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At least 487 records · Page 27

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NASA NTRS1982

The role of multispectral scanners as data sources for EPA hydrologic models

An estimated cost savings of 30% to 50% was realized from using LANDSAT-derived data as input into a program which simulates hydrologic and water quality processes in natural and man-made water systems. Data from the satellite were used in conjunction with EPA's 11-channel multispectral scanner to obtain maps for characterizing the distribution of turbidity plumes in Flathead Lake and to predict the effect of increasing urbanization in Montana's Flathead River Basin on the lake's trophic state. Multispectral data are also being studied as a possible source of the parameters needed to model the buffering capability of lakes in an effort to evaluate the effect of acid rain in the Adirondacks. Water quality in Lake Champlain, Vermont is being classified using data from the LANDSAT and the EPA MSS. Both contact-sensed and MSS data are being used with multivariate statistical analysis to classify the trophic status of 145 lakes in Illinois and to identify water sampling sites in Appalachicola Bay where contaminants threaten Florida's shellfish.

Slack, R.↗

DOE OSTI2023

Cryogenic System Preliminary Design for a 0.5m-Long, Conduction-Cooled Nb3Sn Undulator Magnet Prototype

There are several NbTi superconducting undulator (SCU) magnets currently in operation at the Advanced Photon Source (APS) at Argonne National Laboratory (ANL). The development on Nb3Sn-based superconducting undulator magnets at APS is underway due to the potential to further enhance the performance of the SCUs. Superconducting undulator magnets need to keep temperature gradients minimized in order to retain thermal and operating current margin. We have designed the thermal links for efficient heat conduction using 3D finite element analysis (FEA) simulation in COMSOL Multiphysics software, which was later used for the calculation of the temperature distribution across a 0.5 m long, conduction-cooled, Nb3Sn undulator magnet prototype that includes both conductive heat transfer and radiative heating components. We have modelled the evolution of the thermal properties of the magnet winding as well as other cold parts during cool-down from ambient temperature with the operation of a SHI RDK-415D cryocooler to examine the estimated time that is needed for the cooldown as well as the baseline temperature we could achieve. A key result was that a maximum coil delta T = 0.11 K along the designed thermal links and a temperature range of 3.42 K-3.53 K for the winding were predicted at steady state. A pair of G10 support rods for carrying the magnet as well as a pair of current leads made of metals were also designed and optimized for the testing system, targeting for an operation temperature of 4 K and a coil current of 950 A DC.

Zhang, Danlu↗

DOE OSTI2025

Solving high-dimensional inverse problems using amortized likelihood-free inference with noisy and incomplete data

Here, we present a likelihood-free probabilistic inversion method based on normalizing flows for high-dimensional inverse problems. The proposed method is composed of two complementary networks: a summary network for data compression and an inference network for parameter estimation. The summary network encodes raw observations into a fixed-size vector of summary features, while the inference network generates samples of the approximate posterior distribution of the model parameters based on these summary features. The posterior samples are produced in a deep generative fashion by sampling from a latent Gaussian distribution and passing these samples through an invertible transformation. We construct this invertible transformation by sequentially alternating conditional invertible neural network and conditional neural spline flow layers. The summary and inference networks are trained simultaneously. We apply the proposed method to an inversion problem in groundwater hydrology to estimate the posterior distribution of the log-conductivity field conditioned on spatially sparse time-series observations of the system’s hydraulic head responses. The conductivity field is represented with 706 degrees of freedom in the considered problem. Comparison with the likelihood-based iterative ensemble smoother PEST-IES method demonstrates that the proposed method accurately estimates the parameter posterior distribution and the observations’ predictive posterior distribution at a fraction of the inference time of PEST-IES.

conditional invertible neural network↗

DOE OSTI2017

The Impacts of Changes to Nevada's Net Metering Policy on the Financial Performance and Adoption of Distributed Photovoltaics

