Publications

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The effect of collision-partner selection schemes on the accuracy and the efficiency of the Direct Simulation Monte Carlo (DSMC) method of Bird is investigated. Several schemes to reduce the total discretization error as a function of the mean collision separation and the mean collision time are examined. These include the historically first sub-cell scheme, the more recent nearest-neighbor scheme, and various near-neighbor schemes, which are evaluated for their effect on the thermal conductivity for Fourier flow. Their convergence characteristics as a function of spatial and temporal discretization and the number of simulators per cell are compared to the convergence characteristics of the sophisticated and standard DSMC algorithms. Improved performance is obtained if the population from which possible collision partners are selected is an appropriate fraction of the population of the cell.

Continued reduction of characteristic dimensions in nanosystems has given rise to increasing importance of material interfaces on the overall system performance. With regard to thermal transport, this increases the need for a better fundamental understanding of the processes affecting interfacial thermal transport, as characterized by the thermal boundary conductance. When thermal boundary conductance is driven by phononic scattering events, accurate predictions of interfacial transport must account for anharmonic phononic coupling as this affects the thermal transmission. In this paper, a new model for phononic thermal boundary conductance is developed that takes into account anharonic coupling, or inelastic scattering events, at the interface between two materials. Previous models for thermal boundary conductance are first reviewed, including the Diffuse Mismatch Model, which only consdiers elastic phonon scattering events, and earlier attempts to account for inelastic phonon scattering, namely, the Maximum Transmission Model and the Higher Harmonic Inelastic model. A new model is derived, the Anharmonic Inelastic Model, which provides a more physical consideration of the effects of inelastic scattering on thermal boundary conductance. This is accomplished by considering specific ranges of phonon frequency interactions and phonon number density conservation. Thus, this model considers the contributions of anharmonic, inelastically scattered phonons to thermal boundary conductance. This new Anharmonic Inelastic Model shows excellent agreement between model predictions and experimental data at the Pb/diamond interface due to its ability to account for the temperature dependent changing phonon population in diamond, which can couple anharmonically with multiple phonons in Pb.

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The Waste Isolation Pilot Plant (WIPP) disposal operations currently employ two different disposal methods: one for Contact Handled (CH) waste and another for Remote Handled (RH) waste. CH waste is emplaced in a variety of payload container configurations on the floor of each disposal room. In contrast, RH waste is packaged into a single type of canister and emplaced in pre-drilled holes in the walls of disposal rooms. Emplacement of the RH waste in the walls must proceed in advance of CH waste emplacement and therefore poses logistical constraints, in addition to the loss of valuable disposal capacity. To improve operational efficiency and disposal capacity, the Department of Energy (DOE) has proposed a shielded container for certain RH waste streams. RH waste with relatively low gammaemitting activity would be packaged in lead-lined containers, shipped to WIPP in existing certified transportation packages for CH waste and emplaced in WIPP among the stacks of CH waste containers on the floor of a disposal room. RH waste with high gamma-emitting activity would continue to be emplaced in the boreholes along the walls. The new RH container is similar to the nominal 208-liter (55-gallon) drum, however it includes about 2.5 cm (1 in) of lead, sandwiched between thick steel sheets. Furthermore, the top and bottom are made of thick plate steel to strengthening the package to meet transportation requirements. This robust configuration provides an overpack for materials that otherwise would be RH waste. This paper describes the container and the regulatory approach used to meet the requirements imposed by regulations that apply to WIPP. This includes a Performance Assessment used to evaluate WIPP's long-term performance and the DOE's approach to gain approval for the transportation of shielded containers. This paper also describes estimates of the DOE's RH transuranic waste inventory that may be packaged and emplaced in shielded containers. Finally, the paper includes a discussion of how the DOE proposes to track the waste packaged into shielded containers against the RH waste inventory and how this will comply with the regulated volume.

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The original Trusted Radiation Identification System (TRIS) was developed from 1999-2001, featuring information barrier technology to collect gamma radiation template measurements useful for arms control regime operations. The first TRIS design relied upon a multichannel analyzer (MCA) that was external to the protected volume of the system enclosure, undesirable from a system security perspective. An internal complex programmable logic device (CPLD) contained data which was not subject to software authentication. Physical authentication of the TRIS instrument case was performed by a sensitive but slow eddy-current inspection method. This paper describes progress to date for the Next Generation TRIS (NG-TRIS), which improves the TRIS design. We have incorporated the MCA internal to the trusted system volume, achieved full authentication of CPLD data, and have devised rapid methods to authenticate the system enclosure and weld seals of the NG-TRIS enclosure. For a complete discussion of the TRIS system and components upon which NG-TRIS is based, the reader is directed to the comprehensive user's manual and system reference of Seager, et al.

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In this work, we developed a self-organizing map (SOM) technique for using web-based text analysis to forecast when a group is undergoing a phase change. By 'phase change', we mean that an organization has fundamentally shifted attitudes or behaviors. For instance, when ice melts into water, the characteristics of the substance change. A formerly peaceful group may suddenly adopt violence, or a violent organization may unexpectedly agree to a ceasefire. SOM techniques were used to analyze text obtained from organization postings on the world-wide web. Results suggest it may be possible to forecast phase changes, and determine if an example of writing can be attributed to a group of interest.

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The world currently faces tremendous energy challenges stemming from the need to curb potentially catastrophic anthropogenic climate change. In addition, many nations, including the United States, recognize increasing political and economic risks associated with dependence on uncertain and limited energy sources. For these and other reasons the chemical composition of transportation fuels is changing, both through introduction of nontraditional fossil sources, such as oil sands-derived fuels in the US stream, and through broader exploration of biofuels. At the same time the need for clean and efficient combustion is leading engine research towards advanced low-temperature combustion strategies that are increasingly sensitive to this changing fuel chemistry, particularly in the areas of pollutant formation and autoignition. I will highlight the new demands that advanced engine technologies and evolving fuel composition place on investigations of fundamental reaction chemistry. I will focus on recent progress in measuring product formation in elementary reactions by tunable synchrotron photoionization, on the elucidation of pressure-dependent effects in the reactions of alkyl and substituted alkyl radicals with O{sub 2}, and on new combined efforts in fundamental combustion chemistry and engine performance studies of novel potential biofuels.

