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NASA NTRS2016

Utilizing the ISS Mission as a Testbed to Develop Cognitive Communications Systems

The ISS provides an excellent opportunity for pioneering artificial intelligence software to meet the challenges of real-time communications (comm) link management. This opportunity empowers the ISS Program to forge a testbed for developing cognitive communications systems for the benefit of the ISS mission, manned Low Earth Orbit (LEO) science programs and future planetary exploration programs. In November, 1998, the Flight Operations Directorate (FOD) started the ISS Antenna Manager (IAM) project to develop a single processor supporting multiple comm satellite tracking for two different antenna systems. Further, the processor was developed to be highly adaptable as it supported the ISS mission through all assembly stages. The ISS mission mandated communications specialists with complete knowledge of when the ISS was about to lose or gain comm link service. The current specialty mandated cognizance of large sun-tracking solar arrays and thermal management panels in addition to the highly-dynamic satellite service schedules and rise/set tables. This mission requirement makes the ISS the ideal communications management analogue for future LEO space station and long-duration planetary exploration missions. Future missions, with their precision-pointed, dynamic, laser-based comm links, require complete autonomy for managing high-data rate communications systems. Development of cognitive communications management systems that permit any crew member or payload science specialist, regardless of experience level, to control communications is one of the greater benefits the ISS can offer new space exploration programs. The IAM project met a new mission requirement never previously levied against US space-born communications systems management: process and display the orientation of large solar arrays and thermal control panels based on real-time joint angle telemetry. However, IAM leaves the actual communications availability assessment to human judgement, which introduces unwanted variability because each specialist has a different core of experience with comm link performance. Because the ISS utilizes two different frequency bands, dynamic structure can be occasionally translucent at one frequency while it can completely interdict service at the other frequency. The impact of articulating structure on the comm link can depend on its orientation at the time it impinges on the link. It can become easy for a human specialist to cross-associate experience at one frequency with experience at the other frequency. Additionally, the specialist's experience is incremental, occurring one nine-hour shift at a time. Only the IAM processor experiences the complete 24x7x365 communications link performance for both communications links but, it has no "learning capability." If the IAM processor could be endowed with a cognitive ability to remember past structure-induced comm link outages, based on its knowledge of the ISS position, attitude, communications gear, array joint angles and tracking accuracy, it could convey such experience to the human operator. It could also use its learned communications link behaviors to accurately convey the availability of future communications sessions. Further, the tool could remember how accurately or inaccurately it predicted availability and correct future predictions based on past performance. The IAM tool could learn frequency-specific impacts due to spacecraft structures and pass that information along as "experience." Such development would provide a single artificial intelligence processor that could provide two different experience bases. If it also "knew" the satellite service schedule, it could distinguish structure blockage from schedule or planet blockage and then quickly switch to another satellite. Alternatively, just as a human operator could judge, a cognizant comm system based on the IAM model could "know" that the blockage is not going to last very long and continue tracking a comm satellite, waiting for it to track away from structure. Ultimately, once this capability was fully developed and tested in the Mission Control Center, it could be transferred on-orbit to support development of operations concepts that include more advanced cognitive communications systems. Future applications of this capability are easily foreseen because even more dynamic satellite constellations with more nodes and greater capability are coming. Currently, the ISS fully employs its high-data-rate return link for harvesting payload science. In the coming months, it will double that data rate and is forecast to fully utilize that capability. Already there is talk of an upgrade that quadruples the current data rate allocated to ISS payload science before the end of its mission and laser comm links have already been tested from the ISS. Every data rate upgrade mandates more complicated and sensitive communications equipment which implies greater expertise invested in the human operator. Future on-orbit cognizant comm systems will be needed to meet greater performance demands aboard larger, far more complicated spacecraft. In the LEO environment, the old-style one-satellite-per-spacecraft operations concept will give way to a new concept of a single customer spacecraft simultaneously using multiple comm satellites. Much more highly-dynamic manned LEO missions with decades of crew members potentially increase the demand for communications link performance. A cognizant on-board communications system will meet advanced communications demands from future LEO missions and future planetary missions. The ISS has fledgling components of future exploration programs, both LEO and planetary. Further, the Flight Operations Directorate, through the IAM project, has already begun to develop a communications management system that attempts to solve advanced problems ideally represented by dynamic structure impacting scheduled satellite service. With an earnest project to integrate artificial intelligence into the IAM processor, the ISS Program could develop a cognizant communications system that could be adapted and transferred to future on-orbit avionics designs.

