We show theoretically that an electric current in a high-mobility quasi-two-dimensional electron layer induces a significant drift of excitons in an adjacent layer through interlayer Coulomb interaction. The exciton gas is shown to drift with a velocity which can be a significant fraction of the electron drift velocity at low temperatures. The estimated drift length is of the order of micrometers or larger during the typical exciton lifetime for GaAs/Al{sub x}Ga{sub 1-x} double quantum wells. A possible enhancement of the exciton radiative lifetime due to the drift is discussed.
The U.S. Department of Energy's (DOE's) GeoPowering the West (GPW) program works with the U.S. geothermal industry, power companies, industrial and residential consumers, and federal, state, and local officials to provide technical and institutional support and limited, cost-shared funding to state-level activities. By demonstrating the benefits of geothermal energy, GPW increases state and regional awareness of opportunities to enhance local economies and strengthen our nation's energy security while minimizing environmental impact. By identifying barriers to development and working with others to eliminate them, GPW helps a state or region create a regulatory and economic environment that is more favorable for geothermal and other renewable energy development. Electricity is produced using expanding steam or very hot water from the underground reservoir to spin a conventional turbine-generator. Geothermal power plants operate at high capacity factors (70-100%), with availability factors typically greater than 95%. Geothermal plants are among the cleanest sources of electric power available. Direct use applications directly pipe hot water from geothermal resources to provide heat for industrial processes, crop drying, greenhouses, aquaculture, recreation, sidewalk snow-melting, and buildings. Geothermal district heating systems supply heat to multiple buildings through a network of pipes carrying the hot geothermal water.
The effects of wall interaction on combustion and soot formation processes of a diesel fuel jet were investigated in an optically-accessible constant-volume combustion vessel at experimental conditions typical of a diesel engine. At identical ambient and injector conditions, soot processes were studied in free jets, plane wall jets, and 'confined' wall jets (a box-shaped geometry simulating secondary interaction with adjacent walls and jets in an engine). The investigation showed that soot levels are significantly lower in a plane wall jet compared to a free jet. At some operating conditions, sooting free jets become soot-free as plane wall jets. Possible mechanisms to explain the reduced or delayed soot formation upon wall interaction include an increased fuel-air mixing rate and a wall-jet-cooling effect. However, in a confined-jet configuration, there is an opposite trend in soot formation. Jet confinement causes combustion gases to be redirected towards the incoming jet, causing the lift-off length to shorten and soot to increase. This effect can be avoided by ending fuel injection prior to the time of significant interaction with redirected combustion gases. For a fixed confined-wall geometry, an increase in ambient gas density delays jet interaction, allowing longer injection durations with no increase in soot. Jet interaction with redirected combustion products may also be avoided using reduced ambient oxygen concentration because of an increased ignition delay. Although simplified geometries were employed, the identification of important mechanisms affecting soot formation after the time of wall interaction is expected to be useful for understanding these processes in more complex and realistic diesel engine geometries.
One challenge faced by engineers today is replicating an operating environment such as transportation in a test lab. This paper focuses on the process of identifying sine-on-random content in an aircraft transportation environment, although the methodology can be applied to other events. The ultimate goal of this effort was to develop an automated way to identify significant peaks in the PSDs of the operating data, catalog the peaks, and determine whether each peak was sinusoidal or random in nature. This information helps design a test environment that accurately reflects the operating environment. A series of Matlab functions have been developed to achieve this goal with a relatively high degree of accuracy. The software is able to distinguish between sine-on-random and random-on-random peaks in most cases. This paper describes the approach taken for converting the time history segments to the frequency domain, identifying peaks from the resulting PSD, and filtering the time histories to determine the peak amplitude and characteristics. This approach is validated through some contrived data, and then applied to actual test data. Observations and conclusions, including limitations of this process, are also presented.
