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At least 793 records · Page 44

Tactical Separation and Safety Alerting System for Terminal Airspace

Provision of tactical alerts to aid air traffic controllers in providing separation assurance in terminal airspace is hindered by the complexity of the airspace, its operations, and flight procedures. A prototype automation system is studied that provides controllers with both separation and safety alerts based on or derived from the separation standard for terminal airspace. The system models flight trajectories heuristically, with use of merged intent information from readily available sources: area navigation departure procedures, flight-plan routes, and arrival nominal interior routes used in terminal automation systems. Flight vertical intent is modeled according to standard procedural restrictions except when superseded by controller-issued altitude clearances. Importantly, flight trajectories are modeled for all aircraft, including those conducting visual approaches. New safety-alert thresholds for aircraft conducting visual approaches are studied. Performance of the system is evaluated through fast-time playback of recorded air traffic data from high-fidelity Human-In-The-Loop simulations and real-world operations in two Terminal Radar Approach Control facilities. The prototype system is found to produce a false-alert rate of 8% for separation alerts. The number and validity of safety alerts are studied by comparing with the current Conflict Alert system, showing that the false alerts of Conflict Alert are at 85% and they are avoided in the prototype system.

Air Traffic Management↗

A Mathematical Analysis of an Example Delay Tolerant Network using the Theory of Sheaves

NASA’s High-Data Rate Architecture (HiDRA) project is working towards a general yet practical toolkit and knowledge base to help usher in the era of new technologies for space systems communications, such as optical links. The High-Rate Delay Tolerant Networking (HDTN) implementation falls under the umbrellas of both the toolkit and the knowledge base, as its advancements illuminate more general areas of Delay Tolerant Networking (DTN) that need growth. The goal of this paper is to explore the usage of particular mathematical machineries, namely temporal flow networks and sheaves, to identify fundamental, underlying structures in DTN for space systems. Satellites, space assets, ground stations, etc. give rise to a disconnected network, and it is the goal of DTN to glue disparate links together into a cohesive system, that is, a network. Depending on a given link, the latencies might be beyond that which the Transmission Control Protocol (TCP) can handle, and contact times might have one-way light times in excess of minute (sometimes significantly longer). Some links might be periodic (say, due to orbital mechanics) or they might not be. This diversity has made it difficult to probe the underlying structure. An immediate consequence is that DTNs in practice today are controlled by globally distributed contact plans (schedules), which are the input to the contact graph routing (CGR) algorithm. While this is effective for smaller networks, it will be very difficult to scale for future networks. Deeper and more rigorous theory is needed to bring DTN to the next evolutionary step. To this end, this paper introduces and suggests a mathematical framework for DTN, and applies it to a space network that is simulated using an orbital analysis toolkit. The tag-line for the structure known as sheaves is that they are the mathematically precise way of gluing local data together into unique, global data. If we consider routing, we see that networking is a “sheafy” science. We then discuss a simplified sheaf model, known as the cellular sheaf. The sheaf-theoretic analysis is presented and discussed, as it is hoped that this and related papers will help form the primordial ooze of DTN theory. Finally there is a section of future work suggesting follow-on research.

Delay Tolerant Networking↗

Low-Temperature Formation of Carbonaceous Grains from PAHs

Astronomical observations have detected interstellar carbon in the form of polycyclic aromatic hydrocarbons(PAHs) as well as carbonaceous dust, confirming its presence in both gaseous and solid phases. The goal of this study is to experimentally investigate low-temperature chemical pathways between these two phases in order to better understand the evolution of cosmic carbon. Cosmic dust analogs are produced in the supersonic expansion of an argon jet seeded with aromatic molecules: benzene, naphthalene, anthracene, phenanthrene, and pyrene. These are prototype aromatic molecules of compact and non compact structure, and are used to evaluate the effect of precursor structure on the molecular complexity of the resulting grains. The seeded jet is exposed to an electrical discharge and the carbonaceous grains are collected and probed ex situ via laser desorption mass spectrometry. Mass spectra reveal a rich molecular diversity within the grains, including fragments of the parent molecule but also growth into larger complex organic molecules (COMs). In all experiments, the largest number of products is found in the m/z range 200-250, and C16H10 (attributed to pyrene and/or its isomers) is found to be a dominant product, pointing at the formation of this stable PAH as a preferential route in the growth to larger PAHs. Comparison to mass spectra from the Murchison meteorite reveals a similar dominance of compounds related toC16H10 at m/z = 202. Evidence of the methyl addition-cyclization mechanism in the anthracene experiment is reported. PAH structure is found to impact the dust production yield, as seen by the greater yield for the anthracene compared to the phenanthrene experiment. PAH growth at low temperatures via barrierless routes involving the addition of alkyl- and phenyl-type radicals is suggested as a viable pathway to COMs. These results suggest that PAH growth and dust formation from PAHs are feasible at low temperatures in photon-dominated regions and circumstellar envelopes.

