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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

L – H transition trigger physics in ITER-similar plasmas with applied n = 3 magnetic perturbations

In this work, the L – H transition power threshold Ρ LH is observed to increase with applied n = 3 Resonant Magnetic Perturbations (RMP) in ITER-similar-shape (ISS) plasmas with balanced neutral beam torque injection in DIII-D. The increase is most pronounced with added ECH: Ρ LH increases with decreasing edge plasma collisionality as Ρ LH / Ρ LH-08 ~ ( v *) -0.5 , where Ρ LH-08 is the 2008 ITPA multi-machine power threshold scaling. This result raises concerns for H-mode access at low edge collisionality in ITER, where resonant magnetic perturbations (RMP) may have to be applied before the L – H transition to safely suppress the first ELM. Non-axisymmetric modifications with RMP include a simultaneous reduction of the radial electric field ( E r ) well depth and E × B shear. This can be attributed to increasing edge toroidal co-current rotation, and is consistent with substantially increased local long-wavelength turbulence [measured via Beam Emission Spectroscopy (BES)]. At high RMP perturbation strength the edge electric field E r reverses sign locally (becomes positive), with changes in dominant turbulence modes. Edge magnetic stochasticity provides an attractive explanation of the observed modifications, and the observed changes in toroidal rotation and E r are consistent with a simple fluid model describing radial electron current flow along stochastic fieldlines. The observed collisionality dependence of the L-mode edge electric field with applied RMP is also qualitatively consistent with this model. Reflectometry data indicate a significant reduction of the normalized L-mode radial density gradient a/L n at high RMP field with simultaneous increase in radial particle flux and electron thermal flux from power balance analysis. We conjecture that the increase of Ρ LH with RMP results from the combined effects of reduced E × B flow shear (increasing turbulent transport levels) and toroidal/poloidal flow modulation due to edge stochasticity. Initial experiments indicate that non-resonant n = 3 magnetic perturbations lead only to relatively small changes in E r , E × B shear and fluctuation characteristics, and have less impact on the L – H transition power threshold. In conclusion, this motivates further exploration of the RMP spectrum dependence of Ρ LH for possible mitigation of the observed threshold increase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2000

Remote Sensing of Global Wetland Dynamics

Although natural wetlands only cover about 4% of the earth's ice-free land surface, they are the world's largest methane (CH4) source and the only one dominated by climate. In addition, wetlands affect climate by modulating temperatures and heat fluxes, storing water, increasing evaporation, and altering the seasonality of runoff and river discharge to the oceans. Current CH4 emissions from wetlands are relatively well understood but the sensitivity of wetlands and their emissions to climate variations remains the largest uncertainty in the global CH4 cycle and could strongly influence predictions of future climate. Therefore, characterizing climate-sensitive processes prevailing in the world's wetlands is crucial to understanding and predicting physical and biogeochemical responses of wetlands to interannual and longer-term climate variations. Recent research has resulted in the first generation of models to predict methane emissions from wetlands but the models must still be applied to static data on wetland distributions. Moreover, no models currently exist to realistically predict the distribution and dynamics of wetlands themselves for the current, or any other, climate. The dominant obstacle to modeling wetland dynamics has been lack of remote sensing techniques and data useful for characterizing quantitatively the seasonal and interannual variations of wetlands. We report on initial remote sensing studies undertaken to validate a global hydrological model linking rivers, takes and wetlands. Using a combination of SSM/I microwave and TOPEX Poseidon altimetry data sets, we developed and applied techniques to quantify inundation extent and duration for several large wetlands in tropical Africa and South America. Our initial results indicate that seasonally-inundated wetlands can be well characterized over large spatial scales and at monthly time scales using these remote sensing data. The results also confirm that currently available remote sensing products can be applied to provide crucial data to the research community modeling global hydrological and biogeochemical cycles.

