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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

The Human Dimension of Closing the Training Gap for Fifth-Generation Fighters

Based on a review of the recent technical literature there is little question that a serious training gap exists for fifth-generation fighters, primarily arising from the need to provide their own red-air. There are several methods for reducing this gap, including injecting virtual and constructive threats into the live cockpit. This live-virtual-constructive (LVC) training approach provides a cost effective means for addressing training needs but faces several challenges. Technical challenges include data links and information assurance. A more serious challenge may be the human factors dimension of representing virtual and constructive entities in the cockpit while ensuring safety-of-flight. This also needs to happen without increasing pilot workload. This paper discusses the methods Rockwell Collins and the University of Iowa's Operator Performance Lab use to assess pilot workload and training fidelity measures in an LVC training environment and the research we are conducting in safety-of-flight requirements of integrated LVC symbology.

Hoke, Jaclyn↗
NASA NTRS2013

Effects of Type and Strength of Force Feedback on Movement Time in a Target Selection Task

Future cockpits will likely include new onboard technologies, such as cockpit displays of traffic information, to help support future flight deck roles and responsibilities. These new technologies may benefit from multimodal feedback to aid pilot information processing. The current study investigated the effects of multiple levels of force feedback on operator performance in an aviation task. Participants were presented with two different types of force feedback (gravitational and spring force feedback) for a discrete targeting task, with multiple levels of gain examined for each force feedback type. Approach time and time in target were recorded. Results suggested that the two highest levels of gravitational force significantly reduced approach times relative to the lowest level of gravitational force. Spring force level only affected time in target. Implications of these findings for the design of future cockpit displays will be discussed.

CDTI↗
NASA NTRS2014

Optoelectronic Tweezers for Microparticle and Cell Manipulation

An optical image-driven light induced dielectrophoresis (DEP) apparatus and method are described which provide for the manipulation of particles or cells with a diameter on the order of 100 micromillimeters or less. The apparatus is referred to as optoelectric tweezers (OET) and provides a number of advantages over conventional optical tweezers, in particular the ability to perform operations in parallel and over a large area without damage to living cells. The OET device generally comprises a planar liquid-filled structure having one or more portions which are photoconductive to convert incoming light to a change in the electric field pattern. The light patterns are dynamically generated to provide a number of manipulation structures that can manipulate single particles and cells or group of particles/cells. The OET preferably includes a microscopic imaging means to provide feedback for the optical manipulation, such as detecting position and characteristics wherein the light patterns are modulated accordingly.

Wu, Ming Chiang↗
NASA NTRS2015

Java Architecture for Detect and Avoid Extensibility and Modeling

Unmanned aircraft will equip with a detect-and-avoid (DAA) system that enables them to comply with the requirement to "see and avoid" other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. This paper describes a capability called Java Architecture for Detect and Avoid Extensibility and Modeling (JADEM), developed to prototype and help evaluate various DAA technological requirements by providing a flexible and extensible software platform that models all major detect-and-avoid functions. Figure 1 illustrates JADEM's architecture. The surveillance module can be actual equipment on the unmanned aircraft or simulators that model the process by which sensors on-board detect other aircraft and provide track data to the traffic display. The track evaluation function evaluates each detected aircraft and decides whether to provide an alert to the pilot and its severity. Guidance is a combination of intruder track information, alerting, and avoidance/advisory algorithms behind the tools shown on the traffic display to aid the pilot in determining a maneuver to avoid a loss of well clear. All these functions are designed with a common interface and configurable implementation, which is critical in exploring DAA requirements. To date, JADEM has been utilized in three computer simulations of the National Airspace System, three pilot-in-the-loop experiments using a total of 37 professional UAS pilots, and two flight tests using NASA's Predator-B unmanned aircraft, named Ikhana. The data collected has directly informed the quantitative separation standard for "well clear", safety case, requirements development, and the operational environment for the DAA minimum operational performance standards. This work was performed by the Separation Assurance/Sense and Avoid Interoperability team under NASA's UAS Integration in the NAS project.

unmanned aircraft systems↗
NASA NTRS2016

Flight Test Overview for UAS Integration in the NAS Project

The National Aeronautics and Space Administration is conducting a series of flight tests intended to support the reduction of barriers that prevent unmanned aircraft from flying without the required waivers from the Federal Aviation Administration. The most recent testing supported two separate test configurations. The first investigated the timing of Detect and Avoid (DAA) alerting thresholds using a radar-equipped unmanned vehicle and multiple live intruders flown at varying encounter geometries. The second configuration included a surrogate unmanned vehicle (flown from a ground control station, with a safety pilot on board) flying a mission in a virtual air traffic control airspace sector using research pilot displays and DAA advisories to maintain separation from live and virtual aircraft. The test was conducted over a seven-week span in the summer of 2015. The data from over 100 encounter sorties will be used to inform the RTCA Phase 1 Detect and Avoid and Command and Control Minimum Operating Performance Standards (MOPS) intended to be completed by the summer of 2016. Follow-on flight-testing is planned for the spring of 2016 to capture remaining encounters and support validation of the MOPS.

