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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

NASA NTRS2005

Diagnostics Adapted for Heat-Treating Furnace Environment

Diagnostics developed for the in situ monitoring of rocket combustion environments were adapted for use in heat-treating furnaces. Simultaneous, in situ monitoring of the carbon monoxide, carbon dioxide, methane, water, and hydrogen concentrations in the endothermic gas of a heat-treating furnace were demonstrated under a Space Act Agreement between the NASA Lewis Research Center, the Heat Treating Network, and Akron Steel Treating Company. This endothermic gas, or "endogas," is produced in a catalytic process, where natural gas is "cracked" in the presence of air. Variations in the composition of the natural gas supplied lead to variations in the composition of the endothermic gas. These variations could lead to an unacceptable quality of steel products that are hardened through the carborization process that uses this gas. Conventional methods of monitoring the endogas include measuring the dew point of the gas and the oxygen concentration. From these data, the carbon monoxide content of the gas can be calculated. This carbon monoxide concentration creates the carbon potential needed for carburization. Several weak links are present in this approach. The oxygen monitor deteriorates over time, and the measurement might be inaccurate by 50 percent. Also, the chemistry equations, which are based on several assumptions, such as secondary species concentrations, provide only an approximate estimate of the carbon monoxide concentration. To address these weaknesses, we investigated a new method based on ordinary Raman spectroscopy, in which the carbon monoxide concentration is measured directly and in situ. This method measures the laser light scattered from the molecules. Each species interacts with the light and scatters the light at a different frequency. Spectral monitoring of the scattered light intensity at each molecular frequency of interest provides the species concentrations. One advantage over the conventional method is that several species can be monitored simultaneously. A second advantage is that the measurement is direct; there is no need to make assumptions, to filter the gas, or to calibrate the instrument. An instrument was designed consisting of a laser and a detection system within an enclosure, connected to an optical probe by fibers. For determining carbon monoxide concentration, the probe is mounted on the endothermic gas line, close to the generator. Optical fibers with a length of 150 ft have been used to transmit laser light from the instrument to the probe. There, the light is focused into the gas, and the scattered light is collected and transmitted back to the instrument where it is analyzed with a photomultiplier and lock-in amplifier. Laboratory tests have shown that with the current system the concentration of carbon monoxide, water, nitrogen, oxygen, and hydrogen in the air can be monitored with an accuracy of 1 percent. The concentration of carbon dioxide in the air can be monitored with an accuracy of 0.5 percent, and the concentration of methane with an accuracy of 0.2 percent. This instrument was taken to the Akron Steel Treating Plant, where field tests are in progress to verify the system capabilities. Planned developments are improving the accuracy, monitoring multiple locations, and reducing instrument size and cost.

Source record↗

DOE OSTI2025

Fiber-Optic Sensing for Earthquake Hazards Research, Monitoring, and Early Warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

58 GEOSCIENCES↗

DOE OSTI2023

Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land

Recent progress in satellite observations has provided unprecedented opportunities to monitor vegetation activity at global scale. However, a major challenge in fully utilizing remotely sensed data to constrain land surface models (LSMs) lies in inconsistencies between simulated and observed quantities. For example, gross primary productivity (GPP) and transpiration (T) that traditional LSMs simulate are not directly measurable from space, although they can be inferred from spaceborne observations using assumptions that are inconsistent with those LSMs. In comparison, canopy reflectance and fluorescence spectra that satellites can detect are not modeled by traditional LSMs. To bridge these quantities, we presented an overview of the next generation land model developed within the Climate Modeling Alliance (CliMA), and simulated global GPP, T, and hyperspectral canopy radiative transfer (RT; 400–2,500 nm for reflectance, 640–850 nm for fluorescence) at hourly time step and 1° spatial resolution using CliMA Land. CliMA Land predicts vegetation indices and outgoing radiances, including solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near infrared reflectance of vegetation (NIRv) for any given sun-sensor geometry. The spatial patterns of modeled GPP, T, SIF, NDVI, EVI, and NIRv correlate significantly with existing data-driven products (mean R 2 = 0.777 for 9 products). CliMA Land would be also useful in high temporal resolution simulations, for example, providing insights into when GPP, SIF, and NIRv diverge.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Reflectin: Protein Driver of Dynamically Tunable Biophotonics; New Paradigm for Tunably Reconfigurable Materials

