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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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NASA NTRS2015

Validation of S-NPP VIIRS Day-Night Band and M Bands Performance Using Ground Reference Targets of Libya 4 and Dome C

This paper provides methodologies developed and implemented by the NASA VIIRS Calibration Support Team (VCST) to validate the S-NPP VIIRS Day-Night band (DNB) and M bands calibration performance. The Sensor Data Records produced by the Interface Data Processing Segment (IDPS) and NASA Land Product Evaluation and Algorithm Testing Element (PEATE) are acquired nearly nadir overpass for Libya 4 desert and Dome C snow surfaces. In the past 3.5 years, the modulated relative spectral responses (RSR) change with time and lead to 3.8% increase on the DNB sensed solar irradiance and 0.1% or less increases on the M4-M7 bands. After excluding data before April 5th, 2013, IDPS DNB radiance and reflectance data are consistent with Land PEATE data with 0.6% or less difference for Libya 4 site and 2% or less difference for Dome C site. These difference are caused by inconsistent LUTs and algorithms used in calibration. In Libya 4 site, the SCIAMACHY spectral and modulated RSR derived top of atmosphere (TOA) reflectance are compared with Land PEATE TOA reflectance and they indicate a decrease of 1.2% and 1.3%, respectively. The radiance of Land PEATE DNB are compared with the simulated radiance from aggregated M bands (M4, M5, and M7). These data trends match well with 2% or less difference for Libya 4 site and 4% or less difference for Dome C. This study demonstrate the consistent quality of DNB and M bands calibration for Land PEATE products during operational period and for IDPS products after April 5th, 2013.

radiance↗

NASA NTRS2016

Improving Nocturnal Fire Detection with the VIIRS Day-Night Band

Building on existing techniques for satellite remote sensing of fires, this paper takes advantage of the day-night band (DNB) aboard the Visible Infrared Imaging Radiometer Suite (VIIRS) to develop the Firelight Detection Algorithm (FILDA), which characterizes fire pixels based on both visible-light and infrared (IR) signatures at night. By adjusting fire pixel selection criteria to include visible-light signatures, FILDA allows for significantly improved detection of pixels with smaller and/or cooler subpixel hotspots than the operational Interface Data Processing System (IDPS) algorithm. VIIRS scenes with near-coincident Advanced Spaceborne Thermal Emission and Reflection (ASTER) overpasses are examined after applying the operational VIIRS fire product algorithm and including a modified "candidate fire pixel selection" approach from FILDA that lowers the 4-μm brightness temperature (BT) threshold but includes a minimum DNB radiance. FILDA is shown to be effective in detecting gas flares and characterizing fire lines during large forest fires (such as the Rim Fire in California and High Park fire in Colorado). Compared with the operational VIIRS fire algorithm for the study period, FILDA shows a large increase (up to 90%) in the number of detected fire pixels that can be verified with the finer resolution ASTER data (90 m). Part (30%) of this increase is likely due to a combined use of DNB and lower 4-μm BT thresholds for fire detection in FILDA. Although further studies are needed, quantitative use of the DNB to improve fire detection could lead to reduced response times to wildfires and better estimate of fire characteristics (smoldering and flaming) at night.

Day-night band↗

NASA NTRS2018

Preliminary Study of JPSS-1/NOAA-20 VIIRS Day-Night Band Straylight Characterization and Correction Methods

The JPSS-1 (now named NOAA-20) VIIRS instrument has successfully operated since its launch in November 18, 2017. A panchromatic channel onboard NOAA-20 VIIRS is called the day-night band (DNB). With its large dynamic range and high sensitivity, the DNB detectors can make observations during both daytime and nighttime. However, the DNB night image quality is affected by the straylight contamination. In this study, we focused on Earth view data in the midto-high latitude of the northern and southern hemispheres when spacecraft is crossing the day/night terminators at the beginning of NOAA-20 mission. Based on on-orbit data analysis from previous VIIRS sensor onboard S-NPP mission, straylight contamination mainly depends on the Earth-Sun-spacecraft geometry, and it is also detector and scan-angle dependent. Inter-comparison investigation of straylight behavior in both SNPP and NOAA-20 instruments will be conducted to better understand straylight characteristics. The preliminary study has been performed in this paper to mitigate straylight contamination for NOAA-20VIIRS DNB night images. The effectiveness of the straylight correction algorithm, directly adapted from the S-NPP DNB, is assessed for night images in the day/night terminators. Further work has been identified to improve current straylight correction methodology and DNB-based environmental data products.NOAA-20.