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This paper discusses a new approach to making hybrid power electronic circuits by combining a low-temperature (850 C to 950 C) co-fired ceramic (LTCC) substrate, planar LTCC ferrite transformers/inductors and integrated passive components into a multilayer monolithic package using a ferrite-based LTCC material system. A ferrite tape functions as the base material for this LTCC system. The material system includes physically and chemically compatible dielectric paste, dielectric tape and conductor materials which can be co-fired with the base ferrite LTCC tape to create sintered devices with excellent magnetic coupling, high permeability ({approx}400), high resistivity (> 10{sup 12} {Omega} {center_dot} cm) and good saturation ({approx}0.3 T). The co-fired ferrite and dielectric materials can be used as a substrate for attaching or housing semiconductor components and other discrete devices that are part of the power electronics system. Furthermore, the ability to co-fire the ferrite with dielectric and conductor materials allows for the incorporation of embedded passives in the multilayer structure to create hybrid power electronic circuits. Overall this thick film material set offers a unique approach to making hybrid power electronics and could potentially allow a size reduction for many commercial dc-dc converter and other power electronic circuits.

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Nanoporous carbon (NPC) is a purely graphitic material with highly controlled densities ranging from less than 0.1 to 2.0 g/cm3, grown via pulsed-laser deposition. Decreasing the density of NPC increases the interplanar spacing between graphene-sheet fragments. This ability to tune the interplanar spacing makes NPC an ideal model system to study the behavior of carbon electrodes in electrochemical capacitors and batteries. We examine the capacitance of NPC films in alkaline and acidic electrolytes, and measure specific capacitances as high as 242 F/g.

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Advances in structural adhesives have permitted engineers to contemplate the use of bonded joints in areas that have long been dominated by mechanical fasteners and welds. Although strength, modulus, and toughness have been improved in modern adhesives, the typical concerns with using these polymers still exist. These include concerns over long-term durability and an inability to quantify bond strength (i.e., identify weak bonds) in adhesive joints. Bond deterioration in aging structures and bond strength in original construction are now critical issues that require more than simple flaw detection. Whether the structure involves metallic or composite materials, it is necessary to extend inspections beyond the detection of disbond flaws to include an assessment of the strength of the bond. Use of advanced nondestructive inspection (NDI) methods to measure the mechanical properties of a bonded joint and associated correlations with post-inspection failure tests have provided some clues regarding the key parameters involved in assessing bond strength. Recent advances in ultrasonic- and thermographic-based inspection methods have shown promise for measuring such properties. Specialized noise reduction and signal enhancement schemes have allowed thermographic interrogations to image the subtle differences between bond lines of various strengths. Similarly, specialized ultrasonic (UT) inspection techniques, including laser UT, guided waves, UT spectroscopy, and resonance methods, can be coupled with unique signal analysis algorithms to accurately characterize the properties of weak interfacial bonds. The generation of sufficient energy input levels to derive bond strength variations, the production of sufficient technique sensitivity to measure such minor response variations, and the difficulty in manufacturing repeatable weak bond specimens are all issues that exacerbate these investigations. The key to evaluating the bond strength lies in the ability to exploit the critical characteristics of weak bonds such as nonlinear responses, poor transmission of shear waves, and changes in response to stiffness-based interrogations. This paper will present several ongoing efforts that have identified promising methods for quantifying bond strength and discuss some completed studies that provide a foundation for further evolution in weak bond assessments.

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The authors have developed two versions of a flexible fabrication technique known as membrane projection lithography that can produce nearly arbitrary patterns in '212 D' and fully three-dimensional (3D) structures. The authors have applied this new technique to the fabrication of split ring resonator-based metamaterials in the midinfrared. The technique utilizes electron beam lithography for resolution, pattern design flexibility, and alignment. The resulting structures are nearly three orders of magnitude smaller than equivalent microwave structures that were first used to demonstrate a negative index material. The fully 3D structures are highly isotropic and exhibit both electrically and magnetically excited resonances for incident transverse electromagnetic waves.

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Results show that a time-series based classification may be possible. For the test cases considered, the correct model can be selected and the number of index case can be captured within {+-} {sigma} with 5-10 days of data. The low signal-to-noise ratio makes the classification difficult for small epidemics. The problem statement is: (1) Create Bayesian techniques to classify and characterize epidemics from a time-series of ICD-9 codes (will call this time-series a 'morbidity stream'); and (2) It is assumed the morbidity stream has already set off an alarm (through a Kalman filter anomaly detector) Starting with a set of putative diseases: Identify which disease or set of diseases 'fit the data best' and, Infer associated information about it, i.e. number of index cases, start time of the epidemic, spread rate, etc.

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In order to provide large quantities of high-reliability disk-based storage, it has become necessary to aggregate disks into fault-tolerant groups based on the RAID methodology. Most RAID levels do provide some fault tolerance, but there are certain classes of applications that require increased levels of fault tolerance within an array. Some of these applications include embedded systems in harsh environments that have a low level of serviceability, or uninhabited data centers servicing cloud computing. When describing RAID reliability, the Mean Time To Data Loss (MTTDL) calculations will often assume that the time to replace a failed disk is relatively low, or even negligible compared to rebuild time. For platforms that are in remote areas collecting and processing data, it may be impossible to access the system to perform system maintenance for long periods. A disk may fail early in a platform's life, but not be replaceable for much longer than typical for RAID arrays. Service periods may be scheduled at intervals on the order of months, or the platform may not be serviced until the end of a mission in progress. Further, this platform may be subject to extreme conditions that can accelerate wear and tear on a disk, requiring even more protection from failures. We have created a high parity RAID implementation that uses a Graphics Processing Unit (GPU) to compute more than two blocks of parity information per stripe, allowing extra parity to eliminate or reduce the requirement for rebuilding data between service periods. While this type of controller is highly effective for RAID 6 systems, an important benefit is the ability to incorporate more parity into a RAID storage system. Such RAID levels, as yet unnamed, can tolerate the failure of three or more disks (depending on configuration) without data loss. While this RAID system certainly has applications in embedded systems running applications in the field, similar benefits can be obtained for servers that are engineered for storage density, with less regard for serviceability or maintainability. A storage brick can be designed to have a MTTDL that extends well beyond the useful lifetime of the hardware used, allowing the disk subsystem to require less service throughout the lifetime of a compute resource. This approach is similar to the Xiotech ISE. Such a design can be deliberately placed remotely (without frequent support) in order to provide colocation, or meet cost goals. For workloads where reliability is key, but conditions are sub-optimal for routine serviceability, a high-parity RAID can provide extra reliability in extraordinary situations. For example, for installations requiring very high Mean Time To Repair, the extra parity can eliminate certain problems with maintaining hot spares, increasing overall reliability. Furthermore, in situations where disk reliability is reduced because of harsh conditions, extra parity can guard against early data loss due to lowered Mean Time To Failure. If used through an iSCSI interface with a streaming workload, it is possible to gain all of these benefits without impacting performance.

