Simulation And Measurement Of Space And Time Varying Pollutant Concentrations From A Diesel Powered Vehicle In A Dead-Ended Drift

The cases of no auxiliary ventilation and ventilation with tubing were mathematically modeled, using a turbulent dispersion model. The scooptram that is used to load is modeled as a variable-speed, variable-strength source of pollutants moving in and out of the dead-ended drift. Model predictions are compared to experimental measurements. A parametric analysis was performed to determine the effect of exhaust pipe location and time spent out of the drift, as well as to determine if a relationship existed between CO2 and NO levels. It was concluded from this analysis that when modeling a load-haul-dump cycle, it is necessary to use a model that has the capability of predicting changes in source strength as well as source location. It was also determined that four relevant factors include effective heading height, apparent longitudinal diffusion coefficient, transverse concentration gradient at the face, and average dispersion width of the exhaust jet. As these factors change with heading geometry and ventilation configuration, they were determined experimentally, Carbon dioxide was used as a tracer to calibrate the model; since, knowing the fuel flow rate, it is possible to calculate CO2 production. The above four factors in the computer model were calculated using a regression analysis, comparing predicted local concentrations to measured local concentrations. The model was then verified after this calibration process using additional experimental results. With the calibrated model, it is possible to predict pollutant concentrations at any location in the heading using an engine map and the previously calculated flow field. A parametric analysis shows that the exhaust pipe location can have a significant impact on operator exposure to exhaust gases. It was also shown that NO concentration varies directly with C02 levels. Predictions using the dynamic model are contrasted with constant source strength (pollutant flow rate) results. An analysis of these predictions for computing time-weighted average NO shows the dynamic model predictions of operator exposure to this pollutant to be less than one-half of the value predicted using a constant source model.