Dielectric spectroscopy, lattice structure, and thermal properties have revealed the relaxor dielectric response of Ba-substituted lead zirconate/titanate (PZT) having the composition (Pb0.71Ba0.29) (Zr0.71Ti0.29)O3 and containing 2 at. % Bi as an additive. The relaxor behavior is attributed to the compositional disorder introduced by the substitution of Ba2+ at the A site and Bi3+/5+ at the B site (and possibly A site) of the ABO3 PZT host lattice. Analysis of the results gives clear evidence for the nucleation of polar nanodomains at a temperature much higher than the peak (Tm) in the dielectric susceptibility. These nanodomains grow in size as their correlation length increases with decreasing temperature, and ultimately their dipolar fluctuations slow down below Tm leading to the formation of the relaxor state. The influences of hydrostatic pressure on the dielectric susceptibility and the dynamics of the relaxation of the polar nanodomains were investigated and can be understood in terms of the decrease in the size of the nanodomains with pressure. The influence of dc electrical bias on the susceptibility was also investigated. Physical models of the relaxor response of this material are discussed.
Preliminary investigation areas (PIA) for a potential repository of high-level radioactive waste must be evaluated by NUMO with regard to a number of qualifying factors. One of these factors is related to earthquakes and fault activity. This study develops a spatial statistical assessment method that can be applied to the active faults in Japan to perform such screening evaluations. This analysis uses the distribution of seismicity near faults to define the width of the associated process zone. This concept is based on previous observations of aftershock earthquakes clustered near active faults and on the assumption that such seismic activity is indicative of fracturing and associated impacts on bedrock integrity. Preliminary analyses of aggregate data for all of Japan confirmed that the frequency of earthquakes is higher near active faults. Data used in the analysis were obtained from NUMO and consist of three primary sources: (1) active fault attributes compiled in a spreadsheet, (2) earthquake hypocenter data, and (3) active fault locations. Examination of these data revealed several limitations with regard to the ability to associate fault attributes from the spreadsheet to locations of individual fault trace segments. In particular, there was no direct link between attributes of the active faults in the spreadsheet and the active fault locations in the GIS database. In addition, the hypocenter location resolution in the pre-1983 data was less accurate than for later data. These pre-1983 hypocenters were eliminated from further analysis.
The Arsenic Water Technology Partnership (AWTP) program is a multi-year program funded by a congressional appropriation through the Department of Energy to develop and test innovative technologies that have the potential to reduce the costs of arsenic removal from drinking water. The AWTP members include Sandia National Laboratories, the American Water Works Association (Awwa) Research Foundation and WERC (A Consortium for Environmental Education and Technology Development). The program is designed to move technologies from bench-scale tests to field demonstrations. The Awwa Research Foundation is managing bench-scale research programs; Sandia National Laboratories is conducting the pilot demonstration program and WERC will evaluate the economic feasibility of the technologies investigated and conduct technology transfer activities. The objective of the Sandia Arsenic Treatment Technology Demonstration project (SATTD) is the field demonstration testing of both commercial and innovative technologies. The scope for this work includes: (1) Identification of sites for pilot demonstrations; (2) Accelerated identification of candidate technologies through Vendor Forums, proof-of-principle laboratory and local pilot-scale studies, collaboration with the Awwa Research Foundation bench-scale research program and consultation with relevant advisory panels; and (3) Pilot testing multiple technologies at several sites throughout the country, gathering information on: (a) Performance, as measured by arsenic removal; (b) Costs, including capital and Operation and Maintenance (O&M) costs; (c) O&M requirements, including personnel requirements, and level of operator training; and (d) Waste residuals generation. The New Mexico Environment Department has identified over 90 public water systems that currently exceed the 10 {micro}g/L MCL for arsenic. The Sandia Arsenic Treatment Technology Demonstration project is currently operating pilots at three sites in New Mexico. The cities of Socorro, Anthony, and Rio Rancho vary in population, water chemistry, and source of arsenic. Figure 1 shows the locations of each city. The following pages summarize the work being performed at each site. At each site, the owners (e.g. city utility) provide access to the site, water, electricity, means to discharge treated water, and daily operational checks. Daily checks include filling out a logsheet with information on the flow rates, pressure drops, flow adjustments (when needed), and notification of Sandia personnel if a leak is present. Sandia owns all equipment and is responsible for the disposal of spent media and other waste streams. Sandia also performs all field tests and collects water samples for laboratory analysis.