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Chemically reacting flow models generally involve inputs and parameters that are determined from empirical measurements, and therefore exhibit a certain degree of uncertainty. Estimating the propagation of this uncertainty into computational model output predictions is crucial for purposes of reacting flow model validation, model exploration, as well as design optimization. Recent years have seen great developments in probabilistic methods and tools for efficient uncertainty quantification (UQ) in computational models. These tools are grounded in the use of Polynomial Chaos (PC) expansions for representation of random variables. The utility and effectiveness of PC methods have been demonstrated in a range of physical models, including structural mechanics, transport in porous media, fluid dynamics, aeronautics, heat transfer, and chemically reacting flow. While high-dimensionality remains nominally an ongoing challenge, great strides have been made in dealing with moderate dimensionality along with non-linearity and oscillatory dynamics. In this talk, I will give an overview of UQ in chemical systems. I will cover both: (1) the estimation of uncertain input parameters from empirical data, and (2) the forward propagation of parametric uncertainty to model outputs. I will cover the basics of forward PC UQ methods with examples of their use. I will also highlight the need for accurate estimation of the joint probability density over the uncertain parameters, in order to arrive at meaningful estimates of model output uncertainties. Finally, I will discuss recent developments on the inference of this density given partial information from legacy experiments, in the absence of raw data.

In this study, risk-significant pressurized-water reactor severe accident sequences are examined using MELCOR 1.8.5 to explore the range of fission product releases to the reactor containment building. Advances in the understanding of fission product release and transport behavior and severe accident progression are used to render best estimate analyses of selected accident sequences. Particular emphasis is placed on estimating the effects of high fuel burnup in contrast with low burnup on fission product releases to the containment. Supporting this emphasis, recent data available on fission product release from high-burnup (HBU) fuel from the French VERCOR project are used in this study. The results of these analyses are treated as samples from a population of accident sequences in order to employ approximate order statistics characterization of the results. These trends and tendencies are then compared to the NUREG-1465 alternative source term prescription used today for regulatory applications. In general, greater differences are observed between the state-of-the-art calculations for either HBU or low-burnup (LBU) fuel and the NUREG-1465 containment release fractions than exist between HBU and LBU release fractions. Current analyses suggest that retention of fission products within the vessel and the reactor coolant system (RCS) are greater than contemplated in the NUREG-1465 prescription, and that, overall, release fractions to the containment are therefore lower across the board in the present analyses than suggested in NUREG-1465. The decreased volatility of Cs2MoO4 compared to CsI or CsOH increases the predicted RCS retention of cesium, and as a result, cesium and iodine do not follow identical behaviors with respect to distribution among vessel, RCS, and containment. With respect to the regulatory alternative source term, greater differences are observed between the NUREG-1465 prescription and both HBU and LBU predictions than exist between HBU and LBU analyses. Additionally, current analyses suggest that the NUREG-1465 release fractions are conservative by about a factor of 2 in terms of release fractions and that release durations for in-vessel and late in-vessel release periods are in fact longer than the NUREG-1465 durations. It is currently planned that a subsequent report will further characterize these results using more refined statistical methods, permitting a more precise reformulation of the NUREG-1465 alternative source term for both LBU and HBU fuels, with the most important finding being that the NUREG-1465 formula appears to embody significant conservatism compared to current best-estimate analyses.

As part of a Nuclear Regulatory Commission (NRC) research program to evaluate the impact of using mixed-oxide (MOX) fuel in commercial nuclear power plants, a study was undertaken to evaluate the impact of the usage of MOX fuel on the consequences of postulated severe accidents. A series of 23 severe accident calculations was performed using MELCOR 1.8.5 for a four-loop Westinghouse reactor with an ice condenser containment. The calculations covered five basic accident classes that were identified as the risk- and consequence-dominant accident sequences in plant-specific probabilistic risk assessments for the McGuire and Catawba nuclear plants, including station blackouts and loss-of-coolant accidents of various sizes, with both early and late containment failures. Ultimately, the results of these MELCOR simulations will be used to provide a supplement to the NRC's alternative source term described in NUREG-1465. Source term magnitude and timing results are presented consistent with the NUREG-1465 format. For each of the severe accident release phases (coolant release, gap release, in-vessel release, ex-vessel release, and late in-vessel release), source term timing information (onset of release and duration) is presented. For all release phases except for the coolant release phase, magnitudes are presented for each of the NUREG-1465 radionuclide groups. MELCOR results showed variation of noble metal releases between those typical of ruthenium (Ru) and those typical of molybdenum (Mo); therefore, results for the noble metals were presented for Ru and Mo separately. The collection of the source term results can be used as the basis to develop a representative source term (across all accident types) that will be the MOX supplement to NUREG-1465.

The Oak Ridge National Laboratory computer code, ORIGEN2.2 (CCC-371, 2002), was used to obtain the elemental composition of irradiated low-enriched uranium (LEU)/mixed-oxide (MOX) pressurized-water reactor fuel assemblies. Described in this report are the input parameters for the ORIGEN2.2 calculations. The rationale for performing the ORIGEN2.2 calculation was to generate inventories to be used to populate MELCOR radionuclide classes. Therefore the ORIGEN2.2 output was subsequently manipulated. The procedures performed in this data reduction process are also described herein. A listing of the ORIGEN2.2 input deck for two-cycle MOX is provided in the appendix. The final output from this data reduction process was three tables containing the radionuclide inventories for LEU/MOX in elemental form. Masses, thermal powers, and activities were reported for each category.

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In a recent acquisition by DOE/NNSA several large capacity computing clusters called TLCC have been installed at the DOE labs: SNL, LANL and LLNL. TLCC architecture with ccNUMA, multi-socket, multi-core nodes, and InfiniBand interconnect, is representative of the trend in HPC architectures. This paper examines application performance on TLCC contrasting them with Red Storm/Cray XT4. TLCC and Red Storm share similar AMD processors and memory DIMMs. Red Storm however has single socket nodes and custom interconnect. Micro-benchmarks and performance analysis tools help understand the causes for the observed performance differences. Control of processor and memory affinity on TLCC with the numactl utility is shown to result in significant performance gains and is essential to attenuate the detrimental impact of OS interference and cache-coherency overhead. While previous studies have investigated impact of affinity control mostly in the context of small SMP systems, the focus of this paper is on highly parallel MPI applications.

