Publications

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As increasing numbers of photovoltaic (PV) systems are connected to utility systems, distribution engineers are becoming increasingly concerned about the risk of formation of unintentional islands. Utilities desire to keep their systems secure, while not imposing unreasonable burdens on users wishing to connect PV. However, utility experience with these systems is still relatively sparse, so distribution engineers often are uncertain as to when additional protective measures, such as direct transfer trip, are needed to avoid unintentional island formation. In the absence of such certainty, utilities must err on the side of caution, which in some cases may lead to the unnecessary requirement of additional protection. The purpose of this document is to provide distribution engineers and decision makers with guidance on when additional measures or additional study may be prudent, and also on certain cases in which utilities may allow PV installations to proceed without additional study because the risk of an unintentional island is extremely low. The goal is to reduce the number of cases of unnecessary application of additional protection, while giving utilities a basis on which to request additional study in cases where it is warranted.

This report explores the technical feasibility of prospective utility-scale photovoltaic system (PV) deployments in Utah. Sandia National Laboratories worked with Rocky Mountain Power (RMP), a division of PacifiCorp operating in Utah, to evaluate prospective 2-megawatt (MW) PV plants in different locations with respect to energy production and possible impact on the RMP system and customers. The study focused on 2-MW{sub AC} nameplate PV systems of different PV technologies and different tracking configurations. Technical feasibility was evaluated at three different potential locations in the RMP distribution system. An advanced distribution simulation tool was used to conduct detailed time-series analysis on each feeder and provide results on the impacts on voltage, demand, voltage regulation equipment operations, and flicker. Annual energy performance was estimated.

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The annual program report provides detailed information about all aspects of the Sandia National Laboratories, California (SNL/CA) Chemical Management Program. It functions as supporting documentation to the SNL/CA Environmental Management System Program Manual. This program annual report describes the activities undertaken during the calender past year, and activities planned in future years to implement the Chemical Management Program, one of six programs that supports environmental management at SNL/CA. SNL/CA is responsible for tracking chemicals (chemical and biological materials), providing Material Safety Data Sheets (MSDS) and for regulatory compliance reporting according to a variety of chemical regulations. The principal regulations for chemical tracking are the Emergency Planning Community Right-to-Know Act (EPCRA) and the California Right-to-Know regulations. The regulations, the Hazard Communication/Lab Standard of the Occupational Safety and Health Administration (OSHA) are also key to the CM Program. The CM Program is also responsible for supporting chemical safety and information requirements for a variety of Integrated Enabling Services (IMS) programs primarily the Industrial Hygiene, Waste Management, Fire Protection, Air Quality, Emergency Management, Environmental Monitoring and Pollution Prevention programs. The principal program tool is the Chemical Information System (CIS). The system contains two key elements: the MSDS library and the chemical container-tracking database that is readily accessible to all Members of the Sandia Workforce. The primary goal of the CM Program is to ensure safe and effective chemical management at Sandia/CA. This is done by efficiently collecting and managing chemical information for our customers who include Line, regulators, DOE and ES and H programs to ensure compliance with regulations and to streamline customer business processes that require chemical information.

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This document describes the implementation level changes in the source code and input files of Sandia National Laboratories Environmental Fluid Dynamics Code (SNL-EFDC) that are necessary for including pH effects into algae-growth dynamics. The document also gives a brief introduction to how pH effects are modeled into the algae-growth model. The document assumes that the reader is aware of the existing algae-growth model in SNL-EFDC. The existing model is described by James, Jarardhanam and more theoretical considerations behind modeling pH effects are presented therein. This document should be used in conjunction with the original EFDC manual and the original water-quality manual.