Day-Night Band↗

NASA NTRS1999

A Combined Length-of-day Series Spanning 1832-1997: Lunar97

Universal time measurements taken by the lunar occultation, optical astrometry, lunar laser ranging, and very long baseline interferometry have been combined using a Kalman filter to produce a smoothed length-of-day series, LUNAR97, spanning 1832.5-1997.5 at yearly intervals.

Earth↗

NASA NTRS2020

NOAA-20 Visible Infrared Imaging Radiometer Suite day–night band on-orbit calibration and performance

The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) instrument has been successfully operating on orbit since November 28, 2017. The day–night band (DNB) onboard NOAA-20 VIIRS is a panchromatic channel covering wavelengths from 0.5 to 0.9 μm, capable of observing the Earth scene in visible/near-infrared spectral range at a spatial resolution of 750 m. The DNB operates at low-, mid-, or high-radiometric gain stages, and it uses an onboard solar diffuser (SD) panel for low-gain stage calibration. The SD observations also provide a means to compute gain ratios between low-to-mid and mid-to-high-gain stages. With their large dynamic range and high sensitivity, the DNB detectors can make observations during both daytime and nighttime. We provide an assessment of the DNB on-orbit performance and behavior in the first two-year mission period and beyond. The calibration methodology used by the VIIRS Characterization Support Team in support of the NASA Earth science community has been described. The trending of on-board calibrators dark-offsets, SD gains, and gain ratios, and signal-to-noise ratio at minimum radiance have been analyzed, especially during key events such as the nadir and cryocooler doors opening. Furthermore, we performed intercomparison studies between Suomi National Polar-orbiting Partnership and NOAA-20 instruments and evaluated DNB radiometric calibration and characterization, including the SD degradation, detector gains, gain ratios, and straylight correction, as well as the calibration comparison between the NOAA Interface Data Processing Segment look-up-tables and our delivery results.

VIIRS↗

DOE OSTI2022

Incorporate day-ahead robustness and real-time incentives for electricity market design

In this paper, we propose a two-stage electricity market framework to explore the participation of distributed energy resources (DERs) in a day-ahead (DA) market and a real-time (RT) market. The objective is to determine the optimal bidding strategies of the aggregated DERs in the DA market and generate online incentive signals for DER-owners to optimize the social-welfare taking into account network operational constraints. Distributionally robust optimization is used to explicitly incorporate data-based statistical information of renewable forecasts into the supply/demand decisions in the DA market. We evaluate the conservativeness of bidding strategies distinguished by different risk aversion settings. In the RT market, a bi-level time-varying optimization problem is proposed to design the online incentive signals to tradeoff the RT imbalance penalty for distribution system operators (DSOs) and the costs of individual DER-owners. This enables tracking their optimal dispatch to provide fast balancing services, in the presence of time-varying network states while satisfying the voltage regulation requirement. Simulation results on both DA wholesale market and RT balancing market demonstrate the necessity of this two-stage design, and its robustness to uncertainties, the performance of convergence, the tracking ability and the feasibility of the resulting network operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Long-term effects of cycle time and volume exchange ratio on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) production from food waste digestate by Haloferax mediterranei cultivated in sequencing batch reactors for 450 days

