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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Wind Tunnel Model Design for Sonic Boom Studies of Nozzle Jet Flows with Shock Interactions

NASA and the U.S. aerospace industry are performing studies of supersonic aircraft concepts with low sonic boom pressure signatures. The computational analyses of modern aircraft designs have matured to the point where there is confidence in the prediction of the pressure signature from the front of the vehicle, but uncertainty remains in the aft signatures due to boundary layer and nozzle exhaust jet effects. Wind tunnel testing without inlet and nozzle exhaust jet effects at lower Reynolds numbers than in-flight make it difficult to accurately assess the computational solutions of flight vehicles. A wind tunnel test in the NASA Ames 9- by 7-Foot Supersonic Wind Tunnel is planned for February 2016 to address the nozzle jet effects on sonic boom. The experiment will provide pressure signatures of test articles that replicate waveforms from aircraft wings, tails, and aft fuselage (deck) components after passing through cold nozzle jet plumes. The data will provide a variety of nozzle plume and shock interactions for comparison with computational results. A large number of high-fidelity numerical simulations of a variety of shock generators were evaluated to define a reduced collection of suitable test models. The computational results of the candidate wind tunnel test models as they evolved are summarized, and pre-test computations of the final designs are provided.

Wind Tunnel↗
NASA NTRS2024

Evaluating Differences Among Crop Models in Simulating Soybean in-Season Growth

Crop models are useful tools for simulating agricultural systems that require continued model development and testing to increase their robustness and improve how they describe our current understanding of processes. Coordinated and “blind” evaluation of multiple models using same protocols and experimental datasets provides unique opportunities to further improve models and enhance their reliability. For soybean [Glycine max (L.) Merr.], there has been limited coordinated multi-model evaluations for the simulation of in-season plant growth dynamics. We evaluated ten dynamic soybean crop models for their simulation of in-season plant growth using data from five experiments conducted in Argentina, Brazil, France, and USA. We evaluated models after a Blind (using only phenology data) and a Full calibration (with in-season and end-of-season variables). Calibration reduced model uncertainty by reducing standard bias for the simulation of in-season variables (biomass, leaf, pod, and stem weights, and leaf area index, LAI). However, we found that most models had difficulty in reproducing leaf growth dynamics, with normalized root mean squared error (nRMSE) of 56% for leaf weight and 43% for LAI (across locations and models after Full calibration). Models with different levels of complexity and experience were capable of simulating final seed yield at maturity with reasonable accuracy (nRMSE of 8–31% after Full calibration). However, the nRMSE for pod weight (of 17–64% after Full calibration) was two-fold larger than that of seed yield. Moreover, the models differed in how they simulated timing from sowing to beginning seed growth (47–93 days) and effective seed filling period (18–54 days), owing to model structural differences in defining the reproductive developmental stages. Overall, we identified the following processes that can benefit from further model improvement: leaf expansion and senescence, reproductive phenology, and partitioning to reproductive growth. Simulation of pod wall tissue and individual seed cohorts is another aspect that many models currently lack. Model improvement can benefit from high-temporal resolution experimental datasets that concurrently account for phenology, plant growth, and partitioning. Further, we recommend collecting reproductive phenology in the field consistent with actual dry matter allocation to organs in the models and collecting multiple observations of seed and pod weight to aid model improvement for simulation of seed growth and yield formation.