We present theoretical performance estimates for nanotube optoelectronic devices under bias. Current-voltage characteristics of illuminated nanotube p-n junctions are calculated using a self-consistent nonequilibrium Green's function approach. Energy conversion rates reaching tens of percent are predicted for incident photon energies near the band gap energy. In addition, the energy conversion rate increases as the diameter of the nanotube is reduced, even though the quantum efficiency shows little dependence on nanotube radius. These results indicate that the quantum efficiency is not a limiting factor for use of nanotubes in optoelectronics.
Tabu search is one of the most effective heuristics for locating high-quality solutions to a diverse array of NP-hard combinatorial optimization problems. Despite the widespread success of tabu search, researchers have a poor understanding of many key theoretical aspects of this algorithm, including models of the high-level run-time dynamics and identification of those search space features that influence problem difficulty. We consider these questions in the context of the job-shop scheduling problem (JSP), a domain where tabu search algorithms have been shown to be remarkably effective. Previously, we demonstrated that the mean distance between random local optima and the nearest optimal solution is highly correlated with problem difficulty for a well-known tabu search algorithm for the JSP introduced by Taillard. In this paper, we discuss various shortcomings of this measure and develop a new model of problem difficulty that corrects these deficiencies. We show that Taillard's algorithm can be modeled with high fidelity as a simple variant of a straightforward random walk. The random walk model accounts for nearly all of the variability in the cost required to locate both optimal and sub-optimal solutions to random JSPs, and provides an explanation for differences in the difficulty of random versus structured JSPs. Finally, we discuss and empirically substantiate two novel predictions regarding tabu search algorithm behavior. First, the method for constructing the initial solution is highly unlikely to impact the performance of tabu search. Second, tabu tenure should be selected to be as small as possible while simultaneously avoiding search stagnation; values larger than necessary lead to significant degradations in performance.
Contaminant dispersal models for use at scales ranging from meters to miles are widely used for planning sensor locations, first-responder actions for release scenarios, etc. and are constantly being improved. Applications range from urban contaminant dispersal to locating buried targets from an exhaust signature. However, these models need detailed data for model improvement and validation. A small Sandia National Laboratories Laboratory Directed Research and Development (LDRD) program was funded in FY04 to examine the feasibility and usefulness of a scale-model capability for quantitative characterization of flow and contaminant dispersal in complex environments. This report summarizes the work performed in that LDRD. The basics of atmospheric dispersion and dispersion modeling are reviewed. We examine the need for model scale data, and the capability of existing model test methods. Currently, both full-scale and model scale experiments are performed in order to collect validation data for numerical models. Full-scale experiments are expensive, are difficult to repeat, and usually produce relatively sparse data fields. Model scale tests often employ wind tunnels, and the data collected is, in many cases, derived from single point measurements. We review the scaling assumptions and methods that are used to relate model and full scale flows. In particular, we examine how liquid flows may be used to examine the process of atmospheric dispersion. The scaling between liquid and gas flows is presented. Use of liquid as the test fluid has some advantages in terms of achieving fully turbulent Reynolds numbers and in seeding the flow with neutrally buoyant tracer particles. In general, using a liquid flow instead of a gas flow somewhat simplifies the use of full field diagnostics, such as Particle Image Velocimetry and Laser Induced Fluorescence. It is also possible to create stratified flows through mixtures of fluids (e.g., water, alcohol, and brine). Lastly, we describe our plan to create a small prototype water flume for the modeling of stratified atmospheric flows around complex objects. The incoming velocity profile could be tailored to produce a realistic atmospheric boundary layer for flow-in-urban-canyon measurements. The water tunnel would allow control of stratification to produce, for example, stable and unstable atmospheric conditions. Models ranging from a few buildings to cityscapes would be used as the test section. Existing noninvasive diagnostics would be applied, including particle image velocimetry for detailed full-field velocity measurement, and laser induced fluorescence for noninvasive concentration measurement. This scale-model facility will also be used as a test-bed for data acquisition and model testing related to the inverse problem, i.e., determination of source location from distributed, sparse measurement locations. In these experiments the velocity field would again be measured and data from single or multiple concentration monitors would be used to locate the continuous or transient source.
