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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 559 records · Page 31

Sizing of colloidal particle and protein molecules in a hanging fluid drop

We report non-invasive particle size measurements of polystyrene latex colloidal particles and bovine serum albumin (BSA) protein molecules suspended in tiny hanging fluid drops of 30 micro-Liter volume using a newly designed fiber optic probe. The probe is based upon the principles of the technique of dynamic light scattering (DLS). The motivation for this work comes from growing protein crystals in outer space. Protein crystals have been grown previously in hanging drops in microgravity experiments on-board the space shuttle orbiter. However, obtaining quantitative information on nucleation and growth of the protein crystals in real time has always been a desired goal, but hitherto not achieved. Several protein researchers have shown interest in using DLS to monitor crystal growth process in a droplet, but elaborate instrumentation and optical alignment problems have made in-situ applications difficult. We demonstrate that such an experiment is now possible. Our system offers fast (5 seconds) determination of particle size, utilize safe levels of very low laser power (less than or equal to 0.2 mW), a small scattering volume (approximately 2 x 10(exp -5) cu mm) and high spatial coherence (Beta) values. This is a major step forward when compared to currently available DLS systems.

Ansari, Rafat R.↗

Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17-22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

Steffen, K.↗

The Coupling of Solution Chemistry to Plant Nutrient Demand in an on Demand Nutrient Delivery System

The goal of the proposal will be to determine the suitability of the DASI instrument in providing a signal that can be recognized and be utilized as an indicator of plant stress. The method to be utilized for evaluating stress is the presentation of an every increasing level of nutrient deficiency and salinity stress (addition of salt (NACl) or increasing concentration of balanced nutrient) while simultaneously recording spectral reflectance using the DASI instrument and monitoring the traditional processes of gas exchange and nutrient uptake parameters. In this manner, we will be able to directly compare the DASI measurements with known stresses as determined by the traditional gas exchange and nutrient uptake measures of stress. We anticipate that the DASI will provide a sensitive identifier of plant stress; recording signals of the resulting changes in plant metabolism in real time, far before any visible effects of stress could be observed. Thus, there is a potential for very early management intervention to correct a stress condition before damage could develop. The present response time for the observation of visual symptoms of plant stress is considerable and only provides an indication that a stress is present after it has been present for an extended period of time. Thus, the impact of a plant-based life support function will have already been significant. An additional benefit of this research to regenerative life support will be the characterization of a potential recovery scenario from various degrees of stress. The experimental approach to be employed includes the removal of the stress at various points in the stress gradient and the characterization of plant performance and reflectance spectra during recovery from various degrees of stress. Spectral reflectance imaging techniques have been developed and used to measure the biochemical composition of plants and relate these characteristics to the fluxes of biochemical elements within the ecosystem.

Savage, Wayne↗

Analysis of proteins involved in biodegradation of crop biomass

The biodegradation of crop biomass for re-use in crop production is part of the bioregenerative life support concept proposed by the National Aeronautics and Space Administration (NASA) for long duration, manned space exploration. The current research was conducted in the laboratory to evaluate the use of electrophoretic analysis as a means of rapidly assaying for constitutive and induced proteins associated with the bacterial degradation of crop residue. The proteins involved in crop biomass biodegradation are either constitutive or induced. As a result, effluent and cultures were examined to investigate the potential of using electrophoretic techniques as a means of monitoring the biodegradation process. Protein concentration for optimum banding patterns was determined using the Bio-Rad Protein Assay kit. Four bacterial soil isolates were obtained from the G.W. Carver research Farm at Tuskegee University and used in the decomposition of components of plant biomass. The culture, WDSt3A was inoculated into 500 mL of either Tryptic Soy Broth or Nutrient Broth. Incubation, with shaking of each flask was for 96 hours at 30 C. The cultures consistently gave unique banding patterns under denaturing protein electrophoresis conditions, The associated extracellular enzymes also yielded characteristic banding patterns over a 14-day period, when native electrophoresis techniques were used to examine effluent from batch culture bioreactors. The current study evaluated sample preparation and staining protocols to determine the ease of use, reproducibility and reliability, as well as the potential for automation.

