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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Artificial Neural Network (ANN) Surface Longwave and Shortwave Fluxes Trained on CERES Observations

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of the radiative fluxes and clouds systems. CERES climate quality data products typically take several months of calibration and validation before release to the public. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed to provide key data for the applied sciences and educational users within a week of observation. FLASHFlux achieves this by using simplified calibration, an operational meteorological product from Global Modeling and Assimilation Office (GMAO), and its own surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Terra and NOAA-20 observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1o x 1o gridded data that combines Terra and NOAA-20 observations. Currently, FLASHFlux uses the Langley Parameterized Shortwave Algorithm (LPSA) and Langley Parameterized Longwave Algorithm (LPLA) to derive its surface fluxes (Kratz et al., 2010; Gupta et al, 2001). A new Machine Learning (ML) based approach using Artificial Neural Networks to derive Surface Longwave (LW) & Shortwave (SW) fluxes based on training data from the CERES Clouds Radiative Swath (CRS) product is being investigated to replace LPSA and LPLA in the SSF surface flux products. One of the biggest hurdles in training ML model is model fitting. To overcome the problem of overfitting we use feature engineering that helps in finding the important feature and remove features that are irrelevant to the model. In our training we employed the Leave-One-Feature-Out Importance (LOFO) to evaluate the significance of each feature in our training. We intercompare ANN fluxes against surface fluxes produced from the Fu-Liou model in CRS and the LPSA/LPLA in FLASHFlux SSF. Furthermore, we validated ANN derived fluxes to the Baseline Surface Radiation Network (BSRN).

P C Sawaengphokhai↗
NASA NTRSDate not supplied

Anticipating Hazard Impacts through Capacity Building and Co-development

Improving forecast accuracy, extending lead time, understanding hazard susceptibility, and integrating exposure and vulnerability data to generate impact-based forecasts are critical in mitigating disaster impacts. These efforts enable anticipatory action through enhancing the efficacy of early warning systems to assess potential multi-dimensional hazard impacts. In response to this need, SERVIR has co-developed a series of hazard services providing vital information from national to regional scales. This poster showcases examples of geospatial services co-developed with partners through a capacity building approach, supporting the establishment of hazard early warning / early action systems. These services integrate multidimensional vulnerability and exposure data to comprehensively assess impacts. Furthermore, these services demonstrate how co-development and capacity building can advance the development of impact-based forecasts and multi-hazards services. By prioritizing collaboration, human insights, local knowledge, capacity building, and employing applied science approaches in geospatial service development, this work has helped create inclusive and customized solutions. These solutions are tailored to meet the needs of local communities and are readily adaptable into decision-making processes.

weather↗
NASA NTRSDate not supplied

A Long-Term GOES Satellite Overshooting Cloud Top and Anvil Cloud Climatology Over South America

The modern-era GOES satellite series began in 1994 with the GOES-8 satellite, and was augmented in 2018 with higher spatial resolution and more frequent imaging when GOES-16 became operational. GOES imagery has provided forecasters and researchers new perspectives into cloud top patterns associated with severe convection, and the ability to better forecast convection in regions without adequate ground-based weather radar coverage. While much attention has been given to convection over North America, convection over South America can be equally, if not more, intense and frequent. Recent studies have demonstrated that overshooting cloud tops (OT) and surrounding anvil clouds can be detected within infrared satellite imagery. Relative storm updraft intensity metrics such as the tropopause-relative infrared brightness temperature, the prominence of an OT relative to its surrounding anvil, and cloud top height can also be derived using automated methods combined with reanalysis data. These automated OT detection and intensity estimation methods have recently been applied to all GOES images collected over South America, in combination with the MERRA-2 reanalysis, from 1995 to 2022 at NASA Langley within a project supported by the NASA Applied Sciences Disasters program. Innovative aggregation methods have merged these products into daily, monthly, annual, and multi-annual composites, with hourly time bins, at ~4 km pixel spacing to enable researchers a new opportunity to study South American convective processes throughout the diurnal cycle. These products have recently become publicly available from NASA. This presentation will overview this new dataset, and novel insights into South American convection depicted by the data.

