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NASA NTRS2016

GPS and Galileo Developments on Board the International Space Station With the Space Communications and Navigation (SCaN) Testbed

The Space Communications and Navigation (SCaN) is a facility developed by NASA and hosted on board the International Space Station (ISS) on an external truss since 2013.It has the objective of testing navigation and communication experimentations with a Software Defined Radio (SDR) approach, which permits software updates for testing new experimentations.NASA has developed the Space Telecommunications Radio System (STRS) architecture standard for SDRs used in space and ground-based platforms to provide commonality among radio developments to provide enhanced capability. The hardware is equipped with both L band front-end radios and the NASA space network communicates with it using S-band, Ku-band and Ka-band links.In May 2016 Qascom started GARISS (GPS and Galileo Receiver for the ISS), an activity of experimentation in collaboration with ESA and NASA that has the objective to develop and validate the acquisition and processing of combined GPS and Galileo signals on board the ISS SCaN testbed. This paper has the objective to present the mission, and provide preliminary details about the challenges in the design, development and verification of the waveform that will be installed on equipment with limited resources. GARISS is also the first attempt to develop a waveform for the ISS as part of an international collaboration between US and Europe. Although the final mission objective is to target dual frequency processing, initial operations will foresee a single frequency processing. Initial results and trade-off between the two options, as well as the final decision will be presented and discussed. The limited resources on board the SCaN with respect to the challenging requirements to acquire and track contemporaneously two satellite navigation systems, with different modulations and data structure, led to the need to assess the possibility of aiding from ground through the S-band. This option would allow assistance to the space receiver in order to provide knowledge of GNSS orbits and reduce the processing on board. Trade off and various options for telemetry and uplink data are presented and discussed. Finally, integration and validation of the waveform are one of the major challenges of GARISS: The Experiment Development System (EDS) and the the Ground Integration Unit (GIU) for VV will be used prior to conducting the experiment on the ISS. The EDS can be used in lab environment and allows prototyping and verification activities with the simulator, but does not include all hardware components. The GIU on the other side is the flight model which replicates the flying equipment, but has limited flexibility for testing.As conclusion, the project is now approaching the Preliminary Design Review (PDR) and indeed only preliminary results are available. This paper is an opportunity to present the GARISS mission as part of an International cooperation between ESA, NASA and Qascom. The preliminary results include GPS and Galileo processing from space signals, the challenges and trade off decisions, the high level STRS architecture and foreseen experimentation campaign. Detailed results from the test campaigns are expected in 2017.

space navigation↗
NASA NTRS2016

Craters of the Pluto-Charon System

NASA's New Horizons flyby mission of the Pluto-Charon binary system and its four moons provided humanity with its first spacecraft-based look at a large Kuiper Belt Object beyond Triton. Excluding this system, multiple Kuiper Belt Objects (KBOs) have been observed for only 20 years from Earth, and the KBO size distribution is unconstrained except among the largest objects. Because small KBOs will remain beyond the capabilities of ground-based observatories for the foreseeable future, one of the best ways to constrain the small KBO population is to examine the craters they have made on the Pluto-Charon system. The first step to understanding the crater population is to map it. In this work, we describe the steps undertaken to produce a robust crater database of impact features on Pluto, Charon, and their two largest moons, Nix and Hydra. These include an examination of different types of images and image processing, and we present an analysis of variability among the crater mapping team, where crater diameters were found to average +/-10% uncertainty across all sizes measured (approx.0.5-300 km). We also present a few basic analyses of the crater databases, finding that Pluto's craters' differential size-frequency distribution across the encounter hemisphere has a power-law slope of approximately -3.1 +/- 0.1 over diameters D approx. = 15-200 km, and Charon's has a slope of -3.0 +/- 0.2 over diameters D approx. = 10-120 km; it is significantly shallower on both bodies at smaller diameters. We also better quantify evidence of resurfacing evidenced by Pluto's craters in contrast with Charon's. With this work, we are also releasing our database of potential and probable impact craters: 5287 on Pluto, 2287 on Charon, 35 on Nix, and 6 on Hydra.