Crawford, Kamau↗

High Resolution Imaging Spectrometer (HIRIS): Science and Instrument

The High Resolution Imaging Spectrometer (HIRIS) is a facility instrument slated for flight on the second of the EOS-A series of platforms. HIRIS is designed to acquire 24-km wide, 30-m pixel images in 192 spectral bands simultaneously in the 0.4-2.45-micrometer wavelength region. With pointing mirrors it can sample any place on Earth, except the poles, every two days. HIRIS operates at the intermediate scale between the human and the global and therefore links studies of Earth surface processes to global monitoring carried out by lower-resolution instruments. So far, over 50 science data products from HIRIS images have been identified in the fields of atmospheric gases, clouds, snow and ice, water, vegetation, and rocks and soils. The key attribute of imaging spectrometry that makes it possible to derive quantitative information from the data is the large number of contiguous spectral bands. Therefore spectrum matching techniques can be applied. Such techniques are not possible with present-day, multispectral scanner data.

Goetz, Alexander F. H.↗

Small Business Innovations

Under a Small Business Innovation Research (SBIR) contract to Kennedy Space Center, EIC Laboratories invented a Raman Spectrograph with fiber optic sampling for space applications such as sensing hazardous fuel vapors and making on-board rapid analyses of chemicals and minerals. Raman spectroscopy is a laser-based measurement technique that provides through a unique vibrational spectrum a molecular 'fingerprint,' and can function in aqueous environments. EIC combined optical fiber technology with Raman methods to develop sensors that can be operated at a distance from the spectrographic analysis instruments and the laser excitation source. EIC refined and commercialized the technology to create the Fiber Optic Raman Spectrograph and the RamanProbe. Commercial applications range from process control to monitoring hazardous materials.

Source record↗

Beyond the Prototype: The Design Evolution of a Deployed AI System

Our previous experiences with deployed intelligent control agents for NASA advanced life support systems (Schreckenghost et al., 2002) inspired us to develop the Distributed Collaboration and Interaction (DCI) system to help humans and mostly-autonomous software agents work together. We discovered many unaddressed needs for human interaction with control agents that operate continuously over months to years to monitor and perform process control for regenerative life support systems. These systems recover usable water or air from the waste products created by biological systems over time. Through the DCI project, we have addressed the needs for interaction between humans and autonomous control systems. This paper describes the software engineering aspects of our experiences, first, in designing and developing a prototype of the DCI system, and later, in adjusting the implementation to make the leap from initial prototype to a system ready to be applied under varying circumstances to meet different needs. The details in the paper focus primarily on the second stage of development. The DCI system is currently deployed, operating 24/7, to assist humans to interact with an advanced Water Recovery System (WRS). In addition, we have demonstrated an application of DCI to support ground personnel in mission support roles.

Martin, C.↗

Beyond the Prototype: The Design Evolution of a Deployed AI System

Our previous experiences with deployed intelligent control agents for NASA advanced life support systems (Schreckenghost et al., 2002) inspired us to develop the Distributed Collaboration and Interaction (DCI) system to help humans and mostly-autonomous software agents work together. We discovered many unaddressed needs for human interaction with control agents that operate continuously over months to years to monitor and perform process control for regenerative life support systems. These systems recover usable water or air from the waste products created by biological systems over time. Through the DCI project, we have addressed the needs for interaction between humans and autonomous control systems. This paper describes the software engineering aspects of our experiences, first, in designing and developing a prototype of the DCI system, and later, in adjusting the implementation to make the leap from initial prototype to a system ready to be applied under varying circumstances to meet different needs. The details in the paper focus primarily on the second stage of development. The DCI system is currently deployed, operating 24/7, to assist humans to interact with an advanced Water Recovery System (WRS). In addition, we have demonstrated an application of DCI to support ground personnel in mission support roles.