Geomechanical analyses have been performed to investigate potential mine interactions with wellbores that could occur in the Potash Enclave of Southeastern New Mexico. Two basic models were used in the study; (1) a global model that simulates the mechanics associated with mining and subsidence and (2) a wellbore model that examines the resulting interaction impacts on the wellbore casing. The first model is a 2D approximation of a potash mine using a plane strain idealization for mine depths of 304.8 m (1000 ft) and 609.6 m (2000 ft). A 3D wellbore model then considers the impact of bedding plane slippage across single and double cased wells cemented through the Salado formation. The wellbore model establishes allowable slippage to prevent casing yield.

An electromagnetic analysis is performed on the ITER shield modules under different plasma-disruption scenarios using the OPERA-3d software. The models considered include the baseline design as provided by the International Organization and an enhanced design that includes the more realistic geometrical features of a shield module. The modeling procedure is explained, electromagnetic torques are presented, and results of the modeling are discussed. © 2010 IEEE.

Two-dimensional (r, z) magnetohydrodynamic simulations with nonlocal thermodynamic equilibrium ionization and radiation transport are used to investigate the K-shell radiation output from doubly nested large-diameter (> 60 mm) stainlesssteel arrays fielded on the refurbished Z pulsed-power generator. The effects of the initial density perturbations, wire ablation rate, and current loss near the load on the total power, K-shell power, and K-shell yield are examined. The broad mass distribution produced by wire ablation largely overcomes the deleterious impact on the K-shell power and yield of 2-D instability growth. On the other hand, the possible current losses in the final feed section lead to substantial reductions in K-shell yield. Following a survey of runs, the parameters for the perturbation level, ablation rate, and current loss are chosen to benchmark the simulations against existing 65-mm-diameter radiation data. Themodel is then used to predict the K-shell properties of larger diameter (70 mm) arrays to be imploded on the Z generator. © 2010 IEEE.

There has been a concerted effort since 2007 to establish a dashboard of metrics for the Science, Technology, and Engineering (ST&E) work at Sandia National Laboratories. These metrics are to provide a self assessment mechanism for the ST&E Strategic Management Unit (SMU) to complement external expert review and advice and various internal self assessment processes. The data and analysis will help ST&E Managers plan, implement, and track strategies and work in order to support the critical success factors of nurturing core science and enabling laboratory missions. The purpose of this SAND report is to provide a guide for those who want to understand the ST&E SMU metrics process. This report provides an overview of why the ST&E SMU wants a dashboard of metrics, some background on metrics for ST&E programs from existing literature and past Sandia metrics efforts, a summary of work completed to date, specifics on the portfolio of metrics that have been chosen and the implementation process that has been followed, and plans for the coming year to improve the ST&E SMU metrics process.

Efficient design of hardware and software for large-scale parallel execution requires detailed understanding of the interactions between the application, computer, and network. The authors have developed a macroscale simulator (SST/macro) that permits the coarse-grained study of distributed-memory applications. In the presented work, applications using the Message Passing Interface (MPI) are simulated; however, the simulator is designed to allow inclusion of other programming models. The simulator is driven from either a trace file or a skeleton application. Trace files can be either a standard format (Open Trace Format) or a more detailed custom format (DUMPI). The simulator architecture is modular, allowing it to easily be extended with additional network models, trace file formats, and more detailed processor models. This paper describes the design of the simulator, provides performance results, and presents studies showing how application performance is affected by machine characteristics.

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The Phebus and VERCORS data have played an important role in contemporary understanding and modeling of fission product release and transport from damaged LWR fuel. The data from these test programs have allowed improvement of MELCOR modeling of release and transport processes for both low enrichment uranium fuel as well as high burnup and MOX fuels. The following paper describes the derivation, testing and incorporation of improved radionuclide release models into the MELCOR severe accident code.

The Phebus and VERCORS data have played an important role in contemporary understanding and modeling of fission product release and transport from damaged light water reactor fuel. The data from these test programs have allowed improvement of MELCOR modeling of release and transport processes for both low enrichment uranium fuel as well as high burnup and mixed oxide (MOX) fuels. This paper discusses the synthesis of these findings in the MELCOR severe accident code. Based on recent assessments of MELCOR 1.8.5 fission product release modeling against the Phebus FPT-1 test and on observations from the ISP-46 exercise, modifications to the default MELCOR 1.8.5 release models are recommended. The assessments identified an alternative set of Booth diffusion parameters recommended by ORNL (ORNL-Booth), which produced significantly improved release predictions for cesium and other fission product groups. Some adjustments to the scaling factors in the ORNL-Booth model were made for selected fission product groups, including UO{sub 2}, Mo and Ru in order to obtain better comparisons with the FPT-1 data. The adjusted model, referred to as 'Modified ORNL-Booth,' was subsequently compared to original ORNL VI fission product release experiments and to more recently performed French VERCORS tests, and the comparisons was as favorable or better than the original CORSOR-M MELCOR default release model. These modified ORNL-Booth parameters, input to MELCOR 1.8.5 as 'sensitivity coefficients' (i.e. user input that over-rides the code defaults) are recommended for the interim period until improved release models can be implemented into MELCOR. For the case of ruthenium release in air-oxidizing conditions, some additional modifications to the Ru class vapor pressure are recommended based on estimates of the RuO{sub 2} vapor pressure over mildly hyperstoichiometric UO{sub 2}. The increased vapor pressure for this class significantly increases the net transport of Ru from the fuel to the gas stream. A formal model is needed. Deposition patterns in the Phebus FPT-1 circuit were also significantly improved by using the modified ORNL-Booth parameters, where retention of lower volatile Cs{sub 2}MoO{sub 4} is now predicted in the heated exit regions of the FPT-1 test, bringing down depositions in the FPT-1 steam generator tube to be in closer alignment with the experimental data. This improvement in 'RCS' deposition behavior preserves the overall correct release of cesium to the containment that was observed even with the default CORSOR-M model. Not correctly treated however is the release and transport of Ag to the FPT-1 containment. A model for Ag release from control rods is presently not available in MELCOR. Lack of this model is thought to be responsible for the underprediction by a factor of two of the total aerosol mass to the FPT-1 containment. It is suggested that this underprediction of airborne mass led to an underprediction of the aerosol agglomeration rate. Underprediction of the agglomeration rate leads to low predictions of the aerosol particle size in comparison to experimentally measured ones. Small particle size leads low predictions of the gravitational settling rate relative to the experimental data. This error, however, is a conservative one in that too-low settling rate would result in a larger source term to the environment. Implementation of an interim Ag release model is currently under study. In the course of this assessment, a review of MELCOR release models was performed and led to the identification of several areas for future improvements to MELCOR. These include upgrading the Booth release model to account for changes in local oxidizing/reducing conditions and including a fuel oxidation model to accommodate effects of fuel stoichiometry. Models such as implemented in the French ELSA code and described by Lewis are considered appropriate for MELCOR. A model for ruthenium release under air oxidizing conditions is also needed and should be included as part of a fuel oxidation model since fuel stoichiometry is a fundamental parameter in determining the vapor pressure of ruthenium oxides over the fuel. There is also a need to expand the MELCOR architecture for tracking fission product classes to allow for more speciation of fission products. An example is the formation of CsI and Cs{sub 2}MoO{sub 4} and potentially CsOH if all Mo is combined with Cs such that excess Cs exists in the fuel. Presently, MELCOR can track only one class combination (CsI) accurately, where excess Cs is assumed to be CsOH. Our recommended interim modifications map the CsOH (MELCOR Radionuclide Class 2) and Mo (Class 7) vapor pressure properties to Cs{sub 2}MoO{sub 4}, which approximates the desired formal class combination of Cs and Mo. Other extensions to handle properly iodine speciation from pool/gas chemistry are also needed.

