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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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Thermal control surfaces experiment (SOO69) flight systems performance

The thermal control surfaces experiment (TCSE) was the most complex hardware system aboard the Long Duration Exposure Facility (LDEF). The TCSE system consists of a scanning spectroreflectometer that measured test samples mounted on a rotatable carousel assembly. A microprocessor based data system controlled all aspects of TCSE system operation. Power was provided by four primary batteries. Flight measurement and housekeeping data were stored on a tape recorder for postflight analysis. The TCSE is a microcosm of complex electro-optical payloads being developed by NASA, DoD, and the aerospace community. The TCSE provides valuable data on the performance of these systems in space. The TCSE flight system and its excellent performance on the LDEF mission are described. A few operational anomalies were encountered and are discussed. Initial post-flight tests show that the TCSE system remains functional although some degradation in the optical measurements were observed. The results of these tests are also presented.

Wilkes, Donald R.↗

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

In engineering and aerospace applications, it is vital to operational success to have insight into the expected performance and health of physical systems. The field of prognostics and health management provides quantitative methods for monitoring, predicting, and managing system health. Prognostics algorithms can be employed to assess the current state of a system, propagate the system throughout time, and predict potential anomalies or failures that may occur. While they can provide accurate prediction results, effective prognostics algorithms can be challenging to use in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for future remaining useful life predictions. In this work, we implement new algorithmic approaches for prediction, quantitatively compare them via a battery degradation use-case, and provide recommendations of potential improvements to a prognostics framework. One approach to prediction is through sampling, whereby the current state of a physical system is sampled many times and each sample is propagated forward until failure is reached, resulting in a distribution of failure values. To improve the efficiency of this process, we implemented five new algorithmic approaches to prediction, including three distinct sampling methods (standard Monte Carlo, Quasi-Monte Carlo, and Latin Hypercube Sampling), a variable time step algorithm, and a variable sample size algorithm. To compare the algorithms, we employ a variety of metrics designed specifically to analyze both computational efficiency and model accuracy. Our metrics include accuracy to compare the average predicted value to ground truth, mean absolute deviation to illustrate dispersion, specific percentile error to describe accuracy within a user-defined risk tolerance, and code run-time. To quantitatively analyze our results, we employ a use-case of degradation of a Lithium-ion battery. We use an electrochemistry-based model to describe the current health state of the battery, and implement our prediction algorithms to propagate forward in time until end-of-discharge (EOD) is reached. Notably, through this work it was found that none of our sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. We find that while the sampling methods are unique, the distributions they generate are similar, ultimately producing final predictions that are nearly identical. In exploring the effect of the time step within the prediction algorithm, we found that prediction accuracy was highly dependent on the time step used, and that implementing a variable time step within a particular prediction may provide an increase in computational efficiency while also maintaining prediction accuracy. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment can result in improved computation speed and maintained prediction accuracy. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency.

prognostics↗

Nickel-hydrogen LEO cycling at 20 percent - 50 percent DOD

The test setup consists of four major elements: the programmable power supplies and load banks, the data acquisition and control system control computer, and the NiH2 specimen test cells. A simplified block diagram of the test setup is shown. The test setup provides complete battery isolation should a fault occur, and fusing as necessary to protect the battery cells and other equipment. Front panel switches provide for power supply configuration and battery isolation. Front panel meters provide continuous real-time visual monitoring of the voltage and current for each pack of cells. A strip chart recorder provides a hard copy of the voltage and current profiles for each of the packs. The test operates continuously with minimal human interface, except during special tests. The two power supplies are controlled by resistance programming. A bank of resistors and relays was built which can be switched by the control computer to provide control over the charge current to the batteries. The load banks are controlled by the 3497A. The 3497A is equipped with a 0.5 volt programmable power supply which is used to voltage program the load banks. A Hewlett-Packard Vectra 9000 running an HP Basic program is used as the control computer to remotely instruct the 3497A (data acquisition and control) to scan the data channels and retrieve test data. The program then reads, calculates, and stores the data. If an anomaly occurs, the program will disconnect the cells and shut down the test to avoid damage to the cells or equipment.