Agricultural Model Intercomparison and Improvement↗
DOE OSTI2024

Graph neural networks for CO 2 solubility predictions in Deep Eutectic Solvents

Deep Eutectic Solvents (DESs) are a promising class of solvents for CO 2 capture. DESs are complex mixtures that can be designed to optimize CO solubility and overall capture process efficiency. However, the vast design landscape of DES mixtures makes experimental investigation prohibitive; as such, there is a need for computational models that can quickly and efficiently navigate the design space and inform data collection efforts. In this work, we propose Graph Neural Network (GNN) models for predicting CO 2 solubility for DESs; the GNN leverages a mixture graph representation that captures the molecular structure of the DES components as well as their intermolecular interactions. Here, we compare the GNN framework against alternative architectures (neural networks, graph convolution networks, and random forests) and data representations (molecular fingerprints, sigma profiles, and graphs). We show that the proposed approach offers superior predictive performance; specifically, we show that solubility can be predicted reliably directly from molecular structure (without the need of using sigma profiles as proposed in previous studies). This result is important, as obtaining sigma profiles requires expensive density functional theory computations. We also explored the ability of GNNs to predict solubility for new DES mixtures and operating conditions. We found that the model extrapolates across temperature reliably. However, we also found deficiencies in the ability of the model to predict solubility for DES mixtures, pressures, and molar ratio not included in the training sets; we show that this is due to an inherent lack of chemical diversity in datasets available in the literature. The proposed computational capabilities can thus help navigate the design space of DES and inform data collection efforts. Our models, data, and benchmarks are shared as Python code implemented in Jupyter notebooks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Continental Scale Aerosol Optical Properties Over East Asia as Measured by Aeronet and Comparison to Satellite and Modeled Results

The AERONET program has operated in E. Asia since 1995 providing time continuous and time averaged ground-based column-integrated aerosol optical properties in a variety of aerosol regimes In the last four years the distribution has greatly increased in Siberia, China, SE Asia and India in particular. Commensurate with that, significant improvement in data processing algorithms (Version 2.0) and access to ancillary data products through the WWW have become available to the scientific community. At this writing the following distribution represents E and S. Asia: 5 sites operate in Siberia (2 years), 1 in Mongolia (9 years), 3 in Korea (3 to 6 years), 3 in Japan (2 to 7 years), China 11 (6 to 0 years), Taiwan 4 (7 to 2 yrs), Viet Nam 2 (4 years), Thailand 2 to 5 (4 years), and Singapore 1 (4 months), India 1 to 3 (7 to 1 years), Pakistan 2 (1 year), and UAE 3 (3 years). An analysis of the aerosol optical depth at 500 nm using annual average quality assured AERONET data (pre 2006) was used to estimate the mean annual aerosol loading by continent, sub continent and ocean. The individual site data were assumed representative of regional aerosol loading and aggregated to the sub-continental, continental and oceanic areas and presented. This analysis will be updated with more recent data with particular emphasis on seasonal results for Asia and the addition of single scattering albedo retrievals. The ground based results will be compared to MODIS collection 5 results and model estimates for E. Asia using the AERONET Synergy Tool.

Holben, B. N.↗
NASA NTRS1998

Stratospheric Sulfuric Acid and Black Carbon Aerosol Measured During POLARIS and its Role in Ozone Chemistry

Stratospheric aerosol can affect the environment in three ways. Sulfuric acid aerosol have been shown to act as sites for the reduction of reactive nitrogen and chlorine and as condensation sites to form Polar Stratospheric Clouds, under very cold conditions, which facilitate ozone depletion. Recently, modeling studies have suggested a link between BCA (Black Carbon Aerosol) and ozone chemistry. These studies suggest that HNO3, NO2, and O3 may be reduced heterogeneously on BCA particles. The ozone reaction converts ozone to oxygen molecules, while HNO3 and NO2 react to form NOx. Finally, a buildup of BCA could reduce the single-scatter albedo of aerosol below a value of 0.98, a critical value that has been postulated to change the effect of stratospheric aerosol from cooling to warming. Correlations between measured BCA amounts and aircraft usage have been reported. Attempts to link BCA to ozone chemistry and other stratospheric processes have been hindered by questions concerning the amount of BCA that exists in the stratosphere, the magnitude of reaction probabilities, and the scarcity of BCA measurements. The Ames Wire Impactors (AWI) participated in POLARIS as part of the complement of experiments on the NASA ER-2. One of our main objectives was to determine the amount of aerosol surface area, particularly BCA, available for reaction with stratospheric constituents and assess if possible, the importance of these reactions. The AWI collects aerosol and BCA particles on thin Palladium wires that are exposed to the ambient air in a controlled manner. The samples are returned to the laboratory for subsequent analysis. The product of the AWI analysis is the size, surface area, and volume distributions, morphology and elemental composition of aerosol and BCA. This paper presents results from our experiments during POLARIS and puts these measurements in the context of POLARIS and other missions in which we have participated. It describes modifications to the AWI data analysis procedures in which the collection of BCA is modeled as a fractal aggregate. The new analysis results in an increase in BCA surface area of approximately 24 and an increase in mass of 7-10 from the previous method. For the current study, BCA surface area is used in computer models that attempt to predict measured NOx/NOy ratios and O3 depletion rates. Inclusion of the HNO3 reaction with BCA in one model tends to improve the agreement of calculated to measured NOx/NOy ratio. However, it was found that these trends are viable only if the reactions are catalytic.

