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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Distributed fiber sensor

In an embodiment, a sensor comprises a waveguide comprising a photoacoustic generation element disposed on the waveguide, the photoacoustic generation element comprising a photoabsorptive material; and a sensing element comprising an optical acoustic wave detector. In another embodiment, a sensing system comprises the sensor and a laser. In yet another embodiment, a method of sensing comprises providing the sensing system; heating the photoabsorptive material with a laser to generate an acoustic signal; sensing an intensity of laser light reflected by the optical acoustic wave detector to detect the acoustic signal; and determining a time of flight of the acoustic signal between the generation and the detection to determine a change in a parameter change in a medium between the photoabsorptive material and the optical acoustic wave detector.

Wang, Xingwei↗
DOE OSTI2024

Quantum for Energy Systems and Technologies

Quantum information science (QIS) is creating a transformative opportunity to improve processes for energy production, distribution, and consumption. In this presentation, we will show the works that are currently pursued into two major directions, (i) quantum sensing and (ii) quantum computing is undergoing in order to find applications in the areas of carbon captures, critical minerals and gas sensing applications.

Paudel, Hari P.↗
DOE OSTI2020

Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes

Conservation planners and resource managers seek information about how the availability and locations of cold-water habitats will change in the future and how these predictions vary among models. In this work, we used a physical process-based model to demonstrate the implications of climate change for streamflow and water temperature in two watersheds with distinctive flow regimes: the Snoqualmie watershed (WA) and Siletz watershed (OR), USA. Our model incorporated a downscaled ensemble of global climate model outputs and was calibrated with in situ and remotely sensed water temperatures. Furthermore, we compared predictions from our processed-based model to those from a publicly available and widely used statistical model. The process-based model projected greater changes in summer maximum water temperatures for the mixed-rain-snow Snoqualmie watershed than for the rain-dominated Siletz watershed as a result of the near-complete loss of winter snowpack and significant reduction in summer flow in the Snoqualmie watershed expected by the 2080s. Both models projected generally similar future spatial patterns of maximum water temperature in the two rivers, with cool reaches distributed farther upstream and fewer in number. However, the process-based model projected higher spatial heterogeneity in water temperature due to our spatially explicit simulation of streamflow and because we calibrated the model with spatially continuous remotely sensed water temperature data. We used stream temperature projections to assess the vulnerability of Pacific salmon and trout to changes in the spatial distribution of cold-water habitats during August by the 2080s. Results suggest that salmonids may have fewer summertime cold-water habitats in both watersheds. Projected stream warming may further limit particular species and life stages, especially in the Snoqualmie watershed. Our comparison of models highlights the importance of considering what might be gained by using a process-based model for evaluating and prioritizing management actions that mitigate climate impacts on cold-water habitats for stream fishes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Predicting the offshore distribution and abundance of marine birds with a hierarchical community distance sampling model

Abstract Proposed offshore wind energy development on the Atlantic Outer Continental Shelf has brought attention to the need for baseline studies of the distribution and abundance of marine birds. We compiled line transect data from 15 shipboard surveys (June 2012–April 2014), along with associated remotely sensed habitat data, in the lower Mid‐Atlantic Bight off the coast of Delaware, Maryland, and Virginia, USA . We implemented a recently developed hierarchical community distance sampling model to estimate the seasonal abundance of 40 observed marine bird species. Treating each season separately, we included six oceanographic parameters to estimate seabird abundance: three static (distance to shore, slope, sediment grain size) and three dynamic covariates (sea surface temperature [ SST ], salinity, primary productivity). We expected that avian bottom‐feeders would respond primarily to static covariates that characterize seafloor variability, and that surface‐feeders would respond more to dynamic covariates that quantify surface productivity. We compared the variation in species‐specific and community‐level responses to these habitat features, including for rare species, and we predicted species abundance across the study area. While several protected species used the study area in summer during their breeding season, estimated abundance and observed diversity were highest for nonbreeding species in winter. Distance to shore was the most common significant predictor of abundance, and thus useful in estimating the potential exposure of marine birds to offshore development. In many cases, our expectations based on feeding ecology were confirmed, such as in the first winter season, when bottom‐feeders associated significantly with the three static covariates (distance to shore, slope, and sediment grain size), and surface‐feeders associated significantly with two dynamic covariates ( SST , primary productivity). However, other cases revealed significant relationships between static covariates and surface‐feeders (e.g., distance to shore) and between dynamic covariates and bottom‐feeders (e.g., primary productivity during that same winter). More generally, we found wide interannual, seasonal, and interspecies variation in habitat relationships with abundance. These results show the importance of quantifying detection and determining the ecological drivers of a community's distribution and abundance, within and among species, for evaluating the potential exposure of marine birds to offshore development.