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Water quality signals from sensors provide a snapshot of the water quality at the monitoring station at discrete sample times. These data are typically processed by event detection systems to determine the probability of a water quality event occurring at each sample time. Inherent noise in sensor data and rapid changes in water quality due to operational actions can cause false alarms in event detection systems. While the event determination can be made solely on the data from each signal at the current time step, combining data across signals and backwards in time can provide a richer set of data for event detection. Here we examine the ability of algebraic combinations and other transformations of the raw signals to further decrease false alarms. As an example, using operational events such as one or more pumps turning on or off to define a period of decreased detection sensitivity is one approach to limiting false alarms. This method is effective when lag times are known or when the sensors are co-located with the equipment causing the change. The CANARY software was used to test and demonstrate these combinatorial techniques for improving sensitivity and decreasing false alarms on both background data and data with simulated events. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. © 2012 ASCE.

The optimization of sensor placements is a key aspect of the design of contaminant warning systems for automatically detecting contaminants in water distribution systems. Although researchers have generally assumed that all sensors are placed at the same time, in practice sensor networks will likely grow and evolve over time. For example, limitations for a water utility's budget may dictate an staged, incremental deployment of sensors over many years. We describe optimization formulations of multi-stage sensor placement problems. The objective of these formulations includes an explicit trade-off between the value of the initially deployed and final sensor networks. This trade-off motivates the deployment of sensors in initial stages of the deployment schedule, even though these choices typically lead to a solution that is suboptimal when compared to placing all sensors at once. These multi-stage sensor placement problems can be represented as mixed-integer programs, and we illustrate the impact of this trade-off using standard commercial solvers. We also describe a multi-stage formulation that models budget uncertainty, expressed as a tree of potential budget scenarios through time. Budget uncertainty is used to assess and hedge against risks due to a potentially incomplete deployment of a planned sensor network. This formulation is a multi-stage stochastic mixed-integer program, which are notoriously difficult to solve. We apply standard commercial solvers to small-scale test problems, enabling us to effectively analyze multi-stage sensor placement problems subject to budget uncertainties, and assess the impact of accounting for such uncertainty relative to a deterministic multi-stage model. © 2012 ASCE.

We present a mixed-integer linear programming formulation to determine optimal locations for manual grab sampling after the detection of contaminants in a water distribution system. The formulation selects optimal manual grab sample locations that maximize the total pair-wise distinguishability of candidate contamination events. Given an initial contaminant detection location, a source inversion is performed that will eliminate unlikely events resulting in a much smaller set of candidate contamination events. We then propose a cyclical process where optimal grab samples locations are determined and manual grab samples taken. Relying only on YES/NO indicators of the presence of contaminant, source inversion is performed to reduce the set of candidate contamination events. The process is repeated until the number of candidate events is sufficiently small. Case studies testing this process are presented using water network models ranging from 4 to approximately 13000 nodes. The results demonstrate that the contamination event can be identified within a remarkably small number of sampling cycles using very few sampling teams. Furthermore, solution times were reasonable making this formulation suitable for real-time settings. © 2012 ASCE.

We consider qubit coupling resulting from the capacitive coupling between two double quantum dot (DQD) singlet-triplet qubits. Calculations of the coupling when the two DQDs are detuned symmetrically or asymmetrically are performed using a full configuration interaction (CI). The full CI reveals behavior that is not observed by more commonly used approximations such as Heitler London or Hund Mulliken, particularly related to the operation of both DQDs in the (0,2) charge sector. We find that there are multiple points in detuning space where a two-qubit entangling gate can be realized, and that tradeoffs between coupling magnitude and sensitivity to fluctuations in detuning make a case for operating the gate in the (0,2) regime not commonly considered. © 2012 American Physical Society.

Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.

