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NASA NTRSDate not supplied

Emulated Spacecraft Communication Testbed for Evaluating Cognitive Networking Technology

The ability to emulate the full space protocol stack is an essential aspect required to evaluate and mature cognitive communication capabilities. The interaction between the physical layer and network layers is key to developing network optimizations for a dynamic and complex environment. We present a laboratory testbed for the evaluation of cognitive radio and networking techniques applied to space communications. The testbed is a high fidelity, flight-like hardware testbed consisting of software-defined radios, channel emulators, modems, and orbital analysis and scheduling software. The testbed uses RF links with signal quality, propagation delay, and Doppler effects driven by orbital mechanics simulations of emulated spacecraft. Our framework enables control of link bidirectionality, data rates, and interference sources. In addition to hardware radio nodes, the testbed can incorporate virtualized emulated nodes for larger and more challenging network scenarios. Our approach to a cognitive communication system uses delay tolerant networking (DTN) to mitigate the challenges of the space environment. While many DTN networks use only preplanned schedules, our system uses User-Initiated Service (UIS) to dynamically schedule service providers. Software-defined radio allows the system to adapt to a variety of service providers. Integration of DTN, UIS, and software-defined radio technologies provides a framework for the implementation of a cognitive communication system. This paper describes the testbed capabilities, network emulation approach, component integration, and initial end-to-end testing results.

cognitive radio↗

NASA NTRS1981

Real time simulation of computer-assisted sequencing of terminal area operations

A simulation was developed to investigate the utilization of computer assisted decision making for the task of sequencing and scheduling aircraft in a high density terminal area. The simulation incorporates a decision methodology termed Constrained Position Shifting. This methodology accounts for aircraft velocity profiles, routes, and weight classes in dynamically sequencing and scheduling arriving aircraft. A sample demonstration of Constrained Position Shifting is presented where six aircraft types (including both light and heavy aircraft) are sequenced to land at Denver's Stapleton International Airport. A graphical display is utilized and Constrained Position Shifting with a maximum shift of four positions (rearward or forward) is compared to first come, first serve with respect to arrival at the runway. The implementation of computer assisted sequencing and scheduling methodologies is investigated. A time based control concept will be required and design considerations for such a system are discussed.

Dear, R. G.↗

NASA NTRSDate not supplied

Advances in Modeling Solar System Internet Structures and their Data Flows

With an ever-increasing presence in space, there is also an increasing burden on existing communications infrastructure. We are heading towards an inflection point where the traditional approach of scheduled, single-path communications for space will no longer be viable. One answer is Delay Tolerant Networking (DTN), which takes the once disparate system of point-to-point links and unifies them in a networked architecture, thereby making communications more scalable. However, much work remains for discovering and harnessing the underlying theory of DTN. For example, in the terrestrial setting the interplay between routing domains is well-understood, however this is not the case in DTNs. In this paper, we build up the fundamental foundations of DTN, with an emphasis on modeling time varying networks and data flows across them, with examples of cross-domain routing in a DTN. A lofty goal of DTN is to enable the so-called Solar System Internet (SSI), which implies a standardized and robust suite of protocols. These protocols include routing across disconnected networks using store, carry, and forward mechanisms, which is necessary due to the disconnections, delays, and mobility intrinsic to space networks. Due to these factors, each of which generalize traditional networking, there is a deep and rich theory of DTNs. Here we build off of past successes to broaden this theory while striving to keep actionable results a goal for future implementations and operations. The approach includes modeling the unicast, broadcast, and multicast communications using the language of hypergraphs, which capture the geometric properties of such networked communications algebraically. Also inherent to these networks is their time-varying nature, particularly given mobility, and hence we also cultivate modeling techniques that respect this time dependence. This leads us to develop models using tools from category theory and algebraic geometry, which provide a language well-suited to describing synchronization and optimization over such networks. We also introduce and study a novel generalization of curvature applicable to time-evolving networks, which provides quantitative controls on diffusion processes on the network. Because an interplanetary network would feature links with propagation delays the preclude discovery (feedback) mechanisms, they will always feature a scheduled component. However, it is beneficial to support discovery where possible. While DTNs do not yet have strong definitions for their analogues of autonomous systems or network areas, we show how to join dynamic and schedule-based routing domains, using the language of sheaves, which marks progress towards such definitions. We conclude with a discussion of the progress made, as well as suggestions for future work.

