Results for “DISTRIBUTION” — Page 21

NASA NTRS1994

(abstract) Distribution of Unimolecular Lifetimes in Ion-Molecule Association Reactions

The distribution of unimolecular lifetimes of ion-molecule complexes formed in association reactions has been measured by ion cyclotron double-resonance. The mean unimolecular lifetimes of (H(sub 2)C(sub 6)N(sub 2)(sup +))(sup *) and (CH(sub 3)CN.CH(sub 3)(sup +))(sup *) were determined to be 180 (micro)s and 140 (micro)s respectively. A theoretical examination of the distribution of lifetimes of (CH(sub 3)CN.CH(sub 3)(sup +))(sup *) was conducted using a RRKM model. The RRKM distribution, when modified by experimental constraints, was found to be a good approximation of the experimentally determined lifetime distribution. The lifetimes for unimolecular dissociation and radiative relaxation, and the absolute efficiency of collisional relaxation are also reported.

unimolecular lifetimes ion-molecule complexes RRKM↗

NASA NTRS2003

Towards a distributed information architecture for avionics data

Avionics data at the National Aeronautics and Space Administration's (NASA) Jet Propulsion Laboratory (JPL consists of distributed, unmanaged, and heterogeneous information that is hard for flight system design engineers to find and use on new NASA/JPL missions. The development of a systematic approach for capturing, accessing and sharing avionics data critical to the support of NASA/JPL missions and projects is required. We propose a general information architecture for managing the existing distributed avionics data sources and a method for querying and retrieving avionics data using the Object Oriented Data Technology (OODT) framework. OODT uses XML messaging infrastructure that profiles data products and their locations using the ISO-11179 data model for describing data products. Queries against a common data dictionary (which implements the ISO model) are translated to domain dependent source data models, and distributed data products are returned asynchronously through the OODT middleware. Further work will include the ability to 'plug and play' new manufacturer data sources, which are distributed at avionics component manufacturer locations throughout the United States.

Information architecture↗

NASA NTRS2006

Advances in Distributed Operations and Mission Activity Planning for Mars Surface Exploration

A centralized mission activity planning system for any long-term mission, such as the Mars Exploration Rover Mission (MER), is completely infeasible due to budget and geographic constraints. A distributed operations system is key to addressing these constraints; therefore, future system and software engineers must focus on the problem of how to provide a secure, reliable, and distributed mission activity planning system. We will explain how Maestro, the next generation mission activity planning system, with its heavy emphasis on portability and distributed operations has been able to meet these design challenges. MER has been an excellent proving ground for Maestro's new approach to distributed operations. The backend that has been developed for Maestro could benefit many future missions by reducing the cost of centralized operations system architecture.

Mars Exploration Rover (MER)↗

NASA NTRS2015

Fuel Distribution Estimate via Spin Period to Precession Period Ratio for the Advanced Composition Explorer

The spin period to precession period ratio of a non-axisymmetric spin-stabilized spacecraft, the Advanced Composition Explorer (ACE), was used to estimate the remaining mass and distribution of fuel within its propulsion system. This analysis was undertaken once telemetry suggested that two of the four fuel tanks had no propellant remaining, contrary to pre-launch expectations of the propulsion system performance. Numerical integration of possible fuel distributions was used to calculate moments of inertia for the spinning spacecraft. A Fast Fourier Transform (FFT) of output from a dynamics simulation was employed to relate calculated moments of inertia to spin and precession periods. The resulting modeled ratios were compared to the actual spin period to precession period ratio derived from the effect of post-maneuver nutation angle on sun sensor measurements. A Monte Carlo search was performed to tune free parameters using the observed spin period to precession period ratio over the life of the mission. This novel analysis of spin and precession periods indicates that at the time of launch, propellant was distributed unevenly between the two pairs of fuel tanks, with one pair having approximately 20% more propellant than the other pair. Furthermore, it indicates the pair of the tanks with less fuel expelled all of its propellant by 2014 and that approximately 46 kg of propellant remains in the other two tanks, an amount that closely matches the operational fuel accounting estimate. Keywords: Fuel Distribution, Moments of Inertia, Precession, Spin, Nutation

Moment of Inertia↗

NASA NTRS2015

How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null-hypothesis that simulating the presence of a large mass fraction of phyllosilicates in dust aerosols in the size range 2 m, in comparison to a simple model assumption where this is neglected, does not yield a significant effect on the magnitude and geographical distribution of the predicted IFN number. Results from sensitivity experiments are presented as well.

