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At least 343 records · Page 19

Nature of the stratospheric haze on Uranus - Evidence for condensed hydrocarbons

The characteristics and origin of lower-stratosphere haze on Uranus are investigated on the basis of high-phase-angle images obtained at 430-600 nm with the wide-angle and narrow-angle cameras of Voyager 2 during its encounter with Uranus in January 1986. The data-reduction and model-fitting procedures are explained in detail, and the results are presented in extensive tables and graphs. The data are found to be best matched by a haze consisting of particles of modal radius 130 + or - 20 nm and number density 2 + or - 1 per cu cm at the 44-mbar level; such aerosols could be formed by the stratospheric condensation of photochemically produced hydrocarbon gases (locally formed diacetylene and ethane, acetylene, and diacetylene formed at higher altitudes). A total aerosol production rate of (2-15) x 10 to the -17th g/sq cm sec is estimated.

Pollack, James B.↗

Maximum likelihood estimation for distributed parameter models of flexible spacecraft

A distributed-parameter model of the NASA Solar Array Flight Experiment spacecraft structure is constructed on the basis of measurement data and analyzed to generate a priori estimates of modal frequencies and mode shapes. A Newton-Raphson maximum-likelihood algorithm is applied to determine the unknown parameters, using a truncated model for the estimation and the full model for the computation of the higher modes. Numerical results are presented in a series of graphs and briefly discussed, and the significant improvement in computation speed obtained by parallel implementation of the method on a supercomputer is noted.

Taylor, L. W., Jr.↗

The Logic of Reachability

In recent years, Graphplan style reachability analysis and mutual exclusion reasoning have been used in many high performance planning systems. While numerous refinements and extensions have been developed, the basic plan graph structure and reasoning mechanisms used in these systems are tied to the very simple STRIPS model of action. In 1999, Smith and Weld generalized the Graphplan methods for reachability and mutex reasoning to allow actions to have differing durations. However, the representation of actions still has some severe limitations that prevent the use of these techniques for many real-world planning systems. In this paper, we 1) separate the logic of reachability from the particular representation and inference methods used in Graphplan, and 2) extend the notions of reachability and mutual exclusion to more general notions of time and action. As it turns out, the general rules for mutual exclusion reasoning take on a remarkably clean and simple form. However, practical instantiations of them turn out to be messy, and require that we make representation and reasoning choices.

Smith, David E.↗

Cellerator: extending a computer algebra system to include biochemical arrows for signal transduction simulations

Cellerator describes single and multi-cellular signal transduction networks (STN) with a compact, optionally palette-driven, arrow-based notation to represent biochemical reactions and transcriptional activation. Multi-compartment systems are represented as graphs with STNs embedded in each node. Interactions include mass-action, enzymatic, allosteric and connectionist models. Reactions are translated into differential equations and can be solved numerically to generate predictive time courses or output as systems of equations that can be read by other programs. Cellerator simulations are fully extensible and portable to any operating system that supports Mathematica, and can be indefinitely nested within larger data structures to produce highly scaleable models.

Non-NASA Center↗

The Cosmic Ray Electron Excess

This slide presentation reviews the possible sources for the apparent excess of Cosmic Ray Electrons. The presentation reviews the Advanced Thin Ionization Calorimeter (ATIC) instrument, the various parts, how cosmic ray electrons are measured, and shows graphs that review the results of the ATIC instrument measurement. A review of Cosmic Ray Electrons models is explored, along with the source candidates. Scenarios for the excess are reviewed: Supernova remnants (SNR) Pulsar Wind nebulae, or Microquasars. Each of these has some problem that mitigates the argument. The last possibility discussed is Dark Matter. The Anti-Matter Exploration and Light-nuclei Astrophysics (PAMELA) mission is to search for evidence of annihilations of dark matter particles, to search for anti-nuclei, to test cosmic-ray propagation models, and to measure electron and positron spectra. There are slides explaining the results of Pamela and how to compare these with those of the ATIC experiment. Dark matter annihilation is then reviewed, which represent two types of dark matter: Neutralinos, and kaluza-Kline (KK) particles, which are next explained. The future astrophysical measurements, those from GLAST LAT, the Alpha Magnetic Spectrometer (AMS), and HEPCAT are reviewed, in light of assisting in finding an explanation for the observed excess. Also the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) could help by revealing if there are extra dimensions.