Lowery, John E.↗

Debris/ice/TPS assessment and integrated photographic analysis for Shuttle Mission STS-62

A pre-launch debris inspection of the pad and Shuttle vehicle was conducted on 2 March 1994. The detailed walkdown of Launch Pad 39B and MLP-1 also included the primary flight elements OV-102 Columbia (16th flight), ET-62 (LWT 55), and BI-064 SRB's. There were no significant facility or vehicle anomalies. After the launch on March 4th, a debris inspection of Pad 39B was performed. Damage to the pad overall was minimal. On-orbit photographs taken by the flight crew and two films from the ET/ORB umbilical cameras of the External Tank after separation from the Orbiter revealed no major damage or lost flight hardware that would have been a safety of flight concern. Orbiter performance on final approach appeared normal. Infrared imagery of landing gear deployment showed the loss of thermal barrier from the nose gear wheel well. The missing thermal barrier material was not recovered. The Solid Rocket Boosters were inspected at Hanger AF after retrieval. Both frustums had a combined total of 44 MSA-2 debonds over fasteners. Significant amounts of BTA had been applied to closeouts on the RH frustum, forward skirt, and aft skirt. Hypalon paint was blistered/missing over the areas were the BTA had been applied. The underlying BTA was not sooted (IFA STS-62-B-1). Investigation of this condition has concluded there was insufficient heat rates to cause blistering of the Hypalon until late in the ascent phase. A post landing inspection of OV-102 was conducted after the landing at KSC. The Orbiter TPS sustained a total of 97 hits, of which 16 had a major dimension of 1 inch or larger. The Orbiter lower surface had a total of 36 hits, of which 7 had a major dimension of 1 inch or larger. Based on these numbers and comparison to statistics from previous missions of similar configuration, both the total number of debris hits and the number of hits 1 inch or larger was less than average. Six thermal barriers, total size approximately 36 in. x 3 in. x 1.5 in., and one corner tile piece 4 in. x 4 in., were missing from the nose landing gear doors. Runway infrared cameras recorded these objects falling from the Orbiter when the nose landing gear doors were opened on final approach. A search of the area under the flight path failed to recover the missing thermal batteries, which may be submerged in the large body of water south of the runway. The cause for the loss of the material was attributed to the way the substrate was prepared for bonding at the vendor. Orbiter post landing microchemical sample results revealed a variety of residuals in the Orbiter window samples. These were attributed to SRB BSM exhaust, Orbiter TPS, window protective covers and processing, natural landing site products, and paints/primers from various sources. The residual sampling data do not indicate a single source of damaging debris and all of these materials have been documented previously in analyses for post landing sample reports. Data from residual sampling also showed no trends when compared to previous mission data. A total of ten Post Launch Anomalies, including one IFA, were observed during the STS-62 mission assessment.

