Thick Coal Seam ◽  
Cross Border ◽  
Coal Roadway

Abstract The slow excavation speed of coal roadways has always been a key factor restricting the safe and efficient production of large-scale coal mines in China, and the problem of unbalanced mining replacement caused by this is widespread. This paper takes the S1231 heading face of the Ningtiaota coal mine of Shaanxi Coal and Chemical Industry Group as the research object, analyzes the characteristics of the stress evolution of coal roadway driving, reveals the principle of low-density cross-border support, and proposes a low-density cross-border support plan. . Using FLAC 3D to study the roadway stress-displacement evolution law of the new support scheme during the driving and mining phases, the results show that the peak stress during the driving is 5.3 Mpa, and the coal pillar side stress concentration is the most obvious during the mining period, with the peak value being 7.9 Mpa. The moving distances of the two banks are both 10 mm, which verifies the feasibility of low-density cross-border support. Field application shows that during roadway excavation, the amount of roof subsidence and the displacement of the two sides are 9 mm and 11 mm, respectively, and the development depth of roof cracks is controlled within 0.5m. The overall control effect is good, and the speed of coal roadway driving is increased by 77.19% compared with the original. The new support builds a thick roof anchor structure to ensure the safety and stability of the roadway. At the same time, by reducing the number of bolts, the bolt support time has been greatly reduced, effectively alleviating the tight situation of mining replacement, and providing solutions for mines under the same conditions.

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