Strawa, Anthony W.↗
NASA NTRS2018

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

Forest Productivity↗
NASA NTRS1993

Mixing model analysis of telescopic lunar spectra

We have analyzed very high quality reflectance spectra of the lunar surface from the University of Hawaii lunar spectral data collection using a spectral mixing model. The spectra analyzed are those of 45 mare sites and 75 highland sites. The spectra were selected on the basis of very high signal to noise ratios based on error bars and point to point scatter, and on quality of removal of telluric water bands. The spectral mixing model used 7 components, not all of which were used in each fit. Four of the components were mineral spectra of the orthopyroxene, a clinopyroxene, an olivine and an anorthite, measured at the Brown University's RELAB. All of the minerals were 45-90 micron splits. Lunar soil contains other components which have the effect of reddening and darkening the soil as well as reducing spectral contrast. In addition, lunar soil contains spectral neutral bright material (likely very fine grained feldspar) which serves to reduce spectral contrast and brighten soils. Early attempts to fit many of the spectra pointed out the need for a component which has a very broad smooth absorption feature centered near 1.1 microns. Glass is a good candidate for this component. For the bright component we used a flat reflectance of 70 percent to represent fine grained feldspar. For the 'glass' component we used a telescopic spectrum of a pyroclastic glass present on the Aristarchus plateau which is characterized by a strong smooth band centered at 1.07 microns. In addition to exhibiting the glass band this spectrum is very red and has a low albedo. On the assumption that the dark component and the red component are agglutinates, which is reasonable but not necessarily true, we sought a dark red component. To derive its properties we modelled the spectrum of an Apollo 16 soil (16xxx) and assumed the dark red component to comprise 60 percent of the soil, appropriate to agglutinate abundance in mature soil. We adjusted the albedo and slope of a straight line representing the dark red component until the contrast and albedo of the model spectrum matched the soil spectrum. The mixing was done after conversion to a single scattering albedo.

Lucey, Paul G.↗
NASA NTRS1983

Acoustic measurements of the X-wing rotor

Noise measurements of a stoppable X-wing rotor system model, tested in the Ames 40- by 80-foot wind tunnel, are summarized. Performance, control system stability, and noise of the model were investigated at various forward speeds, tip speeds, collective blade angles, jet blowing velocities, and model attack angles. The model was tested in the rotating wing helicopter configuration, in the fixed wing configuration, and in wing configurations between the two. Noise data obtained in the helicopter configuration at the two highest tip speeds (Mach 0.44 and 0.47) and at wind tunnel speeds below 140 knots are reported. Test configuration and performance information are included. General acoustic measurements (dB, dBA, and PNdB) at six microphone locations are presented for all conditions under which the background noise was below the model noise. More specific measurements (1/3-octave and blade passage frequency harmonic levels) are presented for selected conditions. Graphs of dBA and 1/3-octave spectra, which show the noise trends as functions of operating condition, are included. The noise depends mainly on the jet blowing velocity. The noise levels were highest at moderate jet blowing velocities, less at the highest velocity, and lowest with no blowing at all.

Mosher, M.↗
NASA NTRS1987

Space Station/Shuttle Orbiter dynamics during docking

Mathematical models of a reference space station configuration (Power Tower) and a Space Shuttle Orbiter are developed and used to study the dynamic behavior of the Space Station/Orbiter system just prior to and subsequent to an impulsive docking of the two spacecraft. The physical model of the space station is a collection of rigid and flexible bodies. The orbiter is modeled as a rigid body. An algorithm developed for use in digitally simulating the dynamics of the system is described and results of its application are presented.