Katnik, Gregory N.↗

Advanced Infant Car Seat Would Increase Highway Safety

An advanced infant car seat has been proposed to increase highway safety by reducing the incidence of crying, fussy behavior, and other child-related distractions that divert an adult driver s attention from driving. In addition to a conventional infant car seat with safety restraints, the proposed advanced infant car seat would include a number of components and subsystems that would function together as a comprehensive infant-care system that would keep its occupant safe, comfortable, and entertained, and would enable the driver to monitor the baby without having to either stop the car or turn around to face the infant during driving. The system would include a vibrator with bulb switch to operate; the switch would double as a squeeze toy that would make its own specific sound. A music subsystem would include loudspeakers built into the seat plus digital and analog circuitry that would utilize plug-in memory modules to synthesize music or a variety of other sounds. The music subsystem would include a built-in sound generator that could synthesize white noise or a human heartbeat to calm the baby to sleep. A second bulb switch could be used to control the music subsystem and would double as a squeeze toy that would make a distinct sound. An anti-noise sound-suppression system would isolate the baby from potentially disturbing ambient external noises. This subsystem would include small microphones, placed near the baby s ears, to detect ambient noise. The outputs of the microphone would be amplified and fed to the loudspeakers at appropriate amplitude and in a phase opposite that of the detected ambient noise, such that the net ambient sound arriving at the baby s ears would be almost completely cancelled. A video-camera subsystem would enable the driver to monitor the baby visually while continuing to face forward. One or more portable miniature video cameras could be embedded in the side of the infant car seat (see figure) or in a flip-down handle. The outputs of the video cameras would be transmitted by radio or infrared to a portable, miniature receiver/video monitor unit that would be attached to the dashboard of the car. The video-camera subsystem can also be used within transmission/reception range when the seat was removed from the car. The system would include a biotelemetric and tracking subsystem, which would include a Global Positioning System receiver for measuring its location. This subsystem would transmit the location of the infant car seat (even if the seat were not in a car) along with such biometric data as the baby s heart rate, perspiration rate, urinary status, temperature, and rate of breathing. Upon detecting any anomalies in the biometric data, this subsystem would send a warning to a paging device installed in the car or carried by the driver, so that the driver could pull the car off the road to attend to the baby. A motion detector in this subsystem would send a warning if the infant car seat were to be moved or otherwise disturbed unexpectedly while the infant was seated in it: this warning function, in combination with the position- tracking function, could help in finding a baby who had been kidnapped with the seat. Removable rechargeable batteries would enable uninterrupted functioning of all parts of the system while transporting the baby to and from the car. The batteries could be recharged via the cigarette-lighter outlet in the car or by use of an external AC-powered charger.

Dabney, Richard↗

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

The field of prognostics and health management provides quantitative methods for monitoring and predicting the health of physical systems. Prognostics algorithms are useful in that they can be employed to assess the current state of a system, propagate the system state throughout time, and predict potential anomalies or failures that may occur. However, effective prognosis can be challenging to achieve in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for some prognostics applications. In this work, we implement three new algorithmic approaches to prediction (sampling methods, variable prediction time step, variable prediction sample size) with the goal of improving computational efficiency while minimizing decrease in model accuracy. To quantitatively analyze our results, we examine a use-case of degradation of a Lithium-ion battery. Notably, through this work it was found that none of the sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. However, our results show that prediction accuracy is highly dependent on the time step used, and that an appropriate time step can optimize both model accuracy and simulation efficiency. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment in an application-specific manner may prove useful in some applications. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency of prognosis.

Prognostics↗

Project Vanguard Magnetic-Field Instrumentation and Measurements

The Vanguard III Satellite, 1959 Eta, placed in orbit on September 18, 1959, contained a proton precessional magnetometer for magnetic-field studies of exceptional accuracy. Throughout the 85 days of battery life, the instrumentation functioned according to plan. Measurements of the absolute total field were obtained in the meridian belts of Minitrack stations at altitudes 510 to 3750 kilometers and at latitudes +/- 33.4 degrees. Surface magnetic observatories were operated at eight of the Minitrack stations to furnish correlative information. This paper reviews briefly the instrumentation employed in these experiments, and the data collection and reduction procedures. Emphasis is given to results from a preliminary analysis. Specifically, this analysis bears on the accuracy of computed fields, the stability of the earth's field in space, the Capetown anomaly, and magnetic-storm effects.

