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

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

An Analysis of the Lightning Jump Algorithm Using Geostationary Lightning Mapper Flashes

Lightning's relation to severe weather has been studied since the 1980's. The invention of the Lightning Mapping Array allowed for total lightning measurements in a 125 km operational range. This brought forth an automated lightning Jump Algorithm (LIA) that predicted severe weather based on two-sigma increases in total lightning. The LIA's biggest downfall is being restrained to the limited field of view (FOV) of LMA's. The launch of the Geostationary Lightning Mapper (GLM) aboard the GOES-16 satellite now gives us hemispheric total lightning measurements. The wide FOV makes the GLM a good candidate to apply the LIA to. However the GLM and LMA have some differences. One being the coarser spatial resolution of GLM. Another being that LMA measures very high frequency (VHF) electromagnetic radiation while GLM measures optical radiation. These differences suggest an extensive study must be done on using the LIA with GLM to understand potential differences in the LIA and to maximize its operational skill. Four deep dive cases are conducted showcasing the differences between the GLM and LMA and their jumps.

Curtis, Nathan↗
NASA NTRS2018

An Analysis of the Lightning Jump Algorithm Using Geostationary Lightning Mapper Flashes

This project aims to implement the two-sigma lightning jump algorithm (LJA) developed using Lightning Mapping Arrays (LMAs), with GOES-16 Geostationary Lightning Mapper (GLM) flashes, evaluate its performance, and identify any needed adjustments to the algorithm to optimize operational skill. The GLM is projected to have lower detection efficiency (DE) (70-90 percent) than operational LMAs (95-99 percent). The reduced GLM DE coupled with the coarser spatial resolution of the GLM could have impacts on flash rates and trends that could affect the LJA in various ways. Deep dives are conducted on four separate cases. Three of four cases show LMAs seeing two to three times as many flashes as the GLM. Only fifteen of twenty five GLM jumps saw increases in radar intensity while fourteen of nineteen LMA jumps did. These results suggest a larger sample sized study must be conducted to determine how to implement the LJA with the GLM.

Curtis, Nathan↗
NASA NTRS2018

Controllable Buoys and Networked Buoy Systems

Buoyant sensor networks are described, comprising floating buoys with sensors and energy harvesting capabilities. The buoys can control their buoyancy and motion, and can organize communication in a distributed fashion. Some buoys may have tethered underwater vehicles with a smart spooling system that allows the vehicles to dive deep underwater while remaining in communication and connection with the buoys.

Davoodi, Faranak↗
NASA NTRS2016

Analyzing Double Delays at Newark Liberty International Airport (EWR)

When weather or congestion impacts the National Airspace System, multiple different Traffic Management Initiatives can be implemented, sometimes with unintended consequences. One particular perceived inequity that is commonly identified is in the interaction between Ground Delay Programs (GDPs) and time based scheduling of internal departures by the Traffic Management Advisor (TMA) (now operationally superseded by the FAA's the Time-Based Flow Management system). Internal departures under TMA scheduling can take large GDP delays, followed by large TMA scheduling delays, because they cannot easily fit into the arrival flow at the runway. In this paper we examine the causes of these double delays through an analysis of arrival operations at Newark Liberty International Airport (EWR) from June to August 2010. TMA scheduling delays are found to be generally higher than TMA airborne metering delays, regardless of prior GDP delays. Depending on how the double delay is defined, between 42 and 62 of all internal departures in GDP and TMA scheduling experienced double delays in this period. A deep dive into the data reveals that contributors to double delays include upstream flights departing before their Expect Departure Clearance Times (EDCTs); differences in the rates used for setting EDCTs and TMA Scheduled Times of Arrival; differences in the arrival demand expected based on EDCTs and the arrival demand entering TMA; and shorter en route times between takeoff and entry into TMA than assumed in the calculation of flight EDCTs, all of which undermine the sequencing and spacing underlying flight EDCTs. Double delays are also found to coincide with periods in which the virtual runway arrival queue being served by a TMA is large, there are periods of high demand relative to capacity, and there are high airborne metering delays. Data mining techniques are used to confirm that each of these factors contribute to the occurrence of double delay andor high internal departure scheduling delay across three months of data from June to August 2010. Predictors of the occurrence of double delay and high TMA scheduling delay are built using logistic regression, providing prediction accuracies of 69 and 73, respectively.

