Results for “physical rules” — Page 5

NASA NTRS1995

On the nature of spectral features in peculiar DQ white dwarfs

Spectropolarimetric measurements are presented for the DQ white dwarfs ESO 439-162, LHS 1126, and G225-68, whose spectroscopic features in the optical have been interpreted in the past as pressure-shifted or magnetically shifted C2 Swan bands. The results convincingly demonstrate that none of these objects is strongly magnetic, with upper limits of 30, 3, and 2 MG respectively. Since Bergeron et al. (B 94) have recently ruled out the pressure-shift interpretation for LHS 1126 as well, we discuss alternative physical mechanisms for displacing the Swan bands. Although possibilities for explaining the observed shifts may exist, a comparison of the optical spectra (and that of a similar DQ star, LP 77-57) indicates that the locations and shapes of the profiles in all four objects are virtually identical. This last result suggests instead that a different molecular species could be responsible. A detailed chemical equilibrium analysis of H/He/C mixtures under the physical conditions encountered in the atmospheres of these peculiar objects reveals that C2H is a molecule preferentially formed in the photospheric regions. The nature and evolution of these objects are discussed.

Schmidt, Gary D.↗

NASA NTRS2002

Science opportunity analyzer - a multi-mission tool for planning

For many years the diverse scientific community that supports JPL's wide variety ofinterplanetary space missions has needed a tool in order to plan and develop their experiments. The tool needs to be easily adapted to various mission types and portable to the user community. The Science Opportunity Analyzer, SOA, now in its third year of development, is intended to meet this need. SOA is a java-based application that is designed to enable scientists to identify and analyze opportunities for science observations from spacecraft. It differs from other planning tools in that it does not require an in-depth knowledge of the spacecraft command system or operation modes to begin high level planning. Users can, however, develop increasingly detailed levels of design. SOA consists of six major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, Data Output and Communications. Opportunity Search is a GUI driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. The user is given extensive flexibility to customize what is displayed in the view. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily impact the cost to science if flight rule changes occur. Data Output generates information based on the spacecraft's trajectory, opportunity search results or based on a created observation. The data can be viewed either in tabular format or as a graph. Finally, SOA is unique in that it is designed to be able to communicate with a variety of existing planning and sequencing tools. From the very beginning SOA was designed with the user in mind. Extensive surveys of the potential user community were conducted in order to develop the software requirements. Throughout the development period, close ties have been maintained with the science community to insure that the tool maintains its user focus. Although development is still in its early stages, SOA is already developing a user community on the Cassini project, which is depending on this tool for their science planning. There are other tools at JPL that do various pieces of what SOA can do; however, there is no other tool which combines all these functions and presents them to the user in such a convenient, cohesive, and easy to use fashion.

SOA science planning mission operations sequence s↗

NASA NTRS2016

Contributions of Solar Wind and Micrometeoroids to Molecular Hydrogen in the Lunar Exosphere

We investigate the density and spatial distribution of the H2 exosphere of the Moon assuming various source mechanisms. Owing to its low mass, escape is non-negligible for H2. For high-energy source mechanisms, a high percentage of the released molecules escape lunar gravity. Thus, the H2 spatial distribution for high-energy release processes reflects the spatial distribution of the source. For low energy release mechanisms, the escape rate decreases and the H2 redistributes itself predominantly to reflect a thermally accommodated exosphere. However, a small dependence on the spatial distribution of the source is superimposed on the thermally accommodated distribution in model simulations, where density is locally enhanced near regions of higher source rate. For an exosphere accommodated to the local surface temperature, a source rate of 2.2 g s-1 is required to produce a steady state density at high latitude of 1200 cm-3. Greater source rates are required to produce the same density for more energetic release mechanisms. Physical sputtering by solar wind and direct delivery of H2 through micrometeoroid bombardment can be ruled out as mechanisms for producing and liberating H2 into the lunar exosphere. Chemical sputtering by the solar wind is the most plausible as a source mechanism and would require 10-50 of the solar wind H+ inventory to be converted to H2 to account for the observations.

Impact↗

NASA NTRS1995

A software tool to design thermal barrier coatings

This paper summarizes work completed for a NASA Phase 1 SBIR program which demonstrated the feasibility of developing a software tool to aid in the design of thermal barrier coating (TBC) systems. Toward this goal, three tasks were undertaken and completed. Task 1 involved the development of a database containing the pertinent thermal and mechanical property data for the top coat, bond coat and substrate materials that comprise a TBC system. Task 2 involved the development of an automated set-up program for generating two dimensional (2D) finite element models of TBC systems. Most importantly, task 3 involved the generation of a rule base to aid in the design of a TBC system. These rules were based on a factorial design of experiments involving FEM results and were generated using a Yates analysis. A previous study had indicated the suitability and benefit of applying finite element analysis to perform computer based experiments to decrease but not eliminate physical experiments on TBC's. This program proved feasibility by expanding on these findings by developing a larger knowledgebase and developing a procedure to extract rules to aid in TBC design.

