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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Matrix-Assisted Ionization of Molecular Uranium Species

Matrix-assisted ionization (MAI) demonstrates high sensitivity for a variety of organic compounds; however, few studies have reported the application of MAI for the detection and characterization of inorganic analytes. Trace-level uranium analysis is important in the realms of nuclear forensics, nuclear safeguards, and environmental monitoring. Traditional mass spectrometry methods employed in these fields require combinations of extensive laboratory chemistry sample preparation and destructive ionization methods. There has been recent interest in exploring ambient mass spectrometry methods that enable timely sample analysis and higher sensitivity than what is attainable by field-portable radiation detectors. Rapid characterization of uranium at nanogram levels is demonstrated in this study using MAI techniques. Mass spectra were collected on an atmospheric pressure mass spectrometer for solutions of uranyl nitrate, uranyl chloride, uranyl acetate, and uranyl oxalate utilizing 3-nibrobenzonitrile as the ionization matrix. The uranyl complexes investigated were detectable, and the chemical speciation was preserved. Sample analysis was accomplished in a matter of seconds, and limits of detection of 5 ng of uranyl nitrate, 10 ng of uranyl oxalate, 100 ng of uranyl chloride, and 200 ng of uranyl acetate were achieved. The observed gas-phase speciation was similar to negative-ion electrospray ionization of uranyl compounds with notable differences. Six matrix-derived ions were detected in all negative-ion mass spectra, and some of these ions formed adducts with the uranyl analyte. Subsequent analysis of the matrix suggests that these molecules are not matrix contaminants and are instead created during the ionization process.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1981

Effect of storing B-staged graphite/polyimide on fabrication of structural elements

Graphite/polyimide structural elements have been successfully fabricated by forming and curing B-staged Celion 6000/PMR-15 and Celion 6000/LaRC-160 laminates in heated matched metal tooling. The B-staged laminates were subjected to storage for various periods of time up to six months at ambient shop conditions and high humidity prior to fabrication into structural elements to determine the processability of the graphite/polyimide after exposure to these conditions. Changes in processability were monitored by measuring flexure and interlaminar shear strengths, glass transition temperature, moisture content, and formability of the B-staged laminates. No significant change in the processability of either Celion 6000/PMR or Celion 6000/LaRC-160 was recorded indicating that after B-staging the graphite/polyimide laminates can be stored for extended periods of time in normal shop and high humidity environments and then be fabricated into defect-free structural elements in heated platen presses.

Baucom, R. M.↗
NASA NTRS2003

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Ghoshal, Anindya↗
NASA NTRS2022

Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast

Forecasting ambient PM2.5 concentrations with spatiotemporal coverage is key to alerting decision-makers of pollution episodes and preventing detrimental public exposure, especially in regions with limited ground air monitoring stations. The existing methods either rely on chemical transport models (CTMs) to forecast spatial distribution of PM2.5 with nontrivial uncertainty or statistical algorithms to forecast PM2.5 concentration time-series at air monitoring locations without continuous spatial coverage. In this study, we developed a PM2.5 forecast framework by combining the robust Random Forest algorithm with a publicly accessible global CTM forecast product – NASA’s Goddard Earth Observing System “Composition Forecasting” (GEOS-CF), providing spatiotemporally continuous PM2.5 concentration forecasts for the next five days at a 1-km spatial resolution. Our forecast experiment was conducted for a region in Central China including the populous and polluted Fenwei Plain. The forecast for the next two days had overall validation R2 of 0.76 and 0.64, respectively; the R2 was around 0.5 for the following three forecast days. Spatial cross-validation showed similar validation metrics. Our forecast model, with validation normalized mean bias close to zero, substantially reduced the large biases in GEOS-CF. The proposed framework requires minimal computational resources compared to running CTMs at urban scales, enabling near-real-time PM2.5 forecast in resource-restricted environments.