traffic flow management↗
NASA NTRS2016

The Last Orbit: Planning Cassini's Plummet into Saturn

Cassini’s final orbit around Saturn will culminate in a dramatic ending as the spacecraft plunges into the ringed planet’s atmosphere, never to escape or be heard from again. The last hours of the mission prior to the final loss of signal have some of the most unique and valuable science to date. Cassini will take a unique trajectory to dive deep into the atmosphere on its approach to final disposal and no spacecraft, Cassini included, has entered these depths of Saturn’s atmosphere. The science community has placed heavy emphasis onthis once-in-a-lifetime opportunity to inspect these deeper regions of Saturn’s atmosphere. The Cassini project specifically aims to collect the very last bits of data during the final plunge to get samples of the deepest regions before the spacecraft is lost forever. The desire to collect the final bits of data presents several challenges. Cassini’s Mission Planning (MP) team has developed an End of Mission (EOM) scenario to tackle these demands. The EOM scenario outlines the framework for the entire last orbit of the mission and details thestrategy for data collection and transmission. Attaining near real-time transmission is key for the acquisition of the very last bits of data. The Cassini spacecraft will use a new mode of operations to successfully achieve this real-time transmission. In addition to this primary investigation and planning for telecommunications, key risks have been studied within the realm of the last orbit. Ultimately, this paper shows how the Cassini Project plans to ensurethe return of every last bit of data before the spacecraft is consumed by Saturn forever.

Bittner, Molly E.↗
NASA NTRS2019

"Sensor Web Evolution - Webs of Webs for NASA Science - Focus on small Uninhabited Aerial Systems (sUAS)"

This paper will describe the evolution of information collection, derivation and delivery mechanisms in webs of NASA sensor webs, with a focus on recent advancements in small Uninhabited Aerial Systems (sUAS). I will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, sUASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary sUASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. I will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing sUASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to sUAS development. This paper will focus on application, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

Sensor Web↗
NASA NTRSDate not supplied

A Quantitative Analysis on the Use of Supervised Machine Learning in Earth Science

Recent review papers (Ball et al., 2017; Reichstein et al., 2019) have investigated the opportunities and challenges in applying supervised machine learning (ML) techniques to Earth science problems. A common challenge is the lack of training (or labeled) data. Supervised ML, and especially deep learning (DL), require large training datasets. While there are large, open access Earth science archives, the data typically require preprocessing in preparation for supervised ML, frequently including manual labeling. Our objective is to understand the landscape of supervised ML in the Earth sciences, including which research communities have most rapidly adopted supervised ML, which algorithms are applied, and what data are used to train these algorithms. We conducted a literature survey of Earth science papers published during the last 10 years in journals from the American Geophysical Union (AGU), American Meteorological Society (AMS), the Institute of Electrical and Electronics Engineers(IEEE), and the Society of Photo-Optical Instrumentation Engineers (SPIE). We identified papers containing the terms ML, DL, or the names of individual supervised ML algorithms. "Earth science" is an additional required search term for IEEE and SPIE. We investigate trends in supervised ML usage during the 10-year study period, and manually analyzed AGU papers from 2018-2019 to enable deep-dive statistics.

Katrina S Virts↗
NASA NTRSDate not supplied

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS↗
NASA NTRSDate not supplied