We discovered that the reflectins, with architecture and sequences unlike those of any other proteins known, exhibit a novel interplay between signal-controlled nucleation and growth of dynamically arrested liquid-liquid phase-segregated assemblies that uniquely enables the continuous and precise fine-tuning of physical properties governing the color and brightness of light reflected from the membrane-enclosed nanostructures that contain them. Our research included high-resolution structural analyses conducted at the DOE-BES user facilities of the Stanford Synchrotron Light Source and LBL National Laboratory’s Molecular Foundry, leveraging their capabilities for time-resolved SAXS and cryo-TEM with our ongoing genetic engineering, biophysical and computational analyses to identify the structural determinants and mechanisms governing the dynamic behaviors of the reflectins. We augmented these methods with EPR analyses that revealed for the first time the existence of a specific pathway of reflectin assembly. Using dynamic light scattering and continuously monitored circular dichroism and Raman microscopy, we elucidated the progression of structural changes underlying the mechanisms of signal-induced condensation, folding, assembly, liquefaction, dynamic arrest, regulation and reversal.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Extreme-scale stochastic optimization and simulation via learning-enhanced decomposition and parallelization (Final Technical Report)

Stochastic optimization and simulation models ubiquitously arise in designing and operating complex service/engineering systems. They can be extreme in scale due to high-dimensional data and decisions, and can also involve decisions made sequentially in response to newly revealed data, both causing significant computational challenge. The objective of this research is to explore a unified framework that integrates machine learning with discrete optimization and risk-averse modeling, to improve the efficiency of decomposition paradigms for stochastic optimization and simulations at extreme scale. The models we consider represent a broad class of complex decision-making problems, where 0-1 or continuous decisions are made before and/or after knowing multiple sources of uncertainties that could be correlated. We will employ machine learning methods to dynamically decide and prioritize computational procedures, including cut generation, branching, and bounding of the optimal objective. Furthermore, the research will shed new lights on the traditional decomposition algorithms for extreme-scale computing. Deliverables of the research include new modeling and computational methods for advancing the state-of-the-art research in optimization and simulation, bringing many relevant risk-averse, data-driven optimization problems in practice within the range of tractability. Examples include distributed computing server scheduling and sensor deployment for monitoring critical infrastructures. Success in this effort will enable progress in solving multiple extreme-scale problems in the complex system design and operations arising from DoE missions in energy, environment, and national security.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1974

Applications of aerospace technology in the public interest: Pollution measurement

This study of selected NASA contributions to the improvement of pollution measurement examines the pervasiveness and complexity of the economic, political, and social issues in the environmental field; provides a perspective on the relationship between the conduct of aerospace R and D and specific improvements in on site air pollution monitoring equipment now in use; describes the basic relationship between the development of satellite-based monitoring systems and their influence on long-term progress in improving environmental quality; and comments on how both instrumentation and satellite remote sensing are contributing to an improved environment. Examples of specific gains that have been made in applying aerospace R and D to environmental problem-solving are included.

Heins, C. F.↗

NASA NTRS1980

Research and Technology Objectives and Plans Summary (RTOPS)

A compilation of the summary portions of each of the Research and Technology Objectives and Plans (RTOPS) used for management review and control research currently in progress throughout NASA is presented. Indexes include: subject, technical monitor, responsible NASA organization, and RTOP number.