Chang, J.↗

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Monte Carlo Tree Search Approach

Numerous unmanned aircraft systems operating at low altitudes to deliver goods and services may one day become ubiquitous in our cities. In the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) framework, such a concept is envisioned, where aerial vehicles operate beyond visual line of sight (BVLOS) within specifically reserved and time stamped “corridors” in the airspace. For example, these corridors or operational intent volumes can connect an aerial vehicle’s origin site to its destination site for package delivery operations. There may also be more than one corridor available for an aerial vehicle to choose from and often different corridors may intersect with one another. Thus, it is imperative to ensure flight trajectories belonging to different aerial vehicles are not in conflict. Per the UTM CONOPs, we assume that a vehicle almost always stays inside its corridor or operational volume. This work provides a framework for strategic deconfliction of UTM or package delivery drones, where we schedule the departure time of all vehicles subject to various temporal constraints (including the corridor deconfliction at the intersections). We present the “multi-route weighted package delivery problem” which serves as an exemplifying model for strategic deconfliction in UTM. In the multi-route weighted package delivery problem, a graph network is given which consists of a set of depots (source) and drop-off (destination) nodes, with multiple routes (defined as a sequence of waypoints) connecting the depots to drop-off nodes. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is for a known set of aerial vehicles to depart from the depots, choose a route and take off time, while avoiding conflicts with other aerial vehicles, and minimizing both risk and distance traveled. We provide a mixed integer linear programming (MILP) formulation of the problem, as well as a heuristic solution based on Monte Carlo Tree Search (MCTS) – a method used in game theory and artificial intelligence – to overcome limitations inherent to optimal solvers. Computational results show the advantages of using MCTS over the MILP formulation; the former can provide a sub-optimal solution quickly, and may sometimes even reach an optimal solution, whereas the latter may not even produce a solution in reasonable time. Furthermore, results from both the MILP formulation and MCTS methods were validated using a preliminary agent-based simulator implementing the UTM concept of operations. Thus, the MCTS method can be seen as a scalable solution to the complex multi-route weighted package delivery problem and may possibly be extended to similar complex optimization problems.

Kenny Chour↗

Reanalysis of Rodent Data from Spacelab Life Sciences-1

The space bioscience field has long been plagued by the challenge of spaceflight with effects of radiation and microgravity. Having multiple and repeated spaceflight experiments for model organisms to solve these space stressors is costly and time consuming. Therefore, reusing and reanalyzing legacy experiments is one way that scientists can draw new conclusions in a timely manner and without using too many resources. Moreover, advances in general biological knowledge allows legacy experiments to be placed into more complete context.Here we aim to analyze all data and metadata taken from rats flown on the SLS-1 mission to create a comprehensive biological model that can be supplemented with current data to allow new discoveries in how space flown organisms adapt to the space environment. Our approach begins with the identification of all the data and metadata, including graphs and tables, for SLS-1 in NASA archives and other sources. Then, each piece of data and metadata will be digitized, reformatted and analyzed. Lastly, a previously developed astronaut model will be used to create the data framework and a comprehensive biological rodent model. The datasets we are using is from the 1991 SpaceLab Life Science 1 (SLS-1) NASA Mission. This was the first designated spacelab mission flown. All 29 rodents were tested for nine days in two different habitats: Research Animal Holding Facility (RAHF) and Animal Enclosure Module (AEM). The rodents were prepared for a live return and compared to a ground control. A total of 30 rodent experiments were accepted as flight studies on the mission. By digitization and reorganizing SLS-1 rat data we will both directly generate new insights and indirectly enable other scientists to by providing the data and metadata in a digitized form.

