Selection of overburden surface mining method in West Virginia by analytical hierarchy process

The broad objective of this research was to improve current surface mining practices and reduce negative environmental impact of overburden removal in West Virginia(WV).The specific objectives were to(i)compare conventional surface mining method(drilling,blasting,digging,and loading)to a surface miner(SM)method,and(ii)apply the analytical hierarchy process(AHP)to help select the optimal mining method based on production,cost and environmental criteria.The design and the procedures used in this research involve five interrelated modules:(i)rock properties of overburden in WV,(ii)drilling and blasting,(iii)digging and loading,(iv)SM method,and(v)comparative analysis and selection of the optimal mining method by AHP.Results of this research indicate that application of SM method would yield higher cost of overburden removal than conventional mining methods in rocks with a high unconfined compressive strength and abrasivity.A significant advantage of SM method,where applicable,is the elimination of the negative environmental impacts associated with blasting.

Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining

The surface subsidence induced by mining is a complex problem, which is related with many complex and uncertain factors. Genetic programming （GP） has a good ability to deal with complex and nonlinear problems, therefore genetic programming approach is propesed to predict mining induced surface subsidence in this article. First genetic programming technique is introduced, second, surface subsidence genetic programming model is set up by selecting its main affective factors and training relating to practical engineering data, and finally, predictions are made by the testing of data, whose results show that the relative error is approximately less than 10%, which can meet the engineering needs, and therefore, this proposed approach is valid and applicable in predicting mining induced surface subsidence. The model offers a novel method to predict surface subsidence in mining.

A new approach to predicting mining induced surface subsidence

There are many parameters influencing mining induced surface subsidence. These parameters usually interact with one another and some of them have the characteristic of fuzziness. Current approaches to predicting the subsidence cannot take into account of such interactions and fuzziness. In order to overcome this disadvantage, many mining induced surface subsidence cases were accumulated, and an artificial neuro fuzzy inference system(ANFIS) was used to set up 4 ANFIS models to predict the rise angle, dip angle, center angle and the maximum subsidence, respectively. The fitting and generalization prediction capabilities of the models were tested. The test results show that the models have very good fitting and generalization prediction capabilities and the approach can be applied to predict the mining induced surface subsidence.

An investigation of surface deformation after fully mechanized,solid back fill mining

The surface deformation after fully mechanized back filling mining was analyzed.The surface deformation for different backfill materials was predicted by an equivalent mining height model and numerical simulations.The results suggest that:(1) As the elastic modulus,E,of the backfill material increases the surface subsidence decreases.The rate of subsidence decrease drops after E is larger than 5 GPa;(2) Fully mechanized back fill mining technology can effectively control surface deformation.The resulting surface deformation is within the specification grade I,which means surface maintenance is not needed.A site survey showed that the equivalent mining height model is capable of predicting and analyzing surface deformation and that the model is conservative enough for engineering safety.Finally,the significance of establishing a complete error correction system based on error analysis and correction is discussed.

Statistical approach to determination of overhaul and maintenance cost of loading equipment in surface mining

The purpose of this research was to develop a new approach in determination of overhaul and maintenance cost of loading equipment in surface mining. Two statistical models including univariate exponential regression (UER) and multivariate linear regression (MLR) were used in this study. Loading equipment parameters such as bucket capacity, machine weight, engine power, boom length, digging depth, and dumping height were considered as variables. The results obtained by models and mean absolute error rate indicate that these models can be applied as the useful tool in determination of overhaul and maintenance cost of loading equipment. The results of this study can be used by the decision-makers for the specific surface mining operations.

Influence of depth-thickness ratio of mining on the stability of a bedding slope with its sliding surface in concave deformation

In order to study the influence of depth-thickness ratio on bedding slope stability, whose sliding surface is flexural concave in shape under mining conditions, this paper aims to study the characteristics ofdeformarion and damage of bedding sliding with depth-thickness ratios of 200：1,150：1,120：1,100：1 and 50：1 by adopting numerical simulation analysis software combined with laboratory-made ＂under the influence of mining variable sliding surface slope similar simulation test bed＂, and to propose identification methods for slope stability under the infuence of mining. The results show that mining activities under the slope reduce slope stability. With a decrease in the mining depth ratio, the influence of mining on the slope increases gradually, and the damage to the slope gradually expands, the stability of the slope grad- ually reduces, fracture occurs on the slope toe and the central fissure gradually develops to the surface, and reaches slide threshold when the depth-thickness ratio is 50：1.

APPLICATION OF HIERARCHY ARTIFICIAL NEURAL NETWORK TO EVALUATE THE EXPLOITATIONCONDITIONS OF SURFACE MINING AREA

It always adopts the direct hierarchy analysis to value the exploitation conditions of surface mining areas. This way has some unavoidable shortcomings because it is mainly under the aid of experts and it is affected by the subjective thinking of the experts. This paper puts forwards a new approach that divides the whole exploitation conditions into sixteen subsidiary systems and each subsidiary system forms a neural network system. The whole decision system of exploitation conditions of surface mining areas is composed of sixteen subsidiary neural network systems. Each neural network is practiced with the data of the worksite, which is reasonable and scientific. This way will be a new decision approach for exploiting the surface mining areas.