New Developments In NASA’s Entry Systems Modeling Project

This paper describes recent developments for modeling entry, descent, and landing (EDL)of spacecraft in support of NASA’s exploration missions. Mission-specific research and model development for entry systems occurs across the Agency (e.g., within flight programs like Artemis/Orion and Mars Sample Return), however the aim of this paper is to discuss the research conducted by NASA’s Entry Systems Modeling (ESM) Project, which serves as the Agency’s only effort dedicated to advancing modeling capabilities that cross-cut multiple technical disciplines, missions and destinations. The ESM portfolio is developed to address the specific needs expressed by a cross-section of NASA stakeholders, including flight and research projects, technical leadership, and subject matter experts. Technology development in ESM is organized and prioritized from a system-level perspective, resulting in four broad technical areas of investment: (1) Thermal Protection System (TPS) material modeling, (2) Shock layer kinetics and radiation, (3) Aerosciences, and (4) Guidance, navigation, and control. In addition to the core technical areas, special topics are rolled into the project portfolio as specific demands arise. Current special topics include TPS Certification by Analysis, improving understanding of woven TPS material performance; Hypersonic Wake Flows, assessing and improving predictions of base flows; and the MEDLI2 Deep Dive, furthering analysis of data obtained during Mars2020 mission’s entry and descent at Mars. Key results from each of these areas are presented in this paper, along with associated references to serve as a roadmap for other EDL researchers to access NASA’s publications.

Aaron M Brandis↗
NASA NTRSDate not supplied

Overview of NASA's Detailed Investigation into the MEDLI2 Flight Data

- MEDLI2 “Deep Dive” - Why a focused investigation? - Deeper understanding of the MEDLI2 dataset, including TPS in-depth temperatures, backshell pressure, and radiative heat flux - Validate new tools for future Mars missions including Mars Sample Return and Humans-to-Mars - MEDLI2 is considerably more complex than MEDLI - Fully leverage the significant investment in the MEDLI2 instrumentation suite - Core research areas: - PICA-NuSil (PICA-N) testing, model development, and validation - Detailed aeroheating investigations - Sensor fusion of collocated measurements - High-fidelity analyses and uncertainty quantification - Trajectory and aerodynamics investigations

Tom West↗
NASA NTRSDate not supplied

FAA/AES - NASA/DIP Technical Interchange Meeting

The purpose of this Technical Interchange Meeting (TIM) is to hold our second of several discussions on select DIP and AES-topics. The first AES- DIP Technical Interchange Meeting was an in-person event in Washington DC. This is a followup meeting to deep dive into some of the areas discussed during the 1st TIM

monitoring↗
NASA NTRS1997

Assessment and Management of the Risks of Debris Hits During Space Station EVAs

The risk of EVAs is critical to the decision of whether or not to automate a large part of the construction of the International Space Station (ISS). Furthermore, the choice of the technologies of the space suit and the life support system will determine (1) the immediate safety of these operations, and (2) the long-run costs and risks of human presence in space, not only in lower orbit (as is the case of the ISS) but also perhaps, outside these orbits, or on the surface of other planets. The problem is therefore both an immediate one and a long-term one. The fundamental question is how and when to shift from the existing EMU system (suit, helmet, gloves and life support system) to another type (e.g. a hard suit), given the potential trade-offs among life-cycle costs, risks to the astronauts, performance of tasks, and uncertainties about new systems' safety inherent to such a shift in technology. A more immediate issue is how to manage the risks of EVAs during the construction and operation of the ISS in order to make the astronauts (in the words of the NASA Administrator) "as safe outside as inside". For the moment (June 1997), the plan is to construct the Space Station using the low-pressure space suits that have been developed for the space shuttle. In the following, we will refer to this suit assembly as EMU (External Maneuvering Unit). It is the product of a long evolution, starting from the U.S. Air Force pilot suits through the various versions and changes that occurred for the purpose of NASA space exploration, in particular during the Gemini and the Apollo programs. The Shuttle EMU is composed of both soft fabrics and hard plates. As an alternative to the shuttle suit, at least two hard suits were developed by NASA: the AX5 and the MRKIII. The problem of producing hard suits for space exploration is very similar to that of producing deep-sea diving suits. There was thus an opportunity to develop a suit that could be manufactured for both purposes with the economies of scale that could be gained from a two-branch manufacturing line (space and deep sea). Of course, the space suit would need to be space qualified. Some of the problems in adopting one of the hard suits were first that the testing had to be completed, and second that it required additional storage space. The decision was made not to develop a hard suit in time for the construction and operation of the ISS. Instead, to improve the safety of the current suit, it was decided to reinforce the soft parts of the shuttle EMU with KEVLAR linings to strengthen it against debris impacts. Test results, however, show that this advanced suit design has little effect on the penetration characteristics.