Matthews, Elaine↗
DOE OSTI2024

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2022-2023

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2022 to July 2023. Eight Wingscape Timelapse Pro cameras, and thirty-one Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory?s Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Monitoring Atmospheric CO2 From Space: Challenge & Approach

Atmospheric CO2 is the key radiative forcing for the Earth's climate and may contribute a major part of the Earth's warming during the past 150 years. Advanced knowledge on the CO2 distributions and changes can lead considerable model improvements in predictions of the Earth's future climate. Large uncertainties in the predictions have been found for decades owing to limited CO2 observations. To obtain precise measurements of atmospheric CO2, certain challenges have to be overcome. For an example, global annual means of the CO2 are rather stable, but, have a very small increasing trend that is significant for multi-decadal long-term climate. At short time scales (a second to a few hours), regional and subcontinental gradients in the CO2 concentration are very small and only in an order of a few parts per million (ppm) compared to the mean atmospheric CO2 concentration of about 400 ppm, which requires atmospheric CO2 space monitoring systems with extremely high accuracy and precision (about 0.5 ppm or 0.125%) in spatiotemporal scales around 75 km and 10-s. It also requires a decadal-scale system stability. Furthermore, rapid changes in high latitude environments such as melting ice, snow and frozen soil, persistent thin cirrus clouds in Amazon and other tropical areas, and harsh weather conditions over Southern Ocean all increase difficulties in satellite atmospheric CO2 observations. Space lidar approaches using Integrated Path Differential Absorption (IPDA) technique are considered to be capable of obtaining precise CO2 measurements and, thus, have been proposed by various studies including the 2007 Decadal Survey (DS) of the U.S. National Research Council. This study considers to use the Intensity-Modulated Continuous-Wave (IM-CW) lidar to monitor global atmospheric CO2 distribution and variability from space. Development and demonstration of space lidar for atmospheric CO2 measurements have been made through joint adventure of NASA Langley Research Center and Exelis, Inc. As prototype space IPDA lidars, airborne laser absorption lidar systems operating in 1.57 CO2 absorption band have been developed and tested through lab, ground-based range, and flight campaigns. Very encouraging results have been obtained. The signal-to-noise ratio (SNR) for clear sky IPDA measurements of CO2 differential absorption optical depth (DAOD) for a 10-s integration over vegetated areas with about 10 km range was found to be as high as 1300, resulting in an error 0.077% or equivalent CO2 mixing ratio (XCO2) column precision of ~0.3 ppm. Precise range measurements using the IM-CW lidar approach were also achieved, and the uncertainties have been shown to be at sub meter level. Based on the airborne lidar development, space lidar and atmospheric CO2 observations are simulated. It shows that with the IM-CW approach, accurate atmospheric CO2 measurements can be achieved from space, and a space mission such as that proposed by the DS will meet science goals of atmospheric CO2 monitoring.

Lin, Bing↗
DOE OSTI2018

Oceanic Heat Delivery to the Antarctic Continental Shelf: Large-Scale, Low-Frequency Variability

According to the article, onshore penetration of oceanic water across the Antarctic continental slope (ACS) plays a major role in global sea level rise by delivering heat to the Antarctic marginal seas, thus contributing to the basal melting of ice shelves. Here the time-mean (Φ mean ) and eddy (Φ eddy ) components of the heat transport (Φ) across the 1,000-m isobath along the entire ACS are investigated using a 0.1° global coupled ocean/sea ice simulation based on the Los Alamos Parallel Ocean Program (POP) and sea ice (Community Ice CodE) models. In this work, comparison with in situ hydrography shows that the model successfully represents the basic water mass structure, with a warm bias in the Circumpolar Deep Water layer. Segments of on-shelf Φ, with lengths of O(100–1,000 km), are found along the ACS. The circumpolar integral of the annually averaged Φ is O(20 TW), with Φ eddy always on-shelf, while Φ mean fluctuates between on-shelf and off-shelf. Stirring along isoneutral surfaces is often the dominant process by which eddies transport heat across the ACS, but advection of heat by both mean flow-topography interactions and eddies can also be significant depending on the along- and across-slope location. The seasonal and interannual variability of the circumpolarly integrated Φ mean is controlled by convergence of Ekman transport within the ACS. Prominent warming features at the bottom of the continental shelf (consistent with observed temperature trends) are found both during high-Southern Annular Mode and high-Niño 3.4 periods, suggesting that climate modes can modulate the heat transfer from the Southern Ocean to the ACS across the entire Antarctic margin.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Ultrafast Modulation and Switching of Quantum-Well Lasers using Terahertz Fields

