Publications

Abstract not provided.

Abstract not provided.

A chemiresistor microchemical sensor has been developed to detect and monitor volatile organic compounds in unsaturated and saturated subsurface environments. A controlled study was conducted at the HAZMAT Spill Center at the Nevada Test Site, where the sensor was tested under a range of temperature, moisture, and trichloroethylene (TCE) concentrations. The sensor responded rapidly when exposed to TCE placed in sand, and it also responded to decreases in TCE vapor concentration when clean air was vented through the system. Variations in temperature and water vapor concentration impacted baseline chemiresistor signals, but at high TCE concentrations the sensor response was dominated by the TCE exposure. Test results showed that the detection limit of the chemiresistor to TCE vapor in the presence of fluctuating environmental variables (i.e., temperature and water vapor concentration) was on the order of 1000 parts per million by volume, which is about an order of magnitude higher than values obtained in controlled laboratory environments. Automated temperature control and preconcentration is recommended to improve the stability and sensitivity of the chemiresistor sensor.

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Abstract not provided.

A probabilistic, risk-based performance-assessment methodology has been developed to assist designers, regulators, and stakeholders in the selection, design, and monitoring of long-term covers for contaminated subsurface sites. This report describes the method, the software tools that were developed, and an example that illustrates the probabilistic performance-assessment method using a repository site in Monticello, Utah. At the Monticello site, a long-term cover system is being used to isolate long-lived uranium mill tailings from the biosphere. Computer models were developed to simulate relevant features, events, and processes that include water flux through the cover, source-term release, vadose-zone transport, saturated-zone transport, gas transport, and exposure pathways. The component models were then integrated into a total-system performance-assessment model, and uncertainty distributions of important input parameters were constructed and sampled in a stochastic Monte Carlo analysis. Multiple realizations were simulated using the integrated model to produce cumulative distribution functions of the performance metrics, which were used to assess cover performance for both present- and long-term future conditions. Performance metrics for this study included the water percolation reaching the uranium mill tailings, radon gas flux at the surface, groundwater concentrations, and dose. Results from uncertainty analyses, sensitivity analyses, and alternative design comparisons are presented for each of the performance metrics. The benefits from this methodology include a quantification of uncertainty, the identification of parameters most important to performance (to prioritize site characterization and monitoring activities), and the ability to compare alternative designs using probabilistic evaluations of performance (for cost savings).

A probabilistic, risk-based performance-assessment methodology is being developed to assist designers, regulators, and involved stakeholders in the selection, design, and monitoring of long-term covers for contaminated subsurface sites. This report presents an example of the risk-based performance-assessment method using a repository site in Monticello, Utah. At the Monticello site, a long-term cover system is being used to isolate long-lived uranium mill tailings from the biosphere. Computer models were developed to simulate relevant features, events, and processes that include water flux through the cover, source-term release, vadose-zone transport, saturated-zone transport, gas transport, and exposure pathways. The component models were then integrated into a total-system performance-assessment model, and uncertainty distributions of important input parameters were constructed and sampled in a stochastic Monte Carlo analysis. Multiple realizations were simulated using the integrated model to produce cumulative distribution functions of the performance metrics, which were used to assess cover performance for both present- and long-term future conditions. Performance metrics for this study included the water percolation reaching the uranium mill tailings, radon flux at the surface, groundwater concentrations, and dose. Results of this study can be used to identify engineering and environmental parameters (e.g., liner properties, long-term precipitation, distribution coefficients) that require additional data to reduce uncertainty in the calculations and improve confidence in the model predictions. These results can also be used to evaluate alternative engineering designs and to identify parameters most important to long-term performance.

Sandia National Laboratories has sponsored an LDRD (Laboratory Directed Research and Development) project to investigate and develop micro-chemical sensors for in-situ monitoring of subsurface contaminants. As part of this project, a literature search has been conducted to survey available technologies and identify the most promising methods for sensing and monitoring subsurface contaminants of interest. Specific sensor technologies are categorized into several broad groups, and these groups are then evaluated for use in subsurface, long-term applications. This report introduces the background and specific scope of the problem being addressed by this LDRD project, and it provides a summary of the advantages and disadvantages of each sensor technology identified from the literature search.

A semi-analytical solution is developed for one-dimensional steady infiltration in unsaturated fractured rock. The differential form of the mass conservation equation is integrated to yield an analytical expression relating elevation to a function of capillary pressure and relative permeability of the fracture and rock matrix. Constitutive relationships for unsaturated flow in this analysis are taken from van Genuchten [1980] and Mualem [1976], but alternative relations can also be implemented in the integral solution. Expressions are presented for the liquid saturations and pore velocities in the fracture, matrix, and effective continuum materials as a function of capillary pressure and elevation. Results of the analytical solution are applied to examples of infiltration in fractured rock consisting of both homogeneous and composite (layered) domains. The analytical results are also compared to numerical simulations to demonstrate the use of the analytical solution as a benchmarking tool to address computational issues such as grid refinement.

In a total-system performance assessment (TSPA), uncertainty in the performance measure (e.g., radiation dose) is estimated by first estimating the uncertain y in the input variables and then propagating that uncertain y through the model system by means of Monte Carlo simulation. This paper discusses uncertainty in surface infiltration, which is one of the input variables needed for performance assessments of the Yucca Mountain site. Infiltration has been represented in recent TSPA simulations by using three discrete infiltration maps (i.e., spatial distributions of infiltration) for each climate state in the calculation of unsaturated-zone flow and transport. A detailed uncertainty analysis of infiltration was carried out for two purposes: to better quantify the possible range of infiltration, and to determine what probability weights should be assigned to the three infiltration cases in a TSPA simulation. The remainder of this paper presents the approach and methodology for the uncertainty analysis, along with a discussion of the results.

The abstraction model used for seepage into emplacement drifts in recent TSPA simulations has been presented. This model contributes to the calculation of the quantity of water that might contact waste if it is emplaced at Yucca Mountain. Other important components of that calculation not discussed here include models for climate, infiltration, unsaturated-zone flow, and thermohydrology; drip-shield and waste-package degradation; and flow around and through the drip shield and waste package. The seepage abstraction model is stochastic because predictions of seepage are necessarily quite uncertain. The model provides uncertainty distributions for seepage fraction fraction of waste-package locations flow rate as functions of percolation flux. In addition, effects of intermediate-scale flow with seepage and seep channeling are included by means of a flow-focusing factor, which is also represented by an uncertainty distribution.

Abstract not provided.