Space Biology↗

Reanalysis of Rodent Data from Spacelab Life Science-1

The space bioscience field has long been plagued by the challenge of spaceflight with effects of radiation and microgravity. Having multiple and repeated spaceflight experiments for model organisms to solve these space stressors is costly and time consuming. Therefore, reusing and reanalyzing legacy experiments is one way that scientists can draw new conclusions in a timely manner and without using too many resources. Moreover, advances in general biological knowledge allows legacy experiments to be placed into more complete context.Here we aim to analyze all data and metadata taken from rats flown on the SLS-1 mission to create a comprehensive biological model that can be supplemented with current data to allow new discoveries in how space flown organisms adapt to the space environment. Our approach begins with the identification of all the data and metadata, including graphs and tables, for SLS-1 in NASA archives and other sources. Then, each piece of data and metadata will be digitized, reformatted and analyzed. Lastly, a previously developed astronaut model will be used to create the data framework and a comprehensive biological rodent model. The datasets we are using is from the 1991 SpaceLab Life Science 1 (SLS-1) NASA Mission. This was the first designated spacelab mission flown. All 29 rodents were tested for nine days in two different habitats: Research Animal Holding Facility (RAHF) and Animal Enclosure Module (AEM). The rodents were prepared for a live return and compared to a ground control. A total of 30 rodent experiments were accepted as flight studies on the mission. By digitization and reorganizing SLS-1 rat data we will both directly generate new insights and indirectly enable other scientists to by providing the data and metadata in a digitized form.

Space Biology↗

QuantifyML: How good is my machine learning model?

This paper presents an approach, QuantifyML, which employs model counting to assess the learnability and robustness of machine learning models. Typically the efficacy of machine learning models is determined by computing their accuracy statistically on test data sets. However, this may be misleading, if the test data is not representative of the problem that is being studied. Further, two different models may have the same accuracy on a given data set, measured statistically, but may be very different in their behavior on unseen data. Also, models with high accuracy could have poor adversarial robustness. In QuantifyML, our goal is to precisely quantify the extent to which machine learning models have learned and generalized from the given data. In QuantifyML, a trained model is translated into a C program, which is fed to the CBMC model checking tool to produce a formula in Conjunctive Normal Form (CNF), which in turn is analyzed with state-of-the-art model counters to efficiently obtain precise counts w.r.t different outputs. QuantifyML enables i) evaluating the learnability of models by comparing the counts for the outputs to ground truth, expressed as logical predicates (if available), ii) comparing the performance of different models that may be built with different machine learning algorithms (e.g., decision-trees vs. neural networks), and iii) quantifying the robustness of trained models around given inputs. Our evaluation demonstrates these applications of QuantifyML on decision trees and neural networks trained to learn relational properties of graphs, for which we know the ground truth, and to perform image classification, for which we do not have the ground truth, but we can quantify local robustness.

Deep Neural Networks↗

Stirling Engine Dynamic System Modeling

The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.

Nakis, Christopher G.↗

Effects of source vs. interactive actuator assumptions on modelling of a smart structure

Embedded or internal actuators in a structure are being utilized to perform vibration attenuation, pointing maneuvers, damage control, and other adaptive tasks. The controls-structures-interaction (CSI) design process depends strongly on the coupled dynamic response of the structure and the actuators. A bond graph approach is used to guide this analytical study to uncover the effects of certain generic actuator types on the closed-loop, initial condition control of a single-mode structural model and an eighteen-state model of an active truss. So-called 'flow' and 'effort' source actuator types were studied and were shown to have significant differences in closed-loop response for ranges of initial conditions and system open-loop natural frequencies.