Pate-Cornell, Elisabeth↗
NASA NTRS1971

Inexpensive anti-fog coating for windows

Coating applications include anti-fog protection for deep-sea diving equipment, fire protection helmets, and windows of vehicles used in hazardous environments. Basic coating composition includes liquid detergent, deionized water, and oxygen compatible fire-resistant oil. Composition prevents visor fogging under maximum metabolic load for 5 hours and longer.

Carmin, D. L., Jr.↗
NASA NTRS1992

Team dynamics in isolated, confined environments - Saturation divers and high altitude climbers

The effects of leadership dynamics and social organization factors on team performance under conditions of high altitude climbing and deep sea diving are studied. Teams of two to four members that know each other well and have a relaxed informal team structure with much sharing of responsibilities are found to do better than military teams with more than four members who do not know each other well and have a formal team structure with highly specialized rules. Professionally guided teams with more than four members, a formally defined team structure, and clearly designated role assignments did better than 'club' teams of more than four members with a fairly informal team structure and little role specialization.

Kanki, Barbara G.↗
NASA NTRS2001

Interpretation of Observations of Trans-Spectral Phenomena Acquired Using Hyperspectral Sensors Aboard a Remotely Operated Vehicle in Exuma Sound

Hyper-spectral (512-channel) optical data acquired during a relatively deep (102m) dive of our ROSEBUD Remotely Operated Vehicle (ROV) in the clear waters of Exuma Sound, Bahamas provided the opportunity to investigate the trans-spectral shift of photonic energy (inelastic scattering) as a function of water depth. Results show a convolution of several spectral processes (e.g. absorption, scattering) involving water molecules, dissolved material and particulates as well as trans-spectral (inelastic) processes involving fluorescence by water molecules (Raman), dissolved material and chlorophyll. The spectral signatures of these convolved causes and effects allow deconvolution with a hyperspectral approach. Intrinsic to the convolution was the ability to position the vehicle at depths where Raman fluorescence dominated at red wavelengths. Results show that the calculated Raman absorption coefficients are generally consistent with historical values (i.e. 0.9 x 10(sup)-4 at 525 nm excitation) and that an angstrom exponent of 5 is more appropriate than the often cited value of 4.

Costello, D.↗
NASA NTRS1976

Fogless Ski Goggles

Keeping ski goggles from fogging is just one of dozens of uses for anti-fog coating developed at Johnson Space Center to keep spacecraft windows clear before launch. Basic composition of coating includes a liquid detergent, deionized water, an oxygen-compatible, fire resistant oil. Two thin coatings are applied to glass or plastic surface and buffed lightly. Applications include deep sea diving masks, fire protection helmets, eyeglasses, and vehicle windows.

Source record↗
NASA NTRS2006

Miniature Wireless Sensors Size Up to Big Applications

Like the environment of space, the undersea world is a hostile, alien place for humans to live. But far beneath the waves near Key Largo, Florida, an underwater laboratory called Aquarius provides a safe harbor for scientists to live and work for weeks at a time. Aquarius is the only undersea laboratory in the world. It is owned by the National Oceanic and Atmospheric Administration (NOAA), administered by NOAA s National Undersea Research Program, and operated by the National Undersea Research Center at the University of North Carolina at Wilmington. Aquarius was first deployed in underwater operations in 1988 and has since hosted more than 200 scientists representing more than 90 organizations from around the world. For NASA, Aquarius provides an environment that is analogous to the International Space Station (ISS) and the space shuttle. As part of its NASA Extreme Environment Mission Operations (NEEMO) program, the Agency sends personnel to live in the underwater laboratory for up to 2 weeks at a time, some of whom are crew members or "aquanauts" who are subjected to the same tasks and challenges underwater that they would face in space. In fact, many participants have found the deep-sea diving experience to be much akin to spacewalking. To maintain Aquarius, the ISS, and the space shuttle as safe, healthy living/research habitats for its personnel, while keeping costs in mind, NASA, in 1997, recruited the help of Conroe, Texas-based Invocon, Inc., to develop wireless sensor technology that monitors and measures various environmental and structural parameters inside these facilities.

Source record↗