Source record↗

NASA NTRS1980

Assessment of satellite and aircraft multispectral scanner data for strip-mine monitoring

The application of LANDSAT multispectral scanner data to describe the mining and reclamation changes of a hilltop surface coal mine in the rugged, mountainous area of eastern Kentucky is presented. Original single band satellite imagery, computer enhanced single band imagery, and computer classified imagery are presented for four different data sets in order to demonstrate the land cover changes that can be detected. Data obtained with an 11 band multispectral scanner on board a C-47 aircraft at an altitude of 3000 meters are also presented. Comparing the satellite data with color, infrared aerial photography, and ground survey data shows that significant changes in the disrupted area can be detected from LANDSAT band 5 satellite imagery for mines with more than 100 acres of disturbed area. However, band-ratio (bands 5/6) imagery provides greater contrast than single band imagery and can provide a qualitative level 1 classification of the land cover that may be useful for monitoring either the disturbed mining area or the revegetation progress. However, if a quantitative, accurate classification of the barren or revegetated classes is required, it is necessary to perform a detailed, four band computer classification of the data.

Spisz, E. W.↗

NASA NTRS1981

Research and Technology Objectives and Plans Summary (RTOPS)

A compilation of the summary portions of each of the Research and Technology Objective Plans (RTOP) used for management review and control of research currently in progress throughout NASA is presented. Indexes include: subject, technical monitor, responsible NASA organization, and RTOP number.

Source record↗

NASA NTRS2000

Fiber-Optic Imaging Probe Developed for Space Used to Detect Diabetes Through the Eye

Approximately 16 million Americans have diabetes mellitus, which can severely impair eyesight by causing cataracts, diabetic retinopathy, and glaucoma. Cataracts are 1.6 times more common in people with diabetes than in those without diabetes, and cataract extraction is the only surgical treatment. In many cases, diabetes-related ocular pathologies go undiagnosed until visual function is compromised. This ongoing pilot project seeks to study the progression of diabetes in a unique animal model by monitoring changes in the lens with a safe, sensitive, dynamic light-scattering probe. Dynamic light scattering (DLS), has the potential to diagnose cataracts at the molecular level. Recently, a new DLS fiber-optic probe was developed at the NASA Glenn Research Center at Lewis Field for noncontact, accurate, and extremely sensitive particle-sizing measurements in fluid dispersions and suspensions (ref. 1). This compact, portable, and rugged probe is free of optical alignment, offers point-and-shoot operation for various online field applications and challenging environments, and yet is extremely flexible in regards to sample container sizes, materials, and shapes. No external vibration isolation and no index matching are required. It can measure particles as small as 1 nm and as large as few micrometers in a wide concentration range from very dilute (waterlike) dispersions to very turbid (milklike) suspensions. It is safe and fast to use, since it only requires very low laser power (10 nW to 3 mW) with very short data acquisition times (2 to 10 sec).

Ansari, Rafat R.↗

NASA NTRS2002

Development of Microfabricated Chemical Gas Sensors and Sensor Arrays for Aerospace Applications

Aerospace applications require the development of chemical sensors with capabilities beyond those of commercially available sensors. In particular, factors such as minimal sensor size, weight, and power consumption are particularly important. Development areas which have potential aerospace applications include launch vehicle leak detection, engine health monitoring, fire detection, and environmental monitoring. Sensor development for these applications is based on progress in three types of technology: 1) Micromachining and microfabrication (Microsystem) technology to fabricate miniaturized sensors. 2) The use of nanocrystalline materials to develop sensors with improved stability combined with higher sensitivity. 3) The development of high temperature semiconductors, especially silicon carbide. However, due to issues of selectivity and cross-sensitivity, individual sensors are limited in the amount of information that they can provide in environments that contain multiple chemical species. Thus, sensor arrays are being developed to address detection needs in such multi-species environments. This paper discusses the needs of space applications as well as the point-contact sensor technology and sensor arrays being developed to address these needs. Sensors to measure hydrogen, hydrocarbons, hydrazine, nitrogen oxides (NO,), carbon monoxide, oxygen, and carbon dioxide are being developed as well as arrays for leak, fire, and emissions detection. Demonstrations of the technology will also be discussed. It is concluded that microfabricated sensor technology has significant potential for use in a range of aerospace applications.