Martin, Cheryl↗

S&MA Internship to Support Orion and the European Service Module

As a University Space Research Association (USRA) intern for NASA Johnson Space Center (JSC) during the summer 2016 work term, I worked on three main projects for the Space Exploration Division (NC) of the Safety and Mission Assurance (S&MA) Directorate. I worked on all three projects concurrently. One of the projects involved facilitating the status and closure of technical actions that were created during European Service Module (ESM) safety reviews by the MPCV Safety & Engineering Review Panel (MSERP). The two main duties included accurately collecting and summarizing qualitative data, and communicating that information to the European Space Agency (ESA) and Airbus (ESA's prime contractor) in a clear, succinct and precise manner. This project also required that I create a report on the challenges and opportunities of international S&MA. With its heavy emphasis on soft skills, this project taught me how to communicate better, by showing me how to present and share information in an easy-to-read and understandable format, and by showing me how to cooperate with and culturally respect international partners on a technical project. The second project involved working with the Orion Thermal Protection System (TPS) Process Failure Modes and Effects Analysis (PFMEA) Working Group to create the first full version of the Orion TPS PFMEA. The Orion TPS PFMEA Working Group met twice a week to analyze the Avcoat block installation process for failure modes, the failure modes effects, and how such failure modes could be controlled. I was in charge of implementing changes that were discussed in meeting, but were not implemented real time. Another major task included creating a significant portion of the content alongside another team member outside the two weekly meetings. This project caused me to become knowledgeable about TPS, heatshields, space-rated manufacturing, and non-destructive evaluation (NDE). The project also helped me to become better at working with a small team and helped improved my technical communication skills. My main duty for the third project was creating a Safety Verification Tracking Log (SVTL) for the Orbital Maneuvering System Engine (OMS-E), and contacting subject matter experts to close Hazard Report (HR) control verifications. This project also required me to support other OMS-E safety process tasks, like monitoring OMS-E vibration testing for Quality Assurance (QA) purposes. This project helped me become even more proficient in Excel. Throughout the project, I gained knowledge about the OMS-E system and improved my understanding of pressure systems and propellant systems. In terms of education goals, this work term has affirmed my desire to take a few more space-related courses, like orbital mechanics, so that I can have a better understanding of human spaceflight and the industry surrounding it. However, the work term did not persuade me to pursue a master's degree. In terms of career goals, this work term has helped me clarify the direction I would like to head in the future. The perspective of three summer terms working for NASA in S&MA has allowed me to observe that most S&MA employees joined S&MA after working in other NASA directorates, such as Engineering or Flight Operations. It is my belief that it would be advantageous for both NASA and I for me to broaden my knowledge base and technical skill set by completing hands-on technical work on human spaceflight projects, and for me to integrate my safety experience directly into technical work in other directorates. The other significant advantage to this proposed situation is that if I were to eventually return to S&MA, I would be returning with a substantial set of hands-on technical experience and knowledge, which would be a significant resource for S&MA tasks and projects.

Hutcheson, Connor↗

Uncertainty Analysis of the GeoNEX Top-of-Atmospheric Reflectance Products Generated from the Third-Generation Geostationary Satellite Sensors

The GeoNEX (Geostationary-NASA Earth eXchange) Level-1G products consist of top-of-atmosphere (TOA) bi-directional reflectance factor (BRF) and brightness temperature generated with data streams from the latest geostationary (GEO) sensors including GOES-16/17 ABI, Himawari-8/9 AHI, and GK-2A AMI on a global tiled common grid (60oN-60o and 180oW-180oE) in geographic coordinates. With their 16 spectral bands, 0.01o/0.02o nadir spatial resolution, and 10-minute temporal resolutions, these products provide exciting opportunity to monitor Earth surface processes. However, the unique Sun-Target-Satellite geometry of geostationary sensors demands special attention in analyzing/interpreting these datasets. In this study we present a systematic analysis on the relationship between the radiometric uncertainties of the GeoNEX TOA reflectance and the corresponding solar/satellite zenith angles. We show that the signal-to-noise ratio (SNR) of the BRF are positively proportional to the square roots of the cosine of solar illuminating zenith angles. That is, the BRF data are noisier earlier in the morning or later in the afternoon than in the mid of the day. The cosine of satellite viewing zenith angles do not directly influence the SNR of the TOA BRF. However, they positively regulate the relative importance of the surface component in the TOA BRF. This means that variations in surface reflectance are more difficult to detect for pixels with larger view zenith angles, even when the SNR of the TOA BRF is the same. We are developing metrics to specify such illumination-view geometry related uncertainties in the GeoNEX L1G TOA BRF products so that this key information can be easily accessed by the user community.