As the adoption of distributed photovoltaics (DPV) has continued to rapidly increase, a national conversation has begun about the efficacy of full-retail net metering as a means of achieving the diverse objectives of electricity pricing. This conversation has prompted studies that have primarily focused on the total costs and benefits of DPV. To compliment those studies, we here characterize the potential impacts of tariff design on the customer-economics and adoption of DPV, where recent changes in Nevada are taken as a case study. We show that an increase in fixed charges more strongly impacts the payback period of small systems, and a decrease in credit for exported electricity more strongly impacts the payback period of large systems. We project that these combined changes will reduce DPV adoption in Nevada; total capacity in 2030 was projected to reach up to 363 MW, with 226 MW having already been installed at the end of the second quarter of 2016. In contrast, if full retail net metering had continued, DPV capacity was projected to reach up to 1,280 MW at the end of 2030, which would account for an estimated 6.5% of the total sales of electricity by NV Energy at that time. We project that the DPV systems will decrease the gross revenue from bill collection by $48 million per year under the new tariffs, whereas the decrease in gross revenue could have reached $255 million per year if full retail net metering had been continued. Although these results are given in the context of Nevada, the trends shown are intended to help information similar upcoming decisions in other states.

14 SOLAR ENERGY↗

NASA NTRS2002

In vitro cell irradiation systems based on 210Po alpha source: construction and characterisation

One way of studying the risk to human health of low-level radiation exposure is to make biological experiments on living cell cultures. Two 210Po alpha-particle emitting devices, with 0.5 and 100 MBq activity, were designed and constructed to perform such experiments irradiating monolayers of cells. Estimates of dose rate at the cell surface were obtained from measurements by a PIPS alpha-particle spectrometer and from calculations by the SRIM 2000, Monte Carlo charged particle transport code. Particle fluence area distributions were measured by solid state nuclear track detectors. The design and dosimetric characterisation of the devices are discussed. c2002 Elsevier Science Ltd. All rights reserved.

Alpha Particles↗

NASA NTRS2012

Understanding Climate Policy Data Needs. NASA Carbon Monitoring System Briefing: Characterizing Flux Uncertainty, Washington D.C., 11 January 2012

Climate policy in the United States is currently guided by public-private partnerships and actions at the local and state levels. This mitigation strategy is made up of programs that focus on energy efficiency, renewable energy, agricultural practices and implementation of technologies to reduce greenhouse gases. How will policy makers know if these strategies are working, particularly at the scales at which they are being implemented? The NASA Carbon Monitoring System (CMS) will provide information on carbon dioxide fluxes derived from observations of earth's land, ocean and atmosphere used in state of the art models describing their interactions. This new modeling system could be used to assess the impact of specific policy interventions on CO2 reductions, enabling an iterative, results-oriented policy process. In January of 2012, the CMS team held a meeting with carbon policy and decision makers in Washington DC to describe the developing modeling system to policy makers. The NASA CMS will develop pilot studies to provide information across a range of spatial scales, consider carbon storage in biomass, and improve measures of the atmospheric distribution of carbon dioxide. The pilot involves multiple institutions (four NASA centers as well as several universities) and over 20 scientists in its work. This pilot study will generate CO2 flux maps for two years using observational constraints in NASA's state-of -the-art models. Bottom-up surface flux estimates will be computed using data-constrained land and ocean models; comparison of the different techniques will provide some knowledge of uncertainty in these estimates. Ensembles of atmospheric carbon distributions will be computed using an atmospheric general circulation model (GEOS-5), with perturbations to the surface fluxes and to transport. Top-down flux estimates will be computed from observed atmospheric CO2 distributions (ACOS/GOSAT retrievals) alongside the forward-model fields, in conjunction with an inverse approach based on the CO2 model of GEOS ]Chem. The forward model ensembles will be used to build understanding of relationships among surface flux perturbations, transport uncertainty and atmospheric carbon concentration. This will help construct uncertainty estimates and information on the true spatial resolution of the top-down flux calculations. The relationship between the top-down and bottom-up flux distributions will be documented. Because the goal of NASA CMS is to be policy relevant, the scientists involved in the flux modeling pilot need to understand and be focused on the needs of the climate policy and decision making community. If policy makers are to use CMS products, they must be aware of the modeling effort and begin to design policies that can be evaluated with information. Improving estimates of carbon sequestered in forests, for example, will require information on the spatial variability of forest biomass that is far more explicit than is presently possible using only ground observations. Carbon mitigation policies being implemented by cities around the United States could be designed with the CMS data in mind, enabling sequential evaluation and subsequent improvements in incentives, structures and programs. The success of climate mitigation programs being implemented in the United States today will hang on the depth of the relationship between scientists and their policy and decision making counterparts. Ensuring that there is two-way communication between data providers and users is important for the success both of the policies and the scientific products meant to support them..