Modulation and switching of semiconductor lasers are important for laser-based information technology. Typically the speed of modulation and switching is limited by interband processes such as stimulated and spontaneous recombinations which occur on a nanosecond time scale. This is why the diode laser modulation has been restricted to tens of GHz. Modulation at higher speed is highly desirable as the information technology enters into the so-called tera-era. In this paper, we study the possibility of utilizing THz-field-induced plasma heating to modulate quantum-well lasers. This is a timely study since, with the advancement of THz solid-state sources and free-electron lasers, THz physics and related technology is currently coming out of its infancy. The investigation of interplaying THz and optical fields is also of intruiging fundamental interest. First, we introduce theoretical plasma heating results for the quantum-well optical amplifier in the presense of an intense half-cycle THz pulse. The heated carrier distributions are then utilized to calculate the THz-pulse-induced change in refractive index and gain profile. Since the electron-hole-plasma is heated using intraband transitions, we circumvent the usual complications due to an overall change in density, and the nonlinear recovery is governed solely by the carrier-LO-phonon interactions, typically 5 ps for a complete recovery. This procedure implies THz and sub-THz switching and recovery rates, respectively; using either gain modulation or index modulation. Plasma heating via steady-state THz fields is also studied. Finally, numerical simulation of a coupled set of equations to investigate the THz modulation based on a simplified model for quantum-well lasers is presented. Our results show that a semiconductor laser can be modulated at up to 1 THz with little distortion with a THz field amplitude at the order of a few kV/cm. Laser responses to a change in THz frequency will be shown. Constraints, practicalities, and applications will be discussed.

Ning, Cun-Zheng↗
DOE OSTI2018

Monte Carlo simulation of the SABRE PoP background

SABRE (Sodium-iodide with Active Background REjection) is a direct dark matter search experiment based on an array of radio-pure NaI(Tl) crystals surrounded by a liquid scintillator veto. Twin SABRE experiments in the Northern and Southern Hemispheres will differentiate a dark matter signal from seasonal and local effects. The experiment is currently in a Proof-of-Principle (PoP) phase, whose goal is to demonstrate that the background rate is low enough to carry out an independent search for a dark matter signal, with sufficient sensitivity to confirm or refute the DAMA result during the following full-scale experimental phase. As such, the impact of background radiation from the detector materials and the experimental site needs to be carefully investigated, including both intrinsic and cosmogenically activated radioactivity. Based on the best knowledge of the most relevant sources of background, we have performed a detailed Monte Carlo study evaluating the expected background in the dark matter search spectral region. The simulation model described in this paper guides the design of the full-scale experiment and will be fundamental for the interpretation of the measured background and hence for the extraction of a possible dark matter signal.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1997

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

Koch, Patrick N.↗
DOE OSTI2023

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2021-2022

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC, also referred to as the Garfield Fire Site), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from August 2021 to July 2022. Ten Wingscape Timelapse Pro cameras, and twenty seven Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory's Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. Additional information available in *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Impact of vegetation physiology and phenology on watershed hydrology in a semiarid watershed in the Pacific Northwest in a changing climate

