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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Challenges in Achieving Trajectory-Based Operations

In the past few years much of the global ATM research community has proposed advanced systems based on Trajectory-Based Operations (TBO). The concept of TBO uses four-dimensional aircraft trajectories as the base information for managing safety and capacity. Both the US and European advanced ATM programs call for the sharing of trajectory data across different decision support tools for successful operations. However, the actual integration of TBO systems presents many challenges. Trajectory predictors are built to meet the specific needs of a particular system and are not always compatible with others. Two case studies are presented which examine the challenges of introducing a new concept into two legacy systems in regards to their trajectory prediction software. The first case describes the issues with integrating a new decision support tool with a legacy operational system which overlap in domain space. These tools perform similar functions but are driven by different requirements. The difference in the resulting trajectories can lead to conflicting advisories. The second case looks at integrating this same new tool with a legacy system originally developed as an integrated system, but diverged many years ago. Both cases illustrate how the lack of common architecture concepts for the trajectory predictors added cost and complexity to the integration efforts.

Cate, Karen Tung↗
NASA NTRS2023

Compact Lightweight Aerial Sensor System (CLASSy)

In the wake of increasingly intense wildfires, innovative solutions are imperative to enhance wildfire mitigation strategies. Current technological integrations have hit a communicative limit. Between limited flight time, computational expenses as well as financial expenses, there is a hole in the market for an effective, low-tech, and disposable solution. The Compact Lightweight Aerial Sensor System (CLASSy) is designed to revolutionize active disaster operations through comprehensive decision support. CLASSy consists of a lightweight launch mechanism and a flight body equipped with a sensor package and parachute. The assembly integrates sensor networks with data analytics to provide real-time, high-resolution information to incident commanders, directly facilitating decision-making and resource allocation. Infrared imagery and temperature differentials are processed and analyzed throughout flight, offering valuable insights into fire behavior, hotspot detection, and fire spread trajectories. CLASSy is intended to meet a variety of natural disaster mitigation needs through its variable launch height and disposability. CLASSy’s goal is to assist wildfire fighting without taking up any human or material resources. As a result, CLASSy is as lightweight as possible, easily expendable, inexpensive to manufacture, and only requires one operator for effective use. CLASSy’s integrated sensor suite, real-time analytics, and closed loop active communications empower firefighting teams to proactively address wildfire challenges. As the frequency of wildfires continues to rise, technological innovations like CLASSy are crucial to effective wildfire management systems.

Kyleigh Anderson↗
NASA NTRS2020

Medics: Medical Decision Support System for Long-Duration Space Exploration

The Autonomous Medical Operations (AMO) group at NASA Ames is developing a “medical decision support system” to enable astronauts on long-duration exploration missions to operate autonomously. The system will support clinical actions by providing medical interpretation advice and procedural recommendations during emergent care and clinical work performed by crew. The current state of development of the system, called MedICS (Medical Interpretation Classification and Segmentation) includes two separate aspects: a set of machine learning diagnostic models trained to analyze organ images and patient health records, and an interface to ultrasound diagnostic hardware and to medical repositories. Three sets of images of different organs and medical records were utilized for training machine learning models for various analyses, as follows: 1. Pneumothorax condition (collapsed lung). The trained model provides a positive or negative diagnosis of the condition. 2. Carotid artery occlusion. The trained model produces a diagnosis of 5 different occlusion levels (including “normal”). 3. Ocular retinal images. The model extracts optic disc pixels (image segmentation). This is a precursor step for advanced autonomous fundus clinical evaluation algorithms to be implemented in FY20. 4. Medical health records. The model produces a differential diagnosis for any particular individual, based on symptoms and other health and demographic information. A probability is calculated for each of 25 most common conditions. The same model provides the likelihood of survival. All results are provided with a confidence level. Item 1 images were provided by the US Army and were part of a data set for the clinical treatment of injured battlefield soldiers. This condition is relevant to possible space mishaps, due to pressure management issues. Item 2 images were provided by Houston Methodist Hospital, and item 3 health records were acquired from the MIT laboratory of computational physiology. The machine learning technology utilized is deep multilayer networks (Deep Learning), and new models will continue to be produced, as relevant data is made available and specific health needs of astronaut crews are identified. The interfacing aspects of the system include a GUI for running the different models, and retrieving and storing data, as well as support for integration with an augmented reality (AR) system deployed at JSC by Tietronix Software Inc. (HoloLens). The AR system provides guidance for the placement of an ultrasound transducer that captures images to be sent to the MedICS system for diagnosis. The image captured and the associated diagnosis appear in the technician’s AR visual display.