L Gavilan↗

Implementation of (O-)CGR in The ONE

Routing in Delay-/Disruption-Tolerant Networking (DTN) requires specific solutions as link impairments prevent the use of ordinary Internet algorithms, based on a timely dissemination of network topology information. Among DTN routing algorithms there is a dichotomy between opportunistic and deterministic (scheduled) solutions. The former are numerous and apply to terrestrial environments; CGR is the most widely supported algorithm designed for scheduled connectivity, and it is usually applied to space networks. However, in an attempt to provide a unified approach, an opportunistic variant of CGR, Opportunistic CGR (OCGR) has been recently proposed by some of the authors. Performance evaluations are normally carried out for opportunistic solutions by means of simulators, such as The ONE considered in this paper. CGR by contrast is more often studied by means of small testbeds. As the simulation approach could be complementary for CGR, and essential for OCGR, the authors have recently ported both of them into The ONE, by developing and releasing as free software a specific additional package. The aim of this paper is to show the rationale of this choice and discuss the many challenges that needed to be tackled to achieve this primary goal.

Tempesta, G.↗

Applying the Cognitive Space Gateway to Swarm Topologies

NASA's future vision for interplanetary networking includes a lunar network, Cube Satellite (CubeSat) constellations, and deep space robotic missions, comprising what could be viewed as a network of networks. Delay-tolerant networking (DTN) architecture and protocols provide a standard network layer among these varying scenarios and mitigate many challenges of the space environment, such as long delays, unplanned service interruptions, and asymmetric links. The Cognitive Space Gateway (CSG) is a routing method in a DTN architecture that uses spiking neural networks as the learning element to optimize routing decisions in a complex environment. This work aims to further develop cognitive networking technologies in several critical areas, including DTN, the CSG algorithm, CubeSat swarm topologies, and cloud services. To test the algorithm in a realistic scenario, the emulated network topology is based on a CubeSat swarm. The swarm may function as a mesh of nodes or as a hub-and-spoke network. An emulation environment will be built upon a commercial cloud service, such as Amazon Web Services (AWS) Elastic Compute Cloud. The cloud environment may enable a flexible, lower maintenance approach versus a multi-hop network based in a physical laboratory. The cloud platform will provide a secure environment allowing for collaboration among government and academic entities.

Ricardo Lent↗

Sleep Obtained by Cabin Crewmembers during a Long-haul Flight

Sleep loss and circadian disruption pose a significant risk in safety-sensitive occupations. In aviation, many studies have demonstrated how inflight rest locations influence alertness and performance among pilots, but few studies have evaluated cabin crew. The purpose of the present study was to evaluate sleep outcomes among cabin crewmembers sleeping in a bunk compared to a jump seat during one long-haul route. Thirty-one (6 male) cabin crewmembers (age M = 30, SD = +/-13) flew the same long-haul route (outbound and return) with a flight duration of 10:41 (± 0:14) hours. Participants were randomly assigned to fly on an aircraft with a bunk or a jump seat for their sleep opportunity. Participants wore an Actiwatch (Phillips-Respironics Spectrum) throughout the entire study and completed a sleep diary at bedtime and upon waking. During flight they completed a nap diary entering the start time of the inflight sleep (if any) and the duration. Sixty-five flights (32 outbound and 33 return) were included in the analyses. Seventy-seven percent of the flights had a bunk and 23% had a jump seat. Crewmembers obtained M = 146.46 (± 67.20) minutes of rest out of which they slept M = 125.33 (± 64.91) minutes in the bunk. While using the jump seat, crewmembers obtained M = 169.53 (± 133.30) minutes of rest out of which they slept M = 142.92 (± 149.72) minutes. When crewmembers slept in the bunk, sleep latency was shorter (M = 13.69 ± 12.64 minutes) and efficiency was better (M = 76.16 ± 16.09 %) compared to the jump seat (sleep onset: M = 16.77 ± 13.89 minutes; sleep efficiency: M = 60.64 ± 17.42 %). We found that cabin crewmembers slept for longer time when they used the jump seat. They fell asleep faster and their sleep efficiency was better when using the bunk compared to the jump seat. Further research is needed to understand how sleep quality and subsequent performance are influenced by sleep opportunity in a bunk compared to a jump seat.

