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At least 235 records · Page 13

Solder Joint Health Monitoring Testbed System

The density and pin count for Field Programmable Gate Arrays (FPGAs) has been increasing, and has exceeded current methods of solder joint inspection, making early detection of failures more problematic. These failures are a concern for both flight safety and maintenance in commercial aviation. Ridgetop Group, Inc. has developed a method for detecting solder joint failures in real time. The NASA Dryden Flight Research Center is developing a set of boards to test this method in ground environmental and accelerated testing as well as flight test on a Dryden F-15 or F-18 research aircraft. In addition to detecting intermittent and total solder joint failures, environmental data on the boards, such as temperature and vibration, will be collected and time-correlated to aircraft state data. This paper details the technical approach involved in the detection process, and describes the design process and products to date for Dryden s FPGA failure detection boards.

Delaney, Michael M.↗

Evaluation of an Enhanced Bank of Kalman Filters for In-Flight Aircraft Engine Sensor Fault Diagnostics

In this paper, an approach for in-flight fault detection and isolation (FDI) of aircraft engine sensors based on a bank of Kalman filters is developed. This approach utilizes multiple Kalman filters, each of which is designed based on a specific fault hypothesis. When the propulsion system experiences a fault, only one Kalman filter with the correct hypothesis is able to maintain the nominal estimation performance. Based on this knowledge, the isolation of faults is achieved. Since the propulsion system may experience component and actuator faults as well, a sensor FDI system must be robust in terms of avoiding misclassifications of any anomalies. The proposed approach utilizes a bank of (m+1) Kalman filters where m is the number of sensors being monitored. One Kalman filter is used for the detection of component and actuator faults while each of the other m filters detects a fault in a specific sensor. With this setup, the overall robustness of the sensor FDI system to anomalies is enhanced. Moreover, numerous component fault events can be accounted for by the FDI system. The sensor FDI system is applied to a commercial aircraft engine simulation, and its performance is evaluated at multiple power settings at a cruise operating point using various fault scenarios.

Kobayashi, Takahisa↗

Fabrication of Fabry-Perot Interferometer Sensors and Characterization of their Performances for Aircraft Inspection

This work provides the information for fabricating Fabry-Perot Interferometer sensors and their performances. The Fabry-Perot Interferometer sensors developed here will be used for the detection of flaws in aircraft structures. The sequel also contains discussion of the experimental setups for the Ultrasonic technique and the Fabry-Perot Interferometer.

Pendergrass, LeRuth Q.↗

Aircraft to Medicine

This video discusses how the technology of computer modeling can improve the design and durability of artificial joints for human joint replacement surgery. Also, ultrasound, originally used to detect structural flaws in aircraft, can also be used to quickly assess the severity of a burn patient's injuries, thus aiding the healing process.

Source record↗

Detect-and-Avoid Alerting Performance for High-Speed UAS and Non-Cooperative Aircraft

This paper presents a set of experiments designed to assess the viability of using a smaller Detect and Avoid (DAA) volume for large Unmanned Aircraft Systems (UAS) when they are trying to remain well clear of non-cooperative visual flight rules (VFR) aircraft, in compliance with Federal regulations. The current DAA volume was defined for both cooperative and non-cooperative VFR traffic by the work of RTCA Special Committee 228 in 2017, in what is referred to in this paper as the Phase 1 standards. Subsequent work by the committee has been focused on enabling operations by smaller UAS that cannot carry the heavy radars required for the Phase 1 DAA Minimum Operational Performance Standards (MOPS). The work discussed in this paper will explore whether a Phase 1 UAS using a Phase 1 radar can use the reduced non-cooperative DAA alerting volume being studied for smaller, slower Phase 2 UAS without significantly degrading system safety. The study uses UAS models and background traffic from previous Phase 1 and Phase 2 research to run an unmitigated simulation that will examine alerting performance using different DAA well clear definitions. The primary metrics are also tied to the alerting performance of the DAA system, and include average alerting times, probabilities of missed and late alerts, and the probability of a near mid-air collision given a loss of "well clear," as defined by the DAA system. Results are expected to help RTCA make the determination whether or not the DAA well clear definition for Phase 1 UAS can be reduced for non-cooperative VFR aircraft.

