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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain

Magnetic resonance (MR) brain section images are segmented and then synthetically colored to give visual representations of the original data with three approaches: the literal and approximate fuzzy c-means unsupervised clustering algorithms and a supervised computational neural network, a dynamic multilayered perception trained with the cascade correlation learning algorithm. Initial clinical results are presented on both normal volunteers and selected patients with brain tumors surrounded by edema. Supervised and unsupervised segmentation techniques provide broadly similar results. Unsupervised fuzzy algorithms were visually observed to show better segmentation when compared with raw image data for volunteer studies. However, for a more complex segmentation problem with tumor/edema or cerebrospinal fluid boundary, where the tissues have similar MR relaxation behavior, inconsistency in rating among experts was observed.

Hall, Lawrence O.↗
NASA NTRS1993

Emergency medical service (EMS): A unique flight environment

The EMS flight environment is unique in today's aviation. The pilots must respond quickly to emergency events and often fly to landing zones where they have never been before . The time from initially receiving a call to being airborne can be as little as two to three minutes. Often the EMS pilot is the only aviation professional on site, they have no operations people or other pilots to aid them in making decisons. Further, since they are often flying to accident scenes, not airports, there is often complete weather and condition information. Therefore, the initial decision that the pilot must make, accepting or declining a flight, can become very difficult. The accident rate of EMS helicopters has been relatively high over the past years. NASA-Ames research center has taken several steps in an attempt to aid EMS pilots in their decision making and situational awareness. A preflight risk assessment system (SAFE) was developed to aid pilots in their decision making, and was tested at an EMS service. The resutls of the study were promising and a second version incorporating the lessons learned is under development. A second line of research was the development of a low cost electronic chart display (ECD). This is a digital map display to help pilots maintain geographical orientation. Another thrust was undertaken in conjunction with the Aviation Safety Reporting System (ASRS). This involved publicizing the ASRS to EMS pilots and personnel, and calling each of the reporters back to gather additional information. This paper will discuss these efforts and how they may positively impact the safety of EMS operations.

Shively, R. Jay↗
NASA NTRS2024

Flight Certification Approach for NASA's Space Launch System

NASA’s Space Launch System (SLS) vehicle was successfully launched on November 16, 2022, initiating the Artemis I mission to send the uncrewed Orion spacecraft to the Moon and further into space than any human-rated spacecraft had previously flown. Flight certification of the launch vehicle was part of the systems engineering and integration (SE&I) effort conducted by NASA to successfully certify the mission and begin a new era of human space exploration of the Moon and eventually Mars. This paper describes the SLS Program flight certification approach including the organization, processes, and reporting. This approach used traditional NASA SE&I milestone reviews and lessons learned from the Space Shuttle Program, as well as unique methods to certify the complex system, procedures, and personnel readiness. The approach utilized by the SLS Program to conduct flight certification for the Artemis I mission can be extended to address flight certification for other complex programs.

flight certification↗
NASA NTRS2011

Debris Disks in Aggregate: Using Hubble Space Telescope Coronagraphic Imagery to Understand the Scattered-Light Disk Detection Rate

Despite more than a decade of coronagraphic imaging of debris disk candidate stars, only 16 have been imaged in scattered light. Since imaged disks provide our best insight into processes which sculpt disks, and can provide signposts of the presence of giant planets at distances which would elude radial velocity and transit surveys, we need to understand under what conditions we detect the disks in scattered light, how these disks differ from the majority of debris disks, and how to increase the yield of disks which are imaged with 0.1" angular resolution. In this talk, I will review what we have learned from a shallow HSTINICMOS NIR survey of debris disks, and present first results from our on-going HST /STIS optical imaging of bright scattered-light disks.

Grady, Carol A.↗
NASA NTRS2002

The Microwave Anisotropy Probe (MAP) Guidance, Navigation, and Control Hardware Suite

The on-orbit success of the Microwave Anisotropy Probe (MAP) Guidance, Navigation, and Control System can partially be attributed to the performance of a hardware suite chosen to meet the complex attitude determination and control requirements of the mission. To meet these requirements, a diverse set of components was used. The set included two Lockheed Martin AST-201 star trackers, two Kearfott Two-Axis Rate Assemblies mounted to provide X, Y and redundant Z-axis rates, two Adcole Digital Sun Sensor heads sharing one set of electronics, twelve Adcole Coarse Sun Sensor eyes, three Ithaco E-sized Reaction Wheel Assemblies, a Propulsion Subsystem that employed eight Primex Rocket Engine Modules, and a pair of Goddard-designed Attitude Control Electronics which connect all of the components to the spacecraft processor. The performance of this hardware is documented, as are some of the spacecraft accommodations and lessons learned that came from working with this particular set of hardware.