Concurrent with changes in climate conditions, increases in atmospheric composition and transport can affect land surface processes by regulating physiological and phenological responses of plants, and consequently perturb water, carbon, and nitrogen (N) dynamics at multiple scales. Howerver, the relationships bwtween plants physiological and phenological and land surface processes in a changing climate are less well known due to the limitation of representing palnts properties in traditional hydrological models. In this study, we use the Community Land Model version 5 (CLM5) to investigate how projected changes in large scale atmospheric conditions can affect hydrologic and biogeochemical dynamics in the Upper Columbia-Priest Rapids (UCPR) watershed, a typical semi-arid watershed located in the north-western United States dominated by croplands. Six numerical experiments considering climate change, CO2 concentration, and N deposition consistent with the Representative Concentration Pathways (RCPs) 4.5 and 8.5 are performed at 1-km resolution over the period of 2015-2099. Our results show that, compared with historical results (1985-2014), the elevated CO2 directly increases plants N uptake rates that provide additional leaf N to enhance photosynthesis by the end of 21st century (2070-2099). The higher GPP leads to changes in stomatal resistance and increased leaf area index (LAI) that affect evaporatranspiration (ET) and its components. As a result of stomatal responses to a higher CO2 concentration, ET over corn fields declines by 24.6 mm yr-1 under RCP4.5, and by 64.0 mm yr-1 under RCP8.5, respectively by the end of the century from its historical mean of 428 mm yr-1. Meanwhile, ET over soybean fields increases by 27.7 mm yr-1 under RCP4.5 and 9.98 mm yr-1 under RCP8.5 from its historical mean of 507 mm yr-1 as a result of CO2 fertilization as soybeans are able to uptake more N to increase LAI significantly. Furtherfore, the changes in physiological and phenological in corn and soybean can strongly modulate water budget terms over the watershed in response to expected changes in greenhouse gas concentrations and atmospheric composition. Additionally, increases in CO2 concentration and N deposition are beneficial for improving water use efficiency of corn and soybean, therefore lead to less water consumption per unit gram of carbon produced from these crops. Our study elucidates the need to jointly consider effects of surface climate and atmospheric composition and transport in understanding and predicting watershed hydrologic and biogeochemical responses, especially for an agricultural watershed.

Zhu, Bowen↗
DOE OSTI2020

Hysteretic temperature sensitivity of wetland CH4 fluxes explained by substrate availability and microbial activity: Model Archive

This Modeling Archive is in support of an NGEE Arctic publication "Hysteretic temperature sensitivity of wetland CH4 fluxes explained by substrate availability and microbial activity" in the Journal Biogeosciences (https://doi.org/10.5194/bg-17-5849-2020), which includes the model data used in the publication. CH4 emissions from terrestrial systems are posited to increase, which can offset mitigation efforts and accelerate climate change. Yet, the accuracy of modeled CH4 emissions is sensitive to the prescribed CH4 production (or emission) temperature dependencies that are currently uncertain. Here, we use a comprehensive biogeochemistry model (ecosys) to investigate factors modulating CH4 production and emission rates across a permafrost thaw gradient encompassing a partly thawed bog and a fully thawed fen. We find that seasonally varying substrate availability drives lower and higher modeled methanogen biomass and activity, and thereby CH4 production, during the earlier and later periods of the thawed season, respectively. Package follows the Model data archiving guidelines with data in a *.zip file with three subfolders containing *.csv files and raw model output files; a data dictionary table (data_dictionary.csv) and two model output description tables (ecosys_plantspecies_output_notes.csv and ecosys_soil_ouput_notes.csv) to explain the format and meaning of individual output variables; and a user guide as a *.pdf. A detailed model description can be found in the supplement of (Grant, 2013). The ecosys source code is available at https://doi:10.5281/zenodo.3906642. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