Brown, Molly E.↗

DOE OSTI2025

Preserving nonlinear constraints in variational flow filtering data assimilation

Data assimilation aims to estimate the states of a dynamical system by optimally combining sparse and noisy observations of the physical system with uncertain forecasts produced by a computational model. The states of many dynamical systems of interest obey nonlinear physical constraints, and the corresponding dynamics is confined to a certain sub-manifold of the state space. Standard data assimilation techniques applied to such systems yield posterior states lying outside the manifold, violating the physical constraints. This work focuses on particle flow filters which use stochastic differential equations to evolve state samples from a prior distribution to samples from an observation-informed posterior distribution. The variational Fokker-Planck (VFP)—a generic particle flow filtering framework—is extended to incorporate non-linear, equality state constraints in the analysis. To this end, two algorithmic approaches that modify the VFP stochastic differential equation are discussed: (i) VFPSTAB, to inexactly preserve constraints with the addition of a stabilizing drift term, and (ii) VFPDAE, to exactly preserve constraints by treating the VFP dynamics as a stochastic differential-algebraic equation (SDAE). Additionally, an implicit-explicit time integrator is developed to evolve the VFPDAE dynamics. The strength of the proposed approach for constraint preservation in data assimilation is demonstrated on three test problems: the double pendulum, Korteweg-de-Vries, and the incompressible Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Reactor simulations with nuclear data uncertainties

This work demonstrates the influence of uncertainties in microscopic nuclear data on the results of reactor simulations, both for stationary and transient states. It gives an overview on the methods in use for uncertainty and sensitivity analyses with respect to nuclear data, and discusses the pros and cons. For full-scale reactor simulations, in particular with coupled neutron transport and thermo-hydraulics, random sampling provides a powerful means to propagate nuclear data uncertainties through the complete calculation sequence. Results of uncertainty analyses performed with the GRS XSUSA – “cross section (XS) Uncertainty and Sensitivity Analysis” methodology are shown for radial power distributions from steady-state PWR calculations and for the time evolution of the reactor power in the course of a control rod withdrawal from a PWR mini-core. In all cases, the output uncertainties are considerable. For the radial power distributions, relative 1σ uncertainties of up to 10% are observed, and for the power peak during the transient, the relative 1σ uncertainty reaches 20%. These large uncertainties strongly suggest to routinely accompany best-estimate simulations by uncertainty analyses with respect to nuclear data, in particular for systems beyond LWR for which much less operation experience is available.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2009

