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Journal articles on the topic "Strip mining – Computer simulation":
1
Shao, Xiaoping, Xin Li, Long Wang, Zhiyu Fang, Bingchao Zhao, Ershuai Liu, Yeqing Tao, and Lang Liu. "Study on the Pressure-Bearing Law of Backfilling Material Based on Three-Stage Strip Backfilling Mining." Energies 13, no. 1 (January 2, 2020): 211. http://dx.doi.org/10.3390/en13010211.
During strip backfilling mining in coal mines, the backfilling material is the main support structure. Therefore, studying the pressure law of the backfilling material is essential for the safe and efficient mining of coal resources. Based on research into strip backfilling mining at working face number 3216 of the Shanghe Coal Mine, and to smooth transition of overlying strata loads to the backfilling material, this study proposes a three-stage strip backfilling mining method. Based on thin-plate theory, an elastic thin-plate model, a reasonable spacing of strip mining is constructed, and the reasonable mining parameters of “mining 7 m to retain 8 m” at working face number 3216 of the Shanghe Coal Mine are determined. The law of backfilling pressure in three-stage strip backfilling mining is studied through numerical simulation and physical simulation experiments. The results show that field measurement results are basically consistent with the experimental results and numerical simulation results. When three-stage strip backfilling mining is adopted, the stage-one backfilling material is the main bearing body to which the overlying rock load transfers smoothly and gradually, and the structure of the “overburden-coal pillar (or backfilling strip)” in the stope remains stable. In three-stage strip backfilling mining, the overlying rock load is ultimately transferred to the stage-one backfilling material, the stage-two backfilling material is the auxiliary bearing body, and the stage-three backfilling material mainly provides long-term stable lateral support for the stage-one backfilling material.
2
Xie, H. B., Z. Y. Jiang, X. H. Liu, G. D. Wang, and A. K. Tieu. "Prediction of coiling temperature on run-out table of hot strip mill using data mining." Journal of Materials Processing Technology 177, no. 1-3 (July 2006): 121–25. http://dx.doi.org/10.1016/j.jmatprotec.2006.04.089.
Ji, Hong, and Xue Yi Yu. "Research on Numerical Simulation of Mining Subsidence." Applied Mechanics and Materials 148-149 (December 2011): 384–87. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.384.
The strip mining method is proposed to prohibit overlying strata and surface moving. The law of displacement and deformation damage of overlying strata and surface which is a sophisticated process of physical and mechanical dynamics is analyzed in theory. Based on the actual project data, the law is obtained by the numerical simulation with FLAC3D. Moreover, the strip reasonable mining method and interrelated parameters is presented according to the specific geology and mining conditions of coal. It is proved that the strip mining method can avoid geological damage effectively for overlying strata and surface movement in practice.
4
Gao, Bao Bin, Lin Li, and Hui Gui Li. "Experimental Study on Wide Strip Mining with Similar Simulation under Deep-Lying Seams." Applied Mechanics and Materials 295-298 (February 2013): 3318–22. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.3318.
The ground movement laws due to wide strip mining under deep-lying seams has been studied with the experiment of similar material model, and the results of experiment could analysis qualitatively that it is feasible for wide strip mining under deep-lying seams. Taking 25 mining area of Hemei 9th mine as geologic background, the model of wide strip mining under deep seams has been made, which was used to study on the deformation of overburden and the ground movement laws. The results of experiment show that the properties and thickness of strata play a control role on the deformation, and the key strata play a core role; the deformation was dispersed with wide strip mining. When the width of strip mining and protective coal pillar are scientific and reasonable, the purpose of increasing the width of strip mining under the condition of controlling deformation could be achieved, and the entire mining area would be formed a flat subsidence basin. These achievements provide a scientific basis for solving the problem for the ground buildings protection in the conditions of wide strip mining under deep-lying seams, and that also provide some references for further studying on the method of wide strip mining under deep-lying seams.
5
Zhang, Pei Sen, Wei Yan, and Wen Quan Zhang. "Simulation Analysis of Surface Deformation by Strip Replacement Mining in the Short-Distance Thin Coal Seam." Advanced Materials Research 250-253 (May 2011): 193–97. http://dx.doi.org/10.4028/www.scientific.net/amr.250-253.193.