UAS↗
NASA NTRS2011

Human Factors Throughout the Life Cycle: Lessons Learned from the Shuttle Program

With the ending of the Space Shuttle Program, it is critical that we not forget the Human Factors lessons we have learned over the years. At every phase of the life cycle, from manufacturing, processing and integrating vehicle and payload, to launch, flight operations, mission control and landing, hundreds of teams have worked together to achieve mission success in one of the most complex, high-risk socio-technical enterprises ever designed. Just as there was great diversity in the types of operations performed at every stage, there was a myriad of human factors that could further complicate these human systems. A single mishap or close call could point to issues at the individual level (perceptual or workload limitations, training, fatigue, human error susceptibilities), the task level (design of tools, procedures and aspects of the workplace), as well as the organizational level (appropriate resources, safety policies, information access and communication channels). While we have often had to learn through human mistakes and technological failures, we have also begun to understand how to design human systems in which individuals can excel, where tasks and procedures are not only safe but efficient, and how organizations can foster a proactive approach to managing risk and supporting human enterprises. Panelists will talk about their experiences as they relate human factors to a particular phase of the shuttle life cycle. They will conclude with a framework for tying together human factors lessons-learned into system-level risk management strategies.

human factors↗
NASA NTRS2014

User Interaction with the CNPC Link

As part of NASAs UAS in the NAS project, human factor guidelines are being developed for the ground control station of unmanned aircraft systems. A critical task for the pilot of a UAS is the management and control of the terrestrial radio links used to provide control of the vehicle and relay communications with air traffic control. An analysis of the task of the UAS pilot has been conducted to identify areas where guidelines are required. This analysis has identified a set of information requirements that must be supported by the radio equipment used to provide Control and Non-payload Communication (CNPC). Key requirements include the need for an alert when the link is lost, information on the current quality and latency of the link, and information to enable the future quality of the link to be anticipated as the aircraft changes location. These identified requirements can assist in the development of minimum operational performance standards for CNPC equipment.

unmanned aerial systems↗
NASA NTRS2015

UAS Integration into the NAS: Detect and Avoid Display Evaluations in Support of SC-228 MOPS Development

This presentation provides an overview of the work the Human Systems Integration (HSI) sub-project has done on detect and avoid (DAA) displays while working on the UAS Integration into the NAS project. Much of the work has been used to support the ongoing development of minimum operational performance standards (MOPS) for UAS by RTCA Special Committee 228. The design and results of three different human-in-the-loop simulations are discussed, with particular emphasis on the role of the UAS pilot in the Self Separation Timeline.

unmanned aircraft systems↗
NASA NTRS2015

Development of Logistics for Building Radiation Storm Shelters and Their Operational Evaluation

Over the past three years NASA has been studying the operational effectiveness and astronaut protection efficacy of numerous radiation protection shelters for use in space exploration activities outside of earth's magnetosphere. The work presented was part of NASA's Advanced Exploration Systems (AES) RadWorks Storm Shelter project. This paper is a summary of the concept development activities of this third year. Fabricated items were integrated into mock up deep space habitat vehicle sections for operational evaluations. Two full scale human-in-loop simulations were designed, fabricated, and implemented through an Institutional Review Board approved solicited participant assessment process. Fabricated items are described, along with usage scenarios of two protection approaches. Existing ISS type logistics along with proposed variations of those logistics were used. Preliminary Discrete Event Simulation (DES) work is noted to be useful in quantifying and documenting operational performance measures for the two primary shelter methods, including some characterization of radiation dose accumulation over a mission timeline. The project also performed correlation analyses between effective radiation dose and the Risk of Exposure Induced Death (REID) to show that concept level work may be able to include such a performance metric in early stages of mission scenario habitat design trade space investigation.

Cerro, Jeffrey A.↗
NASA NTRS2015

DAIDALUS: Detect and Avoid Alerting Logic for Unmanned Systems

This paper presents DAIDALUS (Detect and Avoid Alerting Logic for Unmanned Systems), a reference implementation of a detect and avoid concept intended to support the integration of Unmanned Aircraft Systems into civil airspace. DAIDALUS consists of self-separation and alerting algorithms that provide situational awareness to UAS remote pilots. These algorithms have been formally specified in a mathematical notation and verified for correctness in an interactive theorem prover. The software implementation has been verified against the formal models and validated against multiple stressing cases jointly developed by the US Air Force Research Laboratory, MIT Lincoln Laboratory, and NASA. The DAIDALUS reference implementation is currently under consideration for inclusion in the appendices to the Minimum Operational Performance Standards for Unmanned Aircraft Systems presently being developed by RTCA Special Committee 228.