Cone, Andrew C.↗

Detect-and-Avoid Alerting Performance for High-Speed UAS and Non-Cooperative Aircraft

This paper presents a set of experiments designed to assess the viability of using a smaller Detect and Avoid (DAA) volume for large Unmanned Aircraft Systems (UAS) when they are trying to remain well clear of non-cooperative visual flight rules (VFR) aircraft, in compliance with Federal regulations. The current DAA volume was defined for both cooperative and non-cooperative VFR traffic by the work of RTCA (Radio Technical Commission for Aeronautics) Special Committee 228 in 2017, in what is referred to in this paper as the Phase 1 standards. Subsequent work by the committee has been focused on enabling operations by smaller UAS that cannot carry the heavy radars required for the Phase 1 DAA Minimum Operational Performance Standards (MOPS). The work discussed in this paper will explore whether a Phase 1 UAS using a Phase 1 radar can use the reduced non-cooperative DAA alerting volume being studied for smaller, slower Phase 2 UAS without significantly degrading system safety. The study uses UAS models and background traffic from previous Phase 1 and Phase 2 research to run an unmitigated simulation that will examine alerting performance using different DAA well clear definitions. The primary metrics are also tied to the alerting performance of the DAA system, and include average alerting times, probabilities of missed and late alerts, and the probability of a near mid-air collision given a loss of "well clear," as defined by the DAA system. Results are expected to help RTCA make the determination whether or not the DAA well clear definition for Phase 1 UAS can be reduced for non-cooperative VFR aircraft.

UAS↗

Detection of the Impact of Ice Crystal Accretion in an Aircraft Engine Compression System During Dynamic Operation

The accretion of ice in the compression system of commercial gas turbine engines operating in high ice water content conditions is a safety issue being studied by the aviation community. While most of the research focuses on the underlying physics of ice accretion and the meteorological conditions in which accretion can occur, a systems-level perspective on the topic lends itself to potential near-term operational improvements. Here a detection algorithm is developed which has the capability to detect the impact of ice accretion in the Low Pressure Compressor of an aircraft engine during steady flight as well as during changes in altitude. Unfortunately, the algorithm as implemented was not able to distinguish throttle changes from ice accretion and thus more work remains to be done.

detection↗

Cooperative Collision Avoidance Step 1 - Technology Demonstration Flight Test Report. Revision 1

The National Aeronautics and Space Administration (NASA) Access 5 Project Office sponsored a cooperative collision avoidance flight demonstration program for unmanned aircraft systems (UAS). This flight test was accomplished between September 21st and September 27th 2005 from the Mojave Airport, Mojave, California. The objective of these flights was to collect data for the Access 5 Cooperative Collision Avoidance (CCA) Work Package simulation effort, i.e., to gather data under select conditions to allow validation of the CCA simulation. Subsequent simulation to be verified were: Demonstrate the ability to detect cooperative traffic and provide situational awareness to the ROA pilot; Demonstrate the ability to track the detected cooperative traffic and provide position information to the ROA pilot; Demonstrate the ability to determine collision potential with detected cooperative traffic and provide notification to the ROA pilot; Demonstrate that the CCA subsystem provides information in sufficient time for the ROA pilot to initiate an evasive maneuver to avoid collision; Demonstrate an evasive maneuver that avoids collision with the threat aircraft; and lastly, Demonstrate the ability to assess the adequacy of the maneuver and determine that the collision potential has been avoided. The Scaled Composites, LLC Proteus Optionally Piloted Vehicle (OPV) was chosen as the test platform. Proteus was manned by two on-board pilots but was also capable of being controlled from an Air Vehicle Control Station (AVCS) located on the ground. For this demonstration, Proteus was equipped with cooperative collision sensors and the required hardware and software to place the data on the downlink. Prior to the flight phase, a detailed set of flight test scenarios were developed to address the flight test objectives. Two cooperative collision avoidance sensors were utilized for detecting aircraft in the evaluation: Traffic Alert and Collision Avoidance System-II (TCAS-II) and Automatic Dependent Surveillance Broadcast (ADS-B). A single intruder aircraft was used during all the flight testing, a NASA Gulfstream III (G-III). During the course of the testing, six geometrically different near-collision scenarios were evaluated. These six scenarios were each tested using various combinations of sensors and collision avoidance software. Of the 54 planned test points 49 were accomplished successfully. Proteus flew a total of 21.5 hours during the testing and the G-III flew 19.8 hours. The testing fully achieved all flight test objectives. The Flight IPT performed an analysis to determine the accuracy of the simulation model used to predict the location of the host aircraft downstream during an avoidance maneuver. The data collected by this flight program was delivered to the Access 5 Cooperative Collision Avoidance (CCA) Work Package Team who was responsible for reporting on their analysis of this flight data.

