Publications

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Low-temperature co-fired ceramic (LTCC) enables development and testing of critical elements on microsystem boards as well as nonmicroelectronic meso-scale applications. We describe silicon-based microelectromechanical systems packaging and LTCC meso-scale applications. Microfluidic interposers permit rapid testing of varied silicon designs. The application of LTCC to micro-high-performance liquid chromatography (?-HPLC) demonstrates performance advantages at very high pressures. At intermediate pressures, a ceramic thermal cell lyser has lysed bacteria spores without damaging the proteins. The stability and sensitivity of LTCC/chemiresistor smart channels are comparable to the performance of silicon-based chemiresistors. A variant of the use of sacrificial volume materials has created channels, suspended thick films, cavities, and techniques for pressure and flow sensing. We report on inductors, diaphragms, cantilevers, antennae, switch structures, and thermal sensors suspended in air. The development of 'functional-as-released' moving parts has resulted in wheels, impellers, tethered plates, and related new LTCC mechanical roles for actuation and sensing. High-temperature metal-to-LTCC joining has been developed with metal thin films for the strong, hermetic interfaces necessary for pins, leads, and tubes.

This paper surveys the needs associated with environmental monitoring and long-term environmental stewardship. Emerging sensor technologies are reviewed to identify compatible technologies for various environmental monitoring applications. The contaminants that are considered in this report are grouped into the following categories: (1) metals, (2) radioisotopes, (3) volatile organic compounds, and (4) biological contaminants. United States regulatory drivers are evaluated for different applications (e.g., drinking water, storm water, pretreatment, and air emissions), and sensor requirements are derived from these regulatory metrics. Sensor capabilities are then summarized according to contaminant type, and the applicability of the different sensors to various environmental monitoring applications is discussed.

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Chemical transport through human skin can play a significant role in human exposure to toxic chemicals in the workplace, as well as to chemical/biological warfare agents in the battlefield. The viability of transdermal drug delivery also relies on chemical transport processes through the skin. Models of percutaneous absorption are needed for risk-based exposure assessments and drug-delivery analyses, but previous mechanistic models have been largely deterministic. A probabilistic, transient, three-phase model of percutaneous absorption of chemicals has been developed to assess the relative importance of uncertain parameters and processes that may be important to risk-based assessments. Penetration routes through the skin that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times. This probabilistic analysis of percutaneous absorption (PAPA) method has been developed to improve risk-based exposure assessments and transdermal drug-delivery analyses, where parameters and processes can be highly uncertain. © 2004 Elsevier B.V. All rights reserved.

This report surveys the needs associated with environmental monitoring and long-term environmental stewardship. Emerging sensor technologies are reviewed to identify compatible technologies for various environmental monitoring applications. The contaminants that are considered in this report are grouped into the following categories: (1) metals, (2) radioisotopes, (3) volatile organic compounds, and (4) biological contaminants. Regulatory drivers are evaluated for different applications (e.g., drinking water, storm water, pretreatment, and air emissions), and sensor requirements are derived from these regulatory metrics. Sensor capabilities are then summarized according to contaminant type, and the applicability of the different sensors to various environmental monitoring applications is discussed.

This report provides a summary of the three-year LDRD (Laboratory Directed Research and Development) project aimed at developing microchemical sensors for continuous, in-situ monitoring of volatile organic compounds. A chemiresistor sensor array was integrated with a unique, waterproof housing that allows the sensors to be operated in a variety of media including air, soil, and water. Numerous tests were performed to evaluate and improve the sensitivity, stability, and discriminatory capabilities of the chemiresistors. Field tests were conducted in California, Nevada, and New Mexico to further test and develop the sensors in actual environments within integrated monitoring systems. The field tests addressed issues regarding data acquisition, telemetry, power requirements, data processing, and other engineering requirements. Significant advances were made in the areas of polymer optimization, packaging, data analysis, discrimination, design, and information dissemination (e.g., real-time web posting of data; see www.sandia.gov/sensor). This project has stimulated significant interest among commercial and academic institutions. A CRADA (Cooperative Research and Development Agreement) was initiated in FY03 to investigate manufacturing methods, and a Work for Others contract was established between Sandia and Edwards Air Force Base for FY02-FY04. Funding was also obtained from DOE as part of their Advanced Monitoring Systems Initiative program from FY01 to FY03, and a DOE EMSP contract was awarded jointly to Sandia and INEEL for FY04-FY06. Contracts were also established for collaborative research with Brigham Young University to further evaluate, understand, and improve the performance of the chemiresistor sensors.