Food waste digestate was fed into a sequencing batch reactor (SBR) for Haloferax mediterranei (HM) to produce poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV). This SBR was operated uninterruptedly for 450 days to test its stability, during which the cycle time and volume exchange ratio were varied to understand their impacts on the PHBV fermentation performance under ranged organic loading rates (OLR). Results showed that 1) PHBV productivity was proportional to OLR of food waste digestate; 2) substrate and product inhibitions were two limiting factors constraining substrate utilization and PHBV yields; 3) PHBV titer was dependent on the hydraulic retention time of the SBR while a volume exchange ratio lower than 0.5 is unfavorable due to the product inhibitor accumulation. Furthermore, this study for the first time demonstrated that the long-term stability of food waste-fed PHBV production by HM and revealed that inhibition effects could be barriers in SBR limiting the full-scale application of the technology.

09 BIOMASS FUELS↗

DOE OSTI2022

A hybrid robust-stochastic optimization approach for day-ahead scheduling of cascaded hydroelectric system in restructured electricity market

Uncertainties arising from complicated natural and market environments pose great challenges for the efficient operation of cascaded hydroelectric systems. To overcome these challenges, this paper studies the day-ahead scheduling of cascaded hydroelectric systems in a restructured electricity market with the presence of uncertainties in electricity price and natural water inflow. To properly model the uncertainty, we consider the unique characteristics of these two types of uncertainties and capture them via the uncertainty set and stochastic scenarios, respectively. Further, a hybrid robust-stochastic optimization model is developed to simultaneously hedge against these two types of uncertainties, which is formulated as a large-scale non-convex optimization problem with mixed integer recourse. After introducing linearization of nonlinear terms, a tailored hybrid decomposition scheme combining Lagrangian relaxation and Dantzig-Wolfe decomposition is adopted to achieve efficient computation of the proposed model. Two real-world cases are conducted to demonstrate the capability and characteristics of the proposed model and algorithms.

13 HYDRO ENERGY↗

DOE OSTI2021

Clinical Outcomes of a Randomized Trial of Adaptive Plan-of-the-Day Treatment in Patients Receiving Ultra-hypofractionated Weekly Radiation Therapy for Bladder Cancer

Hypofractionated radiation therapy can be used to treat patients with muscle-invasive bladder cancer unable to have radical therapy. Toxicity is a key concern, but adaptive plan-of the day (POD) image-guided radiation therapy delivery could improve outcomes by minimizing the volume of normal tissue irradiated. The HYBRID trial assessed the multicenter implementation, safety, and efficacy of this strategy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform

Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. Finally, we explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Quasi-Two-Day and Diurnal Cloud Variation Timescales over Convectively Active Regions

Climatological features of the cloud variability on quasi-two-day (Q2D) and diurnal cycle (DC) timescales are investigated by utilizing the high-resolution satellite infrared brightness temperature (IRBT) observations from January 1998 to December 2019. A distinct land-sea contrast between the distributions of Q2D and DC signals is evident. Diurnally driven cloud activity mainly occurs over land and mountainous regions, and the Q2D timescale is more prominent over tropical ocean basins and land where organized convection is usually observed, e.g., Congo and Amazon Rainforests, the U.S. and subtropical South America during warm seasons. The long-term relationship between the Q2D variability and sea surface temperature (SST) shows that the clouds are more active on Q2D timescales over higher SST environments. The Q2D variability correlates well with both the Indian Ocean Dipole (IOD) and El Niño/Southern Oscillation (ENSO) from 1998 to 2019. The cloud variability associated with a range of convective available potential energy (CAPE) values is analyzed. The result over land shows that increased Q2D cloud variability emerges with higher CAPE, suggesting the coincidence of Q2D and organized convection, particularly given that this effect is strongest over regions with frequent mesoscale convective systems (MCSs) around the world. The cloud variability and the Q2D timescale analyses provide an alternative perspective to understand the global features of mesoscale convective systems. Overall, this study objectively examines the global variability of convective timescales related to the diurnal cycle and longer-lived convective systems to provide a greater understanding of how the global convection population varies in space and time.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Comparing the Effect of Anthropogenically Amplified Halogen Natural Emissions on Tropospheric Ozone Chemistry Between Pre-Industrial and Present-Day

