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At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluation of Global Climate Models for Use in Energy Analysis

The interplay between energy, climate, and weather is becoming more complex due to increasing contributions of renewable energy generation, energy storage, electrified end uses, and the increasing frequency of extreme weather events. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and subjective process. In this work, we assess datasets from various global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We present evaluations of their skills with respect to the historical climate and comparisons of their future projections of climate change for two climate change scenarios. We present the results for different climatic and energy system regions and include interactive figures in the accompanying software repository. Previous work has presented similar GCM evaluations, but none have presented variables and metrics specifically intended for comprehensive energy systems analysis including impacts on energy demand, thermal cooling, hydropower, water availability, solar energy generation, and wind energy generation. We focus on GCM output meteorological variables that directly affect these energy system components including the representation of extreme values that can drive grid resilience events. The objective of this work is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and scenarios in subsequent work.

14 SOLAR ENERGY↗
DOE OSTI2022

How Does Flow Alteration Propagate Across a Large, Highly Regulated Basin? Dam Attributes, Network Context, and Implications for Biodiversity

Abstract Large dams are a leading cause of river ecosystem degradation. Although dams have cumulative effects as water flows downstream in a river network, most flow alteration research has focused on local impacts of single dams. Here we examined the highly regulated Colorado River Basin (CRB) to understand how flow alteration propagates in river networks, as influenced by the location and characteristics of dams as well as the structure of the river network—including the presence of tributaries. We used a spatial Markov network model informed by 117 upstream‐downstream pairs of monthly flow series (2003–2017) to estimate flow alteration from 84 intermediate‐to‐large dams representing >83% of the total storage in the CRB. Using Least Absolute Shrinkage and Selection Operator regression, we then investigated how flow alteration was influenced by local dam properties (e.g., purpose, storage capacity) and network‐level attributes (e.g., position, upstream cumulative storage). Flow alteration was highly variable across the network, but tended to accumulate downstream and remained high in the main stem. Dam impacts were explained by network‐level attributes (63%) more than by local dam properties (37%), underscoring the need to consider network context when assessing dam impacts. High‐impact dams were often located in sub‐watersheds with high levels of native fish biodiversity, fish imperilment, or species requiring seasonal flows that are no longer present. These three biodiversity dimensions, as well as the amount of dam‐free downstream habitat, indicate potential to restore river ecosystems via controlled flow releases. Our methods are transferrable and could guide screening for dam reoperation in other highly regulated basins.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Molecular mechanisms underlying host-induced gene silencing

Abstract Host-induced gene silencing (HIGS) refers to the silencing of genes in pathogens and pests by expressing homologous double-stranded RNAs (dsRNA) or artificial microRNAs (amiRNAs) in the host plant. The discovery of such trans-kingdom RNA silencing has enabled the development of RNA interference-based approaches for controlling diverse crop pathogens and pests. Although HIGS is a promising strategy, the mechanisms by which these regulatory RNAs translocate from plants to pathogens, and how they induce gene silencing in pathogens, are poorly understood. This lack of understanding has led to large variability in the efficacy of various HIGS treatments. This variability is likely due to multiple factors, such as the ability of the target pathogen or pest to take up and/or process RNA from the host, the specific genes and target sequences selected in the pathogen or pest for silencing, and where, when, and how the dsRNAs or amiRNAs are produced and translocated. In this review, we summarize what is currently known about the molecular mechanisms underlying HIGS, identify key unanswered questions, and explore strategies for improving the efficacy and reproducibility of HIGS treatments in the control of crop diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

The challenges of modelling antibody repertoire dynamics in HIV infection

Antibody affinity maturation by somatic hypermutation of B-cell immunoglobulin variable region genes has been studied for decades in various model systems using well-defined antigens. While much is known about the molecular details of the process, our understanding of the selective forces that generate affinity maturation are less well developed, particularly in the case of a co-evolving pathogen such as HIV. Despite this gap in understanding, high-throughput antibody sequence data are increasingly being collected to investigate the evolutionary trajectories of antibody lineages in HIV-infected individuals. Here, we review what is known in controlled experimental systems about the mechanisms underlying antibody selection and compare this to the observed temporal patterns of antibody evolution in HIV infection. In addition, we describe how our current understanding of antibody selection mechanisms leaves questions about antibody dynamics in HIV infection unanswered. Without a mechanistic understanding of antibody selection in the context of a co-evolving viral population, modelling and analysis of antibody sequences in HIV-infected individuals will be limited in their interpretation and predictive ability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Catalyst Ammonia Storage Measurements Using Radio Frequency Sensing1