Modular Battery Charge Controller

A new approach to masterless, distributed, digital-charge control for batteries requiring charge control has been developed and implemented. This approach is required in battery chemistries that need cell-level charge control for safety and is characterized by the use of one controller per cell, resulting in redundant sensors for critical components, such as voltage, temperature, and current. The charge controllers in a given battery interact in a masterless fashion for the purpose of cell balancing, charge control, and state-of-charge estimation. This makes the battery system invariably fault-tolerant. The solution to the single-fault failure, due to the use of a single charge controller (CC), was solved by implementing one CC per cell and linking them via an isolated communication bus [e.g., controller area network (CAN)] in a masterless fashion so that the failure of one or more CCs will not impact the remaining functional CCs. Each micro-controller-based CC digitizes the cell voltage (V(sub cell)), two cell temperatures, and the voltage across the switch (V); the latter variable is used in conjunction with V(sub cell) to estimate the bypass current for a given bypass resistor. Furthermore, CC1 digitizes the battery current (I1) and battery voltage (V(sub batt) and CC5 digitizes a second battery current (I2). As a result, redundant readings are taken for temperature, battery current, and battery voltage through the summation of the individual cell voltages given that each CC knows the voltage of the other cells. For the purpose of cell balancing, each CC periodically and independently transmits its cell voltage and stores the received cell voltage of the other cells in an array. The position in the array depends on the identifier (ID) of the transmitting CC. After eight cell voltage receptions, the array is checked to see if one or more cells did not transmit. If one or more transmissions are missing, the missing cell(s) is (are) eliminated from cell-balancing calculations. The cell-balancing algorithm is based on the error between the cell s voltage and the other cells and is categorized into four zones of operation. The algorithm is executed every second and, if cell balancing is activated, the error variable is set to a negative low value. The largest error between the cell and the other cells is found and the zone of operation determined. If the error is zero or negative, then the cell is at the lowest voltage and no balancing action is needed. If the error is less than a predetermined negative value, a Cell Bad Flag is set. If the error is positive, then cell balancing is needed, but a hysteretic zone is added to prevent the bypass circuit from triggering repeatedly near zero error. This approach keeps the cells within a predetermined voltage range.

Button, Robert↗

DOE OSTI2015

Tools for Enhanced Grid Operation and Optimized PV Penetration Utilizing Highly Distributed Sensor Data.

Increasing number s of PV on distribution systems are creating more grid impacts , but it also provides more opportunities for measurement, sensing, and control of the grid in a distributed fashion. This report demonstrates three software tools for characterizing and controlling distribution feeders by utilizing large numbers of highly distributed current, voltage , and irradiance sensors. Instructions and a user manual is presented for each tool. First, the tool for distribution system secondary circuit parameter estimation is presented. This tool allows studying distribution system parameter estimation accuracy with user-selected active power, reactive power, and voltage measurements and measurement error levels. Second, the tool for multi-objective inverter control is shown. Various PV inverter control strategies can be selected to objectively compare their impact on the feeder. Third, the tool for energy storage for PV ramp rate smoothing is presented. The tool allows the user to select different storage characteristics (power and energy ratings) and control types (local vs. centralized) to study the tradeoffs between state-of-charge (SOC) management and the amount of ramp rate smoothing.

Reno, Matthew J.↗

NASA NTRS1974

Utility of ERTS for monitoring the breeding habit of migratory waterfowl

Waterfowl breeding-ground surveys conducted each year by the Bureau of Sport Fisheries and Wildlife extend over a vast region of the United States and Canada. Data from these surveys are used to estimate waterfowl production by means of a mathematical model. Counts of May and July ponds are some the variables used in this model. Annual production estimates are used to predict fall flights of ducks. This information is then used for establishing waterfowl hunting regulations. Work to date indicates that satellite remote sensing techniques hold considerable promise for the accurate and rapid assessment of waterfowl breeding habitat, especially changes in pond numbers and distribution. Development of an operational system utilizing satellite sensors as a primary source of data appears to be a realistic goal for the future.