X-Ray and UV Orbital Phase Dependence in LMC X-3

The black-hole binary LMC X-3 is known to be variable on time scales of days to years. We investigated X-ray and ultraviolet variability in the system as a function of the 1.7 d binary orbit using a 6.4 day observation with the Rossi X-ray Timing Explorer (RXTE) in 1998 December. An abrupt 14 % flux decrease lasting nearly an entire orbit was followed by a return to previous flux levels. This behavior occurred twice at nearly the same binary phase, but is not present in consecutive orbits. When the X-ray flux is at lower intensity, a periodic amplitude modulation of 7 % is evident in data folded modulo the orbital period. The higher intensity data show weaker correlation with phase. This is the first report of X-ray variability at the orbital period of LMC X-3. Archival RXTE observations of LMC X-3 during a high flux state in 1996 December show similar phase dependence. An ultraviolet light curve obtained with the High Speed Photometer (HSP) on the Hubble Space Telescope (HST) shows a phase dependent variability consistent with that observed in the visible, ascribed to the ellipsoidal variation of the visible star. The X-ray spectrum of LMC X-3 is acceptably represented by a phenomenological disk black-body plus a power law. Changes in the spectrum of LMX X-3 during our observations are compatible with earlier observations during which variations in the 2-10 keV flux are closely correlated with the disk geometry spectral model parameter.

Dolan, Joseph F.↗
NASA NTRS2009

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

Reichle, Rolf↗
DOE OSTI2025

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women

Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the semantic relationships in the text document although it has been widely applied in text mining. BERTopic, created in 2022, leveraged advances in deep learning and can capture the contextual relationships between words. In this work, we integrated Artificial Intelligence (AI) modules to LDA and BERTopic and provided a comprehensive comparison on the analysis of prescription opioid-related cardiovascular risks in women. Opioid use can increase the risk of cardiovascular problems in women such as arrhythmia, hypotension etc. 1,837 abstracts were retrieved and downloaded from PubMed as of April 2024 using three Medical Subject Headings (MeSH) words: “opioid,” “cardiovascular,” and “women.” Machine Learning of Language Toolkit (MALLET) was employed for the implementation of LDA. BioBERT was used for document embedding in BERTopic. Eighteen was selected as the optimal topic number for MALLET and 23 for BERTopic. ChatGPT-4-Turbo was integrated to interpret and compare the results. The short descriptions created by ChatGPT for each topic from LDA and BERTopic were highly correlated, and the performance accuracies of LDA and BERTopic were similar as determined by expert manual reviews of the abstracts grouped by their predominant topics. The results of the t-SNE (t-distributed Stochastic Neighbor Embedding) plots showed that the clusters created from BERTopic were more compact and well-separated, representing improved coherence and distinctiveness between the topics. Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. In addition, BERTopic has the connection port for ChatGPT-4-Turbo or other large language models in its algorithm for automatic interpretation, while with LDA interpretation must be manually, and needs special procedures for data pre-processing and stop words exclusion. Therefore, while LDA remains valuable for large-scale text analysis with resource constraints, AI-assisted BERTopic offers significant advantages in providing the enhanced interpretability and the improved semantic coherence for extracting valuable insights from textual data.