Motivated by increasingly strict nitrogen oxides (NOx) limits, engine manufacturers have adopted selective catalytic reduction (SCR) technology to reduce engine-out NOx. In the SCR process, NOx react with ammonia (NH3) to form nitrogen and water vapor. The reaction is influenced by several variables, including stored ammonia on the catalyst, exhaust gas composition, and catalyst temperature. Currently, measurements from NOx and/or NH3 sensors upstream and downstream of the SCR are used with predictive models to estimate ammonia storage levels on the catalyst and control urea dosing. This study investigated a radio frequency (RF)-based method to directly monitor the ammonia storage state of the SCR. This approach utilizes the catalyst as a cavity resonator, in which an RF antenna excites electromagnetic waves within the cavity to monitor changes in the catalyst state. Ammonia storage causes changes in the dielectric properties of the catalyst, which directly impacts the RF signal. Changes in the RF signal relative to stored ammonia (NH3) were evaluated over a wide range of frequencies, temperatures, and exhaust conditions. The RF response to NH3 storage, desorption, and oxidation on the SCR was well correlated with changes in the catalyst state. Calibrated RF measurements demonstrate the ability to monitor the adsorption state of the SCR to within 10% of the sensor full scale. The results indicate direct measurement of SCR ammonia storage levels, and resulting catalyst feedback control, via RF sensing to have significant potential for optimizing the SCR system to improve NOx conversion and decrease urea consumption.

Engineering↗
DOE OSTI2024

Matilda v1.0: An R package for probabilistic climate projections using a reduced complexity climate model

A primary advantage to using reduced complexity climate models (RCMs) has been their ability to quickly conduct probabilistic climate projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses has been a target of several RCMs used in studies of the future co-evolution of the human and Earth systems. In this paper, we present Matilda, an open-science R software package that facilitates probabilistic climate projection analysis, implemented here using the Hector simple climate model in a seamless and easily applied framework. The primary goal of Matilda is to provide the user with a turn-key method to build parameter sets from literature-based prior distributions, run Hector iteratively to produce perturbed parameter ensembles (PPEs), weight ensembles for realism against observed historical climate data, and compute probabilistic projections for different climate variables. This workflow gives the user the ability to explore viable parameter space and propagate uncertainty to model ensembles with just a few lines of code. The package provides significant freedom to select different scoring criteria and algorithms to weight ensemble members, as well as the flexibility to implement custom criteria. Additionally, the architecture of the package simplifies the process of building and analyzing PPEs without requiring significant programming expertise, to accommodate diverse use cases. We present a case study that provides illustrative results of a probabilistic analysis of mean global surface temperature as an example of the software application.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Distributed Rules-Based Deconfliction of ADMS Applications: Part 1: Requirements & Decomposition

This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. This first document introduces the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem is decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. Selection of the optimal number of decompositions of the deconfliction problem should be made based on a tradeoff analysis between computational speed and global optimality. This second document will define an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Application of Principal Component Analysis to Electrochemical Reprocessing PM and NMAC

In this report, data from an electrorefiner (ER) for nuclear fuel reprocessing is evaluated for process monitoring (PM) conclusions. This data comes from tests performed at the Idaho National Laboratory in 2022. Multivariate approaches utilizing methods of Principal Component Analysis (PCA) is applied. This is based off established work in process monitoring for fault detection in industrial facilities. This report will discuss the background, methods, and results of the application and some of the conclusions and applications that can be drawn from them. PCA is applied to two different electrorefiner (ER) operations that occurred at Idaho National Laboratory between August and October 2022. The first operation occurred with little incident while the second had several noted faults in the equipment in operational logs. The data from the first run was used to train the data for “normal” operations and applied to both sets of data to determine when operations were in an “off-normal” condition and identify where the fault occurs through PCA. PCA was able to identify off-normal events and identify the cause for off-normal operations. These identified off-normal events matched with the events and their causes in the operational logs. However, small amounts of variance in the data led to false detection of “off-normal” events. Thus, careful selection of training data and a-posteriori conclusions based off operator assessments will both be required for application of PCA to PM applications. This work demonstrated that multivariate approaches and latent variables are applicable to pyroprocessing PM applications and can be further expanded in future work as quality variables such as salt concentration from sensors and sampling become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1974

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. Primary emphasis during the period has been given to completing the resource and land use mask overlays for ultimate subsite MSS data extraction and analysis, refining the computer mask program, verifying resultant masks, and evaluating the initial subsite data. Standard deviations for the selected subsites were generally reduced significantly when compared to the values for the overall 7km x 7km test site areas. This indicates that the masking technique has been successful in reducing the variability of the ERTS-1 MSS data for ultimate subsite comparisons with ground data. The techniques used to locate the 7km x 7km test site areas and extract masked subsite data apparently limit the ability to reliably locate identical very small subsite areas for temporal comparisons. Current evidence indicates that areas which include less than about four pixel elements in either dimension are probably unreliable.