Reactive halogens (X + XO, X = I, Br or Cl) catalytically destroy a fraction of tropospheric ozone under present-day (PD) conditions, however, their distribution and potential impact on tropospheric ozone under pre-industrial (PI) conditions remain largely unexplored. This study uses the Community Atmosphere Model with Chemistry (CAM-Chem) to investigate the effect of anthropogenically amplified natural emissions of halogenated species and their subsequent chemistry on tropospheric ozone under PI and PD atmospheric conditions. Model results show that the global tropospheric ozone depletion due to natural halogens is slightly more sensitive in PI than PD, with percentage changes in tropospheric ozone burden (TOB) of -14.1 ± 0.6% for PI and -12.9 ± 0.6% for PD. Individually, the role of iodine and chlorine in ozone depletion is equivalent in both periods (ΔTOB I : ~-7% and ΔTOB Cl : ~-2.5%), while bromine plays a larger role in PI (ΔTOB Br : -5.5 ± 0.6%) versus PD (ΔTOB Br : -4.3 ± 0.7%). The increase in anthropogenic ozone precursor emissions from PI to PD has amplified the natural emission of inorganic halogens and led to a shift in the partitioning of inorganic halogens from reactive to reservoir species. Consequently, halogen-driven ozone depletion from the surface to the free troposphere is larger in PI than PD. In contrast, in the upper troposphere, the ozone depletion is larger in PD influenced mainly by stratospheric intrusion of reactive halogens from long-lived species. This study highlights the importance of including a complete chemical coupling of natural halogens and atmospheric pollutants in chemistry-climate models to adequately assess their effects on tropospheric ozone in a changing climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Flower‐Type Organized Trade‐Wind Cumulus: A Multi‐Day Lagrangian Large Eddy Simulation Intercomparison Study

Shallow cumulus cloud fields in subtropical marine trade wind environments, particularly over the tropical Atlantic Ocean, show distinct organizational patterns. Among these, Flower‐type clouds are characterized by expansive stratiform cloud patches surrounded by regions of scattered convection. The objectives of this study were (a) to construct a case study of a time period during the EUREC 4 A/ATOMIC field campaign when Flower‐type organization was observed, (b) to evaluate the fidelity of a multi‐model ensemble of large eddy simulations of that case, and (c) to analyze the interaction between cloud and precipitation processes and mesoscale organization in the simulations. The simulations follow a quasi‐Lagrangian trajectory, allowing mesoscale features to develop over time in a domain that follows the boundary‐layer airmass. The results show a broad agreement in simulated thermodynamic properties across different LES codes, with Flower‐type cloud patches appearing within hours of each other. The consensus among models is consistent with observations made during the EUREC 4 A/ATOMIC field campaign on the specific day of interest. The cloud structure reveals three distinct peaks in the joint probability densities of cloud base and cloud top height, with the dominant peak at any given time influenced by the stage of cloud organization. The simulated cloud system evolution reveals consistent occurrence of maxima in liquid water path and rain rate before Flower reaches its maximum length scale. Targeted sensitivity tests reveal a weak relationship between Cloud Droplet Number concentration and the extent/degree/type of organization.

EUREC4A↗

DOE OSTI2021

All-day fresh water harvesting by microstructured hydrogel membranes

Abstract Solar steam water purification and fog collection are two independent processes that could enable abundant fresh water generation. We developed a hydrogel membrane that contains hierarchical three-dimensional microstructures with high surface area that combines both functions and serves as an all-day fresh water harvester. At night, the hydrogel membrane efficiently captures fog droplets and directionally transports them to a storage vessel. During the daytime, it acts as an interfacial solar steam generator and achieves a high evaporation rate of 3.64 kg m −2 h −1 under 1 sun enabled by improved thermal/vapor flow management. With a homemade rooftop water harvesting system, this hydrogel membrane can produce fresh water with a daily yield of ~34 L m −2 in an outdoor test, which demonstrates its potential for global water scarcity relief.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Sterile-neutrino search based on 259 days of KATRIN data