PM2.5↗
NASA NTRS1996

Enhanced Raman Monitor Project

Monitoring of gaseous contaminants stems from the need to ensure a healthy and safe environment. NASA/Ames needs sensors that are able to monitor common atmospheric gas concentrations as well as trace amounts of contaminant gases. To provide an accurate assessment of air quality, a monitoring system would need to be continuous and on-line with full spectrum capabilities, allowing simultaneous detection of all gas components in a sample, including both combustible and non-combustible gases. The system demands a high degree of sensitivity to detect low gas concentrations in the low-ppm and sub-ppm regions. For clean and healthy air ('good' category), criteria established by the EPA requires that contaminant concentrations not exceed 4 ppm of carbon monoxide (CO) in an 8 hour period, 60 ppb of ozone(O3) in a one hour period and 30 ppb of sulfur dioxide (SO2) in a 24 hour period. One step below this is the National Ambient Air Quality Standard ('moderate' category) which requires that contaminant concentrations not exceed 9 ppm of carbon monoxide (CO), 120 ppb of ozone (O3) and 140 ppb of sulfur dioxide (SO2) for their respective time periods. Ideally a monitor should be able to detect the concentrations specified in the 'good' category. To benchmark current abilities of Raman technology in gas phase analysis, laboratory experiments were performed to evaluate the RASCAL II anesthetic gas monitor.

Westenskow, Dwayne↗
NASA NTRS1994

Flight test of takeoff performance monitoring system

The Takeoff Performance Monitoring System (TOPMS) is a computer software and hardware graphics system that visually displays current runway position, acceleration performance, engine status, and other situation advisory information to aid pilots in their decision to continue or to abort a takeoff. The system was developed at the Langley Research Center using the fixed-base Transport Systems Research Vehicle (TSRV) simulator. (The TSRV is a highly modified Boeing 737-100 research airplane.) Several versions of the TOPMS displays were evaluated on the TSRV B-737 simulator by more than 40 research, United States Air Force, airline and industry and pilots who rated the system satisfactory and recommended further development and testing. In this study, the TOPMS was flight tested on the TSRV. A total of 55 takeoff and 30 abort situations were investigated at 5 airfields. TOPMS displays were observed on the navigation display screen in the TSRV research flight deck during various nominal and off-nominal situations, including normal takeoffs; reduced-throttle takeoffs; induced-acceleration deficiencies; simulated-engine failures; and several gross-weight, runway-geometry, runway-surface, and ambient conditions. All tests were performed on dry runways. The TOPMS software executed accurately during the flight tests and the displays correctly depicted the various test conditions. Evaluation pilots found the displays easy to monitor and understand. The algorithm provides pretakeoff predictions of the nominal distances that are needed to accelerate the airplane to takeoff speed and to brake it to a stop; these predictions agreed reasonably well with corresponding values measured during several fully executed and aborted takeoffs. The TOPMS is operational and has been retained on the TSRV for general use and demonstration.

Middleton, David B.↗
DOE OSTI2026

Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F 1 score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F 1 scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively.

gated recurrent unit↗
NASA NTRS1994

Effects of Increased CO2 Level on the Well-Being, Growth and Renal Function of Rats

On the Space Shuttle the mean CO2 levels have been 0.3% which is ten times normal air, while there have been extended periods with mean levels of 0.7% and peak concentrations of 2%. On the Space Station the projected mean concentration of CO2 is 0.7% and not to exceed 1.0%. To ensure that high level of CO2 does not compromise the integrity of the science on the Space Station, the effects of chronic exposure to high levels of CO2 were investigated. Following 7 days of cage adaptation animals exposed to 2% CO2 for 30 days were compared to control (ambient air) animals and the effects on the well-being, growth and renal function analyzed. Ten male rats per group were placed in individual metabolic cages which allowed monitoring of daily food and water consumption, as well as feces and urine to be collected. Cages were placed in a plexiglass chamber with internal environment controlled by a computer in conjunction with gas sensors. The elevated CO2 was held constant at 2.0 +/- 0.03% and the O2 at 20.9 +/- 0.15%. Body weight and food and water intake were measured daily for the first ten days of exposure and then every three to four days for the remaining three weeks. Urine was measured for pH, CO2 (as an indicator for bicarbonate) and ammonia (as an indicator for ammonium). During 2% CO2 exposure, animal growth, weight, food and water consumption were within normal ranges suggesting that their well-being was not affected. Urine pH decreased from 7.12 to 6.77 over the first 6 days of exposure and increased the following 24 days returning to pre-exposure levels. Urine NH4+ increased 68% the first 6 days then dropped to and remained at 29% higher than pre-exposure level. Urine bicarbonate concentration did not change the first 6 days, but significantly increased by day 30. These results of chronic exposure to 2% C02 are consistent with renal compensation for respiratory acidosis which may impact science conducted on the Space Shuttle or the Space Station if CO2 levels reach 2%.

