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Subsidence prediction and mine design for underground coal mining in the Collie Basin.Misich, Ian J. January 1997 (has links)
The subsidence characteristics of the Collie Basin sediments have been investigated to provide site specific design criteria for the Wongawilli method of coal extraction. As historical coal extraction (bord and pillar) methods did not generally give rise to large scale subsidence, there were very few details on mining subsidence in the Collie Basin available to base any design methodology on. Consequently, the investigation was conducted on a Green fields basis. Firstly, the mechanisms involved in the development of mining subsidence needed to be investigated and identified. It was then necessary to determine the effects that mining subsidence would have on mine and ground mass (specifically aquitards) structures and surface features. Once these two areas of work were completed, design criteria were formulated to manage the effects of mining subsidence by controlling the critical mechanisms of subsidence development.The results from this study have greatly enhanced the level of understanding of the subsidence mechanisms involved, and allowed for the development of predictive models which can be used for the design of coal extraction by the panel/pillar mining method in the Collie Basin. Mine planning engineers can now use this design information to derive the most cost effective methods for the extraction of coal within the Collie Basin.
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Development Of A Subsidence Model For Cayirhan Coal MineHaciosmanoglu, Esenay Meryem 01 October 2004 (has links) (PDF)
In this study, subsidence analyses were carried out for panels B14, B12, B10, B02, C12, C10, C08 of Ç / ayirhan Lignite Mine using in-situ subsidence measurements.
Using the measurements from stations, installed both parallel and perpendicular to panel-advance direction, subsidence profiles were plotted as a function of time and distance from panel center. Horizontal displacement and strain curves were also plotted and compared with subsidence profiles.
There are various methods used for subsidence prediction. In this study however, a subsidence model was developed based on empirical model obtained from nonlinear regression analysis. During the analyses SPSS (V.10.0) software was used and the unknown parameters associated with subsidence function were determined for the stations above B14 panel. Since it was too complicated to take all the affecting factors into consideration, only the parameters which could be estimated by statistical evaluation were taken into account during analyses.
One significant contribution of this study to subsidence subject was the comparison of the subsidence values measured during this investigation with the values predicted by some other empirical methods.
In this study, the structural damages to the pylons installed on ground surface above retreating longwall panels were also investigated by the use of previous studies. Slope as well as horizontal strain changes caused by ground movements
due to underground mining were determined.
Last but not least, it should be stated another significant contribution of this study to engineering was the collection of a significant database obtained from field measurements.
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Enhancing Mine Subsidence Prediction and Control Methodologies for Long-Term Landscape StabilityAndrews, Kevin 01 August 2008 (has links)
Prediction and control methodologies for ground deformation due to underground mining (commonly referred to as mine subsidence) provide engineers with the means to minimize negative effects on the surface. Due to the complexity of subsidence-related movements, numerous techniques exist for predicting mine subsidence behavior. This thesis focuses on the development, implementation, and validation of numerous enhanced subsidence prediction methodologies. To facilitate implementation and validation, the improved methodologies have been incorporated into the Surface Deformation Prediction System (SDPS), a computer program based primarily on the influence function method for subsidence prediction. The methodologies include dynamic subsidence prediction, alternative model calibration capability, and enhanced risk-based damage assessment. Also, the influence function method is further validated using measured case study data. In addition to discussion of previous research for each of the enhanced methodologies, a significant amount of background information on subsidence and subsidence-related topics is provided. The results of the research presented in this thesis are expected to benefit the mining industry, as well as initiate ideas for future research. / Master of Science
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Investigation of mining subsidence prediction under tectonic influencesBabaryka, Aleksandra 26 January 2024 (has links)
This dissertation addresses the challenge of predicting human-induced subsidence in tectonic settings. The study focuses on the non-symmetric and shape-defying nature of subsidence troughs in tectonic regions, which deviates from conventional symmetric models. The aim of the dissertation is to improve the accuracy of subsidence prediction by incorporating horizontal stress effects into empirical methods. Through a combination of numerical investigations and empirical modelling, the research reveals stress-induced patterns in subsidence profiles. The developed model, based on various concepts, successfully incorporates asymmetry and shape deviation, resulting in significantly improved prediction accuracy. Application of the model to a real subsidence case in a salt cavern shows a 30% improvement in prediction (based on mean squared error comparison with classical solution). This new solution covers subsidence profile patterns not previously considered by empirical models.:Inhalt
1 Introduction
2 State of the art
2.1 Subsidence prediction methods
2.1.1 Empirical subsidence prediction method overview
2.1.2 Numerical methods for subsidence prediction
2.2 Subsidence monitoring methods
2.2.1 Observation methods
2.2.2 Interplay and evolution of techniques
2.3 Subsidence anomalies
2.4 In-situ-stress field
2.5 Subsidence prediction methods for anomalies
2.6 Conclusions
3 Goals and objectives
4 Foundations
4.1 Empirical subsidence prediction methods
4.1.1 Convergence
4.1.2 Transmission coefficient
4.1.2 Influence factor
4.2 Numerical models for subsidence case
4.2.1 Grid size for subsidence case
4.2.2 Boundary conditions
4.2.3 Constitutive models
4.3 Validation
4.3.1 Observation methods
4.3.2 Parameter estimation
4.3.3 Global parameter estimation
4.3.4 Local parameter estimation
4.3.5 Quality measures for result valuation and validation
5 Methodology
6 Numerical investigation
6.1 Preliminary investigation
6.1.1 Method
6.1.2 Choice of constitutive model
6.1.3 Model and input data
6.1.4 Preliminary investigation results
6.2 Design of the main experiment: non-uniform stress distribution
6.2.1 Constitutive model and input data
6.2.2 Model simplification
6.2.3 Output data
6.3 Contribution of asymmetrical stress distribution
6.3.1 Discussion of the basic distribution form
6.3.2 Discussion of maximum subsidence
6.3.3 Discussion of assymetry
6.3.4 Discussion of influence angle
6.4 Conclusions
7 Adaptation of an empirical model to the discovered features
7.1 Subsidence asymmetry
7.2 Subsidence shape flexibility
7.3 Unifying solution
7.4 Conclusion and outlook
8 Application to a full scale
8.1 General information for a salt cavern storage field
8.2 Estimation of the observed subsidence surface as reference
8.3 Model implementation
8.3.1 Parameter estimation results
8.4 Statistical validation of models
8.5 Conclusions
9 Conclusion
9.1 Limitations
9.2 Outlook
References
Appendix
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