Work, E. W., Jr.↗

DOE OSTI2025

Dynamics modeling of molten salt reactor with reduced and expanded representations of delayed neutron precursors

Molten salt reactors (MSRs) present unique challenges in dynamic behavior due to the mobility of their fuel. In these reactors, delayed neutron precursors (DNPs) drift with the fuel circulation through the primary loop. As a result, a fraction of DNPs decays outside the core, effectively reducing the available delayed neutron population for reactivity control. Consequently, precise modeling of the distribution and behavior of DNPs is critical for accurate reactor dynamics simulations. In this study, the System Dynamics Analysis Tool (SDAT) was used to simulate a thermal-spectrum MSR under steady-state conditions and following transients. The effects of using reduced and expanded representations of DNPs with fewer or more groups than the conventional 6-group model were investigated. Their impact on the simulated distribution of precursors in the primary loop, reactivity loss value, and reactor response to transients was analyzed. Simulation results showed that reduced models lead to the loss of the actual DNPs distribution data, resulting in less accurate estimates of reactivity loss. Reactor power predictions using these reduced models showed significant deviations compared to those using the conventional 6-group model in transient simulations. Expanded models offered a more accurate representation of the distribution of DNPs and reactivity loss estimates. Reactor power predictions using expanded models showed minimal deviation from the conventional 6-group model during the simulated transients.

analysis↗

DOE OSTI2020

GridOPTICS/GridPACK

GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.

Palmer, Bruce↗

NASA NTRS2005

Latent Heating from TRMM Satellite Measurements

Rainfall production is a fundamental process within the Earth;s hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations with the Tropics - as well as modify the energetic efficiencies of mid-latitude weather systems. This paper highlights the retrieval of observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional amount of rainfall over the global Tropics and sub-tropics - information which can be used to estimate the spacetime structure of latent heating across the Earth's low latitudes. A set of algorithm methodologies has and continues to be developed to estimate latent heating based on rain rate profile retrievals obtained from TRMM measurements. These algorithms are briefly described followed by a discussion of the foremost latent heating products that can be generate from them. The investigation then provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

Tao, W.-K.↗

DOE OSTI2019

System of ideal quantum dots with Coulomb interaction

The wave functions of single-electron states localised on a system of single-level ideal quantum dots in a semiconductor matrix are constructed. The standard Kane theory, which describes the renormalisation of the effective mass of electrons in bulk III − V semiconductors, is transformed, for the first time as far as we know, for small-size quantum dots. The renormalised electron mass in a quantum dot depends on its ground state energy, which, in turn, depends on this mass. Thus, a self-consistent problem is obtained for calculating the electron binding energy. The radius of the Debye screening of the Coulomb interaction in a system of quantum dots is calculated at room temperature. The Coulomb repulsion of electrons localised on dots limits from above the possible number of filled dots. The condition is formulated for the optimal concentration of quantum dots. A classical distribution function for the probability of quantum dot filling is constructed. It is found the state, where electrons fill exactly half the maximum possible number of filled dots, exhibits the minimal energy (and therefore the most stable), the condition being fairly universal. In particular, it can be used to estimate the limiting efficiency of quantum-dot diode lasers. (quantum dots)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

The Pilatus unmanned aircraft system for lower atmospheric research

This study presents details of the University of Colorado (CU) “Pilatus” unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2016

The Pilatus Unmanned Aircraft System for Lower Atmospheric Research

This paper presents details of the University of Colorado (CU) "Pilatus" unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.

de Boer, Gijs↗

DOE OSTI2018

Energy Resilience Solutions for the Puerto Rico Grid; Final Report June 2018

Hurricane Maria was the second strongest storm on record to hit Puerto Rico when it struck the territory of the United States on September 20, 2017. On that evening, it was estimated by the Puerto Rico Electric Power Authority (PREPA) that near 100% of total customers in Puerto Rico were without power, This report contains recommendations for the Government of Puerto Rico to consider for incorporation into its recovery plans including the plan that Congress required from the Federal Emergency Management Agency (FEMA) to support the Commonwealth in developing through Section 21210 of P.L. 115-123 (2018). The recommendations cover the subjects of Transmission and Distribution; Generation; Microgrids; and System Operations, Management, and Planning. Collectively, the recommendations are intended to inform investments that use federal appropriations in the energy infrastructure in the Commonwealth of Puerto Rico.

24 POWER TRANSMISSION AND DISTRIBUTION↗