Non-equilibrium sorption of contaminants in ground water systems is examined from the perspective of sorption rate estimation. A previously developed Markov transition probability model for solute transport is used in conjunction with a new conditional probability-based model of the sorption and desorption rates based on breakthrough curve data. Two models for prediction of spatially varying sorption and desorption rates along a one-dimensional streamline are developed. These models are a Markov model that utilizes conditional probabilities to determine the rates and an ensemble Kalman filter (EnKF) applied to the conditional probability method. Both approaches rely on a previously developed Markov-model of mass transfer, and both models assimilate the observed concentration data into the rate estimation at each observation time. Initial values of the rates are perturbed from the true values to form ensembles of rates and the ability of both estimation approaches to recover the true rates is examined over three different sets of perturbations. The models accurately estimate the rates when the mean of the perturbations are zero, the unbiased case. For the cases containing some bias, addition of the ensemble Kalman filter is shown to improve accuracy of the rate estimation by as much as an order of magnitude.
Ongoing research at Sandia National Laboratories has been in the area of developing models and simulation methods that can be used to uncover and illuminate the material defects created during He bubble growth in aging bulk metal tritides. Previous efforts have used molecular dynamics calculations to examine the physical mechanisms by which growing He bubbles in a Pd metal lattice create material defects. However, these efforts focused only on the growth of He bubbles in pure Pd and not on bubble growth in the material of interest, palladium tritide (PdT), or its non-radioactive isotope palladium hydride (PdH). The reason for this is that existing inter-atomic potentials do not adequately describe the thermodynamics of the Pd-H system, which includes a miscibility gap that leads to phase separation of the dilute (alpha) and concentrated (beta) alloys of H in Pd at room temperature. This document will report the results of research to either find or develop inter-atomic potentials for the Pd-H and Pd-T systems, including our efforts to use experimental data and density functional theory calculations to create an inter-atomic potential for this unique metal alloy system.
Discrete models of large, complex systems like national infrastructures and complex logistics frameworks naturally incorporate many modeling uncertainties. Consequently, there is a clear need for optimization techniques that can robustly account for risks associated with modeling uncertainties. This report summarizes the progress of the Late-Start LDRD 'Robust Analysis of Largescale Combinatorial Applications'. This project developed new heuristics for solving robust optimization models, and developed new robust optimization models for describing uncertainty scenarios.
The performance and the reliability of many devices are controlled by interfaces between thin films. In this study we investigated the use of patterned, nanoscale interfacial roughness as a way to increase the apparent interfacial toughness of brittle, thin-film material systems. The experimental portion of the study measured the interfacial toughness of a number of interfaces with nanoscale roughness. This included a silicon interface with a rectangular-toothed pattern of 60-nm wide by 90-nm deep channels fabricated using nanoimprint lithography techniques. Detailed finite element simulations were used to investigate the nature of interfacial crack growth when the interface is patterned. These simulations examined how geometric and material parameter choices affect the apparent toughness. Atomistic simulations were also performed with the aim of identifying possible modifications to the interfacial separation models currently used in nanoscale, finite element fracture analyses. The fundamental nature of atomistic traction separation for mixed mode loadings was investigated.
Remotely-fielded unattended sensor networks generally must operate at very low power--in the milliwatt or microwatt range--and thus have extremely limited communications bandwidth. Such sensors might be asleep most of the time to conserve power, waking only occasionally to transmit a few bits. RFID tags for tracking or material control have similarly tight bandwidth constraints, and emerging nanotechnology devices will be even more limited. Since transmitted data is subject to spoofing, and since sensors might be located in uncontrolled environments vulnerable to physical tampering, the high-consequence data generated by such systems must be protected by cryptographically sound authentication mechanisms; but such mechanisms are often lacking in current sensor networks. One reason for this undesirable situation is that standard authentication methods become impractical or impossible when bandwidth is severely constrained; if messages are small, a standard digital signature or HMAC will be many times larger than the message itself, yet it might be possible to spare only a few extra bits per message for security. Furthermore, the authentication tags themselves are only one part of cryptographic overhead, as key management functions (distributing, changing, and revoking keys) consume still more bandwidth. To address this problem, we have developed algorithms that provide secure authentication while adding very little communication overhead. Such techniques will make it possible to add strong cryptographic guarantees of data integrity to a much wider range of systems.