Trongale, Nicholas A.↗

Analysis of Aircraft Clusters to Measure Sector-Independent Airspace Congestion

The Distributed Air/Ground Traffic Management (DAG-TM) concept of operations* permits appropriately equipped aircraft to conduct Free Maneuvering operations. These independent aircraft have the freedom to optimize their trajectories in real time according to user preferences; however, they also take on the responsibility to separate themselves from other aircraft while conforming to any local Traffic Flow Management (TFM) constraints imposed by the air traffic service provider (ATSP). Examples of local-TFM constraints include temporal constraints such as a required time of arrival (RTA), as well as spatial constraints such as regions of convective weather, special use airspace, and congested airspace. Under current operations, congested airspace typically refers to a sector(s) that cannot accept additional aircraft due to controller workload limitations; hence Dynamic Density (a metric that is indicative of controller workload) can be used to quantify airspace congestion. However, for Free Maneuvering operations under DAG-TM, an additional metric is needed to quantify the airspace congestion problem from the perspective of independent aircraft. Such a metric would enable the ATSP to prevent independent aircraft from entering any local areas of congestion in which the flight deck based systems and procedures may not be able to ensure separation. This new metric, called Gaggle Density, offers the ATSP a mode of control to regulate normal operations and to ensure safety and stability during rare-normal or off-normal situations (e.g., system failures). It may be difficult to certify Free Maneuvering systems for unrestricted operations, but it may be easier to certify systems and procedures for specified levels of Gaggle Density that could be monitored by the ATSP, and maintained through relatively minor flow-rate (RTA type) restrictions. Since flight deck based separation assurance is airspace independent, the challenge is to measure congestion independent of sector boundaries. Figure 1 , reproduced from Ref. 1, depicts an example traffic situation. When the situation is analyzed by sector boundaries (left side of figure), a Dynamic Density metric would identify excessive congestion in the central sector. When the same traffic situation is analyzed independent of sector boundaries (right side of figure), a Gaggle Density metric would identify congestion in two dynamically defined areas covering portions of several sectors. The first step towards measuring airspace-independent congestion is to identify aircraft clusters, i.e., groups of closely spaced aircraft. The objective of this work is to develop techniques to detect and classify clusters of aircraft.

Bilimoria, Karl D.↗

Detection of the Impact of Ice Crystal Accretion in an Aircraft Engine Compression System During Dynamic Operation

The accretion of ice in the compression system of commercial gas turbine engines operating in high ice water content conditions is a safety issue being studied by the aviation community. While most of the research focuses on the underlying physics of ice accretion and the meteorological conditions in which accretion can occur, a systems-level perspective on the topic lends itself to potential near-term operational improvements. Here a detection algorithm is developed which has the capability to detect the impact of ice accretion in the Low Pressure Compressor of an aircraft engine during steady flight as well as during changes in altitude. Unfortunately, the algorithm as implemented was not able to distinguish throttle changes from ice accretion and thus more work remains to be done.