Delay Tolerant Networking↗

NASA NTRS1994

Solution and reasoning reuse in space planning and scheduling applications

In the space domain, as in other domains, the CSP (Constraint Satisfaction Problems) techniques are increasingly used to represent and solve planning and scheduling problems. But these techniques have been developed to solve CSP's which are composed of fixed sets of variables and constraints, whereas many planning and scheduling problems are dynamic. It is therefore important to develop methods which allow a new solution to be rapidly found, as close as possible to the previous one, when some variables or constraints are added or removed. After presenting some existing approaches, this paper proposes a simple and efficient method, which has been developed on the basis of the dynamic backtracking algorithm. This method allows previous solution and reasoning to be reused in the framework of a CSP which is close to the previous one. Some experimental results on general random CSPs and on operation scheduling problems for remote sensing satellites are given.

Verfaillie, Gerard↗

NASA NTRSDate not supplied

Enhancing Autonomous Satellite Communication Systems with Weather-Aware Scheduling and Reconfiguration

NASA currently provides communication support to over 100 satellite missions, and the agency is driving developments in Ka-band communications and network management automation to support additional future missions. At Ka-band frequencies, rain can degrade a communication link by more than 10 dB, which may be mitigated by agile scheduling and data rate control. We present a weather forecasting module for Ka-band communications that is intended to be used in an autonomous network management service that employs machine-to-machine scheduling systems for dynamic user access opportunities. Our forecasting module (NIMBUS) runs on AWS Cloud, consumes the freely and publicly available NOAA MRMS precipitation rate dataset (1km x 1km x 2-min), produces 30-minute Nowcasts using the pySTEPS algorithm, and publishes high level ground station specific link quality predictions. We evaluate two potential NIMBUS outputs, a binary classifier that predicts rain attenuation greater than 3 dB and a rain attenuation estimator, and we backtest these outputs using one year of power measurement data collected from observations of the geostationary ANIK F2 satellite’s Ka-band beacon. We report, with a 30-minute lead time, a binary classifier accuracy of 84% and an estimator RMSE of 1.67 dB. Additionally, we discuss how the NIMBUS module could be incorporated into a user-initiated service framework to enable weather-aware scheduling and reconfiguration. Operating a static link budget with minimal link margin can increase network operation costs by creating additional scheduling tasks due to failed packets, which may require human intervention and/or lead to inefficient asset utilization. The proposed system aims to increase throughput by reducing link margin, while mitigating increases in network operations costs by leveraging autonomous machine-to-machine scheduling, shortened prediction lead times, and advances in precipitation Nowcasting.

satellite communications↗

NASA NTRS1990

Parallel simulated annealing algorithms for cell placement on hypercube multiprocessors

Two parallel algorithms for standard cell placement using simulated annealing are developed to run on distributed-memory message-passing hypercube multiprocessors. The cells can be mapped in a two-dimensional area of a chip onto processors in an n-dimensional hypercube in two ways, such that both small and large cell exchange and displacement moves can be applied. The computation of the cost function in parallel among all the processors in the hypercube is described, along with a distributed data structure that needs to be stored in the hypercube to support the parallel cost evaluation. A novel tree broadcasting strategy is used extensively for updating cell locations in the parallel environment. A dynamic parallel annealing schedule estimates the errors due to interacting parallel moves and adapts the rate of synchronization automatically. Two novel approaches in controlling error in parallel algorithms are described: heuristic cell coloring and adaptive sequence control.

Banerjee, Prithviraj↗

NASA NTRS2009

Physical Principle for Generation of Randomness

A physical principle (more precisely, a principle that incorporates mathematical models used in physics) has been conceived as the basis of a method of generating randomness in Monte Carlo simulations. The principle eliminates the need for conventional random-number generators. The Monte Carlo simulation method is among the most powerful computational methods for solving high-dimensional problems in physics, chemistry, economics, and information processing. The Monte Carlo simulation method is especially effective for solving problems in which computational complexity increases exponentially with dimensionality. The main advantage of the Monte Carlo simulation method over other methods is that the demand on computational resources becomes independent of dimensionality. As augmented by the present principle, the Monte Carlo simulation method becomes an even more powerful computational method that is especially useful for solving problems associated with dynamics of fluids, planning, scheduling, and combinatorial optimization. The present principle is based on coupling of dynamical equations with the corresponding Liouville equation. The randomness is generated by non-Lipschitz instability of dynamics triggered and controlled by feedback from the Liouville equation. (In non-Lipschitz dynamics, the derivatives of solutions of the dynamical equations are not required to be bounded.)

