998 resultados para Contaminant transport


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Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

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A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigen values obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigen values from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigen values are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.

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The transport processes of the dissolved chemicals in stratified or layered soils have been studied for several decades. In case of the solute transport through stratified layers, interface condition plays an important role in determining appropriate transport parameters. First‐ type and third‐ type interface conditions are generally used in the literature. A first‐type interface condition will result in a continuous concentration profile across the interface at the expense of solute mass balance. On the other hand, a discontinuity in concentration develops when a third‐ type interface condition is used. To overcome this problem, a combined first‐ and third‐ type condition at the interface has been widely employed which yields second‐ type condition. This results in a similar break‐through curve irrespective of the layering order, which is non‐physical. In this work, an interface condition is proposed which satisfies the mass balance implicitly and brings the distinction between the breakthrough curves for different layering sequence corroborating with the experimental observations. This is in disagreement with the earlier work by H. M. Selim and co‐workers but, well agreement with the hypothetical result by Bosma and van der Zee; and Van der Zee.

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Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

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The movement of chemicals through soil to groundwater is a major cause of degradation of water resources. In many cases, serious human and stock health implications are associated with this form of pollution. The study of the effects of different factors involved in transport phenomena can provide valuable information to find the best remediation approaches. Numerical models are increasingly being used for predicting or analyzing solute transport processes in soils and groundwater. This article presents the development of a stochastic finite element model for the simulation of contaminant transport through soils with the main focus being on the incorporation of the effects of soil heterogeneity in the model. The governing equations of contaminant transport are presented. The mathematical framework and the numerical implementation of the model are described. The comparison of the results obtained from the developed stochastic model with those obtained from a deterministic method and some experimental results shows that the stochastic model is capable of predicting the transport of solutes in unsaturated soil with higher accuracy than deterministic one. The importance of the consideration of the effects of soil heterogeneity on contaminant fate is highlighted through a sensitivity analysis regarding the variance of saturated hydraulic conductivity as an index of soil heterogeneity. © 2011 John Wiley & Sons, Ltd.

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Surface reactive phases of soils and aquifers, comprised of phyllosilicate and metal oxohydroxide minerals along with humic substances, play a critical role in the regulation of contaminant fate and transport. Much of our knowledge concerning contaminant-mineral interactions at the molecular level, however, is derived from extensive experimentation on model mineral systems. Although these investigations have provided a foundation for understanding reactive surface functional groups on individual mineral phases, the information cannot be readily extrapolated to complex mineral assemblages in natural systems. Recent studies have elucidated the role of less abundant mineral and organic substrates as important surface chemical modifiers and have demonstrated complex coupling of reactivity between permanent-charge phyllosilicates and variable-charge Fe-oxohydroxide phases. Surface chemical modifiers were observed to control colloid generation and transport processes in surface and subsurface environments as well as the transport of solutes and ionic tracers. The surface charging mechanisms operative in the complex mineral assemblages cannot be predicted based on bulk mineralogy or by considering surface reactivity of less abundant mineral phases based on results from model systems. The fragile nature of mineral assemblages isolated from natural systems requires novel techniques and experimental approaches for investigating their surface chemistry and reactivity free of artifacts. A complete understanding of the surface chemistry of complex mineral assemblages is prerequisite to accurately assessing environmental and human health risks of contaminants or in designing environmentally sound, cost-effective chemical and biological remediation strategies.

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Flow, recharge and transport dynamics in fractured rock aquifers with low lying rock outcrops is a largely unexplored area of study in hydrogeology. The purpose of this thesis is to examine these topics in an agricultural area in Eastern Ontario. The study consists of a regional scale groundwater quality study, an infiltration experiment that considers bacteria transport from the ground surface to a well, and a numerical modelling study that tests the parameters that affect surface infiltration of a tracer from a rock outcrop to a deeper horizontal fracture. In the water quality study, approximately 65% of the samples contained total coliform, 16% contained E. coli, and 1% contained nitrate-N at greater than 5 mg/L. Occurrence of E. coli increased when considering seasonality, where wells were drilled on rock outcrops, and for shallow well intervals. Nitrate-N did not occur above the Guidelines for Canadian Drinking Water Quality (Health Canada, 2012) of 10 mg/L. Rapid arrival times were observed in the infiltration study for both the microspheres (30 minutes) and a dye tracer (45 minutes) in a well approximately 6.0 m in horizontal and 2.8 m in vertical distance from the tracer source. Transport velocities were approximately 38.9 m/day for the dye tracer and 115.2 m/day for the colloidal tracer. Results of the model runs indicate that overburden can provide an effective protective layer to transport in fractures, that high groundwater velocities occur in larger fracture apertures and higher gradients dilute tracer concentrations, and that lower groundwater velocities occur with smaller fracture apertures and lower gradients result in elevated tracer concentrations. Lower rainfall rates, larger fracture apertures, early tracer time, larger gradients, and lower water levels maintained unsaturated conditions for longer time periods such that tracer transport was delayed until saturated conditions were attained. The overall heterogeneity of this aquifer environment creates a source water protection conundrum where the water quality is generally good, while transport can occur very quickly in proximity to rock outcrops and in areas with limited overburden.