Robbins, Stuart J.↗
NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

route advisories↗
NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

operational acceptability↗
NASA NTRS2017

Rotational Spectral Unmixing of Exoplanets: Degeneracies Between Surface Colors and Geography

Unmixing the disk-integrated spectra of exoplanets provides hints about heterogeneous surfaces that we cannot directly resolve in the foreseeable future. It is particularly important for terrestrial planets with diverse surface compositions like Earth. Although previous work on unmixing the spectra of Earth from disk-integrated multi-band light curves appeared successful, we point out a mathematical degeneracy between the surface colors and their spatial distributions. Nevertheless, useful constraints on the spectral shape of individual surface types may be obtained from the premise that albedo is everywhere between 0 and 1. We demonstrate the degeneracy and the possible constraints using both mock data based on a toy model of Earth, as well as real observations of Earth. Despite the severe degeneracy, we are still able to recover an approximate albedo spectrum for an ocean. In general, we find that surfaces are easier to identify when they cover a large fraction of the planet and when their spectra approach zero or unity in certain bands.

Fujii, Yuka↗
NASA NTRS2018

Gene Expression of Pathogens in Simulated Microgravity

Extended exposure to radiation and microgravity in space has been linked to astronauts developing chronic diseases upon returning to Earth. The Gram-negative pathogen Serratia marcescens has been shown to potentially cause significant infections in humans and in insect models on Earth. Our recent findings also showed that S. marcescens shows an increase in virulence after a short period of growth in the spaceflight environment, which raises initiatives to find the correlation between space environment and the increased virulence. Because we know that the health of astronauts is immunocompromised in space, it is possible that the combination of increased bacterial virulence and the weakened immune system will cause astronauts to be more susceptible to chronic diseases in extended spaceflight. With 75% of human disease genes being conserved in the fruit fly Drosophila melanogaster, these insects act as an ideal model organism to study the human immune system. The high accessibility, low cost, high rate of reproductivity, and short lifespans of D. melanogaster facilitate efficient, high-quality research that seeks to understand altered virulence of this opportunistic pathogen. In this ground-based study, we will use a rotating wall vessel apparatus to simulate microgravity and determine how pathogenicity changes by evaluating differences in gene expression for S. marcescens between bacteria grown in simulated microgravity conditions and controls. We will compare the results of our findings to gene expression patterns in actual spaceflight samples of S. marcescens grown on the ISS (International Space Station) during a recent validation mission, to see if there are common mechanisms across our simulated microgravity and actual spaceflight microgravity samples that both show increased virulence in the fruit fly. With extended space travel in the foreseeable future, understanding how human physiology will be affected by these different factors will help mitigate risks and deaths.

spaceflight analogue↗
NASA NTRS2019

Distinct Pattern of Oculomotor Impairment Associated with Acute Sleep Loss and Circadian Misalignment

Sleep loss and circadianmisalignment have long been known to impair human cognitive and motor performance with significant societal and health consequences. It is well known that human reaction time to a visual cue is impaired following sleep loss and circadian misalignment, but it has remained unclear how more complex visuomotor control behaviour is altered under these conditions. In this study, we measured 14 parameters of the voluntary ocular tracking response of 12 human participants (six females) to systematically examine the effects of sleep loss and circadianmisalignment using a constant routine 24 h acute sleep-deprivation paradigm. The combination of state-of-the-art oculometric and sleep-research methodologies allowed us to document, for the first time, large changes in many components of pursuit, saccades and visual motion processing as a function of time awake and circadian phase. Further, we observed a pattern of impairment across our set of oculometric measures that is qualitatively different from that observed previously with other mild neural impairments. We conclude that dynamic vision and visuomotor control exhibit a distinct pattern of impairment linked with time awake and circadian phase. Therefore, a sufficiently broad set of oculometric measures could provide a sensitive and specific behavioural biomarker of acute sleep loss and circadian misalignment. We foresee potential applications of such oculometric biomarkers assisting in the assessment of readiness-to-perform higher risk tasks and in the characterization of sub-clinical neural impairment in the face of a multiplicity of potential risk factors, including disrupted sleep and circadian rhythms.