Rouse, J. W., Jr.↗
NASA NTRS1989

Ginga observations of dipping low mass X ray binaries

Ginga observations of several low mass X ray binaries displaying pronounced dips of variable depth and duration in their X ray light curves are analyzed. The periodic occultation of the central X ray source by azimuthal accretion disk structure is considered. A series of spectra selected by intensity from the dip data from XB1916-053, are presented. The effects of a rapidly changing column density upon the spectral fitting results are modeled. EXO0748-676 was observed in March 1989 for three days. The source was found to be in a bright state with a 1 to 20 keV flux of 8.8 x 10 (exp -10) erg/sqcms. The data include two eclipses, observed with high time resolution.

Smale, Alan P.↗
NASA NTRS1989

Solar activity influences on atmospheric electricity and on some structures in the middle atmosphere

Only processes in the troposphere and the lower stratosphere are reviewed. General aspects of global atmospheric electricity are summarized in Chapter 3 of NCR (1986); Volland (1984) has outlined the overall problems of atmospheric electrodynamics; and Roble and Hays (1982) published a summary of solar effects on the global circuit. The solar variability and its atmospheric effects (overview by Donelly et al, 1987) and the solar-planetary relationships (survey by James et al. 1983) are so extremely complex that only particular results and selected papers of direct relevance or historical importance are compiled herein.

Reiter, Reinhold↗
NASA NTRS1993

Comparison of single event upset rates for microelectronic memory devices during interplanetary solar particle events

Variability in the methods and models used for single event upset calculations in microelectronic memory devices can lead to a range of possible upset rates. Using heavy ion and proton data for selected DRAM and SRAM memories, we have calculated an array of upset rates in order to compare the Adams worst case interplanetary solar flare model to a model proposed by scientists at the Jet Propulsion Laboratory. In addition, methods of upset rate calculation are compared: the Cosmic Ray Effects on Microelectronics CREME code and a Monte Carlo algorithm developed at the Applied Physics Laboratory. The results show that use of a more realistic, although still conservative, model of the space environment can have significant cost saving benefits.

Mckerracher, P. L.↗
NASA NTRS1993

Current Status in Cavitation Modeling

Cavitation is a common problem for many engineering devices in which the main working fluid is in liquid state. In turbomachinery applications, cavitation generally occurs on the inlet side of pumps. The deleterious effects of cavitation include: lowered performance, load asymmetry, erosion and pitting of blade surfaces, vibration and noise, and reduction of the overall machine life. Cavitation models in use today range from rather crude approximations to sophisticated bubble dynamics models. Details about bubble inception, growth and collapse are relevant to the prediction of blade erosion, but are not necessary to predict the performance of pumps. An engineering model of cavitation is proposed to predict the extent of cavitation and performance. The vapor volume fraction is used as an indicator variable to quantify cavitation. A two-phase flow approach is employed with the assumption of the thermal equilibrium between liquid and vapor. At present velocity slip between the two phases is selected. Preliminary analyses of 2D flows shows qualitatively correct results.

Singhal, Ashok K.↗
NASA NTRS1995

An efficient software implementation of a variable rate modem

This paper describes the software implementation of the baseband portion of a variable rate modem. The modem can handle arbitrary symbol rates with a fixed input/output sample rate. This approach reduces hardware complexity related to external clock generation circuitry, offers complete flexibility in the selection of symbol rates, and conveniently accommodates symbol timing and symbol rate corrections.