Goyert, Holly F.↗
DOE OSTI2016

Forecasting climate change impacts on plant populations over large spatial extents

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Arc-based smoothing of ion beam intensity on targets

Manipulating a set of ion beams upstream of a target, makes it possible to arrange a smoother deposition pattern, so as to achieve more uniform illumination of the target. A uniform energy deposition pattern is important for applications including ion-beam-driven high energy density physics and heavy-ion beam-driven inertial fusion energy (“heavy-ion fusion”). Here, we consider an approach to such smoothing that is based on rapidly “wobbling” each of the beams back and forth along a short arc-shaped path, via oscillating fields applied upstream of the final pulse compression. In this technique, uniformity is achieved in the time-averaged sense; this is sufficient provided the beam oscillation timescale is short relative to the hydrodynamic timescale of the target implosion. This work builds on two earlier concepts: elliptical beams applied to a distributed-radiator target [D. A. Callahan and M. Tabak, Phys. Plasmas 7, 2083 (2000)] and beams that are wobbled so as to trace a number of full rotations around a circular or elliptical path [R. C. Arnold et al., Nucl. Instrum. Methods 199, 557 (1982)]. Here, we describe the arc-based smoothing approach and compare it to results obtainable using an elliptical-beam prescription. In particular, we assess the potential of these approaches for minimization of azimuthal asymmetry, for the case of a ring of beams arranged on a cone. We also found that, for small numbers of beams on the ring, the arc-based smoothing approach offers superior uniformity. In contrast with the full-rotation approach, arc-based smoothing remains usable when the geometry precludes wobbling the beams around a full circle, e.g., for the X-target [E. Henestroza, B. G. Logan, and L. J. Perkins, Phys. Plasmas 18, 032702 (2011)] and some classes of distributed-radiator targets.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Thermal X-ray spectral tools. I. Parameterizing impulsive X-ray heating with a cumulative initial temperature (CIT) distribution

In collisional ionization equilibrium, the X-ray spectrum from a plasma depends on the differential emission measure (DEM), distributed over temperature. Due to the well-known ill conditioning problem, no precisely resolved DEM can be inverted directly from the spectrum, so often only a gross parameterization of the DEM is used to approximate the data, in hopes that the parameterization can provide useful model-independent constraints on the heating process. However, ill conditioning also introduces ambiguity into the various different parameterizations that could approximate the data, which may spoil the perceived advantages of model independence. Thus, this paper instead suggests a single parameterization for both the heating mechanism and the X-ray sources, based on a model of impulsive heating followed by radiative cooling. This approach is similar to a 'cooling flow' approach but allows injection at multiple initial temperatures and applies even when the steady state is a distribution of different shock strengths, as for a standing shock with a range of obliquities, or for embedded stochastic shocks that are only steady in a statistical sense. This produces an alternative parameterization for X-ray spectra that is especially streamlined for higher density plasmas with efficient radiative cooling and minimal thermal conduction and mixing. The method also provides some internal consistency checks on the validity of its assumptions. A heuristic general version is then applied over a wide range of astrophysical applications to schematically explore potential alternative models for these phenomena.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China

Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Single Molecule Spectroscopy Studies of Acid–Base Chemical Gradients Using Nile Red as a Probe of Local Surface Acidity

Single molecule spectroscopy studies of local acidity along bifunctional acid-base gradients are reported. Gradients are prepared by directional vapor phase diffusion and subsequent reaction of 3-aminopropyl-trimethoxysilane with a uniform silica film. Gradient formation is confirmed by spectroscopic ellipsometry and by static water contact angle measurements. X-ray photoelectron spectroscopy is used to characterize the nitrogen content and degree of nitrogen protonation along the gradient. Nile Red is employed as the probe dye in single molecule spectroscopy studies of these gradients. While Nile Red is well-known for its solvent sensitivity, it is used here, for the first time, to sense the acid/base properties of the film in two-color wide-field fluorescence imaging experiments. The data reveal broad bimodal distributions of Nile Red emission spectra that vary along the gradient direction. The single-molecule results are consistent with solution-phase ensemble acid/base studies of the dye. The former reveal a gradual transition from a surface dominated by basic aminosilane sites at the high-amine end of the gradient to one dominated by acidic silanol sites at the low-amine end. The sub-diffraction-limited spatial resolution afforded by superlocalization of the single molecules reveals spatial correlations in the acid/base properties of the gradient over ~ 200 nm distances. Furthermore, these studies provide data relevant to the use of aminosilane-modified silica in bifunctional, cooperative chemical catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Multi-Summer Climatology of Cumuli at SGP site: Vertical Structure

We perform a case study for estimating the impact of the vertical distribution of cloud fraction on the normalized cloud radiative forcing (CRF) using a decade-long (2000-2009) high resolution dataset of cloud macrophysical and radiative properties. This dataset is developed for fair-weather cumuli (FWC) observed at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The design of the case study reduces effects associated with non-cloud factors, such as the diurnal changes of aerosol loading and solar zenith angle. The results of the case study suggest that the impact of the vertical cloud structure can be substantial. Therefore, taking into account the vertical distribution of clouds would be beneficial for more comprehensive parameterizations aimed to portray the complex interactions between clouds and radiation more accurately

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Advanced Laboratory and Field Arrays: Evaluating Sampling Techniques for MHK Biological Monitoring (Task 6)

The overall goal of the task was to identify cost effective biological sampling techniques for MHK environmental monitoring. Protected, demersal, and pelagic fish and selected nektonic invertebrates were surveyed using capture and remote sensing techniques at the PacWave sites. The performance of capture and remote sensing monitoring techniques were evaluated and generic nekton monitoring indices were developed for MHK technologies and sites. In parallel to data collections at the PacWave site, the ability of regression models to characterize, detect, and predict change in acoustic data was evaluated using acoustic data collected in Admiralty Inlet, WA, during a biological monitoring study of the proposed SnoPud tidal turbine project site. Expected outcomes of these efforts included an evaluation of instrumentation and techniques used to monitor biological variability; identification of data streams that can be used to detect and quantify change; and sampling requirements to ensure detection of change in monitored variables.