We present the Sandia Advanced Personnel Locator Engine (SAPLE) web application, a directory search application for use by Sandia National Laboratories personnel. SAPLE's purpose is to return Sandia personnel 'results' as a function of user search queries, with its mission to make it easier and faster to find people at Sandia. To accomplish this, SAPLE breaks from more traditional directory application approaches by aiming to return the correct set of results while placing minimal constraints on the user's query. Two key features form the core of SAPLE: advanced search query interpretation and inexact string matching. SAPLE's query interpretation permits the user to perform compound queries when typing into a single search field; where able, SAPLE infers the type of field that the user intends to search on based on the value of the search term. SAPLE's inexact string matching feature yields a high-quality ranking of personnel search results even when there are no exact matches to the user's query. This paper explores these two key features, describing in detail the architecture and operation of SAPLE. Finally, an extensive analysis on logged search query data taken from an 11-week sample period is presented.

Sandia National Laboratories (SNL) is a multi-program national laboratory in the business of national security, whose primary mission is nuclear weapons (NW). It is a prime contractor to the USDOE, operating under the NNSA and is one of the three NW national laboratories. It has a long history of involvement in the area of geomechanics, starting with the some of the earliest weapons tests at Nevada. Projects in which geomechanics support (in general) and computational geomechanics support (in particular) are at the forefront at Sandia, range from those associated with civilian programs to those in the defense programs. SNL has had significant involvement and participation in the Waste Isolation Pilot Plant (low-level defense nuclear waste), the Yucca Mountain Project (formerly proposed for commercial spent fuel and high-level nuclear waste), and the Strategic Petroleum Reserve (the nation's emergency petroleum store). In addition, numerous industrial partners seek-out our computational/geomechanics expertise, and there are efforts in compressed air and natural gas storage, as well as in CO{sub 2} Sequestration. Likewise, there have also been collaborative past efforts in the areas of compactable reservoir response, the response of salt structures associated with reservoirs, and basin modeling for the Oil & Gas industry. There are also efforts on the defense front, ranging from assessment of vulnerability of infrastructure to defeat of hardened targets, which require an understanding and application of computational geomechanics. Several examples from some of these areas will be described and discussed to give the audience a flavor of the type of work currently being performed at Sandia in the general area of geomechanics.

This report describes the Sandia National Laboratories Medical Isotope Reactor and hot cell facility concepts. The reactor proposed is designed to be capable of producing 100% of the U.S. demand for the medical isotope {sup 99}Mo. The concept is novel in that the fuel for the reactor and the targets for the {sup 99}Mo production are the same. There is no driver core required. The fuel pins that are in the reactor core are processed on a 7 to 21 day irradiation cycle. The fuel is low enriched uranium oxide enriched to less than 20% {sup 235}U. The fuel pins are approximately 1 cm in diameter and 30 to 40 cm in height, clad with Zircaloy (zirconium alloy). Approximately 90 to 150 fuel pins are arranged in the core in a water pool {approx}30 ft deep. The reactor power level is 1 to 2 MW. The reactor concept is a simple design that is passively safe and maintains negative reactivity coefficients. The total radionuclide inventory in the reactor core is minimized since the fuel/target pins are removed and processed after 7 to 21 days. The fuel fabrication, reactor design and operation, and {sup 99}Mo production processing use well-developed technologies that minimize the technological and licensing risks. There are no impediments that prevent this type of reactor, along with its collocated hot cell facility, from being designed, fabricated, and licensed today.

The Department of Homeland Security (DHS), National Cyber Security Division (NSCD), Control Systems Security Program (CSSP), contracted Sandia National Laboratories to develop a generic methodology for prioritizing cyber-vulnerable, critical infrastructure assets and the development of mitigation strategies for their loss or compromise. The initial project has been divided into three discrete deliverables: (1) A generic methodology report suitable to all Critical Infrastructure and Key Resource (CIKR) Sectors (this report); (2) a sector-specific report for Electrical Power Distribution; and (3) a sector-specific report for the water sector, including generation, water treatment, and wastewater systems. Specific reports for the water and electric sectors are available from Sandia National Laboratories.

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Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-model ensemble from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.

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We use the modified iSAFT density functional theory (DFT) to calculate interactions among nanoparticles immersed in a polymer melt. Because a polymer can simultaneously interact with more than two nanoparticles, three-body interactions are important in this system. We treat the nanoparticles as spherical surfaces, and solve for the polymer densities around the nanoparticles in three dimensions. The polymer is modeled as a freely-jointed chain of spherical sites, and all interactions are repulsive. The potential of mean force (PMF) between two nanoparticles displays a minimum at contact due to the depletion effect. The PMF calculated from the DFT agrees nearly quantitatively with that calculated from self-consistent PRISM theory. From the DFT we find that the three-body free energy is significantly different in magnitude than the effective three-body free energy derived from the two-particle PMF.