Zak, Michail↗

NASA NTRS2010

Extreme Ultraviolet Variability Experiment (EVE) Multiple EUV Grating Spectrographs (MEGS): Radiometric Calibrations and Results

The NASA Solar Dynamics Observatory (SDO), scheduled for launch in early 2010, incorporates a suite of instruments including the Extreme Ultraviolet Variability Experiment (EVE). EVE has multiple instruments including the Multiple Extreme ultraviolet Grating Spectrographs (MEGS) A, B, and P instruments, the Solar Aspect Monitor (SAM), and the Extreme ultraviolet SpectroPhotometer (ESP). The radiometric calibration of EVE, necessary to convert the instrument counts to physical units, was performed at the National Institute of Standards and Technology (NIST) Synchrotron Ultraviolet Radiation Facility (SURF III) located in Gaithersburg, Maryland. This paper presents the results and derived accuracy of this radiometric calibration for the MEGS A, B, P, and SAM instruments, while the calibration of the ESP instrument is addressed by Didkovsky et al. . In addition, solar measurements that were taken on 14 April 2008, during the NASA 36.240 sounding-rocket flight, are shown for the prototype EVE instruments.

Hock, R. A.↗

NASA NTRS2021

Faster Exo-Earth Yield for HabEx and LUVOIR via Extreme Precision Radial Velocity Prior Knowledge

The HabEx and LUVOIR mission concepts reported science yields for mission scenarios in which the instruments must search for potentially habitable planets, determine their orbits, and, if worthwhile, invest the integration time for a spectral characterization. We evaluate the impact of prior knowledge of planet existence and orbital parameters on yield for four mission concept architectures: HabEx 4m telescope with hybrid starshade and coronagraph, HabEx4m telescope with starshade only, HabEx 4m telescope with coronagraph only, and LUVOIR B8m telescope with coronagraph only. We use perfect prior knowledge to establish an upperbound on yield and use partial prior knowledge from a potential future extreme precision radial velocity (EPRV) instrument with3cm∕ssensitivity. We detail a modeling framework that per-forms dynamically responsive observation scheduling with realistic mission constraints. We evaluate exo-Earth yields against three metrics of spectral characterization for the four mission architectures and three levels of prior knowledge (none, partial, and perfect). The EPRV pro-vided prior knowledge increases yields by∼30%and accelerates by a factor of 3 to 6 the time to achieve half of the yield of the mission. Prior knowledge makes all the mission architectures more nimble and powerful, and most especially starshade-based architectures. With prior knowledge, a small telescope with a starshade can achieve comparable yield to a larger telescope with a coronagraph.

Rhonda Morgan↗

NASA NTRSDate not supplied

Feasibility Study of a Multi-Tilt-Rotor Aircraft as the Artemis Lunar Training Vehicle

The Lunar Landing Research Vehicles (LLRVs) and the Lunar Landing Training Vehicles (LLTVs) provided astronauts of the Apollo program with essential experience and confidence required to complete the missions, and contributed to six successful manned landings on the moon. The primary challenge in terrestrial training was being able to replicate the ratio of tilt angle to linear acceleration that a pilot would experience in lunar gravity. Presently, as the Artemis program seeks to return humans to the Moon by 2025, engineers are evaluating suitable platforms to serve as an In-Flight Trainer (IFT) or Artemis Lunar Training Vehicle (ALTV) for astronauts training in the task of manual landing. The program is investigating the viability of current technology in the field of electric vertical takeoff and landing (eVTOL) vehicles and is evaluating using a multi-tilt-rotor aircraft platform as a candidate for a preliminary ALTV. The tilt-rotor capability enables the vehicle attitude to be decoupled from its flight path, which is a crucial requirement in realistically simulating lunar gravity on Earth. Other key considerations include compensating for a lack of aerodynamic forces while flying through the atmosphere of Earth, as well as the ability to simulate the dynamics of multiple different lander designs for the Human Landing System (HLS) program. This paper details the feasibility study and presents a preliminary flight control architecture for an IFT based on a notional multi-tilt-rotor platform. The model-following control law, based on nonlinear dynamic inversion (NDI), removes the need for gain scheduling. The inner-loop dynamic control allocation strategy consists of a static portion that is optimized offline for trim while compensating for the difference in gravity and a dynamic portion that is computed in real time. The reference model consists of the full closed-loop dynamics of a generic HLS design. The modularity of the flight control architecture enables evaluation of multiple HLS concepts with minimal modifications to the control law. Simulation results of the multi-tilt-rotor configuration following the final portion of the Apollo 11 descent trajectory are shown.