The safe handling of reprocessed fuel addresses several scientific goals, especially when considering the capture and long-term storage of volatile radionuclides that are necessary during this process. Despite not being a major component of the offgas, radioiodine (I 2) is particularly challenging, because it is a highly mobile gas and 129I is a long-lived radionuclide (1.57 × 10 7 years). Therefore, its capture and sequestration is of great interest on a societal level. Herein, we explore novel routes toward the effective capture and storage of iodine. In particular, we report on the novel use of a new class of porous solid-state functional materials (metal-organic frameworks, MOFs), as high-capacity adsorbents of molecular iodine. We further describe the formation of novel glass-composite material (GCM) waste forms from the mixing and sintering of the I 2-containing MOFs with Bi-Zn-O low-temperature sintering glasses and silver metal flakes. Our findings indicate that, upon sintering, a uniform monolith is formed, with no evidence of iodine loss; iodine is sequestered during the heating process by the in situ formation of AgI. Detailed materials characterization analysis is presented for the GCMs. This includes powder X-ray diffraction, scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), thermal analysis (thermogravimetric analysis (TGA)), and chemical durability tests including aqueous leach studies (product consistency test (PCT)), with X-ray fluorescence (XRF) and inductively coupled plasma-mass spectrometry (ICP-MS) of the PCT leachate. © 2011 American Chemical Society.

Optical absorption due to surface plasmon resonances in ensembles of gold nanorods (Au NRs) depends strongly on the nanorod separation and orientation. Here, we study the dispersion of polystyrene-functionalized Au NRs in polystyrene (PS) thin films using UV-visible (UV-vis) spectroscopy and transmission electron microscopy (TEM) and find that Au NRs are dispersed for brush chain lengths that exceed the PS matrix chain length and are aggregated otherwise. Monte Carlo simulations using parameters from classical density functional theory (DFT) calculations indicate that this behavior is due to substantial depletion-attraction forces for brush chain lengths that are much smaller than the PS matrix chain length. Both UV-vis measurements and discrete dipole approximation (DDA) calculations confirm that optical absorption is a facile method to determine nanorod morphology in nanocomposite films (i.e., aggregation or dispersion). Futhermore, a dispersion map is constructed showing the conditions required for nanorod dispersion and, correspondingly, the optical absorption properties of Au NR:PS nanocomposites. Using this information, optically active materials with tunable morphologies can be fabricated and routinely characterized using optical spectroscopic methods. © 2011 American Chemical Society.

Magnetized inertial fusion (MIF) could substantially ease the difficulty of reaching plasma conditions required for significant fusion yields, but it has been widely accepted that the gain is not sufficient for fusion energy. Numerical simulations are presented showing that high-gain MIF is possible in cylindrical liner implosions based on the MagLIF concept [S. A. Slutz et al Phys. Plasmas 17, 056303 (2010)PHPAEN1070-664X10.1063/1.3333505] with the addition of a cryogenic layer of deuterium-tritium (DT). These simulations show that a burn wave propagates radially from the magnetized hot spot into the surrounding much denser cold DT given sufficient hot-spot areal density. For a drive current of 60 MA the simulated gain exceeds 100, which is more than adequate for fusion energy applications. The simulated gain exceeds 1000 for a drive current of 70 MA. © 2012 American Physical Society.

Rechargeable, all-solid-state Li ion batteries (LIBs) with high specific capacity and small footprint are highly desirable to power an emerging class of miniature, autonomous microsystems that operate without a hardwire for power or communications. A variety of three-dimensional (3D) LIB architectures that maximize areal energy density has been proposed to address this need. The success of all of these designs depends on an ultrathin, conformal electrolyte layer to electrically isolate the anode and cathode while allowing Li ions to pass through. However, we find that a substantial reduction in the electrolyte thickness, into the nanometer regime, can lead to rapid self-discharge of the battery even when the electrolyte layer is conformal and pinhole free. We demonstrate this by fabricating individual, solid-state nanowire core-multishell LIBs (NWLIBs) and cycling these inside a transmission electron microscope. For nanobatteries with the thinnest electrolyte, ≈110 nm, we observe rapid self-discharge, along with void formation at the electrode/electrolyte interface, indicating electrical and chemical breakdown. With electrolyte thickness increased to 180 nm, the self-discharge rate is reduced substantially, and the NWLIBs maintain a potential above 2 V for over 2 h. Analysis of the nanobatteries' electrical characteristics reveals space-charge limited electronic conduction, which effectively shorts the anode and cathode electrodes directly through the electrolyte. Our study illustrates that, at these nanoscale dimensions, the increased electric field can lead to large electronic current in the electrolyte, effectively shorting the battery. The scaling of this phenomenon provides useful guidelines for the future design of 3D LIBs. © 2011 American Chemical Society.