Kristopher Bedka↗
NASA NTRSDate not supplied

Quantifying Burned Area and Smoke from Prescribed and Smaller Fires: West Palm Beach, Florida

In the Central and Southeastern U.S. (C&SE), small, short-lived fires are often underestimated by satellites due to their size, timing, cloud cover, and rapid regrowth or plowing after burns. Satellite data are essential for the National Emissions Inventory, as ground-based inventories are historically incomplete and geographically inconsistent. Agricultural burning, a widespread annual practice in many U.S. regions, significantly impacts air quality on local to regional scales. As part of NASA’s Health and Air Quality Applied Sciences (HAQAST) team, we develop a burned area inventory to account for these ‘missing’ small fires. Our study focuses on West Palm Beach, FL, near Lake Okeechobee, where agriculture fields are burned annually fall-spring for crop management and harvest. This region poses challenges for satellite detection due to frequent rain, flooding, and cloud cover.

Emily Gargulinski↗
DOE OSTI2021

Computational Math Problems for a Clean Energy Future

Cutting edge computational mathematics are ubiquitous in renewable energy research. Problems in resilient and reliable electric grid operations, infrastructure planning, wind farm yaw control, and more demand sophisticated and scalable computational tools that enable the transition of renewable energy technologies from proof of concept to deployment into our energy system. The mission of the Computational Science Center at NREL is to lead the lab's efforts to solve energy challenges using high-performance computing (HPC), computational science, applied mathematics, scientific data management, visualization, and informatics. In this poster, we provide a short overview of three areas of computational mathematics research at NREL: wind power scenario generation for stochastic grid operations and infrastructure planning, improved rational function approximations for electromagnetic transients codes, and wind farm yaw control using a combination of the Alternating Direction Method of Multipliers (ADMM) and reinforcement learning (RL). Increasing penetrations of renewable energy into power grids motivate the investigation of new approaches to characterizing uncertainty for five-minute economic dispatch problems. Similarly, as the penetration of distributed energy resources on power grids increases, it becomes important to revisit our methods of modelling transient phenomena, i.e. electromagnetic transients programs. Finally, the combination of ADMM and RL for wind farm yaw control presented here can potentially increase the efficiency of the deployed distributed controllers by orders of magnitude.

ADMM↗
DOE OSTI2023

In Cell Thermal Creep Frames for Demonstration Project Preparations

The thrust of advanced nuclear reactor demonstrations demands the accelerated qualification of in-core materials to enable licensing processes and developing the performance data. Due to the high-operating temperatures of such reactors, long-term mechanical behavior under constant load is essential to determine the geometrical and mechanical integrity of in-core components during operation and off-normal conditions. Therefore, the thermal creep behavior of neutron-irradiated advanced reactor materials must be determined. The feasibility of using subsize specimens for the irradiation campaigns and the limited available infrastructure challenge the assessment of thermal creep behavior of advanced reactor materials. Therefore, the U.S. Department of Energy Office of Nuclear Energy (DOE-NE) National Reactor Innovation Center (NRIC) prioritizes the development of a thermal creep testing infrastructure for multiple subsize specimens to accelerate the demonstration and deployment of advanced reactor concepts. This report describes the activities for the construction of a thermal creep testing capability at Idaho National Laboratory (INL). The overall project consists of conceptual design, out-of-cell demonstration, and in-cell demonstration phases. During fiscal year (FY)-2021, the team finished the conceptual design of a thermal creep test facility that can test multiple subsize specimens. This conceptual design consisted of the determination of technical and functional requirements, the determination of the design space, and the preparation of the technical drawings. Technical and functional requirements were categorized as required and desired capabilities and the conceptual design was performed to meet all the required capabilities with the flexibility to achieve the desired capabilities. The design space identified the operational capacity of the creep frame for different advanced reactor relevant materials with the consideration of the feasible operation in the hotcell at the Fuels and Applied Science Building (FASB) at INL. Based on the requirements and design space, the multiple specimen creep frame was designed. The official INL engineering drawing process was started and the procurement of materials for construction was initiated. For FY-2022, the out-of-cell demonstration and final installation of the multiple creep frame is planned.