Research & Experimental Medicine↗
NASA NTRS2014

Technology Development for 3-D Wide Swath Imaging Supporting ACE

The National Academy of Sciences Decadal Survey (DS) Aerosol-Cloud-Ecosystems Mission (ACE) aims to advance our ability to observe and predict changes to the Earth's hydrological cycle and energy balance in response to climate forcing, especially those changes associated with the effects of aerosol on clouds and precipitation. ACE is focused on obtaining measurements to reduce the uncertainties in current climate models arising from the lack in understanding of aerosol-cloud interactions. As part of the mission instrument suite, a dual-frequency radar comprised of a fixed-beam 94 gigahertz (W-band) radar and a wide-swath 35 gigahertz (Ka-band) imaging radar has been recommended by the ACE Science Working Group.In our 2010 Instrument Incubator Program project, we've developed a radar architecture that addresses the challenge associated with achieving the measurement objectives through an innovative, shared aperture antenna that allows dual-frequency radar operation while achieving wide-swath (100 kilometers) imaging at Ka-band. The antenna system incorporates 2 key technologies; a) a novel dual-band reflectorreflectarray and b) a Ka-band Active Electronically Scanned Array (AESA) feed module. The dual-band antenna is comprised of a primary cylindrical reflectorreflectarray surface illuminated by a point-focus W-band feed (compatible with a quasi-optical beam waveguide feed, such as that employed on CloudSat); the Ka-band AESA line feed provides wide-swath across-track scanning. The benefits of this shared-aperture approach include significant reductions in ACE satellite payload size, weight, and cost, as compared to a two aperture approach. Four objectives were addressed in our project. The first entailed developing the tools for the analysis and design of reflectarray antennas, assessment of candidate reflectarray elements, and validation using test coupons. The second objective was to develop a full-scale aperture design utilizing the reflectarray surface and to detail specific requirements and trades for the Ka-band AESA line feed. As part of the third objective a subscale antenna, similar to the full-scale aperture design, was developed, integrated, and flown with the Cloud Radar System during the 2014 Integrated Precipitation and Hydrology Experiment. The fourth and ongoing objective entails developing a GaN MMIC (Gallium Nitride Monolithic Microwave Integrated Circuits) power amplifier for use in the Ka-band AESA. An overview of the progress made on this project and a look ahead at the 2013 IIP (Instrument Incubator Program) award selection will be presented.

Antenna↗
NASA NTRS1995

Coupled Monte Carlo Probability Density Function/ SPRAY/CFD Code Developed for Modeling Gas-Turbine Combustor Flows

The success of any solution methodology for studying gas-turbine combustor flows depends a great deal on how well it can model various complex, rate-controlling processes associated with turbulent transport, mixing, chemical kinetics, evaporation and spreading rates of the spray, convective and radiative heat transfer, and other phenomena. These phenomena often strongly interact with each other at disparate time and length scales. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and evaporation in many practical combustion devices. Turbulence manifests its influence in a diffusion flame in several forms depending on how turbulence interacts with various flame scales. These forms range from the so-called wrinkled, or stretched, flamelets regime, to the distributed combustion regime. Conventional turbulence closure models have difficulty in treating highly nonlinear reaction rates. A solution procedure based on the joint composition probability density function (PDF) approach holds the promise of modeling various important combustion phenomena relevant to practical combustion devices such as extinction, blowoff limits, and emissions predictions because it can handle the nonlinear chemical reaction rates without any approximation. In this approach, mean and turbulence gas-phase velocity fields are determined from a standard turbulence model; the joint composition field of species and enthalpy are determined from the solution of a modeled PDF transport equation; and a Lagrangian-based dilute spray model is used for the liquid-phase representation with appropriate consideration of the exchanges of mass, momentum, and energy between the two phases. The PDF transport equation is solved by a Monte Carlo method, and existing state-of-the-art numerical representations are used to solve the mean gasphase velocity and turbulence fields together with the liquid-phase equations. The joint composition PDF approach was extended in our previous work to the study of compressible reacting flows. The application of this method to several supersonic diffusion flames associated with scramjet combustor flow fields provided favorable comparisons with the available experimental data. A further extension of this approach to spray flames, three-dimensional computations, and parallel computing was reported in a recent paper. The recently developed PDF/SPRAY/computational fluid dynamics (CFD) module combines the novelty of the joint composition PDF approach with the ability to run on parallel architectures. This algorithm was implemented on the NASA Lewis Research Center's Cray T3D, a massively parallel computer with an aggregate of 64 processor elements. The calculation procedure was applied to predict the flow properties of both open and confined swirl-stabilized spray flames.