We present the results of large-scale molecular dynamics simulations of two different nanolithographic processes, step-flash imprint lithography (SFIL), and hot embossing. We insert rigid stamps into an entangled bead-spring polymer melt above the glass transition temperature. After equilibration, the polymer is then hardened in one of two ways, depending on the specific process to be modeled. For SFIL, we cross-link the polymer chains by introducing bonds between neighboring beads. To model hot embossing, we instead cool the melt to below the glass transition temperature. We then study the ability of these methods to retain features by removing the stamps, both with a zero-stress removal process in which stamp atoms are instantaneously deleted from the system as well as a more physical process in which the stamp is pulled from the hardened polymer at fixed velocity. We find that it is necessary to coat the stamp with an antifriction coating to achieve clean removal of the stamp. We further find that a high density of cross-links is necessary for good feature retention in the SFIL process. The hot embossing process results in good feature retention at all length scales studied as long as coated, low surface energy stamps are used. © 2011 American Chemical Society.

Due to the high intrinsic thermal conductivity of carbon allotropes, there have been many attempts to incorporate such structures into existing thermal abatement technologies. In particular, carbon nanotubes (CNTs) and graphitic materials (i.e., graphite and graphene flakes or stacks) have garnered much interest due to the combination of both their thermal and mechanical properties. However, the introduction of these carbon-based nanostructures into thermal abatement technologies greatly increases the number of interfaces per unit length within the resulting composite systems. Consequently, thermal transport in these systems is governed as much by the interfaces between the constituent materials as it is by the materials themselves. This paper reports the behavior of phononic thermal transport across interfaces between isotropic thin films and graphite substrates. Elastic and inelastic diffusive transport models are formulated to aid in the prediction of conductance at a metal-graphite interface. The temperature dependence of the thermal conductance at Au-graphite interfaces is measured via transient thermoreflectance from 78 to 400 K. It is found that different substrate surface preparations prior to thin film deposition have a significant effect on the conductance of the interface between film and substrate. © 2012 American Society of Mechanical Engineers.

Simulation of mobility-driven abnormal grain growth in the presence of particles in a 3D Potts Monte Carlo model has been investigated, and even though the driving force in this case is identical to normal grain growth, Zener pinning does not occur. Instead the particles seem merely to have a small inhibiting effect on the number of abnormal grains, and this effect only has a noticeable influence for volume fractions of particles above 5 vol%. © (2012) Trans Tech Publications, Switzerland.

Grain growth in nanocrystalline Ni has been simulated by molecular dynamics. The simulations show the creation of a high density of twin boundaries during the growth as well as the formation of vacancies consistent with recent experimental observations. The growth follows parabolic kinetics with the diameter increasing with the square root of time consistent with behavior of conventional scale metals but in disagreement with prior simulation results. © (2012) Trans Tech Publications, Switzerland.

During large-strain plastic deformation, subgrain structures typically develop within the grains. At large enough equivalent strains above, say 0.5, recrystallization occurs via abnormal coarsening of the subgrain structure or abnormal (sub-) grain growth (AsGG). The fraction of subgrains that develop into new, recrystallized grains has been quantified as a function of texture spread (Grain Reference Orientation Deviation) using Monte Carlo simulation. When this fraction is combined with the known monotonic increase in mean misorientation with strain, the recrystallized grain size can be predicted as a function of von Mises strain. The prediction is in good agreement with experimental results drawn from the literature. © (2012) Trans Tech Publications, Switzerland.