Geostationary satellite↗

Automated Data Accountability for Missions in Mars Rover Data

As the Mars Curiosity Rover transmits data to the JPL Ground Data System (GDS), it frequently observes data loss and corruption, requiring re-transmits from the rover and Ground Data System Analysts (GDSA) to monitor the downlink process. As new missions are launched, the GDSA team redistributes analysts to these new missions, causing shortages in previous missions. The GDSA team can significantly benefit from the automation and optimization of the downlink process of telemetry data. In fact, there is a need for a better understanding of why the data is corrupted, so that the GDSA team can best determine the root cause of the issues in the GDS. This paper presents machine learning and deep learning based approaches to automate and optimize the detection of data loss. We first created a pipeline to automatically accumulate data from the telemetry databases (MAROS, Telemetry Data Storage, and GDS Elastic Search Database) in the downlink process. With our newly created datasets, we perform feature selection to supplement the GDSA understanding of the downlink process and provide supplemental analysis on the importance of different features. We implement various machine learning and deep learning based models, including support vector machines, ensemble methods, and deep neural networks and evaluate their accuracies in identifying whether a downlink process is complete or incomplete. We utilize fast hyperparameter optimization methods that allow our models to quickly be re-trained, allowing them to quickly be tuned and optimized on daily incoming data in real time. This hyperparameter optimization also allows our methods to be quickly integrated into other JPL missions. Our results show that our best-performing machine learning and deep learning based models outperform the existing GDSA detection software by 6 accuracy points and can aid analysts by providing insights into the data accountability problem. Since these various machine learning and deep learning approaches vary significantly in interpretability, we provide a discussion on the tradeoffs between their performance and trustworthiness in helping detect issues in data transmission.

Divsalar, Dariush↗

Simultaneous Retrievals of Biomass Burning Aerosols and Trace Gases From the Ultraviolet to Near-Infrared Over Northern Thailand During the 2019 Pre-Monsoon Season

With the advent of spaceborne spectroradiometers in a geostationary constellation, measuring high spectral resolution ultraviolet–visible (UV-VIS) and selected near-/shortwave-infrared (NIR/SWIR) radiances can enable the probing of the life cycle of key atmospheric trace gases and aerosols at higher temporal resolutions over the globe. The UV-VIS measurements are important for retrieving several key trace gases (e.g., O 3 , SO 2 , NO 2 , and HCHO) and particularly for deriving aerosol characteristics (e.g., aerosol absorption and vertical profile). This study examines the merit of simultaneous retrievals of trace gases and aerosols using a ground-based spectroradiometer covering the UV-NIR to monitor their physicochemical processes and to obtain reliable aerosol information for various applications. During the 2019 pre-monsoon season over northern Thailand, we deployed a ground-based SMART–s (Spectral Measurements for Atmospheric Radiative Transfer–spectroradiometer) instrument, which is an extended-range Pandora with reliable radiometric calibration in the 330–820 nm range, to retrieve remotely sensed chemical and aerosol properties for the first time near biomass burning sources. The high spectral resolution (∼ 1.0 nm full width half maximum with ∼ 3.7 × oversampling) of sun and sky measurements from SMART–s provides several key trace gases (e.g., O 3 , NO 2 , and H 2 O) and aerosol properties covering the UV where significant light absorption occurs by the carbonaceous particles. During the measurement period, highly correlated total column amounts of NO 2 and aerosol optical thickness (т aer ) retrieved from SMART–s (correlation coefficient, R=0.74) indicated their common emissions from biomass burning events. The SMART–s retrievals of the spectral single scattering albedo (ω 0 ) of smoke aerosols showed an abrupt decrease in the UV, which is an important parameter dictating photochemical processes in the atmosphere. The values of ω 0 and column precipitable water vapor (H 2 O) gradually increase with the mixing of biomass burning smoke particles and higher water vapor concentrations when approaching the monsoon season. The retrieved ω 0 and weighted mean radius of fine-mode aerosols from SMART–s showed positive correlations with the H 2 O (R=0.81 for ω 0 at 330 nm and 0.56 for the volume-weighted mean radius), whereas the real part of the refractive index of fine-mode aerosol (n f ) showed negative correlations (R = -0.61 at 330 nm), which suggest that aerosol aging processes including hygroscopic growth (e.g., humidification and cloud processing) can be a major factor affecting the temporal trends of aerosol optical properties. Retrieved n f and ω 0 were closer to those of the water droplet (i.e., n f of about 1.33 and ω 0 of about 1.0) under lower amounts of NO 2 during the measurement period; considering that the NO 2 amounts in the smoke may indicate the aging of the plume after emission due to its short lifetime, the tendency is also consistent with active hygroscopic processes of the aerosols over this area. Retrieved UV aerosol properties from SMART–s generally support the assumed smoke aerosol models (i.e., the spectral shape of aerosol absorption) used in NASA's current satellite algorithms, and their spectral ω 0 retrievals from ground and satellites showed good agreements (R = 0.73–0.79). However, temporal and spectral variabilities in the aerosol absorption properties in the UV emphasize the importance of a realistic optical model of aerosols for further improvements in satellite retrievals.