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Hybrid cells based on ZnO/P3HT heterojunctions have the advantage of better device stability, but suffer poor photovoltaic performance compared to all-organic cells which use PCBM as the electron acceptor. The photovoltaic effect in these hybrid systems is accomplished via photoinduced charge separation at the interface between the absorbing polymer (P3HT) and the electron acceptor (ZnO). Efforts to improve device performance in these hybrid systems have centered on reducing the required diffusion length for P3HT excitons by creating bulk heterojunctions from either ZnO nanoparticles and P3HT or using ZnO precursors which convert in situ to form ZnO networks inside a polymer matrix. In this study, we use transient photoinduced absorption to access the lifetimes of P3HT polarons and excitons in bulk heterojunctions constructed using P3HT and ZnO nanoparticles or ZnO precursors and compare to those in planar ZnO/P3HT devices. Steady-state photoinduced absorption spectra of ZnO/P3HT show characteristic of sub-bandgap transitions associated with the formation of long-lived (msec lifetimes) radical cations (polarons) in P3HT. Similar short-lived polarons (psec lifetimes) are observed by picosecond transient photoinduced absorption in addition to infrared absorption due to excitons. Here we examine the lifetimes of both the excitons and polarons in ZnO:P3HT bulk heterojunctions using both picosecond and millisecond techniques in an effort to understand the effect of the structure and morphology of the electron acceptor on charge separation. We will also compare the relative photoexitation lifetimes, hence charge separation efficiency, for the planar and bulk heterojunction hybrid system to an all-organic P3HT:PCBM system.

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Plasmonic integrated optics is an attempt to bridge the length scale gap between optics and nanometer scale electronic devices. Here we present a hybrid optical interconnect scheme which utilizes low loss dielectric waveguides for global interconnection and plasmonic structures for tightly confining light for local routing and mode manipulation.

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This model predicts thermal boundary conductance at interfaces where one material comprising the junction is characterized by high elastic anisotropy (i.e, graphite). The thermal properties of graphite are determined through a simplified vibrational model, where the bulk structure is treated as an linear assembly of two-dimensional systems. This model is validated at temperatures above cryogenic through comparison to experimentally determined values of specific heat. Elastic processes are accounted for through traditional diffuse transport theory. Inelastic contributions due to multi-phonon processes are also addressed and quantified.

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Sandia National Laboratories has developed a vehicle-scale prototype hydrogen storage system as part of a Work For Others project funded by General Motors. This Demonstration System was developed using the complex metal hydride sodium alanate. For the current work, we have continued our evaluation of the GM Demonstration System to provide learning to DOE's hydrogen storage programs, specifically the new Hydrogen Storage Engineering Center of Excellence. Baseline refueling data during testing for GM was taken over a narrow range of optimized parameter values. Further testing was conducted over a broader range. Parameters considered included hydrogen pressure and coolant flow rate. This data confirmed the choice of design pressure of the Demonstration System, but indicated that the system was over-designed for cooling. Baseline hydrogen delivery data was insufficient to map out delivery rate as a function of temperature and capacity for the full-scale system. A more rigorous matrix of tests was performed to better define delivery capabilities. These studies were compared with 1-D and 2-D coupled multi-physics modeling results. The relative merits of these models are discussed along with opportunities for improved efficiency or reduced mass and volume.

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Erbium metal thin-films have been deposited on molybdenum-on-silicon substrates and then converted to erbium dideuteride (ErD{sub 2}). Here, we study the effects of deposition temperature ({approx}300 or 723 K) and deposition rate (1 or 20 nm/s) upon the initial Er metal microstructure and subsequent ErD{sub 2} microstructure. We find that low deposition temperature and low deposition rate lead to small Er metal grain sizes, and high deposition temperature and deposition rate led to larger Er metal grain sizes, consistent with published models of metal thin-film growth. ErD{sub 2} grain sizes are strongly influenced by the prior-metal grain size, with small metal grains leading to large ErD{sub 2} grains. A novel sample preparation technique for electron backscatter diffraction of air-sensitive ErD{sub 2} was developed, and allowed the quantitative measurement of ErD{sub 2} grain size and crystallographic texture. Finer-grained ErD{sub 2} showed a strong (1 1 1) fiber texture, whereas larger grained ErD{sub 2} had only weak texture. We hypothesize that this inverse correlation may arise from improved hydrogen diffusion kinetics in the more defective fine-grained metal structure or due to improved nucleation in the textured large-grain Er.

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The ionospheric disturbance dynamo signature in geomagnetic variations is investigated using the National Center for Atmospheric Research Thermosphere-Ionosphere-Electrodynamics General Circulation Model. The model results are tested against reference magnetically quiet time observations on 21 June 1993, and disturbance effects were observed on 11 June 1993. The model qualitatively reproduces the observed diurnal and latitude variations of the geomagnetic horizontal intensity and declination for the reference quiet day in midlatitude and low-latitude regions but underestimates their amplitudes. The patterns of the disturbance dynamo signature and its source 'anti-Sq' current system are well reproduced in the Northern Hemisphere. However, the model significantly underestimates the amplitude of disturbance dynamo effects when compared with observations. Furthermore, the largest simulated disturbances occur at different local times than the observations. The discrepancies suggest that the assumed high-latitude storm time energy inputs in the model were not quantitatively accurate for this storm.

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We will describe how novel nanoporous framework materials (NFM) such as metal-organic frameworks (MOFs) can be interfaced with common mechanical sensors, such as surface acoustic wave (SAW), microcantilever array, and quartz crystal microbalance (QCM) devices, and subsequently be used to provide selectivity and sensitivity to a broad range of analytes including explosives, nerve agents, and volatile organic compounds (VOCs). NFM are highly ordered, crystalline materials with considerable synthetic flexibility resulting from the presence of both organic and inorganic components within their structure. Chemical detection using micro-electro-mechanical-systems (MEMS) devices (i.e. SAWs, microcantilevers) requires the use of recognition layers to impart selectivity. Unlike traditional organic polymers, which are dense, the nanoporosity and ultrahigh surface areas of NFM allow for greater analyte uptake and enhance transport into and out of the sensing layer. This enhancement over traditional coatings leads to improved response times and greater sensitivity, while their ordered structure allows chemical tuning to impart selectivity. We describe here experiments and modeling aimed at creating NFM layers tailored to the detection of water vapor, explosives, CWMD, and volatile organic compound (VOCs), and their integration with the surfaces of MEMS devices. Molecular simulation shows that a high degree of chemical selectivity is feasible. For example, a suite of MOFs can select for strongly interacting organics (explosives, CWMD) vs. lighter volatile organics at trace concentrations. At higher gas pressures, the CWMD are deselected in favor of the volatile organics. We will also demonstrate the integration of various NFM on the surface of microcantiliver arrays, QCM crystals, and SAW devices, and describe new synthetic methods developed to improve the quality of NFM coatings. Finally, MOF-coated MEMS devices show how temperature changes can be tuned to improve response times, selectivity, and sensitivity.