DBTools is comprised of a suite of applications for manipulating data in a database. While loading data into a database is a relatively simple operation, loading data intelligently is deceptively difficult. Loading data intelligently means: not duplicating information already in the database, associating new information with related information already in the database, and maintaining a mapping of identification numbers in the input data to existing or new identification numbers in the database to prevent conflicts between the input data and the existing data. Most DBTools applications utilize DBUtilLib--a Java library with functionality supporting database, flatfile, and XML data formats. DBUtilLib is written in a completely generic manner. No schema specific information is embedded within the code; all such information comes from external sources. This approach makes the DBTools applications immune to most schema changes such as addition/deletion of columns from a table or changes to the size of a particular data element.
The 9/30/2007 ASC Level 2 Post-Processing V&V Milestone (Milestone 2360) contains functionality required by the user community for certain verification and validation tasks. These capabilities include loading of edge and face data on an Exodus mesh, run-time computation of an exact solution to a verification problem, delivery of results data from the server to the client, computation of an integral-based error metric, simultaneous loading of simulation and test data, and comparison of that data using visual and quantitative methods. The capabilities were tested extensively by performing a typical ALEGRA HEDP verification task. In addition, a number of stretch criteria were met including completion of a verification task on a 13 million element mesh.
In 2005, over 33% of all the vehicles reported stolen in the United States occurred in the four southwestern border states of California, Arizona, New Mexico, and Texas, which all have very high vehicle theft rates in comparison to the national average. This report describes the utilization of 'bait vehicles' and associated technologies in the context of motor vehicle theft along the southwest border of the U.S. More than 100 bait vehicles are estimated to be in use by individual agencies and auto theft task forces in the southwestern border states. The communications, tracking, mapping, and remote control technologies associated with bait vehicles provide law enforcement with an effective tool to obtain arrests in vehicle theft 'hot spots'. Recorded audio and video from inside the vehicle expedite judicial proceedings as offenders rarely contest the evidence presented. At the same time, law enforcement is very interested in upgrading bait vehicle technology through the use of live streaming video for enhanced officer safety and improved situational awareness. Bait vehicle effectiveness could be enhanced by dynamic analysis of motor theft trends through exploitation of geospatial, timeline, and other analytical tools to better inform very near-term operational decisions, including the selection of particular vehicle types. This 'information-led' capability would especially benefit from more precise and timely information on the location of vehicles stolen in the United States and found in Mexico. Introducing Automated License Plate Reading (ALPR) technology to collect information associated with stolen motor vehicles driven into Mexico could enhance bait vehicle effectiveness.
Downhole sonar surveys from the four active U.S. Strategic Petroleum Reserve sites have been modeled and used to generate a four-volume sonar atlas, showing the three-dimensional geometry of each cavern. This volume 4 focuses on the West Hackberry SPR site, located in southwestern Louisiana. Volumes 1, 2, and 3, respectively, present images for the Bayou Choctaw SPR site, Louisiana, the Big Hill SPR site, Texas, and the Bryan Mound SPR site, Texas. The atlas uses a consistent presentation format throughout. The basic geometric measurements provided by the down-cavern surveys have also been used to generate a number of geometric attributes, the values of which have been mapped onto the geometric form of each cavern using a color-shading scheme. The intent of the various geometrical attributes is to highlight deviations of the cavern shape from the idealized cylindrical form of a carefully leached underground storage cavern in salt. The atlas format does not allow interpretation of such geometric deviations and anomalies. However, significant geometric anomalies, not directly related to the leaching history of the cavern, may provide insight into the internal structure of the relevant salt dome.
For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator's input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario.