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DOE OSTI2020

Organismic materials for beyond von Neumann machines

The elementary basis of intelligence in organisms with a central nervous system includes neurons and synapses and their complex interconnections forming neural circuits. In non-neural organisms such as slime mold with gel-like media, viscosity modulation enables adaptation to changing environments. At a larger scale, collective intelligence emerges via social interactions and feedback in animal colonies. Learning and memory are therefore multi-scale features that evolve as a result of constant interactions with the environment. There is growing interest in emulating such features of intelligence in computing machines and autonomous systems. Materials that can respond to their environment in a manner similar to organisms (referred to as "organismic materials") therefore may be of interest as hardware components in artificial intelligence machines. In this brief review, we present a class of semiconductors called correlated oxides as candidates for learning machines. The term "correlated" refers to the fact that electrons in such lattices strongly interact and the ground state is not what is predicted by classical band theory. Such materials can undergo insulator-metal transitions at near ambient conditions under external stimuli such as thermal or electrical fields, strain, and chemical doping. Depending on the mechanism driving the transition, intermediate states can be metastable with different volatilities, and the time scales of phase change can be controlled over many orders of magnitude. The change in electronic properties can be sharp or gradual, leading to digital or analog behavior. These properties enable the realization of artificial neurons and synapses and emulate the associative and non-associative learning characteristics found in various organisms. We examine microscopic properties concerning electronic and structural transitions leading to collective behavior and theoretical treatments of the ground state and dynamical response, showcasing VO 2 as a model system. Next, we briefly review algorithms designed from the plasticity demonstrated by phase changing systems. Finally, we conclude the brief review with suggestions for future research toward realizing non-von Neumann machines.

42 ENGINEERING↗
DOE OSTI2019

Commercial Building Technology Demonstration (Final Scientific/Technical Report)