We present a model for optimizing the placement of sensors in municipal water networks to detect maliciously injected contaminants. An optimal sensor configuration minimizes the expected fraction of the population at risk. We formulate this problem as a mixed-integer program, which can be solved with generally available solvers. We find optimal sensor placements for three test networks with synthetic risk and population data. Our experiments illustrate that this formulation can be solved relatively quickly and that the predicted sensor configuration is relatively insensitive to uncertainties in the data used for prediction.
As Sandia looks toward petaflops computing and other advanced architectures, it is necessary to provide a programming environment that can exploit this additional computing power while supporting reasonable development time for applications. Thus, they evaluate the Partitioned Global Address Space (PGAS) programming model as implemented in Unified Parallel C (UPC) for its applicability. They report on their experiences in implementing sorting and minimum spanning tree algorithms on a test system, a Cray T3e, with UPC support. They describe several macros that could serve as language extensions and several building-block operations that could serve as a foundation for a PGAS programming library. They analyze the limitations of the UPC implementation available on the test system, and suggest improvements necessary before UPC can be used in a production environment.
The SSP is a hardware implementation of a subset of the JVM for use in high consequence embedded applications. In this context, a majority of the activities belonging to class loading, as it is defined in the specification of the JVM, can be performed statically. Static class loading has the net result of dramatically simplifying the design of the SSP as well as increasing its performance. Due to the high consequence nature of its applications, strong evidence must be provided that all aspects of the SSP have been implemented correctly. This includes the class loader. This article explores the possibility of formally verifying a class loader for the SSP implemented in the strategic programming language TL. Specifically, an implementation of the core activities of an abstract class loader is presented and its verification in ACL2 is considered.
The mathematical and physical foundations and domain of applicability of Sandia's GeoModel are presented along with descriptions of the source code and user instructions. The model is designed to be used in conventional finite element architectures, and (to date) it has been installed in five host codes without requiring customizing the model subroutines for any of these different installations. Although developed for application to geological materials, the GeoModel actually applies to a much broader class of materials, including rock-like engineered materials (such as concretes and ceramics) and even to metals when simplified parameters are used. Nonlinear elasticity is supported through an empirically fitted function that has been found to be well-suited to a wide variety of materials. Fundamentally, the GeoModel is a generalized plasticity model. As such, it includes a yield surface, but the term 'yield' is generalized to include any form of inelastic material response including microcrack growth and pore collapse. The geomodel supports deformation-induced anisotropy in a limited capacity through kinematic hardening (in which the initially isotropic yield surface is permitted to translate in deviatoric stress space to model Bauschinger effects). Aside from kinematic hardening, however, the governing equations are otherwise isotropic. The GeoModel is a genuine unification and generalization of simpler models. The GeoModel can employ up to 40 material input and control parameters in the rare case when all features are used. Simpler idealizations (such as linear elasticity, or Von Mises yield, or Mohr-Coulomb failure) can be replicated by simply using fewer parameters. For high-strain-rate applications, the GeoModel supports rate dependence through an overstress model.
An integrated system for the fusion of product and process sensors and controls for production of flat glass was envisioned, having as its objective the maximization of throughput and product quality subject to emission limits, furnace refractory wear, and other constraints. Although the project was prematurely terminated, stopping the work short of its goal, the tasks that were completed show the value of the approach and objectives. Though the demonstration was to have been done on a flat glass production line, the approach is applicable to control of production in the other sectors of the glass industry. Furthermore, the system architecture is also applicable in other industries utilizing processes in which product uniformity is determined by ability to control feed composition, mixing, heating and cooling, chemical reactions, and physical processes such as distillation, crystallization, drying, etc. The first phase of the project, with Visteon Automotive Systems as industrial partner, was focused on simulation and control of the glass annealing lehr. That work produced the analysis and computer code that provide the foundation for model-based control of annealing lehrs during steady state operation and through color and thickness changes. In the second phase of the work, with PPG Industries as the industrial partner, the emphasis was on control of temperature and combustion stoichiometry in the melting furnace, to provide a wider operating window, improve product yield, and increase energy efficiency. A program of experiments with the furnace, CFD modeling and simulation, flow measurements, and sensor fusion was undertaken to provide the experimental and theoretical basis for an integrated, model-based control system utilizing the new infrastructure installed at the demonstration site for the purpose. In spite of the fact that the project was terminated during the first year of the second phase of the work, the results of these first steps toward implementation of model-based control were sufficient to demonstrate the value of the approach to improving the productivity of glass manufacture.