high ice water content↗

High-Energy Radiation from Thunderstorms with ADELE: TGFs, Steps, and Glows

The biggest challenge in the study of high-energy processes in thunderstorms is getting a detector to the vicinity of the electrically active regions of a storm. The Airborne Detector for Energetic Lightning Emissions (ADELE) has been used to detect gamma rays from aircraft above storms and from a storm-chasing van on the ground. In August 2009, ADELE flew above Florida storms in a Gulfstream V jet, detecting the first terrestrial gamma-ray flash (TGF) seen from a plane and continuous glows of high-energy emission above thunderclouds. The presence of these glows suggests that a gradual process of relativistic runaway and feedback may help limit the total amount of charging in thunderstorms, in contrast to the traditional view that only lightning discharges compete with the charging process. The upper limits on TGF emission from intracloud and cloud-to-ground lightning from the ADELE flights demonstrated conclusively that a TGF of the sort seen from space is not associated with most lightning and not necessary to trigger it. In August 2010, observations from a van detected stepped-leader x-ray emission from at least four lightning strikes in ten days of operations. This mode of operation is therefore promising for future observations of the stepping process, although a more varied suite of instrumentation, in particular a flash-distance detector, would be useful. We will report on these results and on future possibilities for ADELE campaigns.

Smith, David M.↗

Validation of Minimum Display Requirements for a UAS Detect and Avoid System

The full integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS), a prerequisite for enabling a broad range of public and commercial UAS operations, presents several technical challenges to UAS developers, operators and regulators. A primary barrier is the inability for UAS pilots (situated at a ground control station, or GCS) to comply with Title 14 Code of Federal Regulations sections 91.111 and 91.113, which require pilots to “see and avoid” other aircraft in order to maintain well clear. UAS pilots’ removal from the flight deck of the aircraft necessitates the development of a UAS-specific system for detecting nearby traffic and displaying traffic information to the pilot to support their ability to maintain an objectively defined “DAA well clear” threshold from other aircraft. This new UAS-specific function of remaining DAA well clear is called traffic avoidance. The resulting Detect and Avoid (DAA) system, however, will be subject to a collection of requirements that manufacturers will be obligated to meet in order to certify their equipment. RTCA Special Committee 228 (SC-228), a consortium of representatives from government, industry and academia, is responsible for developing and documenting the Minimum Operational Performance Standards (MOPS) for UAS DAA systems. The present study is the final in a series of human-in-the-loop (HITL) experiments designed to explore and test the various display and alerting requirements being incorporated into the DAA MOPS. Whereas the prior DAA HITLs examined a wide variety of DAA display features and concepts, the current experiment aims to validate the latest minimum display requirements for Phase 1 of the DAA MOPS. Rather than test different display concepts, this study tests two configurations of a MOPS-compatible DAA display: a version that is integrated into the primary navigation and control display of the GCS and a version that is physically separated from the primary display. This manipulation tests the draft minimum requirement that allows the DAA traffic display to be a separate, or standalone, configuration. This type of configuration is a more achievable near-term technology solution since it does not stipulate additional certification or integration requirements on UAS manufacturers. However, a standalone display configuration has the potential to result in pilot performance issues resulting from the cognitive costs of switching between the primary DAA display and the primary navigation and control display. This configuration is also particularly susceptible to errors if the displays are in different orientations (e.g., north-up versus track-up). Both the integrated and standalone display configurations were presented to 16 active UAS pilots in a medium-fidelity simulation, which included confederate air traffic controllers and pseudo pilots operating simulated manned traffic. Pilots were tasked with navigating two different mission routes while maintaining DAA well clear with scripted conflicts. Pilot response times (i.e., measured response) and ability to remain DAA well clear are reported. Primary results indicate that both display configurations resulted in favorable response times and well clear rates. While there were clear trends of pilots objectively performing better in the integrated display condition, with several measured response metrics reaching statistical significance, the differences between the two displays were typically moderate. While the primary variable of DAA display location did not have an especially large impact on pilot performance on its own, when examined alongside the type of DAA threat the pilot was facing (a caution-level versus a warning-level alert), the response time benefits associated with the integrated display were amplified. The implications of these American Institute of Aeronautics and Astronautics 2 results on the Phase 1 DAA MOPS and the connection of this data to previous studies is also discussed.