36 MATERIALS SCIENCE↗
DOE OSTI2022

In-Cell Thermal Creep Frame Capability: Out-of-Cell Construction and Subsized Sample Testing

This report describes the activities related to the construction of an in-cell thermal creep test facility for small-scale specimens in the irradiation-assisted stress-corrosion cracking (IASCC) hotcell located at the Fuels and Applied Science Building (FASB) at INL. The whole project includes three stages: (i) conceptual design; (ii) out-of-cell demonstration tests; and (iii) in-cell demonstration testing. During the current fiscal year (FY)-2022, materials and equipment required to construct the conceptual design outlined in a previous report were procured. Frames for conducting out-of-cell testing have been constructed, and testing plans have been developed to assess the operation of the newly constructed frames. Preliminary testing of flat subsized tensile specimens on ASTM creep frames has also been completed for two sample thicknesses: 0.75 mm and 1.0 mm.

36 MATERIALS SCIENCE↗
DOE OSTI2025

FY24 Laboratory Directed Research and Development Annual Report

The Laboratory Directed Research and Development (LDRD) program yields foundational scientific research and development (R&D) essential to growing SRNL’s core competencies, in alignment with SRNL’s Strategic Plan to provide long-term benefits to the Department of Energy (DOE), the National Nuclear Security Administration (NNSA), and other customers and stakeholders. Five strategic goals are outlined in SRNL’s strategic plan: 1) Provide applied science and engineering for EM’s active clean-up sites and LM’s post closure management sites 2) Provide science-based solutions for gaps identified in nonproliferation strategic vision and support the government in activities impacting national security 3) Lead Science, Technology & Engineering as the central technical authority for processing tritium loaded reservoirs and support production of plutonium pits 4) Align science and energy security programs by focusing modern modeling, simulation, and data analytics tools on materials engineering and performance applications 5) Build a workforce for the future

Clark, Sue [Savannah River National Laboratory (SR↗
NASA NTRS1999

The Removal of Periodic Gravitational Perturbations from Mars Global Surveyor's Science Phasing Orbits Applied to the Study of the Martian Exosphere

The martian exosphere and upper atmosphere exert measurable drag on the Mars Global Surveyor (MGS) spacecraft. Using the Goddard Space Flight Center's GEODYN orbit determination software, the science phasing orbits (SPO) were analyzed to determine the atmospheric drag and hence, measure the average density near the orbits' perifocus (170-180 km altitude above high northern latitudes). Future work will include the gravity calibration and mapping periods as well. Additional information is contained in the original extended abstract.

Tracadas, P. W.↗
NASA NTRS1996

An interactive parallel programming environment applied in atmospheric science

This article introduces an interactive parallel programming environment (IPPE) that simplifies the generation and execution of parallel programs. One of the tasks of the environment is to generate message-passing parallel programs for homogeneous and heterogeneous computing platforms. The parallel programs are represented by using visual objects. This is accomplished with the help of a graphical programming editor that is implemented in Java and enables portability to a wide variety of computer platforms. In contrast to other graphical programming systems, reusable parts of the programs can be stored in a program library to support rapid prototyping. In addition, runtime performance data on different computing platforms is collected in a database. A selection process determines dynamically the software and the hardware platform to be used to solve the problem in minimal wall-clock time. The environment is currently being tested on a Grand Challenge problem, the NASA four-dimensional data assimilation system.