Fitz-Coy, N. G.↗
NASA NTRS2021

Post-Landing Major Element Quantification Using SuperCam Laser Induced Breakdown Spectroscopy

The SuperCam instrument on the PerseveranceMars 2020 rover uses a pulsed 1064 nm laser to ablate targets at a distance and conduct laser induced breakdown spectroscopy (LIBS) by analyzing the light from the resulting plasma. SuperCam LIBS spectra are preprocessed to remove ambient light, noise, and the continuum signal present in LIBS observations. Prior to quantification, spectra are masked to remove noisier spectrometer regions andspectra are normalized to minimize signal fluctuations and effectsof target distance.In some cases, the spectra are also standardized or binned prior to quantification. To determine quantitative elemental compositionsof diverse geologic materials at Jezero crater, Mars, we use a suite of 1198 laboratory spectra of 334 well-characterized reference samples. The samples were selected to span a wide range of compositions and include typical silicate rocks, pure minerals (e.g.,silicates, sulfates, carbonates, oxides),more unusual compositions (e.g.,Mn oreand sodalite), andreplicates of the sintered SuperCam calibration targets (SCCTs) onboardthe rover. For each major element (SiO2, TiO2, Al2O3, FeOT, MgO, CaO, Na2O, K2O), the database was subdivided into five“folds” with similar distributions of the element of interest. One fold was held out as an independent test set, and the remaining fourfolds were used to optimize multivariate regression models relating the spectrum to the composition. We considered a variety of models, and selected several for further investigation for each element, based primarily on the root mean squared error of prediction (RMSEP) on the test set, when analyzed at 3m. In cases with several models of comparable performance at 3 m, we incorporated the SCCT performance at different distances to choose the preferred model. Shortly after landing on Mars and collecting initial spectra of geologic targets, we selected one model per element. Subsequently, with additional data from geologic targets, some models were revised to ensure results that are more consistent with geochemical constraints. The calibration discussed here is a snapshot of an ongoing effort to deliver the most accurate chemical compositions with SuperCam LIBS.

Mars 2020↗
DOE OSTI2025

U.S. Solar Siting Regulation and Zoning Ordinances (2025)

A machine readable collection of documented solar siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, which leverages Large Language Models (LLMs) to automate the collection of local codes and ordinances applicable to energy infrastructure. URLs for the ordinance source documents are included in the Solar Ordinances spreadsheet. The GeoPackage file included below contains the jurisdiction shapes for each ordinance. Note that the GeoPackage file is formatted for ingestion by NLR's reVX setbacks tool and therefore does not contain any of the state-level regulations. NOTE: This data was collected with the help of generative AI. The Large Language Models used for this effort make mistakes. Always validate the data for critical use cases. This data is an update to a previously developed database of wind ordinances found in OEDI Submission 5734: see the "U.S. Solar Siting Regulation and Zoning Ordinances 2022" link below. INFRA-COMPASS version used for collection: v0.11.3 LLMs used for collection: GPT-4.1, GPT-4.1 mini, GPT-4.1 nano

14 SOLAR ENERGY↗
DOE OSTI2025

U.S. Wind Siting Regulation and Zoning Ordinances (2025)

A machine readable collection of documented wind siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, which leverages Large Language Models (LLMs) to automate the collection of local codes and ordinances applicable to energy infrastructure. URLs for the ordinance source documents are included in the Wind Ordinances spreadsheet. The GeoPackage file included below contains the jurisdiction shapes for each ordinance. Note that the GeoPackage file is formatted for ingestion by NREL's reVX setbacks tool and therefore does not contain any of the state-level regulations. NOTE: This data was collected with the help of generative AI. The Large Language Models used for this effort make mistakes. Always validate the data for critical use cases. This data is an update to a previously developed database of wind ordinances found in OEDI Submission 5733: see the "U.S. Wind Siting Regulation and Zoning Ordinances 2022" link below. INFRA-COMPASS version used for collection: v0.8.2 LLMs used for collection: GPT-4.1, GPT-4.1 mini, GPT-4.1 nano, GPT-4o mini

17 WIND ENERGY↗
DOE OSTI2024

Searching for beyond the Standard Model physics using the improved description of 100 Mo $2\nu \beta \beta$ decay spectral shape with CUPID-Mo