The background for this project was a unique and innovative concept that had been proposed and demonstrated by enVerid Systems, reducing the energy consumption in HVAC systems in commercial and public buildings by up to 50% at peak loads. The concept involves selective scrubbing of gas contaminants from indoor air as a practical substitute for outside air ventilation, the latter being the conventional practice today. This scrubbing enables recycling of most of the indoor air and significantly decreasing the amount of outside air, resulting in a reduced HVAC load and commensurate energy savings for the facility. Key to our approach is low cost scrubbing of all gas contaminants from indoor air using novel, efficient and regenerable sorbent materials. The total solution, labeled HLR (HVAC Load Reduction) is implemented by means of compact modules that can be retrofitted onto virtually any building, and utilizes novel sorbents that have been developed and brought to scale production by enVerid. Although the technology had been deployed and demonstrated, the US commercial building and HVAC markets, famously conservative with respect to innovation and new technologies, had yet to embrace the idea or the product. The overarching goal of the project was to help overcome market hesitancy and enable widespread adoption, by creating a critical mass of success stories across different regions and building types, all under oversight and verification of the DOE and NREL, to ensure credibility and accuracy. The project, overall, was a resounding success. Several installations were deployed and tested comprehensively for the impact on both energy consumption and indoor air quality, and results were not only excellent, but quantitatively in line with expectations. A total number of eight (8) installations were attempted, with 2 aborted due to building issues. Of the six successful installations, however, complete M&V was performed by NREL on 2 (Miami and NYC) and partial analysis on a third site (ArcBest), and these three, along with their results, were therefore presented from a financial and reporting standpoint. Although the number of case studies fell short of the original target of 10, we nevertheless had excellent demonstrations in vastly different climate zones: Southeast, Northeast and Midwest, and in very different building types. This included a modern high-rise office building in New York City and a University Campus health center in Miami, and a mid-rise high-density office in Arkansas. The cooling load reduction was shown to be significant, averaging 37% during the final cooling season in the Miami site. In the NYC site, the cooling energy savings were generally less, at around 12%, as expected. While this is a lower number for average/total savings, two comments are important to note: (i) the outside airflow (OA) reduction was not consistent during the data collection period, at least in part understating the attainable savings through incorrect measurement of the “high energy” reference state; and (ii) the peak impact in NYC is almost certainly as high as Miami, with critical ramifications for peak load reduction and equipment downsizing ability. Importantly, the measured energy savings in all locations were related to the outdoor climate conditions and the actual achievable reduction in outside air, very much in line with models and calculations; this leaves us with increased confidence in our understanding of the interaction between the technology and the building, and our ability to project the impact of this innovation in the future, through broad adoption. Simply put: the energy savings and load reduction impact of the HLR solution has been confirmed quantitatively. The results also confirmed the air quality objective. This may be even more significant, in that air quality is more complex and harder to measure and quantify, and the performance of the HLR as an air scrubber is the linchpin of the entire solution. In all sites, indoor air quality met or exceeded the required parameters, in terms of achieving the target (low) levels of indoor pollutants. Furthermore, the concentrations of outdoor sourced pollutants were markedly lower, as expected, mostly due to the reduction in outside air intake although in part also due to the scrubbing. The success was not immediate nor easy, and early challenges with the systems, especially (but not only) around controls and communication, caused delays in commissioning and undermined some of our M&V schedules. The good news is no fundamental issues were encountered and the number of such glitches was declining quickly by the end of the project. Other challenges had to do with coordinating the control of the building OA dampers, which the HLR needs to have in order to deliver the load reduction, but which the facility manager controls regularly and independently. This is not necessarily a problem for normal HLR operation but interferes with accurate M&V, where switching OA settings back and forth on a precise timetable is essential for clean data. The project provided valuable experience in retrofitting buildings that had been originally designed to operate with less recirculation and more outside air, and some key learnings related to the cyclical regeneration of the sorbents in the operational environment of the building. Some of these learnings gave already been incorporated into ongoing improvements in the design of the HLR module as well as the software that is used to control its operation. The cost and time of retrofit installations is much better understood; so is the test and balance procedure of the building that determines the available range of outside air reduction, which in turn determines the amount of load reduced. We had also implemented at least one annual cycle of sorbent cartridge replacement in the field, after which we tested the used sorbent to assess the rate of degradation of sorbent potency – an important factor affecting the long-term economics of HLR deployments. A notable shortfall of the project, other than the fact that the number of sites was below target, was that we had not (yet) completed testing to measure and verify (M&V) the winter energy savings. This is primarily due to late start on the NYC sites (Miami does not portend any heating savings associated with reduced outside air), combined with the issues of OA damper control. It is by no means suggested that such savings cannot be captured, only that the M&V with respect to winter in NYC has been incomplete. The value of this project and its interest to the general public are hard to overstate. The case studies created from Miami and especially from NYC have, without a doubt, opened up the interest of the broad HVAC industry to HLR in the past year. Major manufacturer reps have signed up to represent and promote the product, and dozens of top tier engineering consultants have introduced HLR as a base of design in upcoming construction and renovation projects – precisely the overarching goal of this project. These would not have happened without the highly visible installation in NYC and its ultimately satisfied customer. Furthermore, the DOE itself issued a report in late 2017 analyzing hundreds of candidate technologies for reducing energy consumption in HVAC; remarkably, the budding HLR solution ranked among the top 3(!); no doubt, its status as a viable and significant contender on this list is informed by the success of these demonstrations. And furthermore, in the wake of these demos, several major energy utilities, led by ConEdison in NYC, have endorsed the HLR solution and now routinely provide substantial cash rebates for customers choosing to incorporate the HLR in their buildings and reap the benefit of the reduced peak load as well as reduced cumulative energy demand. Last but not least, in January of 2019, as this report was being written, the HLR module won the AHR Expo Innovation Award for Green Buildings and, remarkably, the prestigious and only Product of the Year 2019, being selected by an independent professional panel of judges from AHR and ASHRAE. Given the confirmation of the enormous energy saving potential of HLR in widescale deployment, as well as ancillary but significant benefits in terms of equipment downsizing and indoor air quality, the benefit of this effort to the public speaks for itself. Accelerating adoption of HLR, without dependence on subsidies and driven by the private sector, is well under way. There is still much work to be done in terms of educating the HVAC and construction ecosystems and improving the product’s robustness and simplicity, to further facilitate the adoption of this technology and the capture of its potential value. But the American public will greatly benefit both directly and indirectly in the immediate future and beyond.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