Stone, Leland S.↗
NASA NTRS2019

Small Satellite Industrial Base Study: Foundational Findings

This report documents findings from a Small Satellite (SmallSat) Industrial Base Study conducted by The Aerospace Corporation between November 2018 and September 2019. The primary objectives of this study were a) to gain a better understanding of the SmallSat community’s technical practices, engineering approaches, requirements flow-downs, and common processes and b) identify insights and recommendations for how the government can further capitalize on the strengths and capabilities of SmallSat offerings. In the context of this study, SmallSats are understood to weigh no more than 500 kg, as described in “State of the Art Small Spacecraft Technology, NASA/TP-2018- 220027, December 2018. CubeSats were excluded from this study to avoid overlap and duplication of recently completed work or other studies already under way. The team also touched on differences between traditional space-grade and the emerging “mid-grade” and other non-space, alternate-grade EEEE (electrical, electronic, electromechanical, electro-optical) piece part categories. Finally, the participants sought to understand the potential effects of increased use of alternate-grade parts on the traditional space-grade industrial base. The study team was keenly aware that there are missions for which non-space grade parts currently are infeasible for the foreseeable future. National security, long-duration and high-reliability missions intolerant of risk are a few examples. The team sought to identify benefits of alternative parts and approaches that can be harnessed by the government to achieve greater efficiencies and capabilities without impacting mission success.

Allyson D Yarbrough↗
NASA NTRS2020

Breakthrough Materials for Space Applications Workshop

In the course of its 60 year history, the National Aeronautics and Space Administration (NASA) has blazed trails in the development and advancement of aerospace materials and the transition of these advancements to industry. The Agency has overseen the infusion of new high-performance materials into a diverse array of mission applications, including aeronautics, planetary science, and human spaceflight. The next generation of demanding exploration missions, including a return to the lunar surface with humans in the 2020s, will present new and unprecedented material challenges. Selecting or developing materials to survive the environments of launch and the high temperatures present in propulsion systems, operate in a microgravity and/or a vacuum environment (which includes exposure to radiation), and/or survive years on a planetary surface is an immense challenge. In addition to functioning in their intended use environment, materials for space must also possess extremely high-performance characteristics. The anecdotal Von Braun quote “space is weightlifting” reminds us of the need to minimize the mass of a space system while still meeting safety margins. The cost of launching a kg to orbit is estimated currently at $10,000; barring a drastic reduction in launch costs, lightweight and high-strength materials will remain the most sought-after spaceflight materials for the foreseeable future. Other primary considerations for materials in spaceflight applications include affordability, compatibility with other systems and materials, and manufacturability. The emergence of new advanced manufacturing processes such as friction stir welding and additive manufacturing have revolutionized the aerospace industry in recent years. Additive manufacturing in particular allows for rapid fabrication of components and greater design freedom. With the advent of these new processes, however, comes the need to develop new specifications, process control approaches (including material modeling), testing, and nondestructive evaluation techniques to ensure that parts meet the stringent functional requirements for spaceflight.

Prater, T.↗
NASA NTRS2018

The Recent Large Reduction in Space Launch Cost

The development of commercial launch systems has substantially reduced the cost of space launch. NASA’s space shuttle had a cost of about $1.5 billion to launch 27,500 kg to Low Earth Orbit (LEO), $54,500/kg. SpaceX’s Falcon 9 now advertises a cost of $62 million to launch 22,800 kg to LEO, $2,720/kg. Commercial launch has reduced the cost to LEO by a factor of 20. This will have a substantial impact on the space industry, military space, and NASA. Existing launch providers are reducing their costs and so are satellite developers. The military foresees an opportunity to rapidly replace compromised space assets that provided communications, weather, surveillance, and positioning. NASA supported the development of commercial space launch and NASA science anticipates lower cost missions, but human space flight planning seems unreactive. Specifically, it has been claimed that commercial spaceflight has not reduced the cost to provide cargo to the International Space Station (ISS). The key factor is that the space shuttle can provide cargo and crew to ISS while the Falcon 9 must also use the Dragon capsule, which adds cost and reduces payload. The cost of a Falcon 9 and Dragon capsule mission to ISS is about $140 million with a payload of 6,000 kg, $23,300/kg. The shuttle payload to ISS is less than to LEO, 16,050 kg, so its cost is also higher at $93,400/kg. The launch cost to ISS has been reduced by a factor of 4. Calculations that show commercial launch provides no cost reduction to ISS assume half the usually cited shuttle cost and allocate it to the actual delivered payload, about half the full capacity. In a split mission, with crew and pressurized cargo launched separately from hardware and materials, the higher Falcon 9 plus Dragon costs would apply only to a fraction of the launch mass. A 4 to 1 cost reduction saves most, 75%, of the total cost. A further reduction to 10 or 20 to 1 saves 90 or 95%, but this is only a small, 15 or 20%, portion of the original cost. The recently reduced space launch cost can be expected to substantially impact human space flight.