biomass burning↗

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

Silicon Carbide Passive Temperature Sensors at INL

Discuss the SiC passive thermometry methods currently performed at INL and ORNL, decide on best path forward for establishing an ASTM Standard for processing SiC temperature monitors, and expand this ASTM benchmarking efforts to international collaborators (Netherlands, Canada, and Poland).

36 MATERIALS SCIENCE↗

Habitat Inspection Scanner, Bio-Structure Scanner, and In Situ Sub-Surface Composition Sensor

The extension of dielectric and inductive spectroscopy into in situ observations represents a significant exploration-enabling tool. This technology can be widely applied from microscopic to macroscopic. Dielectrometry and inductometry can measure sub-surface composition and its distribution. The primary environment that we cannot easily explored is the sub-surface of solid bodies. Weather as part of our equipment that we bring with us, or the locations we are exploring. These fundamental questions lie at the core of the exploration Initiative. To answer them we must use a whole host of complimentary tools including those that allow us to practically examine the sub-surface environment. A nondestructive approach offers significant advantages for both the initial identification of likely samples but also the monitoring of ecosystems and crew health. These include materials characterization, nondestructive inspection, and process quality control, damage monitoring, and hidden object detection and identification. The identification of natural resources such as water on the Moon or Mars is of great importance to the utilization of local resource in the support of human exploration crews. On the macroscopic scale, the understanding of what resources are available and how they are distributed is of primary importance to their productive utilization. Even if initial explorations do not require the use of local resources to succeed, eventual settlement and commercial development will. The routine examination of the structural integrity (micro cracks, leaks) of hi.inafi habitats in harsh envkmments ww!d also be enabled.

VanSteenberg, Michael↗

Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

In-situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model have been used to select and control the processing properties of an epoxy resin during liquid pressure RTM impregnation and cure. Once correlated with viscosity and degree of cure the FDEMS sensor monitors and the RTM processing model predicts the reaction advancement of the resin, viscosity and the impregnation of the fabric. This provides a direct means for predicting, monitoring, and controlling the liquid RTM process in-situ in the mold throughout the fabrication process and the effects of time, temperature, vacuum and pressure. Most importantly, the FDEMS-sensor model system has been developed to make intelligent decisions, thereby automating the liquid RTM process and removing the need for operator direction.

Kranbuehl, D.↗

YUCSA: A CLIPS expert database system to monitor academic performance

The York University CLIPS Student Administrator (YUCSA), an expert database system implemented in C Language Integrated Processing System (CLIPS), for monitoring the academic performance of undergraduate students at York University, is discussed. The expert system component in the system has already been implemented for two major departments, and it is under testing and enhancement for more departments. Also, more elaborate user interfaces are under development. We describe the design and implementation of the system, problems encountered, and immediate future plans. The system has excellent maintainability and it is very efficient, taking less than one minute to complete an assessment of one student.

Toptsis, Anestis A.↗