Colombano, Silvano↗
DOE OSTI2023

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works recognize surgical activities at a coarse-grained level, such as phases, steps or events, leaving out fine-grained interaction details about the surgical activity; yet those are needed for more helpful AI assistance in the operating room. Recognizing surgical actions as triplets of ‹ instrument, verb, target › combination delivers more comprehensive details about the activities taking place in surgical videos. This paper presents CholecTriplet2021: an endoscopic vision challenge organized at MICCAI 2021 for the recognition of surgical action triplets in laparoscopic videos. Here, the challenge granted private access to the large-scale CholecT50 dataset, which is annotated with action triplet information. In this paper, we present the challenge setup and the assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge. Here, a total of 4 baseline methods from the challenge organizers and 19 new deep learning algorithms from the competing teams are presented to recognize surgical action triplets directly from surgical videos, achieving mean average precision (mAP) ranging from 4.2% to 38.1%. This study also analyzes the significance of the results obtained by the presented approaches, performs a thorough methodological comparison between them, in-depth result analysis, and proposes a novel ensemble method for enhanced recognition. Our analysis shows that surgical workflow analysis is not yet solved, and also highlights interesting directions for future research on fine-grained surgical activity recognition which is of utmost importance for the development of AI in surgery.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1986

Requirements specification for nickel cadmium battery expert system

The requirements for performance, design, test, and qualification of a computer program identified as NICBES, Nickel Cadmium Battery Expert System, is established. The specific spacecraft power system configuration selected was the Hubble Space Telescope (HST) Electrical Power System (EPS) Testbed. Power for the HST comes from a system of 13 Solar Panel Arrays (SPAs) linked to 6 Nickel Cadmium Batteries which are connected to 3 Busses. An expert system, NICBES, will be developed at Martin Marietta Aerospace to recognize a testbed anomaly, identify the malfunctioning component and recommend a course of action. Besides fault diagnosis, NICBES will be able to evaluate battery status, give advice on battery status and provide decision support for the operator. These requirements are detailed.

Source record↗
NASA NTRS1992

Coordinating complex problem-solving among distributed intelligent agents

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.

Adler, Richard M.↗
NASA NTRS2008

The Use of Simulated Visible/Infrared Imager/Radiometer Suite (VIIRS) and Landsat Data Continuity Mission (LDCM) Imagery for Coral Reef Monitoring

Coral reefs are some of the most biologically rich and economically important ecosystems on Earth. Coral reefs are Earth's largest biological structures and have taken thousands of years to form. Coral reefs not only provide important habitat for many marine animals and plants, but they also provide humanity with food, jobs, chemicals, protection against storms, and life-saving pharmaceuticals. Severe bleaching events have occurred that have dramatic long-term ecological impacts to corals, including loss of reef-building corals, changes in benthic habitat, and, in some cases, changes in larval fish populations (Holden and Ledrew, 1998). Some researchers suggest that 10 percent of Earth s coral reefs have already been destroyed and that another 60 percent are in danger. Scientists have proposed that as much as 95 percent of Jamaica's reefs are dying or dead. This poster reports on a Rapid Prototyping Capability (RPC) experiment done to determine whether future NASA sensors - the Visible/Infrared Imager/Radiometer Suite (VIIRS) and Landsat Data Continuity Mission (LDCM) - could generate key data products for the Integrated Coral Reef Observation Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST) operated by the National Oceanic and Atmospheric Administration (NOAA).

Estep, L.↗
NASA NTRS2005

NASA Tech Briefs, June 2005

Topics covered include: Apparatus Characterizes Transient Voltages in Real Time; Measuring Humidity in Sealed Glass Encasements; Adaptable System for Vehicle Health and Usage Monitoring; Miniature Focusing Time-of-Flight Mass Spectrometer; Cryogenic High-Sensitivity Magnetometer; Wheel Electrometer System; Carbon-Nanotube Conductive Layers for Thin-Film Solar Cells; Patch Antenna Fed via Unequal-Crossed-Arm Aperture; LC Circuits for Diagnosing Embedded Piezoelectric Devices; Nanowire Thermoelectric Devices; Code for Analyzing and Designing Spacecraft Power System Radiators; Decision Support for Emergency Operations Centers; NASA Records Database; Real-Time Principal- Component Analysis; Fuzzy/Neural Software Estimates Costs of Rocket- Engine Tests; Multicomponent, Rare-Earth-Doped Thermal-Barrier Coatings; Reactive Additives for Phenylethynyl-Containing Resins; Improved Gear Shapes for Face Worm Gear Drives; Alternative Way of Shifting Mass to Move a Spherical Robot; Parylene C as a Sacrificial Material for Microfabrication; In Situ Electrochemical Deposition of Microscopic Wires; Improved Method of Manufacturing SiC Devices; Microwave Treatment of Prostate Cancer and Hyperplasia; Ferroelectric Devices Emit Charged Particles and Radiation; Dusty-Plasma Particle Accelerator; Frozen-Plug Technique for Liquid-Oxygen Plumbing; Shock Waves in a Bose-Einstein Condensate; Progress on a Multichannel, Dual-Mixer Stability Analyzer; Development of Carbon- Nanotube/Polymer Composites; Thermal Imaging of Earth for Accurate Pointing of Deep-Space Antennas; Modifications of a Composite-Material Combustion Chamber; Modeling and Diagnostic Software for Liquefying- Fuel Rockets; and Spacecraft Antenna Clusters for High EIRP.