Munoz, Cesar↗
NASA NTRS2016

ACES M and S: Unmitigated Factorial Encounter Study on DAA/TCAS Interoperability

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements for DAA alerting and guidance systems. This presentation contains the results of two combinatorial encounter analysis studies using NASA's SAA Control fast-time simulation capability for this purpose. In these studies, encounters between two aircraft were simulated one at a time for the full factorial combination of encounter geometries (e.g., encounter angle, CPA offset) and aircraft performance (e.g., ownership and intruder ground speeds and vertical rates). The first study analyzes the relationships (e.g., timeline) between the different alerting-safety regions in the SC-228 MOPS (in order of increasing severity): 1) DAA warning alert, 2) well clear recovery (WCR) guidance, 3) DAA-Collision Avoidance (CA), and 4) TCAS RA. This study will focus primarily on encounter situations in which TCAS RA occurs prior to any of the other alerting-safety boundaries. In particular, this study will investigate whether using vertical distance or vertical distance at closest point of approach (i.e., vertical miss distance or VMD) is more appropriate for the definition of the DAA-CA region. In addition, cases where transitions between different regions skip an intermediate region will be analyzed. The second study in this presentation explores a proposal to use an altitude rate error threshold to determine if vertical maneuvers are acceptable for DAA WCR guidance against non-cooperative intruders. This study incorporates the radar from the Honeywell sensor model and examines a series of pairwise encounters between a non-cooperative intruder and a UAS ownship, with different combinations of intruder states and ownship performance levels. The study uses SAA Control as a simulation platform and pilot model, and Omnibands to provide DWC recovery guidance. Two simulation sets, one that allows vertical DWC recovery guidance and one that does not, are compared to determine if encounters with altitude rate errors above 250 feet-per-minute are more likely to have more severe losses of well clear, as determined by the Loss of Well-Clear Severity metric.

SaaControl↗
NASA NTRS2016

Defining the Collision Avoidance Region for DAA Systems

Unmanned aircraft systems (UAS) will be required to equip with a detect-­‐and-­‐avoid (DAA) system in order to satisfy the federal aviation regulations to maintain well clear of other aircraft, some of which may be equipped with a Traffic Collision Avoidance System (TCAS) to mitigate the possibility of mid-­‐air collisions. As such, the minimum operational performance standards (MOPS) for UAS DAA systems are being designed with TCAS interoperability in mind by a group of industry, government, and academic institutions named RTCA Special Committee-228 (SC-228). This document will discuss the development of the spatial-­‐temporal volume known as the collision avoidance region in which the DAA system is not allowed to provide vertical guidance to maintain or regain DAA well clear that could conflict with resolution advisories (RAs) issued by the intruder aircraft's TCAS system. Three collision avoidance region definition candidates were developed based on the existing TCAS RA and DAA alerting definitions. They were evaluated against each other in terms of their interoperability with TCAS RAs and DAA alerts in an unmitigated factorial encounter analysis of 1.3 million simulated pairs.

collision avoidance region↗
NASA NTRS2016

Safety and Mission Assurance: A NASA Perspective

Manned spaceflight is an incredibly complex and inherently risky human endeavor. As the result of the lessons learned through years of triumph and tragedy, the National Aeronautics and Space Administration (NASA) has embraced a comprehensive and integrated approach to the challenge of ensuring safety and mission success. This presentation will provide an overview of some of the techniques employed in this effort, with a focus on the processing operations performed at the Kennedy Space Center (KSC).

comprehensive↗
NASA NTRS2016

UAS Integration in the NAS Project: Flight Test 3 Data Analysis of JADEM-Autoresolver Detect and Avoid System

The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS Integration in the NAS, aims to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The UAS Integration in the NAS Project conducted a flight test activity, referred to as Flight Test 3 (FT3), involving several Detect-and-Avoid (DAA) research prototype systems between June 15, 2015 and August 12, 2015 at the Armstrong Flight Research Center (AFRC). This report documents the flight testing and analysis results for the NASA Ames-developed JADEM-Autoresolver DAA system, referred to as 'Autoresolver' herein. Four flight test days (June 17, 18, 22, and July 22) were dedicated to Autoresolver testing. The objectives of this test were as follows: 1. Validate CPA prediction accuracy and detect-and-avoid (DAA, formerly known as self-separation) alerting logic in realistic flight conditions. 2. Validate DAA trajectory model including maneuvers. 3. Evaluate TCAS/DAA interoperability. 4. Inform final Minimum Operating Performance Standards (MOPS). Flight test scenarios were designed to collect data to directly address the objectives 1-3. Objective 4, inform final MOPS, was a general objective applicable to the UAS in the NAS project as a whole, of which flight test is a subset. This report presents analysis results completed in support of the UAS in the NAS project FT3 data review conducted on October 20, 2015. Due to time constraints and, to a lesser extent, TCAS data collection issues, objective 3 was not evaluated in this analysis.