Jackson, Dan↗
NASA NTRS2013

Orion GNC Mitigation Efforts for Van Allen Radiation

The Orion Crew Module (CM) is NASA's next generation manned space vehicle, scheduled to return humans to lunar orbit in the coming decade. The Orion avionics and GN&C architectures have progressed through a number of project phases and are nearing completion of a major milestone. The first unmanned test mission, dubbed "Exploration Flight Test One" (EFT-1) is scheduled to launch from NASA Kennedy Space Center late next year and provides the first integrated test of all the vehicle systems, avionics and software. The EFT-1 mission will be an unmanned test flight that includes a high speed re-entry from an elliptical orbit, which will be launched on an expendable launch vehicle (ELV). The ELV will place CM and the ELV upper stage into a low Earth orbit (LEO) for one revolution. After the first LEO, the ELV upper stage will re-ignite and place the combined upper stage/CM into an elliptical orbit whose perigee results in a high energy entry to test CM response in a relatively high velocity, high heating environment. While not producing entry velocities as high as those experienced in returning from a lunar orbit, the trajectory was chosen to provide higher stresses on the thermal protection and guided entry systems, as compared against a lower energy LEO entry. However the required entry geometry with constraints on inclination and landing site result in a trajectory that lingers for many hours in the Van Allen radiation belts. This exposes the vehicle and avionics to much higher levels of high energy proton radiation than a typical LEO or lunar trajectory would encounter. As a result, Van Allen radiation poses a significant risk to the Orion avionics system, and particularly the Flight Control Module (FCM) computers that house the GN&C flight software. The measures taken by the Orion GN&C, Flight Software and Avionics teams to mitigate the risks associated with the Van Allen radiation on EFT-1 are covered in the paper. Background on the Orion avionics subsystem is provided, as well as an overview of the GN&C software architecture. The measures taken to handle radiation induced failure of the one or both of the FCM's are presented, and finally simulation and actual hardware-in-the-loop (HWIL) results are shown confirming the validity of the implementation. The paper presents an overview of the Orion avionics architecture describing the GNC sensors, onboard data network as well as the flight control computers and their planned restart capabilities. GN&C sensors include two Orion Inertial Measurement Units (OIMU's), a Vision Processing Unit (VPU) to process camera images, three barometric altimeters and a single GPS receiver. All of the sensors communicate to one of two Power and Data Units (PDU's). The PDU's multiplex analog and serial data from the sensors and write the data to the Orion Data Network (ODN). The OIMU s write measurement messages directly as onto the ODN, but they are routed through PDU network switches.

King, Ellis T.↗
NASA NTRS2005

Progress on the Plasmoid Thruster Experiment (PTX)

A plasmoid, also called a compact toroid, is a compact plasma structure with an integral magnetic field, that may be categorized according to the relative strength of the poloidal and toroidal magnetic field (Bp and Bt, respectively). An object with Bp/Bt much greater than 1 is called a Field Reverse Configuration (FRC); if Bp = Bt, it is called a Spheromak. The plasmoid thruster is a pulsed inductive device which operates by repetitively producing plasmoids that are accelerated and ejected at high velocity. As the process is inductive, this thruster avoids the problem of electrode erosion. Also, the magnetic structure of the plasmoid should suppress thermal and mass losses to the wall, and improve detachment of the plasma exhaust from the thruster. This concept should be capable of producing an Isp of 5,000 seconds and greater, with thrust densities of order 10(exp 5) N/sq m. The plasmoid thruster consists chiefly of a conical theta-pinch coil. Propellant is introduced onto a bias magnetic field, produced by an auxiliary coil, and is then pre-ionized, freezing in the magnetic field. The theta-pinch coil is then energized producing a field aligned anti- parallel to the bias field. The reversed field reconnects with the bias field to form the plasmoid. The magnetic pressure of the reversed field accelerates the plasmoid out of the thruster . A series of experiments have been conducted on the PTX device, which consisted of a single turn conical theta-pinch coil, driven by a 560 nF, 35 kV capacitor bank, which rang at a frequency of 500 kHz, and served all three functions required for formation: pre-ionization, bias field loading, and field reversal. Initial ionization was found to occur in an annular region at the exit plane of the coil, and was found to be reproducible with a variety of gases, including H2, D2, Ar, and an H2/N2 mixture (75% / 25%). A fast gas valve for injecting propellant has been tested, as well as a ringing pre-ionization circuit (operating at 5 Mhz) to better control the plasmoid formation. Velocities as high as 20 km/s have been measured for a plasmoid propagating into a static back-fill of neutral gas. Magnetic field and density measurements indicate that the plasmoid retains its structure well into the down-stream exhaust region, and that it is capable of pushing a dense cloud of neutral gas in front of it. Further experiments will focus on the effects of coil geometry and bias-field strength on the performance of the device. A high-power solid-state switching system is being developed in order to replace the spark-gap switch.