Mantha, Ramesh↗
NASA NTRS1999

Rossi X-Ray Timing Explorer Observations of the Gamma-Ray Blazar PKS 2155-304

PKS 2155-304 is the archetypical X-ray-selected BL Lac object (XBL). It is one of the brightest BL Lacs at x-ray through optical wavelengths where it has a relatively featureless continuum and displays rapid, large amplitude variability. This continuum is thought to be direct synchrotron emission from a distribution of ultra-relativistic electrons which extends to unusually high energies (Edelson et al. 1995). The gamma-ray emission from PKS 2155-304 constitutes a second, separate, spectral component. Observations with the EGRET telescope aboard the Compton Gamma Ray Observatory (CGRO) show that the spectral energy distribution of this gamma-ray component must peak at energies above 10 GeV (Vestrand et al. 1995). This, plus the realization that the extension of the synchrotron component into the x-ray band meant that ambient photons would be scattered to TeV energies, led to predictions that PKS 2155-304 would be a detectable TeV gamma ray source (Vestrand et al. 1995; Stecker et al. 1996). The University of Durham group has recently reported the discovery of TeV gamma ray emission from PKS 2155-304 (Chadwick et al. 1998, 1999) . The TeV emission was detected in 1996 September and 1997 October/November, with the largest fluxes being measured in 1997 November. During 1997 November, we detected a record high GeV gamma-ray flux from PKS 2155-304 with CGRO/EGRET (Sreekumar and Vestrand 1997) and subsequently very high x-ray fluxes were measured with BeppoSAX (Chiapeeti et al. 1997). Here we report on the record x-ray fluxes measured with the Rossi X-Ray Timing Explorer (RXTE) during the GeV/TeV outburst.

Vestrand, W. Thomas↗
NASA NTRS2010

Forecasting Lightning Threat Using WRF Proxy Fields

Objectives: Given that high-resolution WRF forecasts can capture the character of convective outbreaks, we seek to: 1. Create WRF forecasts of LTG threat (1-24 h), based on 2 proxy fields from explicitly simulated convection: - graupel flux near -15 C (captures LTG time variability) - vertically integrated ice (captures LTG threat area). 2. Calibrate each threat to yield accurate quantitative peak flash rate densities. 3. Also evaluate threats for areal coverage, time variability. 4. Blend threats to optimize results. 5. Examine sensitivity to model mesh, microphysics. Methods: 1. Use high-resolution 2-km WRF simulations to prognose convection for a diverse series of selected case studies. 2. Evaluate graupel fluxes; vertically integrated ice (VII). 3. Calibrate WRF LTG proxies using peak total LTG flash rate densities from NALMA; relationships look linear, with regression line passing through origin. 4. Truncate low threat values to make threat areal coverage match NALMA flash extent density obs. 5. Blend proxies to achieve optimal performance 6. Study CAPS 4-km ensembles to evaluate sensitivities.

McCaul, E. W., Jr.↗
NASA NTRS2016

A Strategic Approach to Medical Care for Exploration Missions

Exploration missions will present significant new challenges to crew health, including effects of variable gravity environments, limited communication with Earth-based personnel for diagnosis and consultation for medical events, limited resupply, and limited ability for crew return. Providing health care capabilities for exploration class missions will require system trades be performed to identify a minimum set of requirements and crosscutting capabilities which can be used in design of exploration medical systems. Current and future medical data, information, and knowledge must be cataloged and put in formats that facilitate querying and analysis. These data may then be used to inform the medical research and development program through analysis of risk trade studies between medical care capabilities and system constraints such as mass, power, volume, and training. These studies will be used to define a Medical Concept of Operations to facilitate stakeholder discussions on expected medical capability for exploration missions. Medical Capability as a quantifiable variable is proposed as a surrogate risk metric and explored for trade space analysis that can improve communication between the medical and engineering approaches to mission design. The resulting medical system approach selected will inform NASA mission architecture, vehicle, and subsystem design for the next generation of spacecraft.

Antonsen, E.↗
NASA NTRS2022

The Spectral-Timing Analysis of Cygnus X-1 With Insight-HXMT

Cygnus X-1, as the first discovered black hole binary, is a key source for understanding the mechanisms of state transitions, and the scenarios of accretion in extreme gravity fields. We present a spectral-timing analysis of observations taken with the Insight-HXMT mission, focusing on the spectral-state dependent timing properties in the broad energy range of 1–150 keV, thus extending previous RXTE-based studies to both lower and higher energies. Our main results are the following: a) We successfully use a simple empirical model to fit all spectra, confirming that the reflection component is stronger in the soft state than in the hard state; b) The evolution of the total fractional root mean square (rms) depends on the selected energy band and the spectral shape, which is a direct result of the evolution of the power spectral densities (PSDs); c) In the hard/intermediate state, we see clear short-term variability features and a positive correlation between central frequencies of the variability components and the soft photon index Γ(sub 1), also at energies above 15 keV. The power spectrum is dominated by red noise in the soft state instead. These behaviors can be traced to at least 90 keV; d) The coherence and the phase-lag spectra show different behaviors dependent on different spectral shapes.

Binary X-rays↗