Lang, C.↗
NASA NTRS2001

Design And Testing of The Floating Potential Probe For ISS

Flight 4A was an especially critical mission for the International Space Station (ISS). For the first time, the high voltage solar arrays generated significant amounts of power and long predicted environmental interactions (high negative floating potential and concomitant dielectric charging) became serious concerns. Furthermore, the same flight saw the Plasma Contacting Unit (PCU) deployed and put into operation to mitigate and control these effects. The ISS program office has recognized the critical need to verify, by direct measurement, that ISS does not charge to unacceptable levels. A Floating Potential Probe (FPP) was therefore deployed on ISS to measure ISS floating potential relative to the surrounding plasma and to measure relevant plasma parameters. The primary objective of FPP is to verify that ISS floating potential does not exceed the specified level of 40 volts with respect to the ambient. Since it is expected that in normal operations the PCU will maintain ISS within this specification, it is equivalent to say that the objective of FPP is to monitor the functionality of the PCU. In this paper, we report on the design and testing of the ISS FPP. In a separate paper, the operations and results obtained so far by the FPP will be presented.

Hillard, G. Barry↗
DOE OSTI2020

CAPS PMssa Aerosol Extinction and SSA Data

We collected rapid (1 second time response) measurements of aerosol extinction and scattering (Mm-1) using an Aerodyne CAPS PMssa deployed during LASIC (as part of the LASIC SSA-constraint study) to measure ambient SSA at 530 nm wavelength to compare with other optical measurement methods. Measured from August 4 to September 22, 2017. Sampled from both PM1 and PM10 inlets. CAPS PMssa monitors have been tested extensively for PM2.5 and smaller particle sizes, but not for particles greater than 2,500 nm in diameter (i.e., PM10). The data were collected in order to provide an independent measurement of aerosol single scattering albedo at 530 nm wavelength to compare with ARM standard methods.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

SO2 over Central China: Measurements, Numerical Simulations and the Tropospheric Sulfur Budget

SO2 in central China was measured in situ from an aircraft and remotely using the Ozone Monitoring Instrument (OMI) from the Aura satellite; results were used to develop a numerical tool for evaluating the tropospheric sulfur budget - sources, sinks, transformation and transport. In April 2008, measured ambient SO2 concentrations decreased from approx.7 ppbv near the surface to approx. 1 ppbv at 1800 m altitude (an effective scale height of approx.800 m), but distinct SO2 plumes were observed between 1800 and 4500 m, the aircraft's ceiling. These free tropospheric plumes play a major role in the export of SO2 and in the accuracy of OMI retrievals. The mean SO2 column contents from aircraft measurements (0.73 DU, Dobson Units) and operational OMI SO2 products (0.63+/-0.26 DU) were close. The OMI retrievals were well correlated with in situ measurements (r = 0.84), but showed low bias (slope = 0.54). A new OMI retrieval algorithm was tested and showed improved agreement and bias (r = 0.87, slope = 0.86). The Community Multiscale Air Quality (CMAQ) model was used to simulate sulfur chemistry, exhibiting reasonable agreement (r = 0.62, slope = 1.33) with in situ SO2 columns. The mean CMAQ SO2 loading over central and eastern China was 54 kT, approx.30% more than the estimate from OMI SO2 products, 42 kT. These numerical simulations, constrained by observations, indicate that ",50% (35 to 61 %) of the anthropogenic sulfur emissions were transported downwind, and the overall lifetime of tropospheric SO2 was 38+/-7 h.