Robertshaw, Harry H.↗

Strategies for Quantifying Human Space Flight Performance in the Crew Health and Performance System

The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center is planning a customized approach to quantify human spaceflight performance changes with respect to changes to the CHP system functions and capabilities. Using the Directed Acyclic Graphs (DAG) initiated by NASA’s Human Systems Risk Board (HSRB) [1], the team is surveying potential candidate models and novel strategies that generate metrics suitable for supporting decision making related to how the CHP system may influence human system performance risk. One such investigation includes classic Human Reliability Analysis (HRA) models. Traditionally, HRA methods estimate the occurrence of human errors and their impact on the success of an activity when designing and operating a system. While humans perceive, interpret, decide on, and carry out a course of action, the factors affecting performance and error likelihood are commonly referred to as performance shaping factors (PSFs). Originally developed to alleviate safety concerns related to nuclear power plant operations, HRA methods such as THERP [2] and CREAM [3] dismantle an activity into tasks, requiring elemental steps to be executed, and assess their failure due to predefined PSFs. In this study, we compare generic HRA methods and those that incorporate some human spaceflight aspects, such as sleep conditions (SCREAM [4]), with respect to how they may be adopted to capture performance with an intention to mitigate detrimental outcomes elucidated by the HSRB DAGs. We suggest strategies to quantify astronaut performance specific to spaceflight activities and illustrate how such concepts may help in optimizing the CHP system capabilities with respect to Artemis missions.

dag↗

Mariner 10 interplanetary magnetic field observations - Preliminary results

The results being reported consist primarily of distributions of the hourly average field large-scale properties and fluctuation characteristics by solar rotation for the time interval 7 November 1973 to 5 April 1974, as well as the variation of the daily average field as a function of the distance from the sun between 1 and 0.46 AU. The data indicate that the interplanetary magnetic field (IMF) generally increases with decreasing distance from the sun; the field magnitude distribution broadened as Mariner 10 approached Mercury; the positive sector of the IMF tended to rotate progressively toward the theoretical spiral field direction; and magnitude fluctuations increased with increasing distance from the sun, while vector field fluctuations tended to decrease. Data on radial dependence of the IMF were not consistent with theoretical models and did not coincide with extrapolations based on data gathered by Mariner 4 and 5. Comprehensive graphs and charts illustrate all the data obtained by Mariner 10.

Behannon, K. W.↗

Acoustic measurements of the X-wing rotor

Noise measurements of a stoppable X-wing rotor system model, tested in the Ames 40- by 80-foot wind tunnel, are summarized. Performance, control system stability, and noise of the model were investigated at various forward speeds, tip speeds, collective blade angles, jet blowing velocities, and model attack angles. The model was tested in the rotating wing helicopter configuration, in the fixed wing configuration, and in wing configurations between the two. Noise data obtained in the helicopter configuration at the two highest tip speeds (Mach 0.44 and 0.47) and at wind tunnel speeds below 140 knots are reported. Test configuration and performance information are included. General acoustic measurements (dB, dBA, and PNdB) at six microphone locations are presented for all conditions under which the background noise was below the model noise. More specific measurements (1/3-octave and blade passage frequency harmonic levels) are presented for selected conditions. Graphs of dBA and 1/3-octave spectra, which show the noise trends as functions of operating condition, are included. The noise depends mainly on the jet blowing velocity. The noise levels were highest at moderate jet blowing velocities, less at the highest velocity, and lowest with no blowing at all.

Mosher, M.↗

Oscillating airfoils and their wake

The unsteady phenomena in the wake of an oscillating wing or rotor blade are examined theoretically using the Prandtl approximation of the vortex-transport equation. A mathematical model is developed and applied to such problems as the effect of winglets on the performance of fixed wings and the possibly of employing similar designs in rotor blades. Model predictions for several profiles are compared with published and experimental measurements, and good agreement is found. Graphs and diagrams are provided.

Send, W.↗

Roles of initial condition and vortex pairing in jet noise

Sound generation by vortex pairing in circular and elliptic cold-air jets at Mach 0.15-0.35 is investigated experimentally, with a focus on the effects of initial conditions. The results are presented in graphs and interpreted using the theory of vortex sound proposed by Moehring (1978) and vortex-filament models of jet coherent structure. Tripping the nozzle boundary layer is shown to (1) preempt formation of shear-layer vortices, (2) remove the sound they produce in later pairing, and (3) increase the diffusion of coherent vorticity in the vortex rings. Hence pairing noise should not be significant in practical jets, which are initially turbulent.

Bridges, J. E.↗