Dust↗

NASA NTRS2017

Creating a Bimodal Drop-Size Distribution in the NASA Glenn Icing Research Tunnel

The Icing Research Tunnel at NASA Glenn has demonstrated that they can create a drop-size distribution that matches the FAA Part 25 Appendix O FZDZ, MVD40 m normalized cumulative volume within 10. This is done by simultaneously spraying the Standard and Mod1 nozzles at the same nozzle air pressure and different nozzle water pressures. It was also found through these tests that the distributions that are measured when the two nozzle sets are sprayed simultaneously closely matched what was found by combining the two individual distributions analytically. Additionally, distributions were compared between spraying all spraybars and also by spraying only every-other spraybar, and were found to match within 4. The cloud liquid water content uniformity for this condition has been found to be excellent: 10. It should be noted, however, that the liquid water content for this condition in the IRT is much higher than the requirement specified in Part 25 Appendix O.

drop-size↗

NASA NTRS2017

Creating a Bimodal Drop-Size Distribution in the NASA Glenn Icing Research Tunnel

The Icing Research Tunnel at NASA Glenn has demonstrated that they can create a drop-size distribution that matches the FAA Part 25 Appendix O FZDZ, MVD <40 microns normalized cumulative volume within 10%. This is done by simultaneously spraying the Standard and Mod1 nozzles at the same nozzle air pressure and different nozzle water pressures. It was also found through these tests that the distributions that are measured when the two nozzle sets are sprayed simultaneously closely matched what was found by combining the two individual distributions analytically. Additionally, distributions were compared between spraying all spraybars and also by spraying only every-other spraybar, and were found to match within 4%. The cloud liquid water content uniformity for this condition has been found to be excellent. It should be noted, however, that the liquid water content for this condition in the IRT is much higher than the requirement specified in Part 25 Appendix O.

bimodal distribution↗

NASA NTRS2019

A Scheduling Algorithm Compatible with a Distributed Management of Arrivals in the National Airspace System

The current system used by the FAA to schedule arrivals is the Traffic Based Flow Manager (TBFM). It is a centralized system that gives an operator (airline) no influence over scheduled times of arrival assigned to its flights. Future systems for managing arrival scheduling are proposed as distributed systems. Such a system is called upon to give operators influence to schedule and negotiate resources for their flights, and to resolve other technical challenges, such as eliminating a single point of failure. A distributed system for managing diverse air traffic will need the capability of computing a schedule for the given arriving flights in a way that complies with the operational constraints. This paper contributes an algorithm that computes such a schedule. Although developed as part of an effort toward a distributed system, the algorithm itself is neither inherently distributed nor inherently centralized and can be used in either type of system.

negotiation↗

NASA NTRSDate not supplied

Distributed Spacecraft Autonomy - Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC) measurements. DSA will be demonstrated onboard the NASA Ames Starling mission – a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets. The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasmasphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input dataset for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software, aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements, which define the range of observability for the satellites, as well as exploitative measurements, which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth’s magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions. As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown. Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middleware provides reliable delivery, routing, and topic subscription features over User Datagram Protocol (UDP). Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarm scalability from 2 satellites to 100 satellites is shown.

Distributed Autonomy↗

NASA NTRS2022

Evaluating Network Performance of Containerized Test Framework for Distributed Space Systems

Distributed space systems are a mission architecture consisting of multiple spacecraft as a cohesive system which provide multipoint sampling, increased mission coverage, or improved sample resolution, while reducing mission risk through redundancy. To fully realize the potential of these systems, eventually scaling to hundreds or thousands of spacecraft, distributed space systems need to be operated as a single entity, which will enable a variety of novel scientific space missions. The Distributed Spacecraft Autonomy (DSA) project is a software project which aims to mature the technology needed for those systems, namely autonomous decision-making and swarm networking. The DSA project leverages a containerized swarm test framework to simulate spacecraft software, which can identify emergent behavior early in development. Container virtualization allows distributed spacecraft systems to be simulated entirely in software on a single computer, avoiding the overhead associated with conventional approaches like hardware facsimiles and virtual machines. For this approach to be effective, the simulated system behavior must not be artificially influenced by the swarm test framework itself. To address this, we present a series of benchmarks to quantify virtual network bandwidth available on a single-host computer and contextualize this against the network and application behavior of the DSA swarm test framework.

Distributed Spacecraft Autonomy↗

NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

NASA NTRSDate not supplied

Flight Test Design and Implementation for Airspace Independent Surveillance Through a Distributed Ground Based Sensor Network

The paper presents a system architecture for distributed sensing, networking and computing, its hardware implementation, and execution of initial flight experiments to validate theoretical findings. It induces development of distributed sensing requirements, framework, and architecture, development of distributed ground node hardware prototypes, integration of all nodes and testing of baseline functionalities, integration of in-house developed perception, migration and tracking software packages, establishing flight scenario and flyable path for a selected UAS, flying the air vehicle along the path, recording sensors measurements, pre-processing them and transferring the resulting data to an optimal computing center. It also addresses the challenges related to pre-flight hardware calibration, clock synchronization, sensor registration and establishing a communication network. Sensors data processing results demonstrate the functionality of the presented distributed architecture and satisfactory performance of the applied technologies.