Jones, Harry W.↗
NASA NTRSDate not supplied

Experiments to Challenge Jet Noise Prediction

Recent fundamental jet noise tests were conducted with the objective of providing data that challenges jet noise prediction methods. Three cases have been extracted to pose as challenges to the jet noise prediction community. Case 1 targets efforts in LES to appropriately mimic unresolveable turbulent boundary layers in nozzles, and to demonstrate where they are, and are not, important for noise. Case 2 targets acoustic analogy methods, providing cardinal data for the question of azimuthal localization and the broader issue of designing nozzles with favorable azimuthal directivity. Case 3 is an example where nozzle systems exhibit global resonances, which cannot be attacked by steady-state calculations. Given that it is very difficult to foresee such unsteady behavior (speaking from experience), it is crucial that low-cost methods be developed to catch these during the design process. Analysis and documentation of the test data is ongoing.

jet noise↗
NASA NTRS2019

The Future of Exoplanet Direct Detection

Diffraction fundamentally limits our ability to image and characterize exoplanets. Currant and planned coronagraphic searches for exoplanets are making incredible strides but are fundamentally limited by the inner working angle of a few λ/D. Some crucial topics, such as demographics of exoplanets within the first 50 Myr and the infrared characterization of terrestrial planets, are beyond the reach of the single aperture angular resolution for the foreseeable future. Interferometry offers some advantages in exoplanet detection and characterization and we explore in this white paper some of the potential scientific breakthroughs possible. We demonstrate here that investments in "exoplanet interferometry" could open up new possibilities for speckle suppression through spatial coherence, a giant boost in astrometric precision for determining exoplanet orbits, ability to take a census of young giant exoplanets (clusters <50 Myr age), and an unrivaled potential for infrared nulling from space to detect terrestrial planets and search for atmospheric biomarkers. All signs point to an exciting future for exoplanets and interferometers, albeit a promise that will take decades to fulfill.

John Monnier↗
NASA NTRSDate not supplied

CFD 2030 Grand Challenge: CFD-in-the-Loop Monte Carlo Flight Simulation for Space Vehicle Design

Flight qualification of space vehicles is markedly different from those typically employed for aircraft. The concept of an extensive flight test campaign for a space vehicle does not exist, and vehicle designers must look to alternative techniques for demonstrating robust and reliable performance of their vehicles prior to operational flight. A space vehicle may undergo only a handful of flight tests in its development cycle, with each flight representing a drastically different flight phase or flight configuration. For instance, NASA’s Space Launch System (SLS) launch vehicle and Orion spacecraft will only see a total of four flight demonstrations before flying a crew on its first operational mission, and each flight demonstrates a unique vehicle configuration and/or set of flight conditions. The SLS will be flown only one time before it becomes operational (Artemis 1). The Orion spacecraft Crew Module (CM) will have been tested twice, once on a Delta IV launch vehicle (Exploration Flight Test 1) and once as a fully integrated system with the SLS launch vehicle (Artemis 1). The Orion Launch abort system will have been tested twice, once in a pad abort scenario (Pad Abort 1) and once in an inflight abort scenario (Ascent Abort 2) on a modified Peacekeeper booster. Both of these latter tests involve only a boiler plate CM, not a functional Orion spacecraft. Thus, unlike aircraft, there is very little opportunity for engineers to assess and evaluate their preflight predictions. Instead, space vehicle designers rely on Monte Carlo flight simulations with detailed dispersions of predicted nominal flight behavior to determine how robust their design is to errors and uncertainties in the flight conditions their vehicle may encounter. These Monte Carlo analyses entail thousands of trajectory simulations to demonstrate that the vehicle can meet design requirements at a specified level of reliability. From an aerodynamics and aerothermodynamics perspective, these trajectory simulations are fueled by an extensive aerodynamic database that covers the complete range of expected flight conditions, vehicle configurations, and flight attitudes expected in a given mission. Today, these databases amount to a table of engineering parameters that can be quickly interrogated by the trajectory simulator. The aerodynamic and aerothermodynamic databases are assembled via a series of ground tests, empirical and analytical analysis, physics-based computational analysis, applicable past flight performance data, and in some cases, engineering judgment. These databases generally take years to assemble for a new space vehicle system and in the case of SLS/Orion, over a decade of test and analysis have been expended to develop the extensive databases required to cover the myriad of configurations and potential flight conditions required for the system. Recently, it has been proposed that Computational Fluid Dynamic (CFD) and computing capability may be reaching a point where it is foreseeable that CFD could be integrated directly into the production trajectory simulation tools used to design NASA’s space vehicles. To demonstrate this, NASA has embarked on two demonstrations of this type of capability, one where six degree of freedom flight trajectory simulation equations are embedded in an existing CFD solver and another where a production CFD solver is loosely coupled with a production trajectory simulation tool. These efforts represent an initial demonstration of a future approach to flight trajectory simulation, but they are a far cry from the capability required to perform a full-up CFD-in-the-loop Monte Carlo trajectory simulation. Therefore, this represents a viable grand challenge for computational methods addressing space vehicle design and development. The final paper/presentation will discuss the many hurdles, beyond simply raw computational power, to realizing this grand challenge and how they map directly to the CFD Vision 2030 ojectives. Among these are the wide range of flight conditions, including accelerating/decelerating flight, encountered by a space vehicle during launch and/or entry. The vehicle can also encounter numerous configuration changes, some of which can be quite drastic, during the course of its flight, so robust, automated geometry modeling, grid generation, and adaptation will play a huge role in reaching this goal. Multiply this by 1000’s of trajectory simulations occurring simultaneously in a given Monte Carlo analysis, and the problem readily scales to absorb virtually any size of supercomputer envisioned today. The concept of CFD-in-the-loop Monte Carlo trajectory simulation poses a formidable challenge for emerging and future computing systems, and it has the potential to shave years off the development cycle for aerodynamic and aerothermodynamic performance predictions as compared to today’s space vehicle design approach.