Jing Pei↗

NASA NTRSDate not supplied

Evaluation of Self-Scheduling Exercises Completed by Analog Crewmembers in NASA's Human Exploration Research Analog (HERA)

NASA human spaceflight missions are inherently dynamic and require frequent scheduling changes in order to adapt to changing mission priorities and objectives. Tactical level changes to the mission plan are traditionally made by a team of expert planners and operations specialists on the ground. However, astronauts are expected to execute missions more autonomously during future long duration missions. Astronauts will need to take on some of the responsibility of managing their own schedule while still abiding by the numerous constraints required by human spaceflight operations. This paper summarizes salient elements of crew performance in NASA’s Human Exploration Research Analog Campaign 3. Analog crewmembers completed a series of self-scheduling exercises to evaluate Playbook’s usability towards enabling self-scheduling without support from ground control. Playbook is a self-scheduling software tool designed and developed by our team. We also investigated how to best communicate self-scheduling tasks and constraints to the crew in order to facilitate efficient self-scheduling during isolation in a realistic environment. Our analysis identified that 30 minutes was sufficient to complete complex self-scheduling tasks. Our evaluation also identified differences between individual and collaborative performance; analog crewmembers completed self-scheduling exercises more quickly as a team as opposed to individually and reported lower subjective difficulty ratings overall.

HERA↗

NASA NTRS2019

Airspace Technology Demonstration 3 (ATD-3): Dynamic Routes for Arrivals in Weather (DRAW) Technology Transfer Document Summary Version 2.0

Airspace Technology Demonstration – 3 (ATD-3) is part of NASA’s Airspace Operations and Safety Program (AOSP) – specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multi-year research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the third Research Transition Product (RTP) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan, which is Dynamic Routes for Arrivals in Weather (DRAW). This technology transfer consists of artifacts for DRAW Arrival Metering (AM) Operations delivered in June 2018, DRAW AM updates, and DRAW Extended Metering (XM) Operations. Blue highlighting indicates the new or modified deliverables. Some of the artifacts in this technology transfer have distribution restrictions that need to be followed. Distribution information is noted in each section. DRAW is a trajectory-based system that combines the legacy Dynamic Weather Routes (DWR) weather avoidance technology with an arrival-specific rerouting algorithm and arrival scheduler to improve traffic flows on weather-impacted arrival routes into major airports. First, DRAW identifies flights that could be rerouted to more efficient Standard Terminal Arrival Routes (STARs) that may have previously been impacted by weather. Second, when weather is impacting the arrival routing, DRAW proposes simple arrival route corrections that enable aircraft to stay on their flight plan while avoiding weather. The DRAW system proposes reroutes early enough to allow Time Based Flow Management (TBFM) to make the necessary schedule adjustments. As a result, metering operations can be sustained longer and more consistently in the presence of weather because the arrival schedule accounts for the dynamic routing intent of arrival flights to deviate around weather. The first DRAW tech transfer in June 2018 focused on arrival metering operations with the DRAW algorithm implemented in the NASA Center TRACON Automation System (CTAS) automation software. This tech transfer delivery includes updates for DRAW implemented in FAA’s TBFM 4.7 automation software and preliminary research into DRAW for XM operations.

Isaacson, Douglas R.↗

NASA NTRSDate not supplied

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.

Computational Icing↗

NASA NTRSDate not supplied

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

Computational Icing↗

NASA NTRS2018

Quantification of Dynamic Model Validation Metrics Using Uncertainty Propagation from Requirements