Martin, Adam↗
NASA NTRS2015

Hardware in the Loop Testing of an Iodine-Fed Hall Thruster

CUBESATS are relatively new spacecraft platforms that are typically deployed from a launch vehicle as a secondary payload,1 providing low-cost access to space for a wide range of end-users. These satellites are comprised of building blocks having dimensions of 10x10x10 cm cu and a mass of 1.33 kg (a 1-U size). While providing low-cost access to space, a major operational limitation is the lack of a propulsion system that can fit within a CubeSat and is capable of executing high delta v maneuvers. This makes it difficult to use CubeSats on missions requiring certain types of maneuvers (i.e. formation flying, spacecraft rendezvous). Recently, work has been performed investigating the use of iodine as a propellant for Hall-effect thrusters (HETs) 2 that could subsequently be used to provide a high specific impulse path to CubeSat propulsion. Iodine stores as a dense solid at very low pressures, making it acceptable as a propellant on a secondary payload. It has exceptionally high ρIsp (density times specific impulse), making it an enabling technology for small satellite near-term applications and providing the potential for systems-level advantages over mid-term high power electric propulsion options. Iodine flow can also be thermally regulated, subliming at relatively low temperature ( less than100 C) to yield I2 vapor at or below 50 torr. At low power, the measured performance of an iodine-fed HET is very similar to that of a state-of-the-art xenon-fed thruster. Just as importantly, the current-voltage discharge characteristics of low power iodine-fed and xenon-fed thrusters are remarkably similar, potentially reducing development and qualifications costs by making it possible to use an already-qualified xenon-HET PPU in an iodine-fed system. Finally, a cold surface can be installed in a vacuum test chamber on which expended iodine propellant can deposit. In addition, the temperature doesn't have to be extremely cold to maintain a low vapor pressure in the vacuum chamber (it is under 10(exp -6) torr at -75 C), making it possible to 'cryopump' the propellant with lower-cost recirculating refrigerant-based systems as opposed to using liquid nitrogen or low temperature gaseous helium cryopanels. In the present paper, we describe testing performed using an iodine-fed 200 W Hall thruster mounted to a thrust stand and operated in conjunction with MSFCs Small Projects Rapid Integration and Test Environment (SPRITE) Portable Hardware In the Loop (PHIL) hardware. This work is performed in support of the iodine satellite (iSAT) project, which aims to fly a 200-W iodine-fed thruster on a 12-U CubeSat. The SPRITE PHIL hardware allows a given vehicle to do a checkout of its avionics algorithm by allowing it to monitor and feed data to simulated sensors and effectors in a digital environment. These data are then used to determine the attitude of the vehicle and a separate computer is used to interpret the data set and visualize it using a 3D graphical interface. The PHIL hardware allows the testing of the vehicles bus by providing 'real' hardware interfaces (in the case of this test a real RS422 bus) and specific components can be modeled to show their interactions with the avionics algorithm (e.g. a thruster model). For the iSAT project the PHIL is used to visualize the operating cycle of the thruster and the subsequent effect this thrusting has on the attitude of the satellite over a given period of time. The test is controlled using software running on an Andrews Space Cortex 160 flight computer. This computer is the current baseline for a full iSAT mission. While the test could be conducted with a lab computer and software, the team chose to exercise the propulsion system with a representative CubeSat-class computer. For purposes of this test, the "flight" software monitored the propulsion and PPU systems, controlled operation of the thruster, and provided thruster state data to the PHIL simulation. Commands to operate the thruster were initiated from an operator's workstation outside the vacuum chamber and passed through the Cortex 160 to exercise portions of the flight avionics. Two custom-designed pieces of electronics hardware have been designed to operate the propellant feed system. One piece of hardware is an auxiliary board that controls a latch valve, proportional flow control valves (PFCVs) and valve heaters as well as measuring pressures, temperatures and PFCV feedback voltage. An onboard FPGA provides a serial link for issuing commands and manages all lower level input-output functions. The other piece of hardware is a power distribution board, which accepts a standard bus voltage input and converts this voltage into all the different current-voltage types required to operate the auxiliary board. These electronics boards are located in the vacuum chamber near the thruster, exposing this hardware to both the vacuum and plasma environments they would encounter during a mission, with these components communicating to the flight computer through an RS-422 interface. The auxiliary board FPGA provides a 28V MOSFET switch circuit with a 20ms pulse to open or close the iodine propellant feed system latch valve. The FPGA provides a pulse width modulation (PWM) signal to a DC/DC boost converter to produce the 12-120V needed for control of the proportional flow control valve. There are eight MOSFET-switched heating circuits in the system. Heaters are 28V and located in the latch valve, PFCV, propellant tank and propellant feed lines. Both the latch valve and PFCV have thermistors built into them for temperature monitoring. There are also seven resistance temperature device (RTD) circuits on the auxiliary board that can be used to measure the propellant tank and feedline temperatures. The signals are conditioned and sent to an analog to digital converter (ADC), which is directly commanded and controlled by the FPGA.