Target tracking↗

NASA NTRSDate not supplied

Flight Test Design and Implementation for Independent Surveillance of an Airspace Through a Distributed Ground Sensing Network

The paper presents a system architecture for distributed sensing, networking and computing, its hardware implementation, and execution of initial flight experiments to validate theoretical findings. It induces development of distributed sensing requirements, framework, and architecture, development of distributed ground node hardware prototypes, integration of all nodes and testing of baseline functionalities, integration of in-house developed perception, migration and tracking software packages, establishing flight scenario and flyable path for a selected UAS, flying the air vehicle along the path, recording sensors measurements, pre-processing them and transferring the resulting data to an optimal computing center. It also addresses the challenges related to pre-flight hardware calibration, clock synchronization, sensor registration and establishing a communication network. Sensors data processing results demonstrate the functionality of the presented distributed architecture and satisfactory performance of the applied technologies.

Distributed sensing↗

NASA NTRS1972

Subsonic pressure distributions around a solid model of an inflatable decelerator attached to the base of an ogive-cylinder

A wind-tunnel investigation was conducted at free-stream Mach numbers from 0.20 to 1.00 and corresponding Reynolds numbers, based on maximum afterbody diameter, from 2.25 x one million to 6.90 x one million on a solid model of an attached inflatable decelerator (AID) connected to the base of an ogive-cylinder. Tests were conducted to obtain ram-air and surface pressure distributions about the AID. AID shapes derived for subsonic deployment are dependent on the pressure distributions used in their derivation, and the different shapes obtained are dependent on the Mach number for which the design is made. The resulting pressure distributions were used in a design program to obtain new shapes which were compared with the original pressure-distribution shape.

Sawyer, J. W.↗

NASA NTRS1972

Pitot-pressure distributions of the flow field of a delta-wing orbiter

Pitot pressure distributions of the flow field of a 0.0075-scale model of a typical delta wing shuttle orbiter are presented. Results are given for the windward and leeward sides on centerline in the angle-of-attack plane from wind tunnel tests conducted in air. Distributions are shown for three axial stations X/L = .35, .60, and .98 and for angles of attack from 0 to 60 deg. The tests were made at a Mach number of 7.4 and for Reynolds numbers based on body length from 1,500,000 to 9,000,000. The windward distributions at the two survey stations forward of the body boat tail demonstrate the compressive aspects of the flow from the shock wave to the body. Conversely, the distributions at the aft station display an expansion of the flow that is attributed to body boat tail. On the lee side, results are given at low angles of attack that illustrate the complicating aspects of the canopy on the flow field, while results are given to show the effects of flow separation at high angles of attack.

Cleary, J. W.↗

NASA NTRS1972

Applications of the theory of optimal control of distributed-parameter systems to structural optimization

An extension of classical methods of optimal control theory for systems described by ordinary differential equations to distributed-parameter systems described by partial differential equations is presented. An application is given involving the minimum-mass design of a simply-supported shear plate with a fixed fundamental frequency of vibration. An optimal plate thickness distribution in analytical form is found. The case of a minimum-mass design of an elastic sandwich plate whose fundamental frequency of free vibration is fixed. Under the most general conditions, the optimization problem reduces to the solution of two simultaneous partial differential equations involving the optimal thickness distribution and the modal displacement. One equation is the uniform energy distribution expression which was found by Ashley and McIntosh for the optimal design of one-dimensional structures with frequency constraints, and by Prager and Taylor for various design criteria in one and two dimensions. The second equation requires dynamic equilibrium at the preassigned vibration frequency.

Armand, J. P.↗

NASA NTRS1972

Ring current particle distributions during the magnetic storms of 16-18 December 1971

In an effort to summarize the constrasting development of the stormtime ring currents during the December 16-18, 1971 magnetic storms, maps were drawn indicating the proton energy density spatial/temporal distributions. The maps contain distributions for the 5 to 138 keV protons for each of seven orbits. The first storm was not characteristic of a single substorm nor a fully developed magnetic storm, but it was comprised of a sudden commencement, a positive phase, and multiple substorms producing a small depression in the magnetic field. The second storm was classical in development with a short two hour growth phase. Energy density distribution constrasts for the two storms show the second storm displayed three dominant features over the first storm. They were: (1) the intensities were 2 1/2 times larger, (2) the depths of penetration were 1/2 to 1 Reynolds number lower, and (3) the distribution became symmetric.

Smith, P. H.↗