cabin crew↗

Sleep Obtained by Cabin Crewmembers during a Long-haul Flight

Sleep loss and circadian disruption pose a significant risk in safety-sensitive occupations. In aviation, many studies have demonstrated how inflight rest locations influence alertness and performance among pilots, but few studies have evaluated cabin crew. The purpose of the present study was to evaluate sleep outcomes among cabin crewmembers sleeping in a bunk compared to a jump seat during one long-haul route. Thirty-one (6 male) cabin crewmembers (age M = 30, SD = +/-13) flew the same long-haul route (outbound and return) with a flight duration of 10:41 (± 0:14) hours. Participants were randomly assigned to fly on an aircraft with a bunk or a jump seat for their sleep opportunity. Participants wore an Actiwatch (Phillips-Respironics Spectrum) throughout the entire study and completed a sleep diary at bedtime and upon waking. During flight they completed a nap diary entering the start time of the inflight sleep (if any) and the duration. Sixty-five flights (32 outbound and 33 return) were included in the analyses. Seventy-seven percent of the flights had a bunk and 23% had a jump seat. Crewmembers obtained M = 146.46 (± 67.20) minutes of rest out of which they slept M = 125.33 (± 64.91) minutes in the bunk. While using the jump seat, crewmembers obtained M = 169.53 (± 133.30) minutes of rest out of which they slept M = 142.92 (± 149.72) minutes. When crewmembers slept in the bunk, sleep latency was shorter (M = 13.69 ± 12.64 minutes) and efficiency was better (M = 76.16 ± 16.09 %) compared to the jump seat (sleep onset: M = 16.77 ± 13.89 minutes; sleep efficiency: M = 60.64 ± 17.42 %). We found that cabin crewmembers slept for longer time when they used the jump seat. They fell asleep faster and their sleep efficiency was better when using the bunk compared to the jump seat. Further research is needed to understand how sleep quality and subsequent performance are influenced by sleep opportunity in a bunk compared to a jump seat.

cabin crewmembers↗

Noise Exposure Maps of Urban Air Mobility

A noise exposure map is “a scaled geographic depiction of an airport, its noise exposure contours, noise-sensitive facilities, and land uses in the airport surrounding area” developed in accordance with the FAA’s 14 Code of Federal Regulation Part 150. This paper is the first to explore the applicability of airport noise exposure maps to Urban Air Mobility (UAM). The FAA’s airport noise compatibility planning program is first described. Then the applicability of the noise exposure map to Urban Air Mobility (UAM) is explored. Finally, new airspace infrastructure, including vertiport locations and UAM routes from NASA’s UAM engineering simulations, and local noise-sensitive facility locations and land use information were collected and processed to develop the noise exposure maps of UAM near the Dallas-Fort Worth area. The DNL noise contours resulting from a six-passenger electric quadrotor prototype vehicle are predicted using NASA’s AIRNOISEUAM software. The noise exposure maps of UAM are generated automatically using Python’s data analysis and visualization libraries. The results have applications for UAM’s noise compatibility planning, noise-reducing route planning, and vertiport location selection

Urban Air Mobility↗

Flight Demonstration of the Tailored Arrival Manager

A flight demonstration of arrival traffic management automation was conducted in partnership between NASA, FAA and Boeing as an element of the latter’s ecoDemonstrator2020 flight program. For the demonstration, NASA’s prototype Tailored Arrival Manager(TAM) was used to compute efficient trajectory-based solutions to traffic management problems representing those encountered during time-based metering operations today. TAM solutions involving route modifications were uplinked to a Boeing 787 airplane using Controller Pilot Data Link Communications and seamlessly loaded into the airplane’s Flight Management System (FMS). The paper describes the concept and technology behind TAM along with the data exchanges and procedures involved with the demonstration. All TAM solutions were delivered in a timely manner and successfully integrated with the airplane’s FMS, thereby demonstrating the basic feasibility of trajectory-based arrival management using currently available data communications and avionics equipage. Although TAM solutions were not executed during this initial demonstration, a limited study of trajectory prediction accuracy was possible given that the airplane flew uninterrupted, automated descents with known route and speed intent. Analysis revealed that TAM meter-fix arrival time predictions were accurate to within ± 30 seconds for time horizons of 30 minutes or less, which matched closely with FMS predictions acquired through real-time data exchange. Top-of-descent predictions over similar time horizons were found accurate to within ± 5 nautical miles.