detect and avoid↗

Data Optical Networking Architecture Using Wavelength-Division Multiplexing Method for Optical Sensors

Recently there has been a growth in the number of fiber optical sensors used for health monitoring in the hostile environment of commercial aircraft. Health monitoring to detect the onset of failure in structural systems from such causes as corrosion, stress corrosion cracking, and fatigue is a critical factor in safety as well in aircraft maintenance costs. This report presents an assessment of an analysis model of optical data networking architectures used for monitoring data signals among these optical sensors. Our model is focused on the design concept of the wavelength-division multiplexing (WDM) method since most of the optical sensors deployed in the aircraft for health monitoring typically operate in a wide spectrum of optical wavelengths from 710 to 1550 nm.

Nguyen, Hung D.↗

Performance and sensitivity analysis of the generalized likelihood ratio method for failure detection

Results of the generalized likelihood ratio (GLR) technique for the detection of failures in aircraft application are presented, and its relationship to the properties of the Kalman-Bucy filter is examined. Under the assumption that the system is perfectly modeled, the detectability and distinguishability of four failure types are investigated by means of analysis and simulations. Detection of failures is found satisfactory, but problems in identifying correctly the mode of a failure may arise. These issues are closely examined as well as the sensitivity of GLR to modeling errors. The advantages and disadvantages of this technique are discussed, and various modifications are suggested to reduce its limitations in performance and computational complexity.

Bueno, R. A.↗

Airborne Radar for sUAS Sense and Avoid

A primary challenge for the safe integration of small UAS operations into the National Airspace System (NAS) is traffic deconfliction, both from manned and unmanned aircraft. The UAS Traffic Management (UTM) project being conducted at the National Aeronautics and Space Administration (NASA) considers a layered approach to separation provision, ranging from segregation of operations through airspace volumes (geofences) to autonomous sense and avoid (SAA) technologies for higher risk, densely occupied airspace. Cooperative SAA systems, such as Automatic Dependent Surveillance-Broadcast (ADS-B) and/or vehicle-to-vehicle communication systems provide significant additional risk mitigation but they fail to adequately mitigate collision risks for non-cooperative (non-transponder equipped) airborne aircraft. The RAAVIN (Radar on Autonomous Aircraft to Verify ICAROUS Navigation) flight test being conducted by NASA and the Mid-Atlantic Aviation Partnership (MAAP) was designed to investigate the applicability and performance of a prototype, commercially available sUAS radar to detect and track non-cooperative airborne traffic, both manned and unmanned. The radar selected for this research was a Frequency Modulated Continuous Wave (FMCW) radar with 120 degree azimuth and 80 degree elevation field of view operating at 24.55GHz center frequency with a 200 MHz bandwidth. The radar transmits 2 watts of power thru a Metamaterial Electronically Scanning Array antenna in horizontal polarization. When the radar is transmitting, personnel must be at least 1 meter away from the active array to limit nonionizing radiation exposure. The radar physical dimensions are 18.7cm by 12.1cm by 4.1cm and it weighs less than 820 grams making it well suited for installation on small UASs. The onboard, SAA capability, known as ICAROUS, (Independent Configurable Architecture for Reliable Operations of Unmanned Systems), developed by NASA to support sUAS operations, will provide autonomous guidance using the traffic radar tracks from the onboard radar. The RAAVIN set of studies will be conducted in three phases. The first phase included outdoor, ground-based radar evaluations performed at the Virginia Tech’s Kentland Farm testing range in Blacksburg, VA. The test was designed to measure how well the radar could detect and track a small UAS flying in the radar’s field of view. The radar was used to monitor 5 test flights consisting of outbound, inbound and crossing routes at different ranges and altitudes. The UAS flown during the ground test was the Inspire 2, a quad copter weighing less than 4250 grams (10 pounds) at maximum payload. The radar was set up to scan and track targets over its full azimuthal field of view from 0 to 40 degrees in elevation. The radar was configured to eliminate tracks generated from any targets located beyond 2000 meters from the radar and moving at velocities under 1.45 meters per second. For subsequent phases of the study the radar will be integrated with a sUAS platform to evaluate its performance in flight for SAA applications ranging from sUAS to manned GA aircraft detections and tracking. Preliminary data analysis from the first outdoor ground tests showed the radar performed well at tracking the vehicle as it flew outbound and repeatedly maintained a track out to 1000 meters (maximum 1387 meters) until the vehicle slowed to a stop to reverse direction to fly inbound. As the Inspire flew inbound tracks from beyond 800 meters, a reacquisition time delay was consistently observed between when the Inspire exceeds a speed of 1.45 meters per second and when the radar indicated an inbound target was present and maintained its track. The time delay varied between 6 seconds to over 37 seconds for the inbound flights examined, and typically resulted in about a 200 meter closure distance before the Inspire track was maintained. The radar performed well at both acquiring and tracking the vehicle as it flew crossing routes out past 400 meters across the azimuthal field of view. The radar and ICAROUS software will be integrated and flown on a BFD-1400-SE8-E UAS during the next phase of the RAAVIN project. The main goal at the conclusion of this effort is to determine if this radar technology can reliably support minimum requirements for SAA applications of sUAS. In particular, the study will measure the range of vehicle detections, lateral and vertical angular errors, false and missed/late detections, and estimated distance at closest point of approach after an avoidance maneuver is executed. This last metric is directly impacted by sensor performance and indicates its suitability for the task.

