Publications

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.

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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.

An improved gas-damping model for the out-of-plane motion of a near-substrate microbeam is developed based on the Reynolds equation (RE). A boundary condition for the RE is developed that relates the pressure at the beam edge to the beam motion. The coefficients in this boundary condition are determined from Navier-Stokes slip-jump (NSSJ) simulations for small slip lengths (relative to the gap height) and from direct simulation Monte Carlo (DSMC) molecular gas dynamics simulations for larger slip lengths. This boundary condition significantly improves the accuracy of the RE when the microbeam width is only slightly greater than the gap height between the microbeam and the substrate. The improved RE model is applied to microbeams fabricated using the SUMMiT V process. © 2004 IEEE.

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.

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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.

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