GPS and Google Earth based 3D assisted driving system for trucks in surface mines

In order to reduce the number of surface mining accidents related to low visibility conditions and blind spots of trucks and to provide 3D information for truck drivers and real time monitored truck information for the remote dispatcher, a 3D assisted driving system (3D-ADS) based on the GPS, mesh-wireless networks and the Google-Earth engine as the graphic interface and mine-mapping server, was developed at Virginia Tech. The research results indicate that this 3D-ADS system has the potential to increase reliability and reduce uncertainty in open pit mining operations by customizing the local 3D digital mining map, con-structing 3D truck models, tracking vehicles in real time using a 3D interface and indicating available escape routes for driver safety.

Use of SAR interferometry for monitoring illegal mining activities: A case study at Xishimen Iron Ore Mine

The development and application of the ''digital mine'' concept in China depends heavily upon the use of remote sensing data as well as domestic expertise and awareness. Illegal mining of mineral resources has been a serious long term problem frustrating the Xishimen Iron Ore Mine management. This mine is located in Wu'an county in Hebei province, China. Illegal activities have led to enormous economic losses by interfering with the normal operation of the Xishimen mine and have ruined the surrounding environ- ment and the stability of the Mahe riverbed the crosses the mined area. This paper is based on field recon- naissance taken over many years around the mine area. The ground survey data are integrated with Differential Synthetic Aperture Radar Interferometry (D-InSAR) results from ALOS/PALSAR data to pin- point mining locations. By investigating the relationship between the resulting interferometric deforma- tion pattern and the mining schedule, which is known a priori, areas affected by illegal mining activities are identified. To some extent these areas indicate the location of the illegal site. The results clearly dem- onstrate D-InSAR's ability to cost-effectively monitor illegal mining activities.

STUDY ON THE RECLAMATION TECHNIQUE IN A SURFACE MINE WITH CROSS-PIT SYSTEM

A cross-pit system (CPS) could combine the excavation of coal and the reclamation of land together, thus it has been widely used in many countries. Based on a field experiment at Horse Creek mine in Illinois State of the United States, this paper deeply studies the reclamation technique of surface mining by a CPS and comprehensively evaluates its reclamation effect. Problerns and improvements of the reclamation technique are also discussed in this paper.

SURFACE MINE PLANNING OPTIMIZATION BY GOAL PROGRAMMING

This paper introduced an approach to surface mine planning optimization-Goal Programming.The multiobjective[0-1] model has been built and the software has been developed.The method has been applied to a huge surface coal mine,the result of which shows that it is effective and feasible.

Forecasting water disaster for a coal mine under the Xiaolangdi reservoir

Xin’an coal mine, Henan Province, faces the risk of water inrush because 40% of the area of the coal mine is under the surface water of the Xiaolangdi reservoir. To forecast water disaster, an effective aquifuge and a limit of water infiltration were determined by rock-phase analysis and long term observations of surface water and groundwater. By field monitoring, as well as physical and numerical simulation experiments, we obtained data reflecting different heights of a water flow fractured zone (WFFZ) under different mining conditions, derived a formula to calculate this height and built a forecasting model with the aid of GIS. On the basis of these activities, the coal mine area was classified into three sub-areas with different potential of water inrush. In the end, our research results have been applied in and verified by industrial mining experiments at three working faces and we were able to present a successful example of coal mining under a large reservoir.

Designing waste rock barriers by advanced numerical modelling

Design of waste rock barriers forming safety berms for haul trucks requires knowledge of complex interactions which cannot readily be tested by physical means.An advanced numerical model based on non-smooth multi-domain mechanics is presented together with model calibration using limited fullscale experimental data.Waste rock is represented by spherical particles with rolling resistance,and an ultra-class haul truck is represented by a rigid multibody system interconnected with mechanical joints.The model components are first calibrated and then the calibrated model is used for simulating various collision scenarios with different approach conditions and safety berm geometries.Numerical predictions indicate that the width of the berm is most critical for efficiently stopping a runaway truck.The model can also predict if a certain berm geometry is capable of stopping a runaway truck.Results are summarised in a series of diagrams intended for use as design guidelines by practitioners and engineers.

Availability of Residual and/or Applied Inorganic Phosphorus for Sugarcane Uptake and Growth in a Post-Mined Reconstituted Soil

Mineral sands mining is worldwide an environmental issue and also at the Hillendale mine in KwaZulu-Natal, South Africa. The post-mined soil is to be rehabilitated to sugarcane cropping. One of the concerns with the post-mined soil which is reconstituted with a 70:30 mixture of sand: slimes (silt-plus-clay fraction), is its low phosphorus (P) status, which could be limiting for optimum sugarcane production. A field experiment was conducted on a reconstituted soil at Hillendale to establish the availability of either residual or applied inorganic P to the plant and first ratoon sugarcane crop. Four treatments were evaluated including those where P fertilizer was omitted, applied at half the recommended rate or introduced equal to the recommended rate according to chemical analysis of the soil. In the fourth treatment, no fertilizer was applied at all, whereas nitrogen (N) and potassium (K) were added at recommended rates in the first three treatments. Phosphorus application had a significant effect on sugarcane fractional light interception and aboveground biomass yield of the plant and first ratoon crops, and stalk length and diameter of the first ratoon crop. Pol, brix, purity and fibre content and tiller number were not affected by P application. The application of P increased the foliar N, P, K, calcium (Ca), magnesium (Mg) and sulphur (S) contents of both crops. However, foliar N, P and K were deficient in the first ratoon crop even in the case where fertilizer was applied at the recommended rates, which could have been because of waterlogging. The possible effect of waterlogging on P uptake needs to be addressed in future studies in this reconstituted soil.