Polzin, Kurt A.↗
NASA NTRSDate not supplied

Effect of salinity on the preservation of biomarkers in hypersaline microbial mat kerogens

Kerogen is the residue that remains after the minerals and organic compounds have been extracted from a rock using acid and organic solvents, respectively [1]. It is not only the largest organic carbon sink in the geological record but the best-preserved fraction due to its recalcitrance and ability to retain syngenetic source information during deposition [2]. Due to the complex, macromolecular, cross-linked polymeric structure of kerogen, it is difficult to analyse intact, often requiring breakdown into smaller subunits through thermal (pyrolysis) or chemical treatment (chemolysis) [3]. Saline and hypersaline environments host diverse microbial communities, which can trap and bind organic matrices such as cellular components (e.g., extracellular polymeric substances, cell wall, peptidoglycan, sheath material, etc.) with sediments, forming layered, laminated structures called microbial mats. Here we present depth profiles of two hypersaline cores through a microbial mat with differing total salinities. We looked at the composition of organic compounds released from kerogen during high temperature, hydrogen-assisted, pyrolysis to understand the effect of salinity on the composition and timing of their incorporation [4]. Field Site: The Exportadora del Sal S. A. (ESSA) saltern of Guerrero Negro (Baja California Sur, Mexico) lies within a typical sabhka environment adjacent to Laguna Ojo de Liebre. Note the spatial extent of the 13 major ponds of the ESSA system. The GN ponds thrive under well-monitored and stable conditions with steady state accretion and degradation of mat layers (around 0.5–1.4 cm per year). Organic mats typically attain up to 10 cm in thickness, depending on the location, which represents about 60 years of growth since these ponds were established. Sedimentation rate is rapid in these non-lithifying and non-mineralising mats, 1–1.5 cm per year. This environment is ideal for investigating in situ lipid preservation and diagenesis without the influence of constantly changing physical parameters. Methods: P4n5 and P5AB cores were collected as ~9 cm and 6.5 cm fresh cores, respectively, in June 2001 and September 2010, respectively from the ESSA saltern. The P4n5 core (9-9.1% salinity) was taken from Pond 4 near 5 and sub-divided into 10 layers. The P5AB core (11.2% salinity) was taken from Pond 5A near 5B and sub-divided into 8 layers. Lyophilised microbial mat powders were solvent-extracted using a modified Bligh-Dyer method and analysed by gas chromatography-mass spectrometry (GC-MS). Additionally, a subset of layers—layer 4 and layer 7—which represented active biomass and sediment-processed, respectively, were subjected to mild-acid methanolysis. The respective residues from conventional solvent extraction and acid methanolysis were loaded with a molybdenum sulfide catalyst and placed into a stainless-steel reactor. Samples were run on the hydropyrolysis set up (heated to 500 °C with 13-15 MPa of H2 pressure), extracted, and analysed by GC-MS. Results: Molecular profiles from the two ponds were significantly different and reflect the contributions of different photosynthetic and respiratory microbial communities to preserved organic matter. For example, the higher salinity P5AB core showed evidence of greater archaeal inputs (similarly observed in lab culture experiments [5]) as well as potential kerogen-bound carotenoids/carotenoid rearranged products or fragments. A hydrophobic emulsion formed during the acid methanolysis processing of layer 4 from both P4n5 and P5AB and layer 7 of P5AB. Hydropyrolysis of this hydrophobic residues released a greater abundance of polycyclic lipids relative to the pre-extracted control. Implications and Future Work: Catalytic hydropyrolysis of kerogen can rapidly generate abundant saturated pyrolysate products from the bound biomarker pool without altering the structures or stereochemistries of the products [6]. Chemical processing of solvent-extractable residues indicated that cellular matrices such as extracellular polymeric substances (EPS) may play a role in the sequestration of polycyclic lipid biomarkers such as steranes and hopanes. Their higher relative abundance compared to the pre-extracted control in the higher salinity layers and cores preliminarily aligns with this hypothesis, although further experiments are required to confirm this. It has been well-documented that EPS plays an important role in mineralisation, specifically carbonate formation, in microbial ecosystems. EPS can enhance calcium carbonate precipitation by providing diffusion-limited sites that create alkalinity gradients in response to microbial processes [7]. It has been experimentally demonstrated that salinity influences the total amount of EPS (both loosely- and tightly-bound) which increases with increasing salinity [8]. The higher salinity at Guerrero Negro switches the microbial population from filamentous Microcoleus to being dominated by Phormidium, Oscillatoria, and unicellular cyanobacteria. We demonstrated that lipid binding into kerogen via strong covalent linkages occurs at the very earliest stages of sedimentary diagenesis. We are currently investigating the influence of salinity on organic preservation through experimental and modelling approaches. Understanding how key biomarkers transform into preserved organic matter (i.e., from precursor biolipids to bound geolipids) in brine ecosystems will aid the search for organic biosignatures on other planetary bodies, especially Icy Moons and modern Mars.

