Showing papers by "Trilok Singh published in 2006"

Prediction and Analysis of Blast Parameters Using Artificial Neural Network

Abstract: In this study an attempt is made to predict the ratio of muck pile profile before and after the blast, fly rock and total explosive used, based on simple field tests as well blast design parameters. Prediction is done by making three different artificial neural network (ANN) models. Comparative statistical analysis is made among these three networks to ensure their performance suitability. Models of ANN were based on Feed Forward Back Propagation network with training functions – Resilient Backpropagation, One Step Secant and Powell-Beale Restarts. Total numbers of datasets chosen were 92 among which 17 were chosen for testing and validation and the rest were used for the training of networks. Statistical analysis is also made for these datasets. Considering performance for all the outputs, the best results are predicted by Powell-Beale Restarts, with an average percentage error of 5.871% for the ratio of muck pile before and after the blast, 5.335% for fly rocks and 5.775% for total explosive used. These...

Prediction of Cadmium Removal Using an Artificial Neural Network and a Neuro-Fuzzy Technique

Abstract: The prediction of adsorption of cadmium by hematite using an adapted neural fuzzy model and a back propagation artificial neural network was compared. Adsorption was found to depend on the Cd concentration, agitation rate, temperature, pH, and the particle size of the hematite. The adaptive neuro-fuzzy inference system proved to be more efficient in predicting Cd adsorption than a single layered feed forward artificial neural network.

Prediction of Safe Charge to Control Ground Vibration in Surface Mining

Abstract: Many researchers have proposed various predictor equations to determine the PPV (Peak particle velocity) which is the function of distance and maximum safe charge per delay. When the maximum safe charge per delay is calculated by different predictors its values vary because these predictors are formulated on different bases with limited observations. In this paper, an equation has been proposed for estimation of the maximum safe charge per delay and its performance has been compared with other predictors. The proposed predictor is the function of PPV and distance. Results were well correlated and near to the observed value. The maximum charge per delay has been calculated by all predictors and compared with the proposed one. The coefficient of correlation was found to be high for the proposed predictor. This may be give better prediction of safe charge as compared to other predictors for different rock litho units.

Effect of acidic water on physio-mechanical properties of building stone- a case study

Abstract: The physico-mechanical properties of rocks play an important role in planning and designing of civil constructional works. These properties are adversely affected by acidic and alkaline environments, where they are exposed for a longer time. The natural forces and agents of weathering have a degrading effect on the appearance and structural soundness of Kota Stone. These agents include rain, temperature, wind and atmospheric pollutants. Weathering agents almost never work individually or in isolation, they always act in combination with one another or with other agents of deterioration. The durability of building stones is primarily judged by its reactivity with acidic and basic water of different pH values. The conditions are very obvious in any of the large-scale constructions that use building stones like Kota Stone. In this paper, an attempt has been made to assess the variation in the physico-mechanical properties of Kota Stone under different moisture conditions. In the present study, NX size cylindrical cores were prepared with the help of a diamond core drilling machine as per the ISRM standard. The prepared samples were dried in an oven for 24 hours at 104 0 C to eliminate the moisture present. They were then submerged in water having different pH values ranging from nearly 0.89 to 12 for 24 hours till fully saturated at room temperature. The study revealed that there is a prominent change in strength properties under acidic and alkaline conditions. The strength reduction is due to the chemical reaction (corrosion) of the solution and Kota Stone. In acidic conditions, this is because higher concentration of hydrogen ions accelerates the rate of corrosion. However, under alkaline conditions that reduction in the strength properties of Kota Stone is also due to the fact that the liquid influences the surface energy of the specimens. As new surfaces are created during loading of the specimen, the fluid, which wets the surface of the rock, invariably decreases the surface energy and hence the strength properties. Rock is considered as a neutral substance so at pH 7, Kota stone shows maximum strength due to the non-reactive nature of the solution.