Hunter, G. W.↗

NASA NTRS2022

A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode

Although satellite retrievals and data assimilation have progressed to where there is a good skill for monitoring maritime Aerosol Optical Depth (AOD), there remains uncertainty in achieving further degrees of freedom, such as distinguishing fine and coarse mode dominated species in maritime environments (e.g., coarse mode sea salt and dust versus fine mode terrestrial anthropogenic emissions, biomass burning, and maritime secondary production). For the years 2016 through 2019, we performed an analysis of 550 nm total AOD550, fine mode AOD (FAOD550; also known as FM AOD in the literature), coarse mode AOD (CAOD550), and fine mode fraction (η550) between Moderate Resolution Spectral Imaging Radiometer (MODIS) V6.1 MOD/MYD04 dark target aerosol retrievals and the International Cooperative for Aerosol Prediction (ICAP) core four multi-model consensus (C4C) of analyses/short term forecasts that assimilate total MODIS AOD550. Differences were adjudicated by the global shipboard Maritime Aerosol Network (MAN) and selected island AERONET sun photometer observations with the application of the spectral deconvolution algorithm (SDA). Through a series of conditional and regional analyses, we found divergence included regions of terrestrial influence and latitudinal dependencies in the remote oceans. Notably, MODIS and the C4C and its members, while having good correlations overall, have a persistent +0.04 to +0.02 biases relative to MAN and AERONET for typical AOD550 values (84th% < 0.28), with the C4C underestimating significant events thereafter. Second, high biases in AOD550 are largely associated with the attribution of the fine mode in satellites and models alike. Thus, both MODIS and C4C members are systematically overestimating AOD550 and FAOD550 but perform better in characterizing the CAOD550. Third, for MODIS, findings are consistent with previous reports of a high bias in the retrieved Ångström Exponent, and we diagnosed both the optical model and cloud masking as likely causal factors for the AOD550 and FAOD550 high bias, whereas for the C4C, it is likely from secondary overproduction and perhaps numerical diffusion. Fourth, while there is no wind-speed-dependent bias for surface winds <12 m s−1, the C4C and MODIS AOD550s also overestimate CAOD550 and FAOD550, respectively, for wind speeds above 12 m/s. Finally, sampling bias inherent in MAN, as well as other circumstantial evidence, suggests biases in MODIS are likely MODIS and the C4C products have their own strengths and challenges for a given climate application and discuss needed research. even larger than what was diagnosed here. We conclude with a discussion on how

Aerosols↗

NASA NTRSDate not supplied

Firesense: Supporting Operational Partners Through Co-Development

Fire is a natural disturbance and fundamental to many ecosystems, but, across the United States and many areas globally, fires have become more common, larger and more likely to occur at the same time. This has the potential to challenge resource allocation and response and requires coordinated integration of technology and tools at the spatial and temporal scales required by practitioners who make wildland fire management decisions. In the US wildfire is currently managed across state, federal, and tribal agencies who leverage various datasets to guide management decisions. FireSense, a NASA Science Mission Directorate project, aims to develop and deliver trailblazing technology and tools for use before, during, and after wildland fires by working together with land managers and practitioners. FireSense is focused on turning information into solutions by expanding partnerships and collaborations with operational agencies to inform and deliver data and technology to support decisions for wildland fire management. Through implementation across the US and with campaign activities in a variety of landscapes, coordinated research and development work will build upon adaptive and use-inspired approaches that can be put into operation. By leveraging and complementing partner activities through coordinated investment, we support a more comprehensive and cohesive response that can advance fire science to better understand fire behavior and effects through integrated measurement, monitoring and modeling. We present updates from in-progress technology development and field campaigns within the US which include sampling and application across scales with information from multiple sensors collocated with field measurements and highlighting the importance of cross-scale observations during the fire lifecycle. Coordinated investment in new science and technology for the complete fire lifecycle supports a comprehensive and cohesive fire response that help to overcome barriers and anticipate and manage the new reality of extreme fires in a warming world.