hypersaline↗
NASA NTRS1999

Dynamics of Single Chains of Suspended Ferrofluid Particles

We present an experimental study of the dynamics of isolated chains made of super-paramagnetic particles under the influence of a magnetic field. The motivation of this work is to understand if the chain fluctuations exist and, if it does, how does the fluctuation affect chain aggregation. We find that single chains strongly fluctuate and that the characteristic frequency of their fluctuations is inversely proportional to the magnetic field strength. The higher the field the lower the characteristic frequency of the chain fluctuations. In the high magnetic field limit, chains behave like rigid rods without any internal motions. In this work, we used ferrofluid particles suspended in water. These particles do not have any intrinsic magnetization. Once a magnetic field is applied, a dipole moment is induced in each particle, proportional to the magnetic field. A dipolar magnetic interaction then occurs between particles. If dipole-dipole magnetic energy is higher than the thermal energy, the result is a structure change inside the dipolar fluid. The ratio of these two energies is expressed by a coupling constant lambda as: lambda = (pi(a(exp 3))(chi(exp 2))(mu(sub 0))(H(sub 0))(exp 2))/18kT Where a is the particle radius, mu(sub 0) is the vacuum magnetic permeability, H(sub 0) the applied magnetic field, k the Boltzmann constant and T the absolute temperature. If lambda > 1, magnetic particles form chains along the field direction. The lateral coalescence of several chains may form bigger aggregates especially if the particle volume fraction is high. While many studies and applications deal with the rheological properties and the structural changes of these dipolar fluids, this work focuses on the understanding of the chain dynamics. In order to probe the chain dynamics, we used dynamic light scattering (DLS) in self-beating mode as our experimental technique. The experimental geometry is such that the scattering plane is perpendicular to the magnetic field. Therefore, only motions in this plane are probed. A very dilute sample of a ferrofluid emulsion with a particle volume fraction of 10(exp -5) is used in this experiment. We chose such a low volume fraction to avoid multiple light scattering as well as lateral chain-chain aggregation. DLS measures the dynamic structure factor S(q,t) of the sample (q is the scattering wave vector, t is the time). In the absence of the magnetic field, identical particles of ferrofluid droplets are randomly distributed and S(q,t) reduces to exp(-q(exp 2)2D(sub 0)t). D(sub 0)=(kT/(6(pi)(eta)(a)) is the diffusion coefficient of Brownian particles (where Xi = (6(pi)(eta)(a)) is the Stokes frictional coefficient of a spherical particle in a fluid of viscosity eta). If interactions or polydispersity can not be ignored, an effective diffusion coefficient is introduced. Formally, D(sub eff) is defined as: D(sub eff) = - q(exp -2) partial derivative of (ln(S(q,t)) with respect to time, as t goes to 0. D(sub eff) reduces to D(sub 0) if no interactions and only a few particles size are present. Therefore, we can use DLS to measure particle size. The particle radius was found to be a=0.23 mu m with 7% of polydispersity. In this case, if we vary the scattering angle theta (and so q) we do not have any change in the measured diffusion coefficient: it is q-independent. When a magnetic field is applied, particles aggregate into chains if lambda > 1. We first studied the kinetics of the chain formation when lambda = 