Source record↗
NASA NTRS2017

Ecological Forecasting Project Management with Examples

Once scientists publish results of their projects and studies, all too often they end up on the shelf and are not otherwise used. The NASA Earth Science Division established its Applied Sciences Program (ASP) to apply research findings to help solve and manage real-world problems and needs. ASP-funded projects generally produce decision support systems for operational applications which are expected to last beyond the end of the NASA funding. Because of NASAs unique perspective of looking down on the Earth from space, ASP studies involve the use of remotely sensed information consisting of satellite data and imagery as well as information from sub-orbital platforms. ASP regularly solicits Earth science proposals that address one or more focus areas; disasters mitigation, ecological forecasting, health and air quality, and water resources. Reporting requirements for ASP-funded projects are different from those typical for research grants from NASA and other granting agencies, requiring management approaches different from other programs. This presentation will address the foregoing in some detail and give examples of three ASP-funded ecological forecasting projects that include: 1) the detection and survey of chimpanzee habitat in Africa from space, 2) harmful algal blooms (HABs) in the California Current System affecting aquaculture facilities and marine mammal populations, and 3) a call for the public to identify North America wildlife in Wisconsin using trail camera photos. Contact information to propose to ASP solicitations for those PIs interested is also provided.

Management↗
DOE OSTI2021

Enhancing the Operational Resilience of Advanced Reactors with Digital Twins by Recurrent Neural Networks

Because of a lack of operation data during abnormal and accident scenarios, along with the existence of uncertainty in the evaluation model for transient and accident analysis, the established abnormal and emergency operating procedures can be biased in characterizing the reactor states and ensuring operational resilience. To improve state awareness and ensure operational flexibility for minimizing effects on the system due to anomaly, digital twin (DT) technology is suggested to support operator's decision-making by effectively extracting and using knowledge of the current and future plant states from the knowledge base. To demonstrate DT's capability for recovering the complete states of reactors and for predicting the future reactor behaviors, this paper develops and assesses both the diagnosis and prognosis DTs in a nearly autonomous management and control system for an Experimental Breeder Reactor-II simulator during different loss-of-flow scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2019

Gateway Modeling and Simulation Plan

This plan institutes direction across the Gateway Program and the Element Projects to ensure that Cross Program M&S are produced in a manner that (1) generate the artifacts required for NASA-STD-7009 compliance, (2) ensures interoperability of M&S exchanged and integrated across the program and, (3) drives integrated development efforts to provide cross-domain integrated simulation of the Gateway elements, space environment, and operational scenarios. This direction is flowed down via contractual enforcement to prime contractors and includes both the GMS requirements specified in this plan and the NASASTD- 7009 derived requirements necessary for compliance. Grounding principles for management of Gateway Models and Simulations (M&S) are derived from the Columbia Accident Investigation Board (CAIB) report and the Diaz team report, “A Renewed Commitment to Excellence.” As an outcome of these reports, and in response to Action 4 of the Diaz team report, the NASA Standard for Models and Simulations, NASA-STD-7009 was developed. The standard establishes M&S requirements for development and use activities to ensure proper capture and communication of M&S pedigree and credibility information to Gateway program decision makers. Through the course of the Gateway program life cycle M&S will be heavily relied upon to conduct analysis, test products, support operations activities, enable informed decision making and ultimately to certify the Gateway with an acceptable level of risk to crew and mission. To reduce risk associated with M&S influenced decisions, this plan applies the NASA-STD-7009 requirements to produce the artifacts that support credibility assessments and ensure the information is communicated to program management.