Neutrinos are the most abundant fundamental matter particles in the Universe and play a crucial part in particle physics and cosmology. Neutrino oscillation, discovered about 25 years ago, shows that the three known species mix with each other. Anomalous results from reactor and radioactive-source experiments suggest a possible fourth neutrino state, the sterile neutrino, which does not interact through the weak force. The Karlsruhe Tritium Neutrino (KATRIN) experiment, primarily designed to measure the neutrino mass using tritium β-decay, also searches for sterile neutrinos suggested by these anomalies. A sterile-neutrino signal would appear as a distortion in the β-decay energy spectrum, characterized by a discontinuity in curvature (kink) related to the sterile-neutrino mass. This signature, which depends only on the shape of the spectrum rather than its absolute normalization, offers a robust, complementary approach to reactor experiments. Here we report the analysis of the energy spectrum of 36 million tritium β-decay electrons recorded in 259 measurement days within the last 40 eV below the endpoint. The results exclude a substantial part of the parameter space suggested by the gallium anomaly and challenge the Neutrino-4 claim. Together with other neutrino-disappearance experiments, KATRIN probes sterile-to-active mass splittings from a fraction of an eV 2 to several hundred eV 2 , excluding light sterile neutrinos with mixing angles above a few per cent.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

All-day passive radiative cooling using common salts

An infrared transparent foam made from inexpensive salts was developed enabling sub-ambient cooling of underlying surfaces for a full 24 hour cycle. This work showcases how non-convetional materials may be used for passive day-time radiative cooling.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Modelling multiple occurrences of activities during a day: An extension of the MDCEV model

The increased interest in time use among transport researchers has led to a search for flexible but tractable models of time use, such as Bhat's Multiple Discrete Continuous Extreme Value (MDCEV) model. MDCEV formulations typically model aggregate time allocation into different activity types during a given period, such as the amount of time spent working and shopping in a day. While these applications provide valuable insights into activity participation, they ignore disaggregate activity-episodes, that is the fact that people might split their total time spent working in multiple separate blocks, with breaks or other activities in between. Insights into this splitting into episodes are necessary for predicting trips and understanding time use satiation. We propose a modified MDCEV model where an activity-episode, rather than an activity type, is the basic choice alternative, using a modified utility function to capture the reduced likelihood of individuals performing a very large number of episodes of the same activity. Results from two large revealed preference datasets exhibit equivalent forecast accuracy between the traditional and proposed approach at an aggregate level, but the latter also provides insights on the number and duration of activity-episodes with significant accuracy.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Seasonal representation of extreme precipitation indices over the United States in CMIP6 present-day simulations

Realistically representing the present-day characteristics of extreme precipitation has been a challenge for global climate models, which is due in part to deficiencies in model resolution and physics, but is also due to a lack of consistency in gridded observations. In this study, we use three observation datasets, including gridded rain gauge and satellite data, to assess historical simulations from sixteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models. We separately evaluate summer and winter precipitation over the United States (US) with a comprehensive set of extreme precipitation indices, including an assessment of precipitation frequency, intensity and spatial structure. The observations exhibit significant differences in their estimates of area-average intensity distributions and spatial patterns of the mean and extremes of precipitation over the US. In general, the CMIP6 multi-model mean performs better than most individual models at capturing daily precipitation distributions and extreme precipitation indices, particularly in comparison to gauge-based data. Also, the representation of the extreme precipitation indices by the CMIP6 models is better in the summer than winter. Although the ‘standard’ horizontal-resolution can vary significantly across CMIP6 models, from ~0.7° to ~2.8°, we find that resolution is not a good indicator of model performance. Overall, our results highlight common biases in CMIP6 models and demonstrate that no single model is consistently the most reliable across all indices.

54 ENVIRONMENTAL SCIENCES↗