Heppner, J. P.↗

VALENTInE: A Concept for a New Frontiers Class Long Duration In-Situ Balloon Mission to Venus

Venus and Earth are similar in bulk composition, size, density, and approximate distance from the Sun, yet Venus’s modern-day climate and surface geology is distinctly different [1]. Previous missions to Venus revealed unusual volcanic features, possible continental crust, widespread volcanic plains, a weak magnetic field [2], and insights into the Venusian atmosphere [3,4]. Unfortunately, data from these missions were limited in spatial and temporal resolution and global extent. A future mission to Venus is critical to address fundamental questions surrounding the chemical composition and dynamics of the Venusian atmosphere [5], its geologic history [6,7], its internal structure [8,9], and its habitability throughout time [10,11]. We present the Venus Air and Land Expedition: a Novel Trailblazer for In situ Exploration (VALENTInE) mission to meet this need. VALENTInE is a variable altitude balloon that will passively float in Venus’s atmosphere between 45 and 55 km altitude. VALENTInE will acquire atmospheric data at varying latitudes and longitudes in addition to mapping the surface geomorphology and mineralogy across multiple terrains. Mission Objectives: The VALENTInE mission concept is driven by four main science objectives: 1. Determine whether the driving force of the superrotation of Venus’s atmosphere is caused by horizontal or vertical momentum transport. 2. Determine whether the atmospheric composition and noble gas inventory of the Venusian atmosphere is a product of outgassing from the initial protoplanetary source or if there are significant contributions from exogenic sources. 3. Determine whether the tesserae regions (particularly Aphrodite Terra) are felsic and relatively older than surrounding regions. 4. Determine if there is any evidence of a recent dynamo preserved in the rock record of Venus. Mission Overview: A balloon architecture provides a robust system that can survive long-term in the Venusian environment while taking accurate measurements of the lower cloud deck and surface. Two prior balloon missions to Venus, VEGA 1 and VEGA 2 in 1984, have demonstrated the potential for such planetary exploration; however, these missions were short-lived (46 hr), with limited range (54 km). Our spacecraft concept consists of a battery powered balloon with a gondola and flyby carrier stage (Fig. 1). Our novel design allows for at least 15 days of atmospheric exploration, including multiple ascents and descents in the Venus atmosphere. VALENTInE is baselined to launch in 2032, cruise on solar power for 128 days, enter, descend, and inflate (EDI) into Venus’s atmosphere above Aphrodite Terra, and float in Venus’s atmosphere for a total nominal mission duration of 15 days. The balloon, able to control its altitude by changing its buoyancy, will make one full circumnavigation every 4–8 days and move poleward ~1 o latitude per day; it will be passively directed by the horizontal air currents on Venus. The balloon can only be controlled in the z direction, and the expected latitude range is ±10° from EDI. The balloon itself will be a tracer for atmospheric structures such as zonal winds [5, 12]. During the 15-day operational period, there will be five dips to 45 km for a compositional study of the lower atmosphere and geological and magnetic mapping of the surface. Dips are used to take images and measurements closer to the surface and to obtain in situ vertical atmospheric profiles between 45 and 55 km. Instruments: The VALENTInE instrument payload will allow for extensive study of the geology, atmosphere, and interior of Venus. The instrument suite consists of six instruments. The mission profile for each instrument is shown in Fig. 2. Lower Atmosphere Meteorology Analyzer (LAMA) is an atmospheric structure instrument consisting of a thermometer, barometer, and accelerometer to continuously measure temperature and pressure as a function of altitude, longitude, and latitude. TracE and Noble Gas Investigator (TENGI) is aneutral mass spectrometer used to sample the dense