NASA-STD-7009↗
DOE OSTI2021

AI-Guided Reasoning-Based Operator Support System for the Nuclear Power Plant Management

The Decision-making process in the Nuclear Power Plant (NPP) control room faces some challenges: operator incomplete knowledge, insufficient time for responding to the highly dynamic events, and a large number of indicators to monitor. Because of the complexity of the NPP system, it is hard to pre-plan all the failures/mitigative actions. An intelligent operator support system is vital to mitigate these shortcomings. In this paper, an AI declarative approach (Answer Set Programming (ASP)) is employed to represent our knowledge of the nuclear power plant in the form of logic rules. This represented knowledge is structured to form a reasoning-based operator support system. When an incident occurs, this ASP-based reasoning support system is demonstrated to be capable of fault identification (diagnosis), informing the operator of different scenarios and consequences, and generating the control options (decision making).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2001

Development and Validation of the Controller Acceptance Rating Scale (CARS): Results of Empirical Research

The measurement of operational acceptability is important for the development, implementation, and evolution of air traffic management decision support tools. The Controller Acceptance Rating Scale was developed at NASA Ames Research Center for the development and evaluation of the Passive Final Approach Spacing Tool. CARS was modeled after a well-known pilot evaluation rating instrument, the Cooper-Harper Scale, and has since been used in the evaluation of the User Request Evaluation Tool, developed by MITRE's Center for Advanced Aviation System Development. In this paper, we provide a discussion of the development of CARS and an analysis of the empirical data collected with CARS to examine construct validity. Results of intraclass correlations indicated statistically significant reliability for the CARS. From the subjective workload data that were collected in conjunction with the CARS, it appears that the expected set of workload attributes was correlated with the CARS. As expected, the analysis also showed that CARS was a sensitive indicator of the impact of decision support tools on controller operations. Suggestions for future CARS development and its improvement are also provided.

Lee, Katharine K.↗
NASA NTRS2007

Progress in Spacecraft Environment Interactions: International Space Station (ISS) Development and Operations

The set of spacecraft interactions with the space flight environment that have produced the largest impacts on the design, verification, and operation of the International Space Station (ISS) Program during the May 2000 to May 2007 time frame are the focus of this paper. In-flight data, flight crew observations, and the results of ground-based test and analysis directly supporting programmatic and operational decision-making are reported as are the analysis and simulation efforts that have led to new knowledge and capabilities supporting current and future space explorations programs. The specific spacecraft-environment interactions that have had the greatest impact on ISS Program activities during the first several years of flight are: 1) spacecraft charging, 2) micrometeoroids and orbital debris effects, 3) ionizing radiation (both total dose to materials and single event effects [SEE] on avionics), 4) hypergolic rocket engine plume impingement effects, 5) venting/dumping of liquids, 6) spacecraft contamination effects, 7) neutral atmosphere and atomic oxygen effects, 8) satellite drag effects, and 9) solar ultraviolet effects. Orbital inclination (51.6deg) and altitude (nominally between 350 km and 460 km) determine the set of natural environment factors affecting the performance and reliability of materials and systems on ISS. ISS operates in the F2 region of Earth s ionosphere in well-defined fluxes of atomic oxygen, other ionospheric plasma species, solar UV, VUV, and x-ray radiation as well as galactic cosmic rays, trapped radiation, and solar cosmic rays. The micrometeoroid and orbital debris environment is an important determinant of spacecraft design and operations in any orbital inclination. The induced environment results from ISS interactions with the natural environment as well as environmental factors produced by ISS itself and visiting vehicles. Examples include ram-wake effects, hypergolic thruster plume impingement, materials out-gassing, venting and dumping of fluids, and specific photovoltaic (PV) power system interactions with the ionospheric plasma. Vehicle size (L) and velocity (v), combined with the magnitude and direction of the geomagnetic field (B) produce operationally significant magnetic induction voltages (VxB.L) in ISS conducting structure during high latitude flight (>+/- 45deg) during each orbit. In addition, ISS is a large vehicle and produces a deep wake structure from which both ionospheric plasma and neutrals species are largely excluded. ISS must fly in a very limited number of approved flight attitudes, so that exposure of a particular material or system to environmental factors depends upon: 1) location on ISS, 2) ISS flight configuration, 3) ISS flight attitude, and 4) variation of solar exposure (Beta angle), and hence thermal environment, with time. Finally, an induced ionizing radiation environment is produced by trapped radiation and solar/cosmic ray interactions with the relatively massive ISS structural shielding.