The Space Launch System, NASA's new large launch vehicle for long range space exploration, is presently in the final design and construction phases, with the first launch scheduled for 2019. A dynamic model of the system has been created and is critical for calculation of interface loads and natural frequencies and mode shapes for guidance, navigation, and control (GNC). Because of the program and schedule constraints, a single modal test of the SLS will be performed while bolted down to the Mobile Launch Pad just before the first launch. A Monte Carlo and optimization scheme will be performed to create thousands of possible models based on given dispersions in model properties and to determine which model best fits the natural frequencies and mode shapes from modal test. However, the question still remains as to whether this model is acceptable for the loads and GNC requirements. An uncertainty propagation and quantification (UP and UQ) technique to develop a quantitative set of validation metrics that is based on the flight requirements has therefore been developed and is discussed in this paper. There has been considerable research on UQ and UP and validation in the literature, but very little on propagating the uncertainties from requirements, so most validation metrics are "rules-of-thumb;" this research seeks to come up with more reason-based metrics. One of the main assumptions used to achieve this task is that the uncertainty in the modeling of the fixed boundary condition is accurate, so therefore that same uncertainty can be used in propagating the fixed-test configuration to the free-free actual configuration. The second main technique applied here is the usage of the limit-state formulation to quantify the final probabilistic parameters and to compare them with the requirements. These techniques are explored with a simple lumped spring-mass system and a simplified SLS model. When completed, it is anticipated that this requirements-based validation metric will provide a quantified confidence and probability of success for the final SLS dynamics model, which will be critical for a successful launch program, and can be applied in the many other industries where an accurate dynamic model is required.

Brown, Andrew M.↗

NASA NTRS2007

Potential Fifty Percent Reduction in Saturation Diving Decompression Time Using a Combination of Intermittent Recompression and Exercise

Conventional saturation decompression protocols use linear decompression rates that become progressively slower at shallower depths, consistent with free gas phase control vs. dissolved gas elimination kinetics. If decompression is limited by control of free gas phase, linear decompression is an inefficient strategy. The NASA prebreathe reduction program demonstrated that exercise during O2 prebreathe resulted in a 50% reduction (2 h vs. 4 h) in the saturation decompression time from 14.7 to 4.3 psi and a significant reduction in decompression sickness (DCS: 0 vs. 23.7%). Combining exercise with intermittent recompression, which controls gas phase growth and eliminates supersaturation before exercising, may enable more efficient saturation decompression schedules. A tissue bubble dynamics model (TBDM) was used in conjunction with a NASA exercise prebreathe model (NEPM) that relates tissue inert gas exchange rate constants to exercise (ml O2/kg-min), to develop a schedule for decompression from helium saturation at 400 fsw. The models provide significant prediction (p < 0.001) and goodness of fit with 430 cases of DCS in 6437 laboratory dives for TBDM (p = 0.77) and with 22 cases of DCS in 159 altitude exposures for NEPM (p = 0.70). The models have also been used operationally in over 25,000 dives (TBDM) and 40 spacewalks (NEPM). The standard U.S. Navy (USN) linear saturation decompression schedule from saturation at 400 fsw required 114.5 h with a maximum Bubble Growth Index (BGI(sub max)) of 17.5. Decompression using intermittent recompression combined with two 10 min exercise periods (75% VO2 (sub peak)) per day required 54.25 h (BGI(sub max): 14.7). Combined intermittent recompression and exercise resulted in a theoretical 53% (2.5 day) reduction in decompression time and theoretically lower DCS risk compared to the standard USN decompression schedule. These results warrant future decompression trials to evaluate the efficacy of this approach.

Gernhardt, Michael I.↗

NASA NTRS1994

DTS: Building custom, intelligent schedulers

DTS is a decision-theoretic scheduler, built on top of a flexible toolkit -- this paper focuses on how the toolkit might be reused in future NASA mission schedulers. The toolkit includes a user-customizable scheduling interface, and a 'Just-For-You' optimization engine. The customizable interface is built on two metaphors: objects and dynamic graphs. Objects help to structure problem specifications and related data, while dynamic graphs simplify the specification of graphical schedule editors (such as Gantt charts). The interface can be used with any 'back-end' scheduler, through dynamically-loaded code, interprocess communication, or a shared database. The 'Just-For-You' optimization engine includes user-specific utility functions, automatically compiled heuristic evaluations, and a postprocessing facility for enforcing scheduling policies. The optimization engine is based on BPS, the Bayesian Problem-Solver (1,2), which introduced a similar approach to solving single-agent and adversarial graph search problems.

Hansson, Othar↗

NASA NTRS1990

Tethered satellite system dynamics and control

The first tethered satellite system, scheduled for launch in May 1991, is reviewed. The system dynamics, dynamics control, and dynamics simulations are discussed. Particular attention is given to in-plane and out-of-plane librations; tether oscillation modes; orbiter and sub-satellite dynamics; deployer control system; the sub-satellite attitude measurement and control system; the Aeritalia Dynamics Model; the Martin-Marietta and NASA-MSFC Dynamics Model; and simulation results.

Musetti, B.↗