atmosphere. TENGI will operate continuously at 45 km and 55 km and will measure D/H ratios, as well as Ne, Ar, and O isotopic ratios. Kilometer Scale Spectral Imager (KSSI) is amultispectral imager (850-1150 nm) used to resolve surface features on the order of km. Near InfraRed Multispectral Photometer (NIRMP) is an Infrared (IR) photometer used to image the surface through the clouds to characterize mineral assemblages at five different areas of the surface. NIRMP will be operated during dwell. ELevation REConnaissance (ELREC) is a light detection and ranging (LIDAR) instrument used for measuring topography at five different areas of the surface. The ELREC data will be combined with those of NIRMP to determine mineral assemblages and how they correlate to topography. Magnetic Exploration and Interior Detective (MEID) is a magnetometer used to detect any near-surface magnetic anomalies. The magnetometer will continuously operate at all altitudes. Mission Design: The spacecraft’s propulsion system will have a wet mass of 930 kg and will be launched on an Atlas V rocket. The spacecraft will jettison the payload upon arrival in Venus’s atmosphere before decelerating to orbital velocity. Figure 2. Notional power-dip profile while the balloon is on the dayside. Risks and Challenges: Raising and lowering the spacecraft to dip beneath the haze layer require a large amount of energy. This issue was partly compensated by limiting the number of dips over the 15 day prime mission. Power needs for pumping helium are reduced by slowing the descent speed, which consequently increases spatial resolution of in situ measurements between 45 and 55 km. The main limitation for the duration of the mission is the need to carry 15 days’ worth of batteries. The bus experiences external Venusian temperatures ranging from ~27°C at 55 km altitude to ~110°C at 45 km altitude. These high atmospheric temperatures require thermal protection for the bus (instruments, electronics, and flight systems) during its descent, dwell at 45 km, and ascent. The bus is maintained at a mechanically safe temperature range of -10°C to 50°C using white external paint, multi-layer insulation (MLI), mechanical/thermal isolation (e.g. Ti, composites), and ~57 kg of Phase Change Materials (PCM). Images and spectra taken below the haze dominate the available data transmission regardless of the time spent at 45 km. Therefore, less time at the lower altitude mainly reduces the coverage of in situ measurements there. Further, we assumed an unrealistically low-density material for the helium storage tanks on the gondola. However, this issue is partially resolved if we were to jettison 75% of the spent helium storage tanks. After the entry process, the balloon volume remains mostly inflated and storage tanks are required only for reducing balloon volume in dipping to 45 km. This mission was planned against an expected New Frontiers 5 (NF5) cost cap of $1B, as the NF5 call had not yet been released. The mission we describe fits within the predicted cost cap if the flyby carrier stage, responsible for powering the spacecraft during cruise and for relaying in situ measurements back to Earth, can be contributed by another space agency. Acknowledgments: We thank the JPL Planetary Science Summer School, especially A. Nash, J. Scully, K. Mitchell, L. Lowes, and J. Armijo, and our mentors from JPL Team X. Thank you to our review panel for their insightful review. References: [1] Kane, S. et al. (2019) JGR:Ps, 124 , 2015–2028. [2] Phillips, J. L., & Russell, C. T. (1987). JGR: Space Physics , 92 (A3), 2253-2263. [3] Nakamura, M. et al. (2018) Earth Planets Space, 70 (1), 144. [4] Svedhem, H. et al. (2009) JGR:P 114 (E5). [5] Limaye et al. (2009) Decadal Survey White Paper . [6] Ivanov, M. and Head, J. (2011) PSS, 59 (13) , 1559-1600. [7] Smrekar, S. et al. (2018) Space Sci Rev, 214 (5), 88. [8] O’Rourke, J. et al. (2018) EPSL, 502 , 46-56. [9] O’Rourke J. et al. (2019) GRL , (46), 5768–5777 [10] Way, M. et al. (2016) GRL, 43 (16), 8376-8383. [11] Way, M. et al. (2020) JGR:P, 125 (5), e2019JE006276. [12] Preston, R. A. et al. (1986) Science, 231 (4744), 1414-1416.