Koontz, Steve↗
NASA NTRS1988

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Szatkowski, Gerard P.↗
NASA NTRS2005

Invasive Species Forecasting System: A Decision Support Tool for the U.S. Geological Survey: FY 2005 Benchmarking Report v.1.6

The National Institute of Invasive Species Science (NIISS), through collaboration with NASA's Goddard Space Flight Center (GSFC), recently began incorporating NASA observations and predictive modeling tools to fulfill its mission. These enhancements, labeled collectively as the Invasive Species Forecasting System (ISFS), are now in place in the NIISS in their initial state (V1.0). The ISFS is the primary decision support tool of the NIISS for the management and control of invasive species on Department of Interior and adjacent lands. The ISFS is the backbone for a unique information services line-of-business for the NIISS, and it provides the means for delivering advanced decision support capabilities to a wide range of management applications. This report describes the operational characteristics of the ISFS, a decision support tool of the United States Geological Survey (USGS). Recent enhancements to the performance of the ISFS, attained through the integration of observations, models, and systems engineering from the NASA are benchmarked; i.e., described quantitatively and evaluated in relation to the performance of the USGS system before incorporation of the NASA enhancements. This report benchmarks Version 1.0 of the ISFS.

Stohlgren, Tom↗
NASA NTRSDate not supplied

Clinical Decision Support For Exploration Space Flight: Software Augmentation To Enhance Progressively Earth-Independent Medical Operations

This panel identifies the challenges of supporting medical events in deep space using integrated systems software to augment existing capabilities during increasingly Earth-independent missions where an asynchronous communication environment becomes routine. An interdisciplinary team of software designers, physicians, human factors engineers, and computational modelers applied their respective expertise to develop a roadmap for supporting the crew making medical decisions in more autonomous fashion with time-delayed ground support. The first presentation describes predictive modeling implemented to assist medical system design and address risk reduction using robust clinical decision support software. The second presentation details how operational and environmental challenges guide assumptions and, in turn, by what means requirements for medical decision-making in deep space are derived. The third presentation describes and defines the skills and capabilities an exploration spaceflight medical officer will need to perform effectively during extended-duration spaceflight missions. The fourth presentation covers the potential models and function of the software element for supporting clinical decisions. The final presentation covers how these elements may work together with ground support to provide comprehensive care despite deep space travel's extreme challenges and limitations.

Dana Levin↗
NASA NTRS2017

A New Architecture for Visualization: Open Mission Control Technologies

Open Mission Control Technologies (MCT) is a new architecture for visualisation of mission data. Driven by requirements for new mission capabilities, including distributed mission operations, access to data anywhere, customization by users, synthesis of multiple data sources, and flexibility for multi-mission adaptation, Open MCT provides users with an integrated customizable environment. Developed at NASAs Ames Research Center (ARC), in collaboration with NASAs Advanced Multimission Operations System (AMMOS) and NASAs Jet Propulsion Laboratory (JPL), Open MCT is getting its first mission use on the Jason 3 Mission, and is also available in the testbed for the Mars 2020 Rover and for development use for NASAs Resource Prospector Lunar Rover. The open source nature of the project provides for use outside of space missions, including open source contributions from a community of users. The defining features of Open MCT for mission users are data integration, end user composition and multiple views. Data integration provides access to mission data across domains in one place, making data such as activities, timelines, telemetry, imagery, event timers and procedures available in one place, without application switching. End user composition provides users with layouts, which act as a canvas to assemble visualisations. Multiple views provide the capability to view the same data in different ways, with live switching of data views in place. Open MCT is browser based, and works on the desktop as well as tablets and phones, providing access to data anywhere. An early use case for mobile data access took place on the Resource Prospector (RP) Mission Distributed Operations Test, in which rover engineers in the field were able to view telemetry on their phones. We envision this capability providing decision support to on console operators from off duty personnel. The plug-in architecture also allows for adaptation for different mission capabilities. Different data types and capabilities may be added or removed using plugins. An API provides a means to write new capabilities and to create data adaptors. Data plugins exist for mission data sources for NASA missions. Adaptors have been written by international and commercial users. Open MCT is open source. Open source enables collaborative development across organizations and also makes the product available outside of the space community, providing a potential source of usage and ideas to drive product design and development. The combination of open source with an Apache 2 license, and distribution on GitHub, has enabled an active community of users and contributors. The spectrum of users for Open MCT is, to our knowledge, unprecedented for mission software. In addition to our NASA users, we have, through open source, had users and inquires on projects ranging from Internet of Things, to radio hobbyists, to farming projects. We have an active community of contributors, enabling a flow of ideas inside and outside of the space community.

Trimble, Jay↗