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Fire probabilistic risk assessment (PRA) methods utilize data and insights gained from actual fire events in a variety of ways. For example, fire occurrence frequencies, manual fire fighting effectiveness and timing, and the distribution of fire events by fire source and plant location are all based directly on the historical experience base. Other factors are either derived indirectly or supported qualitatively based on insights from the event data. These factors include the general nature and intensity of plant fires, insights into operator performance, and insights into fire growth and damage behaviors. This paper will discuss the potential methodology improvements that could be realized if more complete fire event reporting information were available. Areas that could benefit from more complete event reporting that will be discussed in the paper include fire event frequency analysis, analysis of fire detection and suppression system performance including incipient detection systems, analysis of manual fire fighting performance, treatment of fire growth from incipient stages to fully-involved fires, operator response to fire events, the impact of smoke on plant operations and equipment, and the impact of fire-induced cable failures on plant electrical circuits.

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This abstract explores the potential advantages of discontinuous Galerkin (DG) methods for the time-domain inversion of media parameters within the earth's interior. In particular, DG methods enable local polynomial refinement to better capture localized geological features within an area of interest while also allowing the use of unstructured meshes that can accurately capture discontinuous material interfaces. This abstract describes our initial findings when using DG methods combined with Runge-Kutta time integration and adjoint-based optimization algorithms for full-waveform inversion. Our initial results suggest that DG methods allow great flexibility in matching the media characteristics (faults, ocean bottom and salt structures) while also providing higher fidelity representations in target regions. Time-domain inversion using discontinuous Galerkin on unstructured meshes and with local polynomial refinement is shown to better capture localized geological features and accurately capture discontinuous-material interfaces. These approaches provide the ability to surgically refine representations in order to improve predicted models for specific geological features. Our future work will entail automated extensions to directly incorporate local refinement and adaptive unstructured meshes within the inversion process.

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Reprocessing nuclear fuel releases gaseous radio-iodine containing compounds which must be captured and stored for prolonged periods. Ag-loaded mordenites are the leading candidate for scavenging both organic and inorganic radioiodine containing compounds directly from reprocessing off gases. Alternately, the principal off-gas contaminant, I2, and I-containing acids HI, HIO3, etc. may be scavenged using caustic soda solutions, which are then treated with bismuth to put the iodine into an insoluble form. Our program is focused on using state-of-the-art materials science technologies to develop materials with high loadings of iodine, plus high long-term mechanical and thermal stability. In particular, we present results from research into two materials areas: (1) zeolite-based separations and glass encapsulation, and (2) in-situ precipitation of Bi-I-O waste forms. Ag-loaded mordenite is either commercially available or can be prepared via a simple Ag+ ion exchange process. Research using an Ag+-loaded Mordenite zeolite (MOR, LZM-5 supplied by UOP Corp.) has revealed that I2 is scavenged in one of three forms, as micron-sized AgI particles, as molecular (AgI)x clusters in the zeolite pores and as elemental I2 vapor. It was found that only a portion of the sorbed iodine is retained after heating at 95o C for three months. Furthermore, we show that even when the Ag-MOR is saturated with I2 vapor only roughly half of the silver reacted to form stable AgI compounds. However, the Iodine can be further retained if the AgI-MOR is then encapsulated into a low temperature glass binder. Follow-on studies are now focused on the sorption and waste form development of Iodine from more complex streams including organo-iodine compounds (CH3I). Bismuth-Iodate layered phases have been prepared from caustic waste stream simulant solutions. They serve as a low cost alternative to ceramics waste forms. Novel compounds have been synthesized and solubility studies have been completed using competing groundwater anions (HCO3-, Cl- and SO42-). Distinct variations in solubility were found that related to the structures of the materials.

Grand canonical Monte Carlo simulations were performed to investigate trends in low-pressure adsorption of a broad range of organic molecules by a set of metal-organic frameworks (MOFs). The organic analytes considered here are relevant to applications in chemical detection: small aromatics (o-, m-, and p-xylene), polycyclic aromatic hydrocarbons (naphthalene, anthracene, phenanthrene), explosives (TNT and RDX), and chemical warfare agents (GA and VM). The framework materials included several Zn-MOFs (IRMOFs 1-3, 7, 8), a Cr-MOF (CrMIL-53lp), and a Cu-MOF (HKUST-1). Many of the larger organics were significantly adsorbed by the target MOFs at low pressure, which is consistent with the exceptionally high isosteric heats of adsorption (25 kcal/mol - 60 kcal/mol) for this range of analyte. At a higher loading pressure of 101 kPa, the Zn-MOFs show a much higher volumetric uptake than either CrMIL-53-lp or HKUST-1 for all types of analyte. Within the Zn-MOF series, analyte loading is proportional to free volume, and loading decreases with increasing analyte size due to molecular packing effects. CrMIL-53lp showed the highest adsorption energy for all analytes, suggesting that this material may be suitable for low-level detection of organics.

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This paper discusses the recent development a statistical approach for the automatic identification of anomalous network activity that is characteristic of exfiltration events. This approach is based on the language processing method eferred to as latent dirichlet allocation (LDA). Cyber security experts currently depend heavily on a rule-based framework for initial detection of suspect network events. The application of the rule set typically results in an extensive list of uspect network events that are then further explored manually for suspicious activity. The ability to identify anomalous network events is heavily dependent on the experience of the security personnel wading through the network log. Limitations f this approach are clear: rule-based systems only apply to exfiltration behavior that has previously been observed, and experienced cyber security personnel are rare commodities. Since the new methodology is not a discrete rule-based pproach, it is more difficult for an insider to disguise the exfiltration events. A further benefit is that the methodology provides a risk-based approach that can be implemented in a continuous, dynamic or evolutionary fashion. This permits uspect network activity to be identified early with a quantifiable risk associated with decision making when responding to suspicious activity.

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Electron-interface scattering during electron-phonon nonequilibrium in thin films creates another pathway for electron system energy loss as characteristic lengths of thin films continue to decrease. As power densities in nanodevices increase, excitations of electrons from sub-conduction-band energy levels will become more probable. These sub-conduction-band electronic excitations significantly affect the material's thermophysical properties. In this work, the effects of d-band electronic excitations are considered in electron energy transfer processes in thin metal films. In thin films with thicknesses less than the electron mean free path, ballistic electron transport leads to electron-interface scattering. The ballistic component of electron transport, leading to electron-interface scattering, is studied by a ballistic-diffusive approximation of the Boltzmann Transport Equation. The effect of d-band excitations on electron-interface energy transfer is analyzed during electron-phonon nonequilibrium after short pulsed laser heating in thin films.