This report provides a survey of remediation and treatment technologies for contaminants of concern at environmental restoration (ER) sites at Sandia National Laboratories, New Mexico. The sites that were evaluated include the Tijeras Arroyo Groundwater, Technical Area V, and Canyons sites. The primary contaminants of concern at these sites include trichloroethylene (TCE), tetrachloroethylene (PCE), and nitrate in groundwater. Due to the low contaminant concentrations (close to regulatory limits) and significant depths to groundwater ({approx}500 feet) at these sites, few in-situ remediation technologies are applicable. The most applicable treatment technologies include monitored natural attenuation and enhanced bioremediation/denitrification to reduce the concentrations of TCE, PCE, and nitrate in the groundwater. Stripping technologies to remove chlorinated solvents and other volatile organic compounds from the vadose zone can also be implemented, if needed.

This paper describes the development of a surface-acoustic-wave (SAW) sensor that is designed to be operated continuously and in situ to detect volatile organic compounds. A ruggedized stainless-steel package that encases the SAW device and integrated circuit board allows the sensor to be deployed in a variety of media including air, soil, and even water. Polymers were optimized and chosen based on their response to chlorinated aliphatic hydrocarbons (e.g., trichloroethylene), which are common groundwater contaminants. Initial testing indicates that a running-average data-logging algorithm can reduce the noise and increase the sensitivity of the in-situ sensor.

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A probabilistic, transient, three-phase model of chemical transport through human skin has been developed to assess the relative importance of uncertain parameters and processes during chemical exposure assessments and transdermal drug delivery. Penetration routes through the skin that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes for a hypothetical scenario of chemical transport through the skin. At early times (60 seconds), the sweat ducts provided a significant amount of simulated mass flux into the bloodstream. At longer times (1 hour), diffusion through the stratum corneum became important because of its relatively large surface area. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times.

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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.

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A Total System Performance Assessment (TSPA) of Yucca Mountain consists of integrated sub-models and analyses of natural and engineered systems. Examples of subsystem models include unsaturated-zone flow and transport, seepage into drifts, coupled thermal hydrologic processes, transport through the engineered barrier system, and saturated-zone flow and transport. The TSPA evaluates the interaction of important processes among these subsystems, and it determines the impact of these processes on the overall performance measures (e.g., dose rate to humans). This paper summarizes the evaluation, abstraction, and combination of these subsystem models in a TSPA calculation, and it provides background on the individual TSPA subsystem components that are most directly impacted by geotechnical issues. The potential impact that geologic features, events, and processes have on the overall performance is presented, and an evaluation of the sensitivity of TSPA calculations to these issues is also provided.

Parameters have been identified that can be modeled stochastically using PORFLOW and Latin Hypercube Sampling (LHS). These parameters include hydrologic and transport properties in the vadose and saturated zones, as well as source-term parameters and infiltration rates. A number of resources were used to define the parameter distributions, primarily those provided in the Retrieval Performance Evaluation Report (Jacobs, 1998). A linear rank regression was performed on the vadose-zone hydrologic parameters given in Khaleel and Freeman (1995) to determine if correlations existed between pairs of parameters. No strong correlations were found among the vadose-zone hydrologic parameters, and it was recommended that these parameters be sampled independently until future data or analyses reveal a strong correlation or functional relationship between parameters. Other distributions for source-term parameters, infiltration rates, and saturated-zone parameters that are required to stochastically analyze the performance of the AX Tank Farm using LHS/PORFLOW were adapted from distributions and values reported in Jacobs (1998) and other literature sources. Discussions pertaining to the geologic conceptualization, vadose-zone modeling, and saturated-zone modeling of the AX Tank Farm are also presented.