Modeling of time dependent subsidence for coal and ore deposits

Coal and ore underground mining generates subsidence and deformation of the land surface. Those defor- mations may cause damage to buildings and infrastructures. The environmental impact of subsidence will not be accepted in the future by the society in many countries. Especially acceptance of the ground deformations decreases every year there, where the mining regions are densely urbanized, the The only solution is to limit the subsidence or its impact on the infrastructure. The first is not rentable for the mining industry, the second depends on the precise subsidence prediction and good preventing management involved in the mining areas. The precision of the subsidence prediction depends strictly on the mathematical model of the deformation phenomenon and on the uncertainty of the input data. The subsidence prediction in the geological conditions of the raw materials used to be made on the basis of numerical modeling or the stochastic models. A modified solution of the stochastic model by Knothe will be presented in the paper. The author focuses on the precise description of the deposit shape and on the time dependent displacements of the rock mass. A two parameters＇ time function has been introduced in the algorithm.

Ground movements modeling applying adjusted influence function

Mathematical modeling of surface deformations caused by underground mining operation is commonly carried out with use of empirical,numerical or stochastic models.One of the most frequently applied model for prediction of ground deformation in many countries is Knothe model.The model developed by Knothe belongs to the stochastic methods and is based on the influence function.In China a prediction method named Probability Integration Method(PIF)was established by Liu Baochen and Liao Guohua based on the stochastic medium theory.Modified version of that model allows to predict ground movements caused by mining operation in extremely complex technical and geological conditions.That model is commonly applied for coal,metal ore and salt deposits.The article presents several modifications of the mathematical model used in China and Poland.This model is very widespread in the world,therefore the generalizations proposed in the article can be implemented for the purposes of prediction surface deformations for various types of deposits in many countries.The presented generalizations were then tested on specific examples of coal mining,copper ore mining and rock salt deposit.The obtained results indicate high efficiency of methods based on the influence function in complex geological and mining conditions.

A novel fuzzy approach to gas pipeline risk assessment under infuence of ground movement

The gas transport infrastructure is frequently localized in areas subjected to anthropogenic movements and strains.The potential impact of the ground movements on the gas pipeline in the aspect of its damage can be properly assessed e.g.by predicting strains,taking into account the causes of terrain movement.On the other hand,the hazard is also related to technological factors like design of the pipeline.The presented method is based on artifcial intelligence methods allowing for evaluation of probability of failure risk in gas supply pipeline sections.The Mamdani fuzzy inference was used in this study.Uncertainty of variables characterizing the resistance of the gas pipeline and predicted continuous deformations of ground surface were accounted for in the model by using triangular-shaped membership functions.Based on the surface deformations and gas pipeline resistance and the inference model one can make prediction when the gas pipeline is hazarded.There were estimated two the most hazarded parts for two pipelines.We proved that the proposed model can contribute to the protection,costoptimization of the designed pipelines and to the repairs of the existing gas pipelines.