Jacquelyn Shuman↗

NASA NTRS1993

Monitoring cognitive function and need with the automated neuropsychological assessment metrics in Decompression Sickness (DCS) research

Hypobaric decompression sickness (DCS) research presents the medical monitor with the difficult task of assessing the onset and progression of DCS largely on the basis of subjective symptoms. Even with the introduction of precordial Doppler ultrasound techniques for the detection of venous gas emboli (VGE), correct prediction of DCS can be made only about 65 percent of the time according to data from the Armstrong Laboratory's (AL's) hypobaric DCS database. An AL research protocol concerned with exercise and its effects on denitrogenation efficiency includes implementation of a performance assessment test battery to evaluate cognitive functioning during a 4-h simulated 30,000 ft (9144 m) exposure. Information gained from such a test battery may assist the medical monitor in identifying early signs of DCS and subtle neurologic dysfunction related to cases of asymptomatic, but advanced, DCS. This presentation concerns the selection and integration of a test battery and the timely graphic display of subject test results for the principal investigator and medical monitor. A subset of the Automated Neuropsychological Assessment Metrics (ANAM) developed through the Office of Military Performance Assessment Technology (OMPAT) was selected. The ANAM software provides a library of simple tests designed for precise measurement of processing efficiency in a variety of cognitive domains. For our application and time constraints, two tests requiring high levels of cognitive processing and memory were chosen along with one test requiring fine psychomotor performance. Accuracy, speed, and processing throughout variables as well as RMS error were collected. An automated mood survey provided 'state' information on six scales including anger, happiness, fear, depression, activity, and fatigue. An integrated and interactive LOTUS 1-2-3 macro was developed to import and display past and present task performance and mood-change information.

Nesthus, Thomas E.↗

NASA NTRS2001

Real Time Monitoring of Flooding from Microwave Satellite Observations

In this report, we review the progress to date including results from data analyses and present a schedule of milestones for the remainder of the project. We discuss the processing of flood extent data and SSM/I brightness temperature data for the 1993 Midwest Flood. We present preliminary results from the derivation of open water fraction from brightness temperatures.

Galantowicz, John F.↗

NASA NTRS2001

Neuroprotection for the new millennium. Matchmaking pharmacology and technology

A major theme of the 1990s in the pathophysiology of nervous system injury has been the multifactorial etiology of irreversible injury. Multiple causes imply multiple opportunities for therapeutic intervention--hence the abandonment of the "magic bullet" single pharmacologic agent for neuroprotection in favor of pharmacologic "cocktails". A second theme of the 1990s has been the progress in technology for neuroprotection, minimally- or non-invasive monitoring as well as treatment. Cardiac stenting has eliminated the need, in many cases, for open heart surgery; deep brain stimulation for Parkinson's disease has offered significant improvement in quality of life for many who had exhausted cocktail drug treatment for their disease. Deep brain stimulation of the subthalamic nucleus offers a novel treatment for Parkinson's disease where a technological advance may actually be an intervention with effects that are normally expected from pharmacologic agents. Rather than merely "jamming" the nervous system circuits involved in Parkinson's disease, deep brain stimulation of the subthalamic nucleus appears to improve the neurotransmitter imbalance that lies at the heart of Parkinson's disease. It may also slow the progression of the disease. Given the example of deep brain stimulation of the subthalamic nucleus for Parkinson's disease, in future one may expect other technological or "hardware" interventions to influence the programming or "software" of the nervous system's physiologic response in certain disease states.