He, Hao↗
NASA NTRS2012

Sensor-Only System Identification for Structural Health Monitoring of Advanced Aircraft

Environmental conditions, cyclic loading, and aging contribute to structural wear and degradation, and thus potentially catastrophic events. The challenge of health monitoring technology is to determine incipient changes accurately and efficiently. This project addresses this challenge by developing health monitoring techniques that depend only on sensor measurements. Since actively controlled excitation is not needed, sensor-to-sensor identification (S2SID) provides an in-flight diagnostic tool that exploits ambient excitation to provide advance warning of significant changes. S2SID can subsequently be followed up by ground testing to localize and quantify structural changes. The conceptual foundation of S2SID is the notion of a pseudo-transfer function, where one sensor is viewed as the pseudo-input and another is viewed as the pseudo-output, is approach is less restrictive than transmissibility identification and operational modal analysis since no assumption is made about the locations of the sensors relative to the excitation.

Kukreja, Sunil L.↗
DOE OSTI2026

Evaluation of a Smoke Opacity Sensor for Improving Residential Wood Heater Combustion

Residential wood heating lacks real-time particulate matter (PM) monitoring technologies capable of measuring emissions directly from flue gases. This study evaluates the performance of the Octoring, an opacity-based smoke sensor developed to monitor wood heater emissions and provide feedback for improved combustion. The device was tested on catalytic and non-catalytic cordwood heaters and a pellet heater during startup, high-burn, and low-burn phases. Performance was assessed against reference particle instruments and gravimetric measurements using concordance, correlation, and agreement analyses. Results show that temperature-dependent drift is the primary limitation affecting sensor accuracy, with systematic drift observed across ambient and combustion conditions. Agreement with reference instruments ranged from poor to good depending on operating conditions, with the strongest performance observed during pellet heater high-burn operation. These findings establish a performance baseline for opacity-based sensing technologies and identify key areas for further development before practical deployment in residential wood combustion monitoring systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Mitigating humidity interference in chemiresistive hydrogen sensors through hydrophobic surface functionalization

Chemiresistive gas sensors based on semiconductor metal oxides, such as tin dioxide (SnO₂), are indispensable for detecting and monitoring toxic gases and pollutants, making them critical components in industrial and environmental applications. To enhance their performance, the metal oxides are loaded with noble metals such as palladium (Pd). However, ambient humidity poses a significant challenge to their performance. The presence of adsorbed water molecules on the oxide surface can considerably impair sensor sensitivity and overall performance. To address this issue, in this paper, we report on the application of an ultrathin, hydrophobic layer of hexamethyldisilazane to the surface of a Pd/SnO 2 sensor. This study investigates the influence of hydrophobic surface modifications on the metal oxide interface, focusing on their impact on sensor sensitivity and selectivity. The resulting sensor exhibits superior hydrogen sensing capabilities, operating effectively at low temperatures even in high humidity environments. Furthermore, the hydrophobic modification reduces the sensor’s susceptibility to interfering gases, thus enhancing its selectivity. The combined enhancements in moisture resistance and selectivity achieved through HMDS surface modification, along with the superior sensitivity of Pd/SnO₂ sensors, facilitate the development of gas sensors with enhanced humidity tolerance and broader applications.

Chemiresistive gas sensors↗
NASA NTRS1979

Report of the Ad Hoc Committee on the assessment of models of a wake shield environment around various spacecraft, Universities Space Research Association

Models depicting the ambient atmosphere which can overtake the spacecraft vacuum shield are presented. The subject areas discussed are: possible changing effects on the wake shield environment; possible utilization of the induced environmental contamination monitor; present state of the knowledge of the parameters used to describe the intermolecular collisions; the possibility of using simple models to describe the wake shield environment; possible errors associated with using kinetic theory to calculate that part of the atmosphere overtaking the shield; and a general assessment of the Monte Carlo techniques used to calculate the shield environment.