Szatkowski, George N.↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project

Phase 1 of the UAS-NAS (Unmanned Aircraft Systems-National Airspace System) project focused on MOPS (Minimum Operational Performance Standards) development for large UAS transitioning through Class D, E, and G airspace. Phase 2 activities are currently focused on extended UAS operations in Class D, E, and G airspace, as well as sensors and architectures that will enable DAA (Detect and Avoid) equipment to be installed on a wider range of UAS. Encounters with non-cooperative intruders in low altitude airspace under 10,000 feet will be explored for UAS with a low Size, Weight, and Power (SWaP) radar. New sensors for detecting non-cooperative intruder aircraft will have a more limited detection range and field of regard; therefore, the analysis of non-cooperative encounter geometries may help in developing the requirements for an onboard low SWaP radar (and electro-optical sensor). The current simulation, led by HSI (Human Systems Integration Division at NASA Ames Research Center) as part of the DAA subproject, will support efforts toward developing a modified DAA Well Clear (DWC) definition that would be more appropriate for UAS equipped with limited surveillance and aircraft performance capabilities compared to the Phase 1 DAA system. The findings will inform Phase 2 display requirements for alternative surveillance use cases.

Collision Avoidance↗

The Use of Meteorlogical Data to Improve Contrail Detection in Thermal Imagery over Ireland.

Aircraft induced contrails have been found to have a net warming influence on the climate system, with strong regional dependence. Persistent linear contrails are detectable in 1 Km thermal imagery and, using an automated Contrail Detection Algorithm (CDA), can be identified on the basis of their different properties at the 11 and 12 m w av.el enTgthshe algorithm s ability to distinguish contrails from other linear features depends on the sensitivity of its tuning parameters. In order to keep the number of false identifications low, the algorithm imposes strict limits on contrail size, linearity and intensity. This paper investigates whether including additional information (i.e. meteorological data) within the CDA may allow for these criteria to be less rigorous, thus increasing the contrail-detection rate, without increasing the false alarm rate.

Whelan, Gillian M.↗