Ward, David K.↗
NASA NTRS2004

Team Formation in Partially Observable Multi-Agent Systems

Sets of multi-agent teams often need to maximize a global utility rating the performance of the entire system where a team cannot fully observe other teams agents. Such limited observability hinders team-members trying to pursue their team utilities to take actions that also help maximize the global utility. In this article, we show how team utilities can be used in partially observable systems. Furthermore, we show how team sizes can be manipulated to provide the best compromise between having easy to learn team utilities and having them aligned with the global utility, The results show that optimally sized teams in a partially observable environments outperform one team in a fully observable environment, by up to 30%.

Agogino, Adrian K.↗
NASA NTRSDate not supplied

Cislunar Trajectory Design and Maneuver Autonomy for NASA's Moon to Mars Architecture

NASA’s Moon to Mars architecture is an ambitious roadmap of manned cislunar and deep space exploration. The extensive amount of orbital assets required will place a significant burden on ground-based resources, such as communication networks and operations facilities. Spacecraft autonomy is essential for maintaining a vast number of complex missions beyond Earth orbit. To achieve full autonomy, spacecraft must be able to employ methods of robust maneuver design without an explicit dependence on commands sent from the ground. This level of autonomy is needed not only for stationkeeping, but also for outbound transfers. To address the need of spacecraft maneuver design autonomy, this work investigates the use of neural networks (NNs) in a supervised learning environment. A supervised learning approach for NNs allows for a curated training data set, consisting exclusively of perturbations applied to a desired mission concept of operations (ConOps). The proposed approach allows humans on the ground to design a specific mission ConOps before flight, then employ NNs to fly the mission robustly and autonomously. This investigation numerically tests maneuver autonomy in four highly sensitive regions of flight: orbit raising, translunar injection burns, powered lunar flybys, and invariant manifold insertion burns. These straining cases are contextualized by testing them in a demonstration mission, targeting an Earth-Moon L3 orbit. The study first establishes feasibility by automating impulsive burn maneuvers. However, some guidance algorithms will need more intensive commands, such as inertial pointing and angular rates. To validate this method, NN maneuver autonomy is applied to a finite burn model of the demonstration mission. The use of sequential, mission specific maneuvers provide an appropriate testbed to demonstrate the robustness of a NN trained on feasible perturbed states. Moreover, these scenarios provide preliminary proof-of-concept for fully autonomous missions that execute maneuvers without dependence upon explicit command uplinks. As a result, the technological advancement proposed in this work may significantly ease the strain on ground-based mission operations. This would enable complex and autonomous mission execution in cislunar and deep space regimes, filling a technology gap required to support future manned missions.

NASA↗
NASA NTRS1992

Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET)

A software application to assist end-users of the high burst rate (HBR) link evaluation terminal (LET) for satellite communications is being developed. The HBR LET system developed at NASA Lewis Research Center is an element of the Advanced Communications Technology Satellite (ACTS) Project. The HBR LET is divided into seven major subsystems, each with its own expert. Programming scripts, test procedures defined by design engineers, set up the HBR LET system. These programming scripts are cryptic, hard to maintain and require a steep learning curve. These scripts were developed by the system engineers who will not be available for the end-users of the system. To increase end-user productivity a friendly interface needs to be added to the system. One possible solution is to provide the user with adequate documentation to perform the needed tasks. With the complexity of this system the vast amount of documentation needed would be overwhelming and the information would be hard to retrieve. With limited resources, maintenance is another reason for not using this form of documentation. An advanced form of interaction is being explored using current computer techniques. This application, which incorporates a combination of multimedia and artificial intelligence (AI) techniques to provided end-users with an intelligent interface to the HBR LET system, is comprised of an intelligent assistant, intelligent tutoring, and hypermedia documentation. The intelligent assistant and tutoring systems address the critical programming needs of the end-user.

