Application of particle methods to reliable identification of groundwater pollution sources

Bagtzoglou, Amvrossios C.; Dougherty, David E.; Tompson, Andrew F. B.

doi:10.1007/bf00872184

Cited by 125 publications

(71 citation statements)

References 9 publications

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“…They reversed only the pollutant transport by convection and neglected the effect of diffusion. The method has also been used in groundwater contaminant transport [15,21], where convection transport of pollutants is solved with reversed velocity field and the diffusion was left unchanged.…”

Section: The Direct Inverse Approachmentioning

confidence: 99%

“…The approach uses probability to express a possible causal aspect. In groundwater transport, Bagtzoglou et al (1992) [15] calculated the possibility of a contaminant source in groundwater by reversing only the convective contaminant transport. Other researchers [16] used Bayesian theory to interpret the possibility of each contaminant source.…”

Section: The Probabilistic Approachmentioning

confidence: 99%

See 1 more Smart Citation

Fundamentals of Direct Inverse CFD Modeling to Detect Air Pollution Sources in Urban Areas

Bady¹

2013

CWEEE

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This paper presents the fundamentals of direct inverse modeling using CFD simulations to detect air pollution sources in urban areas. Generally, there are four techniques used for detecting pollution sources: the analytical technique, the optimization technique, the probabilistic technique, and the direct technique. The study discusses the potentialities and limits of each technique, where the direct inverse technique is focused. Two examples of applying the direct inverse technique in detecting pollution source are introduced. The difficulties of applying the direct inverse technique are investigated. The study reveals that the direct technique is a promising tool for detecting air pollution source in urban environments. However, more efforts are still needed to overcome the difficulties explained in the study.

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Section: The Direct Inverse Approachmentioning

confidence: 99%

Section: The Probabilistic Approachmentioning

confidence: 99%

Fundamentals of Direct Inverse CFD Modeling to Detect Air Pollution Sources in Urban Areas

Bady¹

2013

CWEEE

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“…[9]. Commonly employed techniques include the Tikhonov regularization method [38], the nonlinear optimization model [2], particlebased methods [1,7], the backward beam equation method [3,4,8] and geostatistical based methods [6,32]. Some other newly emerged techniques have also been under intensive investigation, such as artificial neural networks [37], a global search algorithm with a constrained least squares estimator [40], geostatistical kriging [36] and iterative regularization [23].…”

Section: Introductionmentioning

confidence: 99%

Estimation of river pollution source using the space-time radial basis collocation method

Mao

et al. 2016

Advances in Water Resources

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a b s t r a c tRiver contaminant source identification problems can be formulated as an inverse model to estimate the missing source release history from the observed contaminant plume. In this study, the identification of pollution sources in rivers, where strong advection is dominant, is solved by the global space-time radial basis collocation method (RBCM). To search for the optimal shape parameter and scaling factor which strongly determine the accuracy of the RBCM method, a new cost function based on the residual errors of not only the observed data but also the specified governing equation, the initial and boundary conditions, was constructed for the k-fold cross-validation technique. The performance of three global radial basis functions, Hardy's multiquadric, inverse multiquadric and Gaussian, were also compared in the test cases. The numerical results illustrate that the new cost function is a good indicator to search for near-optimal solutions. Application to a real polluted river shows that the source release history is reasonably recovered, demonstrating that the RBCM with the k-fold cross-validation is a powerful tool for source identification problems in advectiondominated rivers.

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“…Other approach for source identification consists of solving the differential equations backwards in time (inverse problem). The random walk particle method [10,11], the quasi-reversibility technique [12], the minimum relative entropy method [13], the Bayesian theory and geostatistical techniques [14], and genetic algorithm [15,16] are some examples of this approach.…”

Section: Introductionmentioning

confidence: 99%

Application of Simulated Annealing and Adaptive Simulated Annealing in Search for Efficient Optimal Solutions of a Groundwater Contamination related Problem

Amirabdollahian¹,

Datta²

2017

Computational Optimization in Engineering - Paradigms and Applications

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Characterization of groundwater contamination sources is a complex inverse problem. This inverse problem becomes complicated, due to the nonlinear nature of the groundwater flow and transport processes and the associated natural uncertainties. The mathematical challenges arise due to the nonunique characteristics of this problem resulting from the nonunique response of the aquifer system to a set of stresses and the possibility of instead locating only local optimal solutions. The linked simulation-optimization model is an efficient approach to identifying groundwater contamination source characteristics. Efficiency and accuracy of the search for optimum solutions of a linked simulation-optimization depend on the utilized optimization algorithm. This limited study focuses on the application and efficiency of simulated annealing (SA) as the optimization algorithm for solving the source characterization problem. The advantages in using adaptive simulated algorithm (ASA) as an alternative are then evaluated. The possibility of identifying a local optimal solution rather than a global optimal solution when using SA implies failure to solve the source characterization inverse problem. The cost of such inaccurate characterization may be enormous when a remediation strategy is based on the model inferences. ASA is shown to provide a reliable and acceptable alternative for solving this challenging aquifer contamination problem.

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Application of particle methods to reliable identification of groundwater pollution sources

Cited by 125 publications

References 9 publications

Fundamentals of Direct Inverse CFD Modeling to Detect Air Pollution Sources in Urban Areas

Fundamentals of Direct Inverse CFD Modeling to Detect Air Pollution Sources in Urban Areas

Estimation of river pollution source using the space-time radial basis collocation method

Application of Simulated Annealing and Adaptive Simulated Annealing in Search for Efficient Optimal Solutions of a Groundwater Contamination related Problem

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