Mission Concept↗

BioSentinel: Mission Summary and Lessons Learned From the First Deep Space Biology CubeSat Mission

Launched on Artemis-1, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into Heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “Retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, fluid systems, sensor control electronics, as well at the living yeast cells. BioSentinel also included a TimePix radiation sensor implemented by JSC’s RadWorks group. Dose and Linear Energy Transfer (LET) data is compared directly to the rate of DSB-and repair events measured by the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions.

BioSentinel↗

Biosentinel: Mission Summary and Lessons Learned From the First Deep Space Biology CubeSat Mission

Launched on Artemis-1, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into Heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “Retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, fluid systems, sensor control electronics, as well at the living yeast cells. BioSentinel also included a TimePix radiation sensor implemented by JSC’s RadWorks group. Dose and Linear Energy Transfer (LET) data is compared directly to the rate of DSB-and repair events measured by the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions.

BioSentinel↗

Biosentinel: The First Deep Space Biology CubeSat Mission- Mission Summary and Lessons Learned

Launched on Artemis-1, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into Heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “Retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, fluid systems, sensor control electronics, as well at the living yeast cells. BioSentinel also included a TimePix radiation sensor implemented by JSC’s RadWorks group. Dose and Linear Energy Transfer (LET) data is compared directly to the rate of DSB-and repair events measured by the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions.

BioSentinel↗

Radiation dosimetry measurements during U.S. Space Shuttle missions with the RME-III

Time-resolved radiation dosimetry measurements inside the crew compartment have been made during recent Shuttle missions with the U.S. Air Force Radiation Monitoring Equipment-III (RME-III), a portable battery-powered four-channel tissue equivalent proportional counter. Results from the first six missions are presented and discussed. Half of the missions had orbital inclinations of 28.5 degrees with the remainder at inclinations of 57 degrees or greater; altitudes ranged from 300 to 600 km. The determined dose equivalent rates ranged from 70 to 5300 microSv/day. The RME-III measurements are in good agreement with other dosimetry measurements made aboard the vehicles. Measurements indicate that medium- and high-LET particles contribute less than 2% of the particle fluence for all missions, but up to 50% of the dose equivalent, depending on the spacecraft's altitude and orbital inclination. Isocontours of fluence, dose and dose equivalent rate have been developed from measurements made during the STS-28 mission. The drift rate of the South Atlantic Anomaly is estimated to be 0.49 degrees W/yr and 0.12 degrees N/yr. The calculated trapped proton and GCR dose for the STS-28 mission was significantly lower than the measured values.

STS-28 Shuttle Project↗

The in-flight performance of the Solar Maximum Mission Electrical Power System

Circuitry, power handling, and operational characteristics and anomalies of the Electrical Power System (EPS) of the Solar Maximum Mission are discussed. The EPS is designed as a standard unit to be a candidate for use on future space missions. Blown, improperly derated fuses in the Attitude Control System and the Signal Conditioning Assembly have led to switching to magnetrons for solar angle, with a loss of accuracy, and a loss of one-half of telemetry data, respectively. In addition, reasons for an 11-14% degradation of solar array output are uncertain due to the loss of precise attitude control. Current surges to peak at 76.5 A (down from 94.5 A) at sunrise, stays for four to five minutes, then resumes nominal output for the remainder of the 61-68 daytime period. Eclipse varies between 28 and 35 minutes, with corresponding depth of discharge of 14%. The batteries charge at 20 A, and although an overcharge mode has been continuously sensed, operation has been normal and temperature sensors have not indicated overcharge; cell failure has also not been sensed. The system has a two year design life and a desired life of four years.

Broderick, R. J.↗

Assured Contingency Landing Management for Advanced Air Mobility

Advanced Air Mobility (AAM) is quickly developing as a new air transportation system that moves people and packages in the regions previously not / less served by the current aviation systems. Such AAM must operate safely despite the potential to encounter hazards and experience anomalies and failures in-flight. It becomes especially important to have systematic auto-mitigation strategies to perform safe contingency actions in AAM flight operations, as pilots have limited Situational Awareness (SA) and limited time to make prompt decisions when encountering failures/anomalies in high-density low altitude airspace. This paper presents Assured Contingency Landing Management (ACLM) with an online landing strategy selection to decide between the following three options when a contingency landing is required: (1) Return-to-launch landing site, (2) Land immediately at a nearby clear but unprepared site, (3) Land at a prepared landing site from the approximate footprint. Our presented algorithm shows a real-time auto-mitigation loop with multiple threads that run simultaneously to check controllability, reachability, and intermediate decisions to hold/ loiter or continue the flight plan as the landing strategy solution is being computed. Case study simulation is demonstrated with the safety-critical propulsion system and battery system and shows how different failure scenarios impact the landing strategy selection.