air traffic management↗

Flight Demonstration of the Tailored Arrival Manager

A flight demonstration of arrival traffic management automation was conducted in partnership between NASA, FAA and Boeing as an element of the latter’s ecoDemonstrator2020 flight program. For the demonstration, NASA’s prototype Tailored Arrival Manager(TAM) was used to compute efficient trajectory-based solutions to traffic management problems representing those encountered during time-based metering operations today. TAM solutions involving route modifications were uplinked to a Boeing 787 airplane using Controller Pilot Data Link Communications and seamlessly loaded into the airplane’s Flight Management System (FMS). The paper describes the concept and technology behind TAM along with the data exchanges and procedures involved with the demonstration. All TAM solutions were delivered in a timely manner and successfully integrated with the airplane’s FMS, thereby demonstrating the basic feasibility of trajectory-based arrival management using currently available data communications and avionics equipage. Although TAM solutions were not executed during this initial demonstration, a limited study of trajectory prediction accuracy was possible given that the airplane flew uninterrupted, automated descents with known route and speed intent. Analysis revealed that TAM meter-fix arrival time predictions were accurate to within ± 30 seconds for time horizons of 30 minutes or less, which matched closely with FMS predictions acquired through real-time data exchange. Top-of-descent predictions over similar time horizons were found accurate to within ± 5 nautical miles.

Air traffic managment↗

Noise Exposure Map of Urban Air Mobility

A noise exposure map is “a scaled geographic depiction of an airport, its noise exposure contours, noise-sensitive facilities, and land uses in the airport surrounding area” developed in accordance with the FAA’s 14 Code of Federal Regulation Part 150. This paper is the first to explore the applicability of airport noise exposure maps to Urban Air Mobility (UAM). The FAA’s airport noise compatibility planning program is first described. Then the applicability of the noise exposure map to Urban Air Mobility (UAM) is explored. Finally, new airspace infrastructure, including vertiport locations and UAM routes from NASA’s UAM engineering simulations, and local noise-sensitive facility locations and land use information were collected and processed to develop the noise exposure maps of UAM near the Dallas-Fort Worth area. The DNL noise contours resulting from a six-passenger electric quadrotor prototype vehicle are predicted using NASA’s AIRNOISEUAM software. The noise exposure maps of UAM are generated automatically using Python’s data analysis and visualization libraries. The results have applications for UAM’s noise compatibility planning, noise-reducing route planning, and vertiport location selection. (To hear the voice please utilize the video uploaded to the record)

Urban Air Mobility↗

Alleviating Bundle Throughput Constriction for Delay Tolerance Networking (DTN) Bundles with Software-Defined Networking (SDN)

A load-balancing technique is proposed, executed, and tested against a Delay Tolerant Network (DTN) implementation with well-known characteristics. This would prove that transparently inserting software defined networking (SDN) to achieve load balancing without re-configuring the DTN portion is possible. Two routes were taken to alleviate a DTN bottleneck threat. The first used a P4 networking switch. This manual load-balancing test will balance the incoming packets without the users at the end-points knowing that its original packet destination and/or source may have been changed. The second route utilized a High-rate Delay Tolerant Networking (HDTN) receiving node instead of the typical the delay tolerance networking (DTN) implementation used. Bench-marking results of the DTN implementation receiving node and the HDTN receiving node will be compared.

Delay Tolerant Networking (DTN)↗

Infrared Imaging using Sparse Microresonator Arrays and Compressed Sensing

In this work, we present an uncooled infrared (IR) thermal imager featuring a sparse array of resonant pixels that can be monolithically integrated with the readout electronics for long-term operation in high-temperature environments. Each of the detector pixels is made of an IR-sensitive GaN microresonator developed to be operated at up to 500 0C. The pixels are employed in sparse array configuration to allow for routing the signal carrying traces and to ease the routing from pixel to circuit, as well as to reduce the power consumption at the expense of moderate post-processing time and increased complexity to recover the image. Three 128 by 128 sparse resonator arrays with the array densities of 10%, 25% and 37.5% are designed, and used in conjunction with the Compressed Sensing (CS) method to reconstruct complex test images from highly incomplete data. Capabilities and performance metrics of the recovery technique are explored.