flight test↗
NASA NTRS2016

FT4 Data Analysis Summary (SSI-ARC)

Standards for Unmanned Aircraft System (UAS) Detect-and-Avoid (DAA) systems are currently being developed under the auspices of the RTCA Special Committee 228 (SC-228). To support the development of these standards, a series of flight tests has been conducted at NASAs Armstrong Flight Research Center (NASA-AFRC). The fourth in this series of flight test activities (Flight Test 4, or simply FT4) was conducted during the Spring and Summer of 2016. FT4 supported the objectives of numerous organizations working toward UAS DAA Minimum Operational Performance Standards (MOPS) and UAS DAA Radar MOPS. The summary provided herein is limited to the objectives, analysis and conclusions of the NASA Ames Research Center (NASA-ARC) SSI team toward the refinement of UAS DAA MOPS. This document provides a high-level overview of FT4 and the SSI-ARC objectives, a summary of the data analysis methodology and recommendations for UAS DAA MOPS refinements based on the data analysis results. A total of 72 encounters were flown to support SSI-ARC objectives. Test results were generally consistent with acceptable UAS DAA system performance and will be considered in broader SC-228 requirements validation efforts. Observed alert lead times indicated acceptable UAS DAA alerting performance. Effective interoperability between the UAS DAA system and the Traffic Alert and Collision Avoidance System (TCAS) was observed with one notable exception: TCAS Resolutions Advisories (RA) were observed in the absence of any DAA alert on two occasions, indicating the need for alert parameter refinement. Findings further indicated the need for continued work in the areas of DAA Well Clear Recovery logic and alert stability for Mode-C-only intruders. Finally, results demonstrated a high level of compliance with a set of evaluation criteria designed to provide anecdotal evidence of acceptable UAS DAA system performance.

UAS Test Flight↗
NASA NTRS2017

Progress on the Development of the UAS C2 Link and Supporting Spectrum - from LOS to BLOS

In order to provide for the safe integration of unmanned aircraft systems (UAS) into the National Airspace System, the control and non-payload communications (CNPC) link connecting the ground-based pilot with the unmanned aircraft must be highly reliable and robust, based upon standards that enable certification. Both line-of-sight (LOS) links using terrestrial-based communications and beyond-line-of-sight (BLOS) links using satellite communications are required to support UAS operations. The development of standards has been undertaken by RTCA Special Committee 228 (SC-228), with supporting technical data developed by NASA under the UAS in the National Airspace (NAS) Project. As a result of this work minimum operational performance standards (MOPS) have been completed and published for the LOS CNPC system. The second phase of work, for both NASA and RTCA involves the BLOS CNPC systems. The development of technical data to support MOPS development for UAS BLOS satellite-based CNPC links has now been initiated by NASA, and RTCA SC-228 has organized itself to begin the MOPS development process. This paper will provide an overview of the work that has been completed to date by the Communications Subproject in support of LOS C2 communications for UAS followed by an update of plans and progress for the BLOS phase of the project, with the focus on the UAS C2 spectrum aspects.

Pilotless aircraft↗
NASA NTRS2017

UAS Well Clear Recovery Against Non-Cooperative Intruders Using Vertical Maneuvers

This paper documents a study that drove the development of a mathematical expression in the detect-and-avoid (DAA) minimum operational performance standards (MOPS) for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance should be provided during recovery of DAA well clear separation with a non-cooperative VFR aircraft. Although the original hypothesis was that vertical maneuvers for DAA well clear recovery should only be offered when sensor vertical rate errors are small, this paper suggests that UAS climb and descent performance should be considered-in addition to sensor errors for vertical position and vertical rate-when determining whether to offer vertical guidance. A fast-time simulation study involving 108,000 encounters between a UAS and a non-cooperative visual-flight-rules aircraft was conducted. Results are presented showing that, when vertical maneuver guidance for DAA well clear recovery was suppressed, the minimum vertical separation increased by roughly 50 feet (or horizontal separation by 500 to 800 feet). However, the percentage of encounters that had a risk of collision when performing vertical well clear recovery maneuvers was reduced as UAS vertical rate performance increased and sensor vertical rate errors decreased. A class of encounter is identified for which vertical-rate error had a large effect on the efficacy of horizontal maneuvers due to the difficulty of making the correct left/right turn decision: crossing conflict with intruder changing altitude. Overall, these results support logic that would allow vertical maneuvers when UAS vertical performance is sufficient to avoid the intruder, based on the intruder's estimated vertical position and vertical rate, as well as the vertical rate error of the UAS' sensor.

UAS in the NAS↗