Autonomous Mitigation↗

Development of the ISS EMU SPEEDR

The Self Powered EVA EMU Data Recorder (SPEEDR) is an FPGA (Field-programmable gate array) based device designed to collect high-rate EMU (Extravehicular Mobility Unit) PLSS (Primary Life Support Subsystem) data for download at a later time. The existing EMU PLSS data down-link capability during EVA is one data packet every 2 minutes and is subject to bad packets or loss of signal. High-rate PLSS data is generated by the ECWS (Enhanced Caution and Warning System) but is not normally captured or distributed. Access to high-rate data will increase the capability of EMU anomaly resolution team to pinpoint issues remotely, saving crew time by reducing required call-down Q&A and on-orbit diagnostic activities. With no Shuttle flights post FY11, and potentially limited down-mass capability, the ISS crew and ground support personnel will have to be capable of on-orbit operations to maintain, diagnose, repair, and return to service EMU hardware, possibly through 2028. Collecting high-rate EMU PLSS data during both IVA (Intravehicular Activity) and EVA (Extravehicular Activity) operations will provide trending analysis for life extension and/or predictive performance. The SPEEDR concept has generated interest as a tool/technology that could be used for other ISS subsystems or future exploration-class space suits where hardware reliability/availability is critical and low/variable bandwidth may require "store then forward" methodology. Preliminary work in FY11 produced a functional prototype consisting of an FPGA evaluation board, custom memory/interface circuit board, and custom software. The SPEEDR concept includes a stand-alone battery that is recharged by a computer USB (Universal Serial Bus) port while data is being downloaded.

Bernard. Craig↗

Development of the Self-Powered Extravehicular Mobility Unit Extravehicular Activity Data Recorder

The Self-Powered Extravehicular Mobility Unit (EMU) Extravehicular Activity (EVA) Data Recorder (SPEEDR) is a field-programmable gate array (FPGA)-based device designed to collect high-rate EMU Primary Life Support Subsystem (PLSS) data for download at a later time. During EVA, the existing EMU PLSS data downlink capability is one data packet every 2 minutes and is subject to bad packets or loss of signal. Higher-rate PLSS data is generated by the Enhanced Caution and Warning System but is not normally captured or distributed. Access to higher-rate data will increase the capability of EMU anomaly resolution team to pinpoint issues remotely, saving crew time by reducing required call-down Q&A and on-orbit diagnostic activities. With no Space Shuttle flights post Fiscal Year 2011 (FY11), and potentially limited down-mass capability, the ISS crew and ground support personnel will have to be capable of on-orbit operations to maintain, diagnose, repair, and return to service EMU hardware, possibly through 2028. Collecting high-rate EMU PLSS data during both intravehicular activity (IVA) and EVA operations will provide trending analysis for life extension and/or predictive performance. The SPEEDR concept has generated interest as a tool/technology that could be used for other International Space Station subsystems or future exploration-class space suits where hardware reliability/availability is critical and low/variable bandwidth may require store then forward methodology. Preliminary work in FY11 produced a functional prototype consisting of an FPGA evaluation board, custom memory/interface circuit board, and custom software. The SPEEDR concept includes a stand-alone battery that is recharged by a computer Universal Serial Bus (USB) port while data are being downloaded.

Bernard, Craig↗

Investigating On-Orbit Attitude Determination Anomalies for the Solar Dynamics Observatory Mission