406. At a fixed scattering angle, we measured diffusion coefficient D(sub eff) as a function of time. Experimentally, we find that D(sub eff) decreases monotonously with time. Physically, this means that chains are becoming longer and longer. Since we are only sensitive to motions in the scattering plane and since chains have their main axis perpendicular to this plane, the measured diffusion coefficient is the trans-verse diffusion coefficient. We can relate D(sub eff) to the mean number of particles per chain N(t) at a given time and to the diffusion coefficient of an isolated particle D(sub 0) as D(sub eff)=f(N(t))D(sub 0). Since f(N) is known from other recent work, N can be expressed as a function of the time. We found a square root dependency: N(t) proportional to the square root of t. As expected for very low volume fraction, this behavior is characteristic of a diffusion-limited aggregation as suggested by several authors and by our previous work. In this study, we focus on the dependence of the effective diffusion coefficient on the scattering angle and the magnetic field strength. After the magnetic field is applied (lambda = 406) for a long time, typically 6 hours, kinetics of chain formation becomes very slow. Chain size does not vary much over the next hour period. Thus, we can perform different interesting experiments. First, at a fixed magnetic field, we measure the effective diffusion coefficient as a function of the scattering angle (from 5 to 130 deg). Our results show that the measured diffusion coefficient increases linearly with the scattering angle: D(sub eff) proportional to q. If we do the same experiment for different lambda values, D(sub eff) depends on lambda as D(sub eff) proportional to lambda(exp -1/2). We also find for different lambda values that the same asymptotic D(sub eff) value is obtained when q approaches zero. The angle dependency of D(sub eff) suggests that an additional motion exists besides chain drifting. Chain size is constant during experiment, which was verified by measuring the same diffusion coefficient at the beginning and at the end of the angle switching. If chains are rigid, D(sub eff) is independent of q. Therefore, we found that D(sub eff) not only measures the motion of the entire chain but also its internal fluctuations. These internal motions are the fluctuations of the particles in the chain. To understand the q dependency of D(sub eff), let us look at the probing length used. In our study, the characteristic length scale probed is l=2pi/q which is in the range of 0.9<l/a<20. When l is much larger than the particle radius (l/a going to infinity) we are mainly sensitive to the center of mass diffusion of the chain. D(sub eff) is then the diffusion of the entire chain and depends only on N but not on q and lambda. The value D(sub eff) allows us to obtain the number of particles per chain N. In the opposite limit (i.e. l/a < 1), we are sensitive to motions on the size of individual particles. The main contributions to the measured diffusion coefficient come from internal motions of the chains (i.e. particles' fluctuations inside the chain). We investigated also the effect of the chain size on D(sub eff). For the same value of the magnetic interaction lambda and different chain sizes, we found that the slope of D(sub eff) versus q decreases when N increases as a power law D(sub eff) proportional to N(exp -0.7). This is an important behavior because this means that the longer the chain the slower its internal fluctuations besides the whole chain motion.

Cutillas, S.↗