The strip replacement mining in short-distance thin coal seam is one of the effective methods controlling displacement deformation of overlying strata and surface subsidence in coal mining under buildings and railroads and water bodies. The method has a great theoretical significance and application value by increasing recovery rate of coal resources and cutting down the effect of coal mining on environment and surface of mining area. The numerical simulation method is adopted to study the surface deformation characteristics by the strip replacement mining in short-distance thin coal seam. Such conclusions are drawn as follows: the strip project of forty meters mining with forty meters reserving is quite suitably selected while half of mining rate; ten meters in replacement width of coal pillar is relatively optimum; the feasibility of the strip replacement mining technology is verified by the simulation. Therefore, the strip replacement mining technology has provided one kind of new thought to coal mining under buildings and railroads and water bodies.
6
Wei, Xu, and Li Yu Qing. "Numerical Simulation of Safe Strip Mining under Thick Unconsolidated Layers." Applied Mechanics and Materials 182-183 (June 2012): 941–44. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.941.
It is found in the mine rock mass moving observation that the ground movement characteristics of mining under thick unconsolidated layers are significantly different from the thin surface mining, such as surface cracks developing into a ditch-like shape, and large spread range of subsidence[1-2]. According to incomplete statistics, the coal below constructed projects reached up to 137.64 billion tons in China [3], and strip mining as one of the important measures in “green mining technology” system has become an effective technical way [4]. This paper combined double-layer media model theory of mining under thick unconsolidated layers and the specific geological conditions, established numerical model of strip mining under thick unconsolidated layers. By employing finite element simulation software ANSYS10.0, the author of this paper studied the changes of stress and displacement in overburden rocks，learned the general laws of subsidence in surface and overburden rocks when mining under thick unconsolidated layers, and analyzed the influence that the existence of deep clay layer on development of caving fracture zone and water flowing fractured zone. The simulation results are basically consistent with experimental results, and provided theoretical guidance for the safety production practices.
7
Xie, Fei Hong, Zhi Yong Kou, and Yong Mou Zhang. "Prediction and Discuss of Strap Mining Subsidence by Numerical Simulation Analysis and its Engineering Apply." Advanced Materials Research 308-310 (August 2011): 1683–87. http://dx.doi.org/10.4028/www.scientific.net/amr.308-310.1683.
In this paper, In order to reasonably determine the mining width and reserves length of strip mining, reliable simulation subsidence due to strip mining under earth，according to the cavity environment of the engineering measure, the protected object's space position and the mining rock strata's circumstance, and the relevant mining subsidence mechanic, calculation model are chosen in order to predicting the designing mining area transform and data sorting after mining. Its function and perform is put into practice for all various aspects of subsidence calculation in visual analysis system of own developed software package. It is applicable to all mining geological conditions and mining methods. Based on the condition of strip and pillar practice of Matigou colliery of Huating Mining Group, It is also applicable to this calculation system to guide successfully mining under river and architectural complex, the accurate estimate forecast had been attained.
8
Chen, Jun Tao, Kai Kai Sheng, Li Min Yin, and Chuan Qiang Wu. "Study on Surface Movement and Deformation Characteristics and Pillar Stability of Large Strip Mining under Deep Mining." Advanced Materials Research 734-737 (August 2013): 531–34. http://dx.doi.org/10.4028/www.scientific.net/amr.734-737.531.
Large strip mining technology could effectively control the surface subsidence inducing from overlying strata movement and realize green mining. Bored stress and deformation sensors were laid in 4301 working face pillar of Shandong energy zibo mining group tangkou coal, analyzing the strip pillar stress pre and post working face; numerical simulation was used to study the influence of overlying strata from reserved size of strip pillar. According to the observation results of surface movement and deformation, law of surface movement and deformation characteristics was studied, which contributed to the practical application of large strip mining technology under deep mining and had the important theoretical and practical significance for mining under buildings ,railways and water in Chinese.
9
Schwartz, David G., and Zac Sadan. "Strip-Mining the Web with SAIM." International Journal of Business Data Communications and Networking 2, no. 2 (April 2006): 1–20. http://dx.doi.org/10.4018/jbdcn.2006040101.
Feng, Rui Min, Jin Long Zhang, Hui Fu, and Lei Pei. "Research on the Design for Strip-Partial Mining Method under Villages at Xiaotun Colliery." Advanced Materials Research 361-363 (October 2011): 217–21. http://dx.doi.org/10.4028/www.scientific.net/amr.361-363.217.
Basing on the geological mining condition under villages at Xiaotun Mine, according to the existing theories of the strip-partial mining, using the method of analyzing the field measurements date and calculating by empirical formula, the safe range of mining and retained widths can be confirmed, the mining schemes for different widths of coal pillar can be designed, and the optimum scheme can be worked out; and then the coal pillar stability of each mining scheme will be calculated through numerical simulation analysis, providing the basis for appropriately selecting the optimum scheme; on this basis, through simulation prediction of the surface movement and deformation, the surface movement and deformation laws of strip-partial mining is revealed to guide production of Xiaotun colliery.