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Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-model ensemble from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.

Importance sampling is an unbiased sampling method used to sample random variables from different densities than originally defined. These importance sampling densities are constructed to pick 'important' values of input random variables to improve the estimation of a statistical response of interest, such as a mean or probability of failure. Conceptually, importance sampling is very attractive: for example one wants to generate more samples in a failure region when estimating failure probabilities. In practice, however, importance sampling can be challenging to implement efficiently, especially in a general framework that will allow solutions for many classes of problems. We are interested in the promises and limitations of importance sampling as applied to computationally expensive finite element simulations which are treated as 'black-box' codes. In this paper, we present a customized importance sampler that is meant to be used after an initial set of Latin Hypercube samples has been taken, to help refine a failure probability estimate. The importance sampling densities are constructed based on kernel density estimators. We examine importance sampling with respect to two main questions: is importance sampling efficient and accurate for situations where we can only afford small numbers of samples? And does importance sampling require the use of surrogate methods to generate a sufficient number of samples so that the importance sampling process does increase the accuracy of the failure probability estimate? We present various case studies to address these questions.

P- and S-body wave travel times collected from stations in and near the state of Nevada were inverted for P-wave velocity and the Vp/Vs ratio. These waves consist of Pn, Pg, Sn and Sg, but only the first arriving P and S waves were used in the inversion. Travel times were picked by University of Nevada Reno colleagues and were culled for inclusion in the tomographic inversion. The resulting tomographic model covers the entire state of Nevada to a depth of {approx}90 km; however, only the upper 40 km indicate relatively good resolution. Several features of interest are imaged including the Sierra Nevada, basin structures, and low velocities at depth below Yucca Mountain. These velocity structure images provide valuable information to aide in the interpretation of geothermal resource areas throughout the state on Nevada.

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The compressive mechanical response of fine sand is experimentally investigated. The strain rate, initial density, stress state, and moisture level are systematically varied. A Kolsky bar was modified to obtain uniaxial and triaxial compressive response at high strain rates. A controlled loading pulse allows the specimen to acquire stress equilibrium and constant strain-rates. The results show that the compressive response of the fine sand is not sensitive to strain rate under the loading conditions in this study, but significantly dependent on the moisture content, initial density and lateral confinement. Partially saturated sand is more compliant than dry sand. Similar trends were reported in the quasi-static regime for experiments conducted at comparable specimen conditions. The sand becomes stiffer as initial density and/or confinement pressure increases. The sand particle size become smaller after hydrostatic pressure and further smaller after dynamic axial loading.

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Innovative energy system optimization models are deployed to evaluate novel fuel cell system (FCS) operating strategies, not typically pursued by commercial industry. Most FCS today are installed according to a 'business-as-usual' approach: (1) stand-alone (unconnected to district heating networks and low-voltage electricity distribution lines), (2) not load following (not producing output equivalent to the instantaneous electrical or thermal demand of surrounding buildings), (3) employing a fairly fixed heat-to-power ratio (producing heat and electricity in a relatively constant ratio to each other), and (4) producing only electricity and no recoverable heat. By contrast, models discussed here consider novel approaches as well. Novel approaches include (1) networking (connecting FCSs to electrical and/or thermal networks), (2) load following (having FCSs produce only the instantaneous electricity or heat demanded by surrounding buildings), (3) employing a variable heat-to-power ratio (such that FCS can vary the ratio of heat and electricity they produce), (4) co-generation (combining the production of electricity and recoverable heat), (5) permutations of these together, and (6) permutations of these combined with more 'business-as-usual' approaches.

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Progress in algal biofuels has been limited by significant knowledge gaps in algal biology, particularly as they relate to scale-up. To address this we are investigating how culture composition dynamics (light as well as biotic and abiotic stressors) describe key biochemical indicators of algal health: growth rate, photosynthetic electron transport, and lipid production. Our approach combines traditional algal physiology with genomics, bioanalytical spectroscopy, chemical imaging, remote sensing, and computational modeling to provide an improved fundamental understanding of algal cell biology across multiple cultures scales. This work spans investigations from the single-cell level to ensemble measurements of algal cell cultures at the laboratory benchtop to large greenhouse scale (175 gal). We will discuss the advantages of this novel, multidisciplinary strategy and emphasize the importance of developing an integrated toolkit to provide sensitive, selective methods for detecting early fluctuations in algal health, productivity, and population diversity. Progress in several areas will be summarized including identification of spectroscopic signatures for algal culture composition, stress level, and lipid production enabled by non-invasive spectroscopic monitoring of the photosynthetic and photoprotective pigments at the single-cell and bulk-culture scales. Early experiments compare and contrast the well-studied green algae chlamydomonas with two potential production strains of microalgae, nannochloropsis and dunnaliella, under optimal and stressed conditions. This integrated approach has the potential for broad impact on algal biofuels and bioenergy and several of these opportunities will be discussed.

The quantification of the production of primary defects via displacement cascades is an important ingredient in the prediction of the influence of radiation on the performance of electronic components in radiation environments. Molecular dynamics simulations of displacement cascades are performed for GaAs The interatomic interactions are described using a recently proposed Bond Order Potential, and a simple model of electronic stopping is incorporated. The production of point defects is quantified as a function of recoil energy and recoil species. Correlations in the point defects are examined. There are a large number of anti-site defects nearest-neighbor pairs as well as di-vacancies and larger order vacancy clusters. Radiation damage and ion implantation in materials have been studied via molecular dynamics for many years. A significant challenge in these simulations is the detailed identification and quantification of the primary defect production. For the present case of a compound semiconductor, GaAs, there are a larger number of possible point defects compared to elemental materials; two types of vacancies, two types of interstitials and antisite defects. This is further complicated by the fact that, in addition to the formation of point defects, amorphous zones may also be created. The goal of the current work is to quantify the production of primary defects in GaAs due to radiation exposures. This information will be used as part of an effort to predict the influence of radiation environments on the performance of electronic components and circuits. The data provide the initial state for continuum-level analysis of the temporal evolution of defect populations. For this initial state, it is important to know both the number of the various point defects that may be produced as well as the initial spatial correlations between the primary defects. The molecular dynamics simulations employ a recently developed Bond Order Potential (BOP) for GaAs. The analysis of the resulting atomic configurations follows a generalization of methods presented previously for elemental Si. The number of point defects of various types, exclusive of the amorphous zones, is predicted as a function of recoil energy. It is also shown that certain primary point defects are initially formed in binary or larger clusters.