Interactive Display Devices↗
DOE OSTI2026

Baryon–antibaryon photoproduction cross sections off the proton

The GlueX experiment at Jefferson Lab has observed 𝑝⁢$\overline{p}$ and, for the first time, Λ$\overlineΛ$ and 𝑝$\overlineΛ$ photoproduction from a proton target at photon energies up to 11.6 GeV. The angular distributions are forward peaked for all produced pairs, consistent with Regge-like 𝑡-channel exchange. Asymmetric wide-angle antibaryon distributions show the presence of additional processes. In a phenomenological model, we find consistency with a double-𝑡-channel exchange process where antibaryons are created only at the middle vertex. The model matches all observed distributions with a small number of free parameters. In the hyperon channels, we observe a clear distinction between photoproduction of the Λ$\overlineΛ$ and 𝑝$\overlineΛ$ systems but general similarity to the 𝑝$\overline{p}$ system. We report both total cross sections and cross sections differential with respect to momentum transfer and the invariant masses of the created particle pairs. No narrow resonant structures were found in these reaction channels. The suppression of 𝑠$\overline{s}$ quark pairs relative to 𝑑$\overline{d}$ quark pairs is similar to what has been seen in other reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Outsourced hearing in an orb-weaving spider that uses its web as an auditory sensor

Hearing is a fundamental sense of many animals, including all mammals, birds, some reptiles, amphibians, fish, and arthropods. The auditory organs of these animals are extremely diverse in anatomy after hundreds of millions of years of evolution, yet all are made up of cellular tissue and are morphologically part of the bodies of animals. Here, we show that hearing in the orb-weaving spider Larinioides sclopetarius is not constrained by the organism’s body but is extended through outsourcing hearing to its extended phenotype, the proteinaceous, self-manufactured orb web. We find that the wispy, wheel-shaped orb web acts as a hyperacute acoustic antenna to capture the sound-induced air particle movements that approach the maximum physical efficiency better than the acoustic responsivity of all previously known eardrums. By sensing the motion of web threads, the spider remotely detects and localizes the source of an incoming airborne acoustic wave, such as those emitted by approaching prey or predators. By outsourcing its acoustic sensors to its web, the spider is released from body size constraints and permits the araneid spider to increase its sound-sensitive surface area enormously, up to 10,000 times greater than the spider itself. The spider also enables the flexibility to functionally adjust and regularly regenerate its external "eardrum" according to its needs. The outsourcing and supersizing of auditory function in spiders provides unique features for studying extended and regenerative sensing and designing novel acoustic flow detectors for precise fluid dynamic measurement and manipulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Prevention efficacy of the broadly neutralizing antibody VRC01 depends on HIV-1 envelope sequence features

In the Antibody Mediated Prevention (AMP) trials (HVTN 704/HPTN 085 and HVTN 703/HPTN 081), prevention efficacy (PE) of the monoclonal broadly neutralizing antibody (bnAb) VRC01 (vs. placebo) against HIV-1 acquisition diagnosis varied according to the HIV-1 Envelope (Env) neutralization sensitivity to VRC01, as measured by 80% inhibitory concentration (IC80). Here, we performed a genotypic sieve analysis, a complementary approach to gaining insight into correlates of protection that assesses how PE varies with HIV-1 sequence features. We analyzed HIV-1 Env amino acid (AA) sequences from the earliest available HIV-1 RNA-positive plasma samples from AMP participants diagnosed with HIV-1 and identified Env sequence features that associated with PE. The strongest Env AA sequence correlate in both trials was VRC01 epitope distance that quantifies the divergence of the VRC01 epitope in an acquired HIV-1 isolate from the VRC01 epitope of reference HIV-1 strains that were most sensitive to VRC01-mediated neutralization. In HVTN 704/HPTN 085, the Env sequence-based predicted probability that VRC01 IC80 against the acquired isolate exceeded 1 µg/mL also significantly associated with PE. In HVTN 703/HPTN 081, a physicochemical-weighted Hamming distance across 50 VRC01 binding-associated Env AA positions of the acquired isolate from the most VRC01-sensitive HIV-1 strain significantly associated with PE. These results suggest that incorporating mutation scoring by BLOSUM62 and weighting by the strength of interactions at AA positions in the epitope:VRC01 interface can optimize performance of an Env sequence-based biomarker of VRC01 prevention efficacy. Future work could determine whether these results extend to other bnAbs and bnAb combinations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Data-driven optimized control of the COVID-19 epidemics

Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening ‘in phases’. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing

We used social media data from “covid19positive” subreddit, from 03/2020 to 03/2022 to identify COVID-19 cases and extract their reported symptoms automatically using natural language processing (NLP). We trained a Bidirectional Encoder Representations from Transformers classification model with chunking to identify COVID-19 cases; also, we developed a novel QuadArm model, which incorporates Question-answering, dual-corpus expansion, Adaptive rotation clustering, and mapping, to extract symptoms. Our classification model achieved a 91.2% accuracy for the early period (03/2020-05/2020) and was applied to the Delta (07/2021–09/2021) and Omicron (12/2021–03/2022) periods for case identification. We identified 310, 8794, and 12,094 COVID-positive authors in the three periods, respectively. The top five common symptoms extracted in the early period were coughing (57%), fever (55%), loss of sense of smell (41%), headache (40%), and sore throat (40%). During the Delta period, these symptoms remained as the top five symptoms with percent authors reporting symptoms reduced to half or fewer than the early period. During the Omicron period, loss of sense of smell was reported less while sore throat was reported more. Our study demonstrated that NLP can be used to identify COVID-19 cases accurately and extracted symptoms efficiently.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

n-Butanol production by Rhodopseudomonas palustris TIE-1

Anthropogenic carbon dioxide (CO 2 ) release in the atmosphere from fossil fuel combustion has inspired scientists to study CO 2 to biofuel conversion. Oxygenic phototrophs such as cyanobacteria have been used to produce biofuels using CO 2 . However, oxygen generation during oxygenic photosynthesis adversely affects biofuel production efficiency. To produce n-butanol (biofuel) from CO 2 , here we introduce an n-butanol biosynthesis pathway into an anoxygenic (non-oxygen evolving) photoautotroph, Rhodopseudomonas palustris TIE-1 (TIE-1). Using different carbon, nitrogen, and electron sources, we achieve n-butanol production in wild-type TIE-1 and mutants lacking electron-consuming (nitrogen-fixing) or acetyl-CoA-consuming (polyhydroxybutyrate and glycogen synthesis) pathways. The mutant lacking the nitrogen-fixing pathway produce the highest n-butanol. Coupled with novel hybrid bioelectrochemical platforms, this mutant produces n-butanol using CO 2 , solar panel-generated electricity, and light with high electrical energy conversion efficiency. Overall, this approach showcases TIE-1 as an attractive microbial chassis for carbon-neutral n-butanol bioproduction using sustainable, renewable, and abundant resources.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A modular vaccine platform enabled by decoration of bacterial outer membrane vesicles with biotinylated antigens

Engineered outer membrane vesicles (OMVs) derived from Gram-negative bacteria are a promising technology for the creation of non-infectious, nanoparticle vaccines against diverse pathogens. However, antigen display on OMVs can be difficult to control and highly variable due to bottlenecks in protein expression and localization to the outer membrane of the host cell, especially for bulky and/or complex antigens. Here, we describe a universal approach for avidin-based vaccine antigen crosslinking (AvidVax) whereby biotinylated antigens are linked to the exterior of OMVs whose surfaces are remodeled with multiple copies of a synthetic antigen-binding protein (SNAP) comprised of an outer membrane scaffold protein fused to a biotin-binding protein. We show that SNAP-OMVs can be readily decorated with a molecularly diverse array of biotinylated subunit antigens, including globular and membrane proteins, glycans and glycoconjugates, haptens, lipids, and short peptides. When the resulting OMV formulations are injected in mice, strong antigen-specific antibody responses are observed that depend on the physical coupling between the antigen and SNAP-OMV delivery vehicle. Overall, these results demonstrate AvidVax as a modular platform that enables rapid and simplified assembly of antigen-studded OMVs for application as vaccines against pathogenic threats.

60 APPLIED LIFE SCIENCES↗