Shahidi, Anoosh K.↗
NASA NTRS1998

Linear Aerospike SR-71 Experiment (LASRE): Aerospace Propulsion Hazard Mitigation Systems

A major hazard posed by the propulsion system of hypersonic and space vehicles is the possibility of fire or explosion in the vehicle environment. The hazard is mitigated by minimizing or detecting, in the vehicle environment, the three ingredients essential to producing fire: fuel, oxidizer, and an ignition source. The Linear Aerospike SR-71 Experiment (LASRE) consisted of a linear aerospike rocket engine integrated into one-half of an X-33-like lifting body shape, carried on top of an SR-71 aircraft. Gaseous hydrogen and liquid oxygen were used as propellants. Although LASRE is a one-of-a-kind experimental system, it must be rated for piloted flight, so this test presented a unique challenge. To help meet safety requirements, the following propulsion hazard mitigation systems were incorporated into the experiment: pod inert purge, oxygen sensors, a hydrogen leak detection algorithm, hydrogen sensors, fire detection and pod temperature thermocouples, water misting, and control room displays. These systems are described, and their development discussed. Analyses, ground test, and flight test results are presented, as are findings and lessons learned.

Mizukami, Masashi↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRS1991

Approximate reasoning-based learning and control for proximity operations and docking in space

A recently proposed hybrid-neutral-network and fuzzy-logic-control architecture is applied to a fuzzy logic controller developed for attitude control of the Space Shuttle. A model using reinforcement learning and learning from past experience for fine-tuning its knowledge base is proposed. Two main components of this approximate reasoning-based intelligent control (ARIC) model - an action-state evaluation network and action selection network are described as well as the Space Shuttle attitude controller. An ARIC model for the controller is presented, and it is noted that the input layer in each network includes three nodes representing the angle error, angle error rate, and bias node. Preliminary results indicate that the controller can hold the pitch rate within its desired deadband and starts to use the jets at about 500 sec in the run.

Berenji, Hamid R.↗
NASA NTRS1992

Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

Mitra, Sunanda↗
NASA NTRS2005

Hawaii Space Grant Consortium

The Hawai'i Space Grant Consortium is composed of ten institutions of higher learning including the University of Hawai'i at Manoa, the University of Hawai'i at Hilo, the University of Guam, and seven Community Colleges spread over the 4 main Hawaiian islands. Geographic separation is not the only obstacle that we face as a Consortium. Hawai'i has been mired in an economic downturn due to a lack of tourism for almost all of the period (2001 - 2004) covered by this report, although hotel occupancy rates and real estate sales have sky-rocketed in the last year. Our challenges have been many including providing quality educational opportunities in the face of shrinking State and Federal budgets, encouraging science and technology course instruction at the K-12 level in a public school system that is becoming less focused on high technology and more focused on developing basic reading and math skills, and assembling community college programs with instructors who are expected to teach more classes for the same salary. Motivated people can overcome these problems. Fortunately, the Hawai'i Space Grant Consortium (HSGC) consists of a group of highly motivated and talented individuals who have not only overcome these obstacles, but have excelled with the Program. We fill a critical need within the State of Hawai'i to provide our children with opportunities to pursue their dreams of becoming the next generation of NASA astronauts, engineers, and explorers. Our strength lies not only in our diligent and creative HSGC advisory board, but also with Hawai'i's teachers, students, parents, and industry executives who are willing to invest their time, effort, and resources into Hawai'i's future. Our operational philosophy is to FACE the Future, meaning that we will facilitate, administer, catalyze, and educate in order to achieve our objective of creating a highly technically capable workforce both here in Hawai'i and for NASA. In addition to administering to programs and educating the public in the traditional sense, we also work to facilitate partnerships between other departments (geology & geophysics, engineering, geography, astronomy), state and federal government agencies in Hawai'i, and private industry. In some cases, we are the catalyst for new partnerships between private agency sponsors and education projects or for new joint research and education projects between industry and the University faculty.