Dissertations / Theses on the topic "Strip mining – Computer simulation":
1
Chakraborty, Amal. "An integrated computer simulator for surface mine planning and design." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/90920.
In the increasingly competitive coal market, it is becoming more important for coal operators to develop mathematical models for surface mining which can estimate mining costs before the actual mining begins. The problem becomes even more acute with the new reclamation laws, as they affect surface coal mining methods, productivity, and costs.
This study presents a computer simulator for a mountaintop removal type of surface mining operation. It will permit users to compare the costs associated with different overburden handling and reclamation plans. It may be used to minimize productivity losses, and, perhaps, to increase productivity and consequently to reduce operating costs through design and implementation of modified mountain top removal methods. M.S.
2
Deering, P. R. "Computer simulation of the mine environment." Thesis, University of Nottingham, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.371276.
Data mining is the process of extracting patterns from huge data. One of the branches
in data mining is mining sequence data and here the data can be viewed as a
sequence of events and each event has an associated time of occurrence. Sequence
data is modelled using episodes and events are included in episodes.
The aim of this thesis work is analysing architecture simulation output data by
applying episode mining techniques, showing the previously known relationships
between the events in architecture and providing an environment to predict the
performance of a program in an architecture before executing the codes. One of the
most important points here is the application area of episode mining techniques.
Architecture simulation data is a new domain to apply these techniques and by using
the results of these techniques making predictions about the performance of
programs in an architecture before execution can be considered as a new approach.
For this purpose, by implementing three episode mining techniques which are
WINEPI approach, non-overlapping occurrence based approach and MINEPI
approach a data mining tool has been developed. This tool has three main
components. These are data pre-processor, episode miner and output analyser.
4
Tuck, M. A. "Computer simulation of climate on a longwall coal face." Thesis, University of Nottingham, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.373791.
Healthcare social media is emerging in recent years with increasing attention on people’s health. Online review websites are not only diversi.ed with medicine, hospitals, or doctors but abundant in amount. To discover knowledge from these online reviews, several computational models are proposed. Online healthcare review websites are facing challenges in con.ict of interests among various healthcare stakeholders. To avoid legal complaints and better sustain under such circumstance, we propose a decoupling approach for designing healthcare review websites. Objective components such as medical condition and treatment are remained as the primary parts, as they are generic, impersonal and directly related to patients themselves. Subjective components, however, such as comments to doctors or hospitals are decoupled as secondary parts for sensitive and controversial information and are optional to reviewers. Our proposed approach shows better .exibility in managing of contents in different levels of details and ability of balancing the right of expression of reviewers with other stakeholders. To identity the patient-reported adverse reactions in drug reviews, we propose a consumer-oriented coding scheme using wordnet synonym and derivational related form. Signi.cant discrepancy of incidences of adverse reactions is discovered between online reviews and clinical trials. We proposed an adverse reaction report ratio model for integrated interpretation of adverse reactions reported in online reviews versus those from clinical trial. Our estimation on average adverse reactions shows high correlation with drug acceptability score obtained from a large-scale meta-analysis. To investigate the impact of key adverse reactions in patients’ perspective, we propose a topic model named Fisher’s Linear Discriminant Analysis Projected Nonnegative Matrix Factorization (FLDA-projected-NMF) for discovering discriminative features and topics with additional class information. With satisfaction scores provided in the reviews, discriminative features and topics on satisfaction are discovered and polarities of adverse reactions are estimated based on the discriminative feature weights. Discriminative features and topics on medication duration and on age group are obtained as well. Our method outperforms other supervised methods in evaluation of topic sentiment score and topic interpretation measured by entropy. Patient-reported adverse reaction terms are mined from reviews with comment class label. Some new adverse reactions in depression drug and statin drug are also discovered. To further study patients’ behaviors, we use structural equation modeling for studying the relationship of factors in patients’ treatment experience with patients’ quality of life. In covariance model, most adverse reactions are found of small covariance except nausea, headache and dizziness. In measurement model, coef.cients of individual adverse reactions on latent adverse reaction are correlated to the incidence of adverse reactions. In structural model, we model the relationship of latent adverse reaction, rating score, positive sentiment and negative sentiment. Comparison between the measurement models of rating scores of depression drug and statin drug shows that there could be latent factors to account for the variances of latent rating, which shows correlations with the severity of adverse reactions.