Sandia National Laboratories (SNL) is conducting pilot scale evaluations of the performance and cost of innovative water treatment technologies aimed at meeting the recently revised arsenic maximum contaminant level (MCL) for drinking water. The standard of 10 {micro}g/L (10 ppb) is effective as of January 2006. The pilot tests have been conducted in New Mexico where over 90 sites that exceed the new MCL have been identified by the New Mexico Environment Department. The pilot test described in this report was conducted in Anthony, New Mexico between August 2005 and December 2006 at Desert Sands Mutual Domestic Water Consumers Association (MDWCA) (Desert Sands) Well No.3. The pilot demonstrations are a part of the Arsenic Water Technology Partnership program, a partnership between the American Water Works Association Research Foundation (AwwaRF), SNL and WERC (A Consortium for Environmental Education and Technology Development). The Sandia National Laboratories pilot demonstration at the Desert Sands site obtained arsenic removal performance data for fourteen different adsorptive media under intermittent flow conditions. Well water at Desert Sands has approximately 20 ppb arsenic in the unoxidized (arsenite-As(III)) redox state with moderately high total dissolved solids (TDS), mainly due to high sulfate, chloride, and varying concentrations of iron. The water is slightly alkaline with a pH near 8. The study provides estimates of the capacity (bed volumes until breakthrough at 10 ppb arsenic) of adsorptive media in the same chlorinated water. Adsorptive media were compared side-by-side in ambient pH water with intermittent flow operation. This pilot is broken down into four phases, which occurred sequentially, however the phases overlapped in most cases.
Downhole sonar surveys from the four active U.S. Strategic Petroleum Reserve sites have been modeled and used to generate a four-volume sonar atlas, showing the three-dimensional geometry of each cavern. This volume 3 focuses on the Bryan Mound SPR site, located in southeastern Texas. Volumes 1, 2, and 4, respectively, present images for the Bayou Choctaw SPR site, Louisiana, the Big Hill SPR site, Texas, and the West Hackberry SPR site, Louisiana. The atlas uses a consistent presentation format throughout. The basic geometric measurements provided by the down-cavern surveys have also been used to generate a number of geometric attributes, the values of which have been mapped onto the geometric form of each cavern using a color-shading scheme. The intent of the various geometrical attributes is to highlight deviations of the cavern shape from the idealized cylindrical form of a carefully leached underground storage cavern in salt. The atlas format does not allow interpretation of such geometric deviations and anomalies. However, significant geometric anomalies, not directly related to the leaching history of the cavern, may provide insight into the internal structure of the relevant salt dome.
The reliability of thin film systems is important to the continued development of microelectronic and micro-electro-mechanical systems (MEMS). The reliability of these systems is often tied to the ability of the films to remain adhered to its substrate. By measuring the amount of energy to separate the film from the substrate, researchers can predicts film lifetimes. Recent work has resulted in several different testing techniques to measure this energy including spontaneous buckling, indentation induced delamination and four point bending. This report focuses on developing quantifiable adhesion measurements for multiple thin film systems used in MEMS and other thin film systems of interest to Sandia programs. First, methods of accurately assessing interfacial toughness using stressed overlayer methods are demonstrated using both the W/Si and Au/Si systems. For systems where fracture only occurs along the interface, such as Au/Si, the calculated fracture energies between different tests are identical if the energy put into the system is kept near the needed strain energy to cause delamination. When the energy in the system is greater than needed to cause delamination, calculated adhesion energies can increase by a factor of three due to plastic deformation. Dependence of calculated adhesion energies on applied energy in the system was also shown when comparisons of four point bending and stressed overlayer test methods were completed on Pt/Si systems. The fracture energies of Pt/Ti/SiO{sub 2} were studied using four-point bending and compressive overlayers. Varying the thickness of the Ti film from 2 to 17 nm in a Pt/Ti/SiO{sub 2} system, both test methods showed an increase of adhesion energy until the nominal Ti thickness was 12nm. Then the adhesion energy began to decrease. While the trends in toughness are similar, the magnitude of the toughness values measured between the test methods is not the same, demonstrating the difficulty in extracting mode I toughness as mixed mode loading approaches mode II conditions.
Robust and reliable quantitative proliferation assessment tools have the potential to contribute significantly to a strengthened nonproliferation regime and to the future deployment of nuclear fuel cycle technologies. Efforts to quantify proliferation resistance have thus far met with limited success due to the inherent subjectivity of the problem and interdependencies between attributes that lead to proliferation resistance. We suggest that these limitations flow substantially from weaknesses in the foundations of existing methodologies--the initial data inputs. In most existing methodologies, little consideration has been given to the utilization of varying types of inputs--particularly the mixing of subjective and objective data--or to identifying, understanding, and untangling relationships and dependencies between inputs. To address these concerns, a model set of inputs is suggested that could potentially be employed in multiple approaches. We present an input classification scheme and the initial results of testing for relationships between these inputs. We will discuss how classifying and testing the relationship between these inputs can help strengthen tools to assess the proliferation risk of nuclear fuel cycle processes, systems, and facilities.