Wu, S. T.↗
DOE OSTI2020

Direct SERDS sensing of molecular biomarkers in plants under field conditions

Molecular biomarkers such as microRNAs (miRNAs) play important roles in regulating various developmental processes in plants. Understanding these pathways will help bioengineer designing organisms for efficient biomass accumulation. Current methods for RNA analysis require sample extraction and multi-step sample analysis, hindering work in field studies. Recent work in the incorporation of nanomaterials for plant bioengineering research is leading the way of an agri-tech revolution. As an example, surface-enhanced Raman scattering (SERS)–based sensors can be used to monitor RNA in vivo. However, the use of SERS in the field has been limited due to issues with observing Raman signal over complex background. To this end, shifted-excitation Raman difference spectroscopy (SERDS) offers an effective solution to extract the SERS signal from high background based on a physical approach. In this manuscript, we report the first application of SERDS on SERS sensors. We investigated this technique on SERS sensor developed for the detection of a microRNA biomarker, miR858. We tested the technique on in vitro samples and validated the technique by detecting the presence of exogenous miR858 in plants directly under ambient light in a growth chamber. The possibility of moving the detection of nucleic acid targets outside the constraints of laboratory setting enables numerous important bioengineering applications. Finally, such applications can revolutionize biofuel production and agri-tech through the use of nanotechnology-based monitoring of plant growth, plant health, and exposure to pollution and pathogens.

09 BIOMASS FUELS↗
DOE OSTI2025

Retrospective on decadal progress of the NOAA/NPS ocean noise reference station network

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the U.S. National Park Service (NPS), established the Ocean Noise Reference Station Network (NRS) in 2014 as a foundational component of NOAA’s Ocean Noise Strategy. This long-term effort aims to characterize baseline ocean ambient sound conditions across diverse marine environments and to inform management of noise impacts on protected species and habitats within U.S. waters. The NRS is now composed of 13 autonomous passive acoustic monitoring stations strategically positioned across the U.S. Exclusive Economic Zone (EEZ), extending from Arctic regions to tropical waters in depths ranging from 33 to 4,790 m. These locations include several National Marine Sanctuaries and National Parks, such as the recently designated Chumash Heritage National Marine Sanctuary off the coast of California. Each station is equipped to continuously sample low-frequency underwater sound at five kHz, enabling the detection of anthropogenic, geophysical, and biological acoustic signals. To date the network has sampled over 72 years of calibrated acoustic data. The spatial breadth and consistent methodology of the NRS allow for comparative acoustic assessments across diverse marine ecosystems. In addition to applied research functions, the NRS has served as a platform for education and training, offering opportunities for students to develop skills for marine science and data analysis. Looking forward, the NRS project team is focused on network expansion, improved data delivery, and broader integration with collaborative scientific initiatives. NRS recordings are being archived in partnership with NOAA’s National Centers for Environmental Information to enhance accessibility and long-term utility. Efforts are underway to develop standardized metadata and summary products to accompany raw audio files, making the data more usable for a wide range of stakeholders in the ocean science community. The NRS is evolving into a fully integrated national framework for ocean sound monitoring that supports scientific inquiry, management decision-making, national security interests, and public engagement with ocean acoustic environments.

Long-term monitoring↗
NASA NTRS1986

In situ magnetic field observations of the AMPTE artificial comet

Magnetometers aboard the IRM and UKS spacecraft monitored the magnetic field during the AMPTE artificial comet experiment of Dec. 27, 1984. Rapid photoionization of the released barium vapor resulted in the formation of a magnetic cavity, shielded from the ambient magnetic field.The presence of this highly conductive obstacle caused draping and compression of the solar wind magnetic field.

Luehr, H.↗