6
Park, Hee Bong. "Non-steady state computer simulation of the climate in advanced headings." Thesis, University of Leeds, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.293753.
Artica, I., G. Quispe, and C. Raymundo-Ibañeez. "Ventilation System Simulation Model at a Mine." IOP Publishing Ltd, 2019. http://hdl.handle.net/10757/656302.
This research project modeled and simulated a ventilation system at a Mining Concession, obtaining real-time information regarding the fans used to ventilate the mine. The simulation was developed using the VENTSIM 5 software, which also helped define the number of fans and the operating parameters required, field information, mine dimensions, the mining method, production, geothermal gradient, gas emission, air stream, and air pressure. In addition, the results from software operation revealed the need to open chimneys and use fans. Furthermore, the results also suggest that a specialist dedicated to ventilation and fan maintenance must be hired to formalize mining operations as per the Occupational Safety and Health Mining Regulations from Executive Action No. 024-2016-EM as this Mining Concession is currently operating without license.
8
Jiang, Ming. "A feature-based approach to visualizing and mining simulation data." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1119020006.
Thesis (Ph. D.)--Ohio State University, 2005. Title from first page of PDF file. Document formatted into pages; contains xvi, p. 116; also includes graphics. Includes bibliographical references (p. 108-116). Available online via OhioLINK's ETD Center
9
Grenoble, B. Alex. "Microcomputer simulation of near seam interaction." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/90929.
The mining of coal within 110 feet below a previously mined seam creates interaction effects which can be detrimental to work in the lower seam. These interaction effects are characterized by zones of very high stress and result in floor and roof instability and pillar crushing.
Recent developments in the field of ground control make it possible to determine with a certain degree of confidence the location of these zones and estimate the degree to which the interaction will affect the lower seam. This information has been incorporated into a software package for microcomputers which will predict lower seam problems and suggest design criteria for minimizing the difficulties which will be encountered. M.S.
10
Chau, Kam Shing Patrick. "A finite element model for stress analysis of underground openings /." Thesis, McGill University, 1988. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=63962.
Books on the topic "Strip mining – Computer simulation":
1
Schwartz, F. W. Computer analysis of the factors influencing groundwater flow and mass transport in a system disturbed by strip mining. Edmonton, Alta: SIMCO Groundwater Research Ltd, 1988.
Forcier, Steve. Computer simulation of underground mining processes using AutoMod II. Sudbury, Ont: Laurentian University, School of Engineering, 1996.
Ambrose, Dean H. Three-dimensional graphics simulator for testing mine machine computer-controlled algorithms: Phase 1, development. Washington, D.C: U.S. Dept. of the Interior, Bureau of Mines, 1992.
Ambrose, Dean H. Three-dimensional graphics simulator for testing mine machine computer-controlled algorithms: Phase 1, development. Washington, D.C: U.S. Dept. of the Interior, Bureau of Mines, 1992.
Ambrose, Dean H. Three-dimensional graphics simulator for testing mine machine computer-controlled algorithms: Phase 1, development. Washington, D.C: U.S. Dept. of the Interior, Bureau of Mines, 1992.
Ambrose, Dean H. Three-dimensional graphics simulator for testing mine machine computer-controlled algorithms: Phase 1, development. Washington, D.C: U.S. Dept. of the Interior, Bureau of Mines, 1992.
Colvin, Thomas S. A computer aided mine planning model and energy efficiency ratios of four mining systems. Ann Arbor, Mich: University Microfilms International, 2003.
Book chapters on the topic "Strip mining – Computer simulation":
1
Xie, Wu, Huimin Zhang, and Zengshan Meng. "A Feedback Comprehensive Evaluation Method with Data Mining." In Advanced Research on Computer Education, Simulation and Modeling, 128–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21802-6_21.
Xu, Lei, Sheng Ye, Guilin Lu, and Zhen Zhang. "Modeling and Simulation of the Underground Mining Transportation System." In Advanced Research on Computer Education, Simulation and Modeling, 116–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21802-6_19.
Hong, Ji, and Yu Xueyi. "Research on Computer Simulation of Mining Subsidence Mechanism with FLAC." In Advances in Intelligent and Soft Computing, 249–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27948-5_34.
Tufail, Muhammad, Frans Coenen, Tintin Mu, and Saqib Jamshid Rind. "Mining Movement Patterns from Video Data to Inform Multi-agent Based Simulation." In Lecture Notes in Computer Science, 38–51. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20230-3_4.