CFD 2030↗
NASA NTRSDate not supplied

Exploring data-driven modeling of boundary layer transition

Prediction of laminar-turbulent transition in boundary layer flows is an important component of predicting the aerodynamic performance of a number of aerospace configurations. According to the CFD Vision 2030 [1], transition modeling represents acriticalarea in CFD simulation capability that will remain a pacing item for the foreseeable future. The fact thattransition can take placevia either one of a myriad possible paths adds to the challenges inreliable transition predictions, despite a limited knowledge of the relevant input parameters. In the low disturbance environments typical of flight applications, transition is often initiated by small amplitude disturbances in the form of linear instability waves of the laminar boundary layer. These disturbances amplify linearly at first and eventually undergo a sequence of nonlinear interactions that result in transition to turbulence. Because the nonlinear phase is rather rapid, the amplification of boundary layer instabilities is governed by the linearstability theory over a majority of the distance leading up to the onset of transition. Semi-empirical transition correlations based on the linear stability theory have been successful in explaining the observed trends in transition location within a broad class of flows. However, the application of stability theory is highly non-robust and often requires a significant domain expertise. Recent work at the NASA Langley Research Center has beenaimed at bridging the gap between physics based transition analyses such as those based on linear stability theory and practical applications that require transition prediction by users that may not be well versed in transition physics. The applications of deep learning have been at the center of these efforts. This presentation will focus on the progress achieved thus far, highlighting the applications of neural networks to selectedtransition scenarios across a range of Mach numbers and flow configuration, as well as the lessons learnedand remaining challengeswithrespect to the selection of training data and neural networks architectures, hyperparameter tuning, and the physical insights distilled from the otherwise black-box models.

