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.

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.

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.

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.