The current experiments searching for neutrinoless double-β ($0\nu \beta \beta$) decay also collect large statistics of Standard Model allowed two-neutrino double-β ($2\nu \beta \beta$ ) decay events. These can be used to search for Beyond Standard Model (BSM) physics via $2\nu \beta \beta$ decay spectral distortions. 100 Mo has a natural advantage due to its relatively short half-life, allowing higher $2\nu \beta \beta$ decay statistics at equal exposures compared to the other isotopes. We demonstrate the potential of the dual read-out bolometric technique exploiting a 100 Mo exposure of 1.47 kg years, acquired in the CUPID-Mo experiment at the Modane underground laboratory (France). We set limits on $0\nu \beta \beta$ decays with the emission of one or more Majorons, on $2\nu \beta \beta$ decay with Lorentz violation, and $2\nu \beta \beta$ decay with a sterile neutrino emission. In this analysis, we investigate the systematic uncertainty induced by modeling the $2\nu \beta \beta$ decay spectral shape parameterized through an improved model, an effect never considered before. This work motivates searches for BSM processes in the upcoming CUPID experiment, which will collect the largest amount of $2\nu \beta \beta$ decay events among the next-generation experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1980

Plasma collection by high voltage spacecraft at low earth orbit

A computer model of the three-dimensional sheath formation and plasma current collection by high voltage spacecraft has been developed. By using new space charge density and plasma collection algorithms, it is practical to perform calculations for large, complex spacecraft. The model uses NASCAP compatible objects and geometries. Results indicate that ion focusing observed in the laboratory during high voltage collection experiments is probably due to voltage gradients on the collecting surfaces.

Katz, I.↗
DOE OSTI2025

Development of Predictive Models for Advanced Reactor Autonomous Control

Advanced reactor designs including microreactors and small modular reactors will contribute to the clean production of cheap energy, and autonomous control for advanced reactors is an appealing option for reducing cost. However, there is a lack of industry experience applying autonomous control for advanced nuclear reactors. To accelerate the development and industry acceptance of autonomous control software for nuclear reactors, we aim to demonstrate autonomous control of the Purdue University research reactor (PUR-1) using INL-developed model predictive control (MPC) methods. To prepare for this demonstration, data-driven predictive models based on process data collected from PUR-1 have been developed and integrated with MPC and used to control a physics-based model of PUR-1. A data-driven dynamics model and a gated recurrent unit (GRU) network were both trained on process data from PUR-1. The dynamics model was shown to effectively control the reactor model with MPC when provided reactivity as a control variable but failed to control the model through the control rod positions. The GRU network produced more accurate predictions than the dynamics model when evaluated on operational data, and future work will include the evaluation of the GRU network in the controller.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Structural interactions of TLP18.3 and Psb27-H1 to the luminal CP43 and Rubredoxin-ENH1 to the stromal side of Photosystem II in higher plants

TLP18.3 and Psb27 are known proteins on the luminal side of photosystem II. The structural locations of these two proteins are still absent in the currently available higher plant photosystem II cryo-EM structures. We interrogated the structural locations of these proteins using chemical cross-linking followed by liquid chromatography/tandem MS analysis. Structural mass spectrometry results then provided chemical restrains to direct structural modelling to determine the collective binding/stabilization of these two proteins to the luminal PSII CP43 protein. Using this pipeline, we also found the structural location of a Rubredoxin protein on the stromal side of PSII. Discovery of this redox active iron-sulfur protein in the vicinity of PSII subunit D1/D2 proteins, greatly showcases the importance of the redox processes that are potentially involved in PSII assembly or less known steady state functionality or photoprotection. This structural mass spectrometry platform high-lights its powerful applicability in protein complex discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Microbial inoculants and invasions: a call to action

Microbial inoculants are increasingly used for beneficial purposes in agriculture, bioremediation, and medicine, but they can carry risks of generating invasive microbes. Here, we present a roadmap for guarding against these invasions, proposing developing (i) coherent mechanistic understandings of how microbial inoculants can effect invasions, (ii) predictive models forecasting microbial invasion risks, and (iii) effective management strategies. To guide mechanistic understandings, we distill 17 guiding hypotheses. For predictive modeling, we highlight data collection needs and qualitative approaches. For management strategies, we stress the importance of accurately weighing the risks against benefits. The unified approach presented here provides a route toward an effective research and management infrastructure for microbial inoculants in order to avoid potentially catastrophic microbial invasions.

invasive species↗