Given pre-existing Groundwater Modeling System (GMS) models of the Horonobe Underground Research Laboratory (URL) at both the regional and site scales, this work performs an example uncertainty analysis for performance assessment (PA) applications. After a general overview of uncertainty and sensitivity analysis techniques, the existing GMS sitescale model is converted to a PA model of the steady-state conditions expected after URL closure. This is done to examine the impact of uncertainty in site-specific data in conjunction with conceptual model uncertainty regarding the location of the Oomagari Fault. In addition, a quantitative analysis of the ratio of dispersive to advective forces, the F-ratio, is performed for stochastic realizations of each conceptual model. All analyses indicate that accurate characterization of the Oomagari Fault with respect to both location and hydraulic conductivity is critical to PA calculations. This work defines and outlines typical uncertainty and sensitivity analysis procedures and demonstrates them with example PA calculations relevant to the Horonobe URL.
One problem facing today's nuclear power industry is flow-accelerated corrosion and erosion in pipe elbows. The Korean Atomic Energy Research Institute (KAERI) is performing experiments in their Flow-Accelerated Corrosion (FAC) test loop to better characterize these phenomena, and develop advanced sensor technologies for the condition monitoring of critical elbows on a continuous basis. In parallel with these experiments, Sandia National Laboratories is performing Computational Fluid Dynamic (CFD) simulations of the flow in one elbow of the FAC test loop. The simulations are being performed using the FLUENT commercial software developed and marketed by Fluent, Inc. The model geometry and mesh were created using the GAMBIT software, also from Fluent, Inc. This report documents the results of the simulations that have been made to date; baseline results employing the RNG k-e turbulence model are presented. The predicted value for the diametrical pressure coefficient is in reasonably good agreement with published correlations. Plots of the velocities, pressure field, wall shear stress, and turbulent kinetic energy adjacent to the wall are shown within the elbow section. Somewhat to our surprise, these indicate that the maximum values of both wall shear stress and turbulent kinetic energy occur near the elbow entrance, on the inner radius of the bend. Additional simulations were performed for the same conditions, but with the RNG k-e model replaced by either the standard k-{var_epsilon}, or the realizable k-{var_epsilon} turbulence model. The predictions using the standard k-{var_epsilon} model are quite similar to those obtained in the baseline simulation. However, with the realizable k-{var_epsilon} model, more significant differences are evident. The maximums in both wall shear stress and turbulent kinetic energy now appear on the outer radius, near the elbow exit, and are {approx}11% and 14% greater, respectively, than those predicted in the baseline calculation; secondary maxima in both quantities still occur near the elbow entrance on the inner radius. Which set of results better reflects reality must await experimental corroboration. Additional calculations demonstrate that whether or not FLUENT's radial equilibrium pressure distribution option is used in the PRESSURE OUTLET boundary condition has no significant impact on the flowfield near the elbow. Simulations performed with and without the chemical sensor and associated support bracket that were present in the experiments demonstrate that the latter have a negligible influence on the flow in the vicinity of the elbow. The fact that the maxima in wall shear stress and turbulent kinetic energy occur on the inner radius is therefore not an artifact of having introduced the sensor into the flow.
This document summarizes the equations and applications associated with the photovoltaic array performance model developed at Sandia National Laboratories over the last twelve years. Electrical, thermal, and optical characteristics for photovoltaic modules are included in the model, and the model is designed to use hourly solar resource and meteorological data. The versatility and accuracy of the model has been validated for flat-plate modules (all technologies) and for concentrator modules, as well as for large arrays of modules. Applications include system design and sizing, 'translation' of field performance measurements to standard reporting conditions, system performance optimization, and real-time comparison of measured versus expected system performance.