M. R. Malik↗
NASA NTRSDate not supplied

Systems Health Monitoring: Integrating FMEA into Bayesian Networks

The foreseeable high traffic density suggests that a large number of electric propulsion systems will enter the airspace, and that they will also operate at high frequency, e.g., large number of take offs and landings per unit time. The reliability of such critical systems is therefore key to ensure high safety standards in the low-altitude airspace. Diagnostic systems, which aim at identifying incipient faults, can mitigate unexpected failures or lower-than-expected reliability by performing early fault detection by monitoring the systems. A key element of fault diagnosis is fault detection and isolation (FDI), which complexity increases with the complexity of the system itself, namely the number of subsystems and components, interactions among sub-systems, and the number of sensors available. The proposed approach leverages combination of failure mode and effect analysis (FMEA) integrated with Bayesian networks, thus introducing dependability structures into a diagnostic framework to aid FDI. Faults and failure events from the FMEA are mapped within a Bayesian network, where network edges replicate the links embedded within FMEAs. The integrated framework enables the fault isolation process by identifying the probability of occurrence of specific faults or root causes given evidence observed through sensor signals. In this work, sub systems of Urban Air Mobility (UAM) type vehicle like avionics, structures, power-train etc. are taken into account to show the approach at the system level. This work integrates early design phase in the development of UAM type vehicles with diagnostic tools, which are often developed later in the product life-cycle, or retrofitted at a later time on systems. Failure mode and effect analysis (FMEA) derived for the system in the design phase is embedded within a Bayesian network (BN).

UAM↗
NASA NTRS2004

Deployment process, mechanization, and testing for the Mars Exploration Rovers

NASA’s Mar Exploration Rover (MER) robotic prospectors were produced in an environment of unusually challenging schedule, volume, and mass restrictions. The technical challenges pushed the system’s design towards extensive integration of function, which resulted in complex system engineering issues. One example of the system’s integrated complexity can be found in the deployment process for the rover. Part of this process, rover “standup”, is outlined in this paper. Particular attention is given to the Rover Lift Mechanism’s (RLM) role and its design. Analysis methods are presented and compared to test results. It is shown that because prudent design principles were followed, a robust mechanism was created that minimized the duration of integration and test, and enabled recovery without perturbing related systems when reasonably foreseeable problems did occur. Examples of avoidable, unnecessary difficulty are also presented.

Iskenderian, Ted C.↗
NASA NTRS2003

The development of inflatable array antennas

The deployable array antenna using an inflatable or thin-membrane structure has been identified as one of the enabling technologies to achieve low-mass, high packaging efficiency, low cost, and reliable deployment for future NASNJPL spacebome high-gain and large aperture antennas. Array antennas, when compared to parabolic reflectors, although suffering from limited bandwidth performance, offer wide-angle beam scanning capability and a more reliable flat “natural” aperture. To demonstrate the feasibility and capability of this low-mass array technology, three antenna concepts using inflatable and thin-membrane structures were initiated in 1997 at JPL and several breadboard units have been successfully developed. These three concepts are (1) the inflatable phased array, (2) the inflatable reflectarray, and (3) frame-supported thin membrane array antenna. All three concepts utilize the printed microstrip antenna technology. Although all three concepts will be briefly presented, this paper will discuss in more detail of the recent development of the second concept. The first concept of inflatable phased arrays that have been constructed are 3 to 5-meter size L-band dual-polarized synthetic aperture radar (SAR) arrays for Earth remote sensing application. They all consist of a rectangular configuration with inflatable cylindrical tubes that support and tension a multi-layer thin-membrane radiating aperture with microstrip patches and microstrip power divider lines. For the second concept, an inflatable reflectarray was developed for future deep-space telecom applications. It is a 3m Ka-band inflatable reflectarray (1.8 kg/m2). This reflectarray uses inflated torus tubes to support and tension a flat-membrane reflectarray surface. The reflectarray surface emulates a curved parabolic reflecting surface. However, because of its flat surface being a “natural surface”, it is much easier to achieve and more reliable to maintain the required surface tolerance than that of a curved parabola during long space flight. For the third concept, an L-band dual polarized SAR array with a 5m x 3m aperture and 2.5 kg/m2 of mass has recently been demonstrated. It consists of seven foldable panels each having a rectangular frame that supports a two-layer thinmembrane microstrip subarray aperture. Each frame is made of light-weight graphite composite material. The chief advantage of this deployable “frame” concept is that each frame is able to rigidly support an appropriate number of T/R modules and phase shifters to achieve the desired power distribution and beam scanning. Several technology challenges, such as the development of rigidizable inflatable tubes, a controlled deployment mechanism, thin-membrane thermal effects, a low-mass inflation system, membrane mounted T/R modules, means to counter surface tolerance issues, etc. are being investigated and will be discussed in the presentation. With foreseeable success in the development of these challenging areas, the inflatable/thin-membrane array antennas could be mature enough in a few years for actual space flight.

Lou, Michael↗