Ji, Hong, and Xueyi Yu. "Prediction and Evaluation Methods of Mining Damage Based on Computer Simulation." In Advances in Intelligent and Soft Computing, 589–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28655-1_93.
Flores-Parra, Josue-Miguel, Manuel Castañón-Puga, Carelia Gaxiola-Pacheco, Luis-Enrique Palafox-Maestre, Ricardo Rosales, and Alfredo Tirado-Ramos. "A Fuzzy Inference System and Data Mining Toolkit for Agent-Based Simulation in NetLogo." In Computer Science and Engineering—Theory and Applications, 127–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74060-7_7.
Zhang, Li, Lu Wang, and Jianping Zhang. "A Computer Auditing Model of the Balance Sheet Parallel Simulation Based On Data Mining." In Computational Risk Management, 567–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18387-4_62.
Guo, Yuanyuan, Hong Zhang, Jiangshan Dong, Di Shen, and Jingyuan Yin. "Agent-Based Simulation and Data Mining Analysis for Effect of Purchase Price in Households’ Solar Energy Adoption Process." In Communications in Computer and Information Science, 117–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45286-8_13.
Kang, Zhiqiang, Yanhu Xu, Fuping Li, Yanbo Zhang, and Ruilong Zhou. "Distribution of the Stress of Displacement Field during Residual Slope in Residual Ore Mining Based on the Computer Simulation System." In Communications in Computer and Information Science, 340–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16336-4_45.
Cai, Zhenyu, and Xiaohua Wang. "Research on Vegetation Dynamic Change Simulation Based on Spatial Data Mining of ANN-CA Model Using Time Series of Remote Sensing Images." In Computer and Computing Technologies in Agriculture III, 551–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12220-0_80.
Conference papers on the topic "Strip mining – Computer simulation":
1
Feng, Xianzhang, Yuanpeng Liu, Haodong Luo, Huarui Tang, and Cai Liu. "Numerical Simulation during Expansion for Hot Rolling Sheet Strip." In First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008). IEEE, 2008. http://dx.doi.org/10.1109/wkdd.2008.11.
Hou, Zhen, Hai Gao, and Chen Chen. "Quality Analysis Method for Hot Strip Rolling Based on Data Mining Technology." In 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/iccia-17.2017.91.
Zeng, Peng, Jiangang Yi, and Li Zhao. "Computer Simulation and Analysis of Curl Mechanism for Cold Rolled Steel Strip." In 3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015). Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/ic3me-15.2015.108.
Wu, Haimiao, Zhifeng Pang, Guiying Yao, Yanwei Zhang, and Zhimin Liu. "Research into Edge Drop of Cold Rolled Strip and Its Influencing Factors." In 2010 Second International Conference on Computer Modeling and Simulation (ICCMS). IEEE, 2010. http://dx.doi.org/10.1109/iccms.2010.48.
Yin, Huiyong, Jiuchuan Wei, Jianbin Guo, Lu Zhu, Longqing Shi, Peihe Zhai, and Xuhe Liu. "Application of Strip-Partial Mining to Prevent Water Inrush from Coalbed Floor in Nanding Coal Mine." In 2009 International Conference on Information Engineering and Computer Science. ICIECS 2009. IEEE, 2009. http://dx.doi.org/10.1109/iciecs.2009.5362575.
Yachao, Wang. "Data Mining from Simulation of Six Sigma in Manufacturing Company." In 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.1198.
Liu, Hanwu, Zhiping Zhang, Chao Cao, and Si Liu. "Numerical Simulation of Mining Machine Cutter�s Thermal Spraying Process." In 2013 International Conference on Software Engineering and Computer Science. Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/icsecs-13.2013.41.
Fern, Nicole, and Kwang-Ting Cheng. "Mining mutation testing simulation traces for security and testbench debugging." In 2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). IEEE, 2017. http://dx.doi.org/10.1109/iccad.2017.8203847.
Liu, Yanxi. "Study on Application of Apriori Algorithm in Data Mining." In 2010 Second International Conference on Computer Modeling and Simulation (ICCMS). IEEE, 2010. http://dx.doi.org/10.1109/iccms.2010.398.
Khan, M. Sulaiman, Maybin Muyeba, and Frans Coenen. "A Weighted Utility Framework for Mining Association Rules." In 2008 Second UKSIM European Symposium on Computer Modeling and Simulation (EMS). IEEE, 2008. http://dx.doi.org/10.1109/ems.2008.73.
