Biomedical subjects

Ahmed E Hassan

Publications and source records attributed to Ahmed E Hassan.

4 recordsLinked to original sources

PubMed2006

Experimental and numerical iInvestigations of effects of silica colloids on transport of strontium in saturated sand columns.

Transport experiments with strontium were conducted using saturated sand columns in the presence and absence of silica colloids, and numerical modeling was performed with modeling results compared to experimental data. The experiments were aimed at testing the hypothesis that under certain chemical conditions colloids act as movement-retarding agents and yield a larger effective retardation factor for the migrating contaminant. Four individual experiments were conducted to identify conditions where the mobility of silica colloids is increased or decreased, and a similar set was conducted for strontium transport in the absence of colloids. Mobility of colloids was found to increase with decreasing ionic strength and increasing pH, with the ionic strength having the more significant impact. The reverse effect was obtained for strontium. Based on these results, two additional experiments were conducted where both colloids and strontium were injected at the column inlet. Results showed that under certain conditions of ionic strength and pH (I = 3.0 x 10(-2) M and pH = 4-5.4) colloids retarded the movement of strontium. The retardation effect was obtained in two experiments under slightly modified conditions, which confirms the role of colloids as retarding agents. Afinite difference numerical model was used to (a) simulate mobile breakthrough curves and compare to experimental data and (b) estimate the model parameters describing cotransport of strontium and colloids. The model accurately predicted arrival time and the overall shape of the breakthrough curves.

Colloids↗

PubMedDate not supplied

Validation of numerical ground water models used to guide decision making.

Many sites of ground water contamination rely heavily on complex numerical models of flow and transport to develop closure plans. This complexity has created a need for tools and approaches that can build confidence in model predictions and provide evidence that these predictions are sufficient for decision making. Confidence building is a long-term, iterative process and the author believes that this process should be termed model validation. Model validation is a process, not an end result. That is, the process of model validation cannot ensure acceptable prediction or quality of the model. Rather, it provides an important safeguard against faulty models or inadequately developed and tested models. If model results become the basis for decision making, then the validation process provides evidence that the model is valid for making decisions (not necessarily a true representation of reality). Validation, verification, and confirmation are concepts associated with ground water numerical models that not only do not represent established and generally accepted practices, but there is not even widespread agreement on the meaning of the terms as applied to models. This paper presents a review of model validation studies that pertain to ground water flow and transport modeling. Definitions, literature debates, previously proposed validation strategies, and conferences and symposia that focused on subsurface model validation are reviewed and discussed. The review is general and focuses on site-specific, predictive ground water models used for making decisions regarding remediation activities and site closure. The aim is to provide a reasonable starting point for hydrogeologists facing model validation for ground water systems, thus saving a significant amount of time, effort, and cost. This review is also aimed at reviving the issue of model validation in the hydrogeologic community and stimulating the thinking of researchers and practitioners to develop practical and efficient tools for evaluating and refining ground water predictive models.

Decision Making↗

PubMedDate not supplied

A methodology for validating numerical ground water models.

Ground water validation is one of the most challenging issues facing modelers and hydrogeologists. Increased complexity in ground water models has created a gap between model predictions and the ability to validate or build confidence in predictions. Specific procedures and tests that can be easily adapted and applied to determine the validity of site-specific ground water models do not exist. This is true for both deterministic and stochastic models, with stochastic models posing the more difficult validation problem. The objective of this paper is to propose a general validation approach that addresses important issues recognized in previous validation studies, conferences, and symposia. The proposed method links the processes for building, calibrating, evaluating, and validating models in an iterative loop. The approach focuses on using collected validation data to reduce uncertainty in the model and narrow the range of possible outcomes. This method is designed for stochastic numerical models utilizing Monte Carlo simulation approaches, but it can be easily adapted for deterministic models. The proposed methodology relies on the premise that absolute validity is not theoretically possible, nor is it a regulatory requirement. Rather, the proposed methodology highlights the importance of testing various aspects of the model and using diverse statistical tools for rigorous checking and confidence building in the model and its predictions. It is this confidence that will encourage regulators and the public to accept decisions based on the model predictions. This validation approach will be applied to a model, described in this paper, dealing with an underground nuclear test site in rural Nevada.

Environmental Monitoring↗

PubMedDate not supplied

Developing a long-term monitoring network under uncertain flowpaths.

A long-term monitoring well network is developed using complementary and simple approaches in conjunction with a stochastic ground water flow and transport model. The development is illustrated for a case study of a U.S. nuclear testing site (Shoal) that is undergoing environmental restoration. The network design builds on three different, yet complementary, tools for locating the monitoring wells with a main objective of detection monitoring. The first tool is applied to select potential siting horizons where monitoring wells could be located. The second tool is used to place monitoring wells in locations with high success probability. The success here is defined as the detection of migrating stochastic plumes before a certain mass percentage reaches a compliance boundary. The third tool is used to analyze detection efficiency of multiple combinations of three wells. Seventy-six different three-well networks are selected from 20 candidate locations and are evaluated for detection efficiency. From the 76 networks analyzed, 28 attain detection efficiency close to or above 70%. The results of the different analyses provide multiple alternatives for the locations of the three wells, which will become part of the long-term monitoring network at Shoal. A number of combinations are equally good, and the final choice will depend on practical considerations and future agreements between model sponsor and regulators.

Environmental Monitoring↗