Review Literature↗

NASA NTRS2017

Continuation of Long-Term Global SO2 Pollution Monitoring from OMI to OMPS

Over the past 20 years, advances in satellite remote sensing of pollution-relevant species have made space-borne observations an increasingly important part of atmospheric chemistry research and air quality management. This progress has been facilitated by advanced UV-vis spectrometers, such as the Ozone Monitoring Instrument (OMI) on board the NASA Earth Observing System (EOS) Aura satellite, and continues with new instruments, such as the Ozone Mapping and Profiler Suite (OMPS) on board the NASA-NOAA Suomi National Polar-orbiting Partnership (SNPP) satellite. In this study, we demonstrate that it is possible, using our state-of-the-art principal component analysis (PCA) retrieval technique, to continue the long-term global SO2 pollution monitoring started by OMI with the current and future OMPS instruments that will fly on the NOAA Joint Polar Satellite System (JPSS) 1, 2, 3, and 4 satellites in addition to SNPP, with a very good consistency of retrievals from these instruments. Since OMI SO2 data have been primarily used for (1) providing regional context on air pollution and long-range transport on a daily basis and (2) providing information on point emission sources on an annual basis after data averaging, we focused on these two aspects in our OMI-OMPS comparisons. Four years of retrievals (2012-2015) have been compared for three regions: eastern China, Mexico, and South Africa. In general, the comparisons show relatively high correlations (r = 0. 79-0.96) of daily regional averaged SO2 mass between the two instruments and near-unity regression slopes (0.76-0.97). The annual averaged SO2 loading differences between OMI and OMPS are small (< 0.03 Dobson unit (DU) over South Africa and up to 0.1 DU over eastern China). We also found a very good correlation (r = 0. 92-0.97) in the spatial distribution of annual averaged SO2 between OMI and OMPS over the three regions during 2012-2015. The emissions from ∼ 400 SO2 sources calculated with the two instruments also show a very good correlation (r = ∼ 0.9) in each year during 2012-2015. OMPS-detected SO2 point source emissions are slightly lower than those from OMI, but OMI-OMPS differences decrease with increasing strength of source. The OMI-OMPS SO2 mass differences on a pixel by pixel (daily) basis in each region can show substantial differences. The two instruments have a spatial correlation coefficient of 0.7 or better on < ∼ 50 % of the days. It is worth noting that consistent SO2 retrievals were achieved without any explicit adjustments to OMI or OMPS radiance data and that the retrieval agreement may be further improved by introducing a more comprehensive Jacobian lookup table than is currently used.

satellite remote sensing of pollution↗

NASA NTRS2018

NASA Advanced Explorations Systems: 2018 Advancements in Life Support Systems

The NASA Advanced Exploration Systems (AES) Life Support Systems (LSS) project strives to develop reliable, energy-efficient, and low-mass spacecraft systems to provide envi-ronmental control and life support systems (ECLSS) critical to enabling long duration human missions beyond low Earth orbit (LEO). Highly reliable, closed-loop life support systems are among the capabilities required for the longer duration human space exploration missions planned in the mid-2020s and beyond. The LSS Project is focused on three life support areas: air revitalization, wastewater processing/water management and environmental monitoring. Building upon the International Space Station (ISS) LSS systems (where applicable), the three-fold mission of the LSS Project is to address discrete LSS technology gaps, to improve the reliability of LSS systems, and to advance LSS systems toward integrated testing aboard the ISS. This paper is a follow on to the AES LSS development status reported in 2017 and provides additional details on the progress made since that publication with specific attention to the status of the Aerosol Sampler ISS Flight Experiment, the Spacecraft Atmosphere Monitor (SAM) Flight Experiment, the Brine Processor Assembly (BPA) Flight Experiment as well as the progress of the terrestrial development in air, water and environmental monitoring technologies.

trace contaminant control↗