The Solar Dynamics Observatory (SDO) was launched on February 11, 2010 from Kennedy Space Center on an Atlas V launch vehicle into a geosynchronous transfer orbit. SDO carries a suite of three scientific instruments, whose observations are intended to promote a more complete understanding of the Sun and its effects on the Earth's environment. After a successful launch, separation, and initial Sun acquisition, the launch and flight operations teams dove into a commissioning campaign that included, among other things, checkout and calibration of the fine attitude sensors and checkout of the Kalman filter (KF) and the spacecraft s inertial pointing and science control modes. In addition, initial calibration of the science instruments was also accomplished. During that process of KF and controller checkout, several interesting observations were noticed and investigated. The SDO fine attitude sensors consist of one Adcole Digital Sun Sensor (DSS), two Galileo Avionica (GA) quaternion-output Star Trackers (STs), and three Kearfott Two-Axis Rate Assemblies (hereafter called inertial reference units, or IRUs). Initial checkout of the fine attitude sensors indicated that all sensors appeared to be functioning properly. Initial calibration maneuvers were planned and executed to update scale factors, drift rate biases, and alignments of the IRUs. After updating the IRU parameters, the KF was initialized and quickly reached convergence. Over the next few hours, it became apparent that there was an oscillation in the sensor residuals and the KF estimation of the IRU bias. A concentrated investigation ensued to determine the cause of the oscillations, their effect on mission requirements, and how to mitigate them. The ensuing analysis determined that the oscillations seen were, in fact, due to an oscillation in the IRU biases. The low frequencies of the oscillations passed through the KF, were well within the controller bandwidth, and therefore the spacecraft was actually following the oscillating biases, resulting in movement of the spacecraft on the order of plus or minus 20 arcsec. Though this level of error met the ACS attitude knowledge requirement of [35, 70, 70] arcsec, 3 sigma, the desire of the ACS and instrument teams was to remove as much of the oscillation as possible. The Kearfott IRUs have an internal temperature controller, designed to maintain the IRU temperature at a constant temperature of approximately 70 C, thus minimizing the change in the bias drift and scale factors of the mechanical gyros. During ground testing of the observatory, it was discovered that the 83-Hz control cycle of the IRU heaters put a tremendous amount of stress on the spacecraft battery. Analysis by the power systems team indicated that the constant charge/discharge on the battery due to the IRU thermal control cycle could potentially limit the life of the battery. After much analysis, the decision was made not to run the internal IRU heaters. Analysis of on orbit data revealed that the oscillations in the IRU bias had a connection to the temperature of the IRU; changes in IRU temperature resulted in changes in the amplitude and period of the IRU biases. Several mitigating solutions were investigated, the result of which was to tune the KF with larger IRU noise assumptions which allows the KF to follow and correct for the time-varying IRU biases.

Vess, Melissa F.↗

Flight Testing of In-Time Safety Assurance Technologies for UAS Operations

Ongoing research at NASA is driven by a strategic plan defined by the Aeronautics Research Mission Directorate and a vision for future In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. In both visions, system safety awareness and provision are expanded through increased access to relevant data; integrated analysis and predictive capabilities; improved real-time detection and alerting of domain-specific hazards; decision support, and in some cases, automated risk mitigation strategies. One primary research focus is to develop means by which more timely (i.e., “in-time”) actions may be taken to mitigate precursors, anomalies, or trends that are observed during operations. In this paper, we describe such means as a collection of Services, Functions, and Capabilities (SFCs) that are supported by an underlying information system. For example, an integrated risk assessment capability is envisioned that continuously monitors safety-related metrics and margins and recommends timely operational changes. Assessment functions and/or services can be based on data analytics and predictive models derived from heterogeneous data sets that span relevant indicator metrics and their time histories. Likewise, on-board functions can identify and reduce susceptibility to precursor conditions that have led (and can lead) to aircraft loss-of-control or out-of-control accidents. This paper summarizes development and testing of such an information system tailored to hazards anticipated for future highly autonomous flight missions near and over densely populated areas. Testing is accomplished via simulation and by using small, unmanned aircraft operating over a test range at NASA’s Langley Research Center. Flight plans and test scenarios are defined to emulate several use-cases, including package delivery; reconnaissance; fire management; and urban air taxi vertiport operations. Two test phases are summarized with Phase 1 occurring in (2019-2020) and Phase 2 ongoing (2021-present). Results focus on SFC performance, technology readiness level assessment, and requirements discovery/validation. Companion papers are cited throughout for additional details on the recent testing.

safety management↗