Flynn, Luke P.↗
NASA NTRS1993

Some lessons learned in three years with ADS-33C

Three years of using the U.S. Army's rotorcraft handling qualities specification, Aeronautical Design Standard - 33, has shown it to be surprisingly robust. It appears to provide an excellent basis for design and for assessment, however, as the subtleties become more well understood, several areas needing refinement became apparent. Three responses to these needs have been documented in this paper: (1) The yaw-axis attitude quickness for hover target acquisition and tracking can be relaxed slightly. (2) Understanding and application of criteria for degraded visual environments needed elaboration. This and some guidelines for testing to obtain visual cue ratings have been documented. (3) The flight test maneuvers were an innovation that turned out to be very valuable. Their extensive use has made it necessary to tighten definitions and testing guidance. This was accomplished for a good visual environment and is underway for degraded visual environments.

Key, David L.↗
NASA NTRS2018

Variables Influencing RNAV STAR Adherence

In this study we investigated how variables in the aviation domain impact adherence levels of aircraft flying area navigation arrivals with optimized profile descents (RNAV OPDs) (RNAV STARs: aRea NAVigation Standard Terminal Arrival Routes). Variable categories were: weather, aircraft, procedure, and traffic. Non-adherence events analyzed were: miss above, miss below, skip before merge, and skip after merge. Miss below and miss above describe when a flight does not comply vertically with a procedure. Skips refer to a flight leaving a procedure, then returning. Findings of this work reveal that vertical events are most impacted by altitude restriction size, steepness of flight paths, and merging routes. Lateral events were impacted by merging flight conflicts, number of speed restrictions, and the flow rate of the arrival traffic. This study helps increase understanding of how the system is functioning and identifies where procedures are not flexible enough to handle the variability in normal operations.major airports, procedure design, and recommendations for future work.

RNAV OPD↗
NASA NTRS2019

ATD-2 TFDM Terminal Publication Service (TTP)

Learn the many benefits of the newest SWIM feed from the surface system. This will discuss current options to onboard with this feed, allow participants to ask questions and provide some examples of how the data can be used. Service Includes Flight Data Individual flight updates containing flight identifiers, targeted times, actual times, runway, parking gate, spot, departure fix (predicted, assigned, actual as appropriate), flight states, and more. Airport Information Airport configurations, airport and runway rates, ramp closures, runway closures, taxiway closures. Traffic Management Restrictions Call for Release programs departure MIT/MINIT restrictions, departure stop/ground stop programs. Along with list of impacted flights for each. Flight Delay Airport and runway delay by arrival, departure, and total. Operational Metrics Metrics on airport throughput and individual flight metrics. Surface Metering Program SMP start / end times, metering constraint type / details, updates to existing programs, TMAT compliance window, departure queue length, and more.

Gorman, Shawn M.↗
NASA NTRS2019

Flow Boiling and Condensation Experiment Flight Hardware Development

The Flow Boiling and Condensation Experiment (FBCE) to be manifested on the International Space Station (ISS) consists of a fluid system and the associated electronics to provide for conditioning the test fluid (normal-PerFluorohexane or nPFH-C6F14) to the proper thermodynamic state prior to entering a test module, which can be interchangeable based on the science objectives. Two separate test modules have been manufactured for the FBCE, the Flow Boiling Module (FBM), which investigates flow boiling for a subcooled liquid, saturated liquid, or two phase mixture, and the Condensation Module Heat Transfer (CM-HT), which investigates condensation of a flowing saturated or superheated vapor. The test fluid heating is accomplished using the Bulk Heater Module (BHM), which heats the fluid to various states based on the demands of the currently installed test module. ISS Internal Thermal Control System (ITCS) water is utilized to cool the test fluid prior to entering the circulation pump, and is also utilized for cooling for condensation in CM-HT, for cooling of a camera in FBM. An adjustable pressure bellows-type accumulator is used to set the pressure at the inlet of the test section, but does not provide active pressure control during testing. The flow of the test fluid is achieved using a gear pump controlled by a coriolis flow meter, which also provides the flow rate measurement. Flow rates for the ITCS water loops are measured and controlled using coriolis flow meters with directly controlled proportional valves. During execution of FBCE operations, the FBM is scheduled to collect data for three months before being exchanged with CM-HT for another three month data collection run. In this work, we present the development of the flight hardware, the associated challenges experienced during the development such as packaging flight system hardware, and the lessons learned in overcoming the encountered challenges.

Guzik, Monica C.↗