Rais-Zadeh, Mina↗

Thermal Infrared Detector Sparse Array for NASA Planetary Applications

In this work, we present an uncooled infrared (IR) thermal imager featuring a sparse array of resonant pixels that can be monolithically integrated with the readout electronics for long-term operation in hightemperature environments. Each of the detector pixels is made of an IR-sensitive GaN microresonator developed to be operated at up to 500 0C. The pixels are employed in sparse array configuration to allow for routing the signal carrying traces and to ease the routing from pixel to circuit, as well as to reduce the power consumption. A 128´128 sparse resonator array with the array density of 37.5% is designed and used in conjunction with the Compressed Sensing method to reconstruct complex test images from highly incomplete data. Capabilities and performance metrics of the recovery technique are explored.

Rais-Zadeh, Mina↗

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗

Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

he NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Hydrologic modeling↗

Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

The NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Timothy M. Lahmers↗

Error Sources and Mitigation Strategies for Thermocouples Integrated in Flexible Thermal Protection System Materials

Brief Presenter Biography:Ruth Miller is an aer-ospace systems engineer in the Entry Systems and Ve-hicle Development Branch at NASA Ames Research Center.Introduction:The flexible thermal protection sys-tem (FTPS) on NASA’s Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) vehicle will be in-strumented with thermocouples (TCs) to measure the in-depth thermal response during entry into Earth’s atmos-phere[1, 2]. Accurate flight temperature measurements are critical for verifying vehicle performance during the flight test and reducing uncertainties in the thermal models.However,the deployable nature of inflatable decelerator technology presents challengesfor integrat-ing TCs, specifically the TCsneed to be compactableand cannot damage the FTPSnor the inflatable structure(IS).Unlike traditional rigid aeroshells, routing TCsthrough the thickness of the FTPS could cause signifi-cant damage during packing of the deployable aeroshellbecause the different layers may shift small amounts in relation to each other imparting strain on the TCsand FTPS materials. The LOFTID TCleads are routed from the measurement location back to the data acquisition system in the vehicle centerbody within the same FTPS layer that they are monitoring the temperature. This ap-proach eliminates the need to put holes in the FTPS lay-ers,butas a consequence,the insulated TCleads travel for an appreciable distance through a region that will expose them to high temperaturesand large thermal gra-dients.LOFTID’s TCswere baselined to be commercially available Type K TCswith a binder impregnated glass braid insulation. These TCswere chosen because they had been used successfully on IRVE-3 and in ground-based arc jet testing. Additionally, these TCsdid notdamage the FTPS nor IS during packing and deploy-ment testing. However, the glass braid insulation is only rated to a maximum continuous use temperature of 482ºC. For reference, the duration of the heat pulse on the LOFTID vehicle is on the order of minutes and themaximum predicted temperaturebeneaththe outermost FTPS layersis 1350ºC.Ground-based testing in a tube furnace at NASA Ames Research Centerwas conducted to determine if the baseline TCsrouted through FTPS samples would survive and provide accurate temperature measure-mentsat LOFTID flight-relevant temperatures[3].The test results showed large measurement errors occurred beginning at approximately 400°C due to conductive deposits on the TCinsulation electrically shorting the TCleads.The conductive deposits and thus electrical shorting weredetermined to be caused by twoerror sources:1.The organic binder on the TCinsulation carbon-izingin a high temperature, low oxygen envi-ronment2.Decomposition products from the FTPSperme-atingthe braided TC insulationFurther testing in the tube furnace demonstrated that heat cleaning the TCinsulation effectivelyremovedthe organic binder andeliminatedthe first error source.The second error sourcewas shown to be mitigated by the addition of amica wraparound each individual TCleadtoact as an impermeable barrier.To understand the applicability of theground-based tube furnace test results to flight,anarc jet testseriesat Boeing’s Large Core Arc Tunnel (LCAT) facilitywas conducted[4].The error sourcesand mitigation strate-giesidentified in the tube furnace testing were substan-tiatedin the arc jet testing.However, the arc jet testing also revealed three new error sources:1.Glass TCinsulation meltingwhich resultsin electrical shorting of the TCeither through di-rect contact between the two leads or through the electrically conductive FTPS materials2.TCwire meltingwhich results in a noisy and/or open-loop TCresponse3.Type K TCwire green-rotwhich results in large calibration errors Scope of the Presentation:This presentation will include a brief discussion onthe effect of electrical shorting on the output of a TC(i.e. how to identify elec-trical shorting in TCdataand what the associated erroris).The tube furnace and arc jet test resultswill be dis-cussedand the solutions LOFTID is implementing to mitigate the error sourcesidentified in the tube furnace and arc jet testingwill be presented.Additionally, futureresearch and development work to eliminateTCerror sourcesfor future missionswill be recommended.

R A Miller↗