13 HYDRO ENERGY↗
DOE OSTI2024

Multiscale Flow for robust and optimal cosmological analysis

We propose Multiscale Flow, a generative Normalizing Flow that creates samples and models the field-level likelihood of two-dimensional cosmological data such as weak lensing. Multiscale Flow uses hierarchical decomposition of cosmological fields via a wavelet basis and then models different wavelet components separately as Normalizing Flows. The log-likelihood of the original cosmological field can be recovered by summing over the log-likelihood of each wavelet term. This decomposition allows us to separate the information from different scales and identify distribution shifts in the data such as unknown scale-dependent systematics. The resulting likelihood analysis can not only identify these types of systematics, but can also be made optimal, in the sense that the Multiscale Flow can learn the full likelihood at the field without any dimensionality reduction. We apply Multiscale Flow to weak lensing mock datasets for cosmological inference and show that it significantly outperforms traditional summary statistics such as power spectrum and peak counts, as well as machine learning–based summary statistics such as scattering transform and convolutional neural networks. We further show that Multiscale Flow is able to identify distribution shifts not in the training data such as baryonic effects. Finally, we demonstrate that Multiscale Flow can be used to generate realistic samples of weak lensing data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Drones in Automation - Secured Unmanned Aerial Systems

Factories, refineries, utilities (water/wastewater, electric) and related industrial sites are complex systems and structures with inspection and maintenance procedures required for optimal operation and regulatory compliance. As a specific example, consider just the bulk electric power system which is comprised of more than 200,000 miles of highvoltage transmission lines, thousands of generation plants and millions of digital controls. More than 1,800 entities own and operate portions of the grid system, with thousands more involved in the operation of distribution networks across North America. The interconnected and interdependent nature of the bulk power system requires a consistent and systematic application of risk mitigation across the entire grid system to be truly effective. Similar situations are found throughout automation where frequently an aging infrastructure is in place too. Consider, for example, the situation present in a refinery or chemical processing setting with the requirement for leak detection inspection of pipes, interconnects and systems stretching across the plant. The current practices and challenges relating just to this task - leak detection and repair (LDAR) – of detecting any fugitive emissions present and documenting all measurements thereby meeting air compliance regulations are typically “handled” by a small army of individuals with handheld or backpack-sized detectors who crawl through piping racks conducting measurements at each flange. Such work is performed in difficult conditions (temperature, humidity, physically challenging) with frequently a high level of employee turnover. Finaly, enter low cost sensors and mobile platforms – in other words unmanned aerial systems (UASs, or drones) with enhanced sensing capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Coherence area profiling in multi-spatial-mode squeezed states

The presence of multiple bipartite entangled modes in squeezed states generated by four-wave mixing enables ultra-trace sensing, imaging, and metrology applications that are impossible to achieve with single-spatial-mode squeezed states. For Gaussian seed beams, the spatial distribution of these bipartite entangled modes, or coherence areas, across each beam is largely dependent on the spatial modes present in the pump beam, but it has proven difficult to map the distribution of these coherence areas in frequency and space. We demonstrate an accessible method to map the distribution of the coherence areas within these twin beams. In addition, we also show that the pump shape can impart different noise properties to each coherence area, and that it is possible to select and detect coherence areas with optimal squeezing with this approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Observation of rapid frequency chirping instabilities driven by runaway electrons in a tokamak

In this work, we report the first observation of chirping instabilities driven by runaway electrons (REs) in a tokamak. The instabilities are accessed during the post-disruption RE beam stage in a low density background plasma (n e < 10 19 m -3 ) on DIII-D. The chirping instabilities are observed when a decelerating loop voltage is applied to the RE beam. The frequency chirping is detected in two distinct frequency bands: 0.1–10 MHz and 30–80 MHz. The mode frequency increases linearly when the toroidal magnetic field sensed by the RE beam increases. The frequency chirps by 0.3–2.4 MHz on a timescale of 1 ms. Modification of the RE distribution function is directly measured during the chirping in the low-frequency band consistent with the hole–clump model for frequency chirping. The low-frequency instabilities also correlate with an increase of intermittent RE loss from the plasma. Lastly, these observations provide a novel experimental platform for fundamental studies of nonlinear chirping. They also support continued investigation of opportunities to utilize kinetic instabilities for RE mitigation in a tokamak reactor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