Petrus, Gregory↗

NASA NTRS1976

Approximate method for calculating transonic flow about lifting wing-body configurations

The three-dimensional problem of transonic flow about lifting wing-body configurations is reduced to a two-variable computational problem with the method of matched asymptotic expansions. The computational problem is solved with the method of relaxation. The method accounts for leading-edge separation, the presence of shock waves, and the presence of solid, slotted, or porous tunnel walls. The Mach number range of the method extends from zero to the supersonic value at which the wing leading edge becomes sonic. A modified form of the transonic area rule which accounts for the effect of lift is developed. This effect is explained from simple physical considerations.

Barnwell, R. W.↗

NASA NTRS1990

Modeling reality

Although powerful computers have allowed complex physical and manmade hardware systems to be modeled successfully, we have encountered persistent problems with the reliability of computer models for systems involving human learning, human action, and human organizations. This is not a misfortune; unlike physical and manmade systems, human systems do not operate under a fixed set of laws. The rules governing the actions allowable in the system can be changed without warning at any moment, and can evolve over time. That the governing laws are inherently unpredictable raises serious questions about the reliability of models when applied to human situations. In these domains, computers are better used, not for prediction and planning, but for aiding humans. Examples are systems that help humans speculate about possible futures, offer advice about possible actions in a domain, systems that gather information from the networks, and systems that track and support work flows in organizations.

Denning, Peter J.↗

NASA NTRS2007

NASA Langley's Approach to the Sandia's Structural Dynamics Challenge Problem

The objective of this challenge is to develop a data-based probabilistic model of uncertainty to predict the behavior of subsystems (payloads) by themselves and while coupled to a primary (target) system. Although this type of analysis is routinely performed and representative of issues faced in real-world system design and integration, there are still several key technical challenges that must be addressed when analyzing uncertain interconnected systems. For example, one key technical challenge is related to the fact that there is limited data on target configurations. Moreover, it is typical to have multiple data sets from experiments conducted at the subsystem level, but often samples sizes are not sufficient to compute high confidence statistics. In this challenge problem additional constraints are placed as ground rules for the participants. One such rule is that mathematical models of the subsystem are limited to linear approximations of the nonlinear physics of the problem at hand. Also, participants are constrained to use these models and the multiple data sets to make predictions about the target system response under completely different input conditions. Our approach involved initially the screening of several different methods. Three of the ones considered are presented herein. The first one is based on the transformation of the modal data to an orthogonal space where the mean and covariance of the data are matched by the model. The other two approaches worked solutions in physical space where the uncertain parameter set is made of masses, stiffnesses and damping coefficients; one matches confidence intervals of low order moments of the statistics via optimization while the second one uses a Kernel density estimation approach. The paper will touch on all the approaches, lessons learned, validation 1 metrics and their comparison, data quantity restriction, and assumptions/limitations of each approach. Keywords: Probabilistic modeling, model validation, uncertainty quantification, kernel density

Horta, Lucas G.↗

NASA NTRS1995

A software tool to design thermal barrier coatings

This paper summarizes work completed for a NASA Phase 1 SBIR program which demonstrated the feasibility of developing a software tool to aid in the design of thermal barrier coating (TBC) systems. Toward this goal, three tasks were undertaken and completed. Task 1 involved the development of a database containing the pertinent thermal and mechanical property data for the top coat, bond coat and substrate materials that comprise a TBC system. Task 2 involved the development of an automated set-up program for generating two dimensional (2D) finite element models of TBC systems. Most importantly, Task 3 involved the generation of a rule base to aid in the design of a TBC system. These rules were based on a factorial design of experiments involving FEM results, and were generated using a Yates analysis. A previous study has indicated the suitability and benefit of applying finite element analysis to perform computer based experiments to decrease but not eliminate physical experiments on TBC's. This program proved feasibility by expanding on these findings by developing a larger knowledge base and developing a procedure to extract rules to aid in TBC design.

Petrus, G.↗

NASA NTRS1978

On the dissociation of nitrogen by electron impact and by EUV photo-absorption

The dissociation of N2 by electron impact and by absorption of EUV photons was studied experimentally. It was shown that most of the N2 molecules excited to singlet states in the 12.5-14.86 eV range are depopulated by predissociation and not by the emission of EUV photons and that this is the principal mechanism by which N2 is dissociated by solar EUV absorption and by electron impact. The experiments provide a physical explanation for the near absence of N2 band radiation in airglow and auroral EUV spectra, and rule out the excitation of EUV radiation as a major factor in the overall energy economy of an auroral substorm.

Zipf, E. C.↗

NASA NTRS2004

Goal-directed ultrasound in the detection of long-bone fractures

BACKGROUND: New portable ultrasound (US) systems are capable of detecting fractures in the remote setting. However, the accuracy of ultrasound by physicians with minimal ultrasound training is unknown. METHODS: After one hour of standardized training, physicians with minimal US experience clinically evaluated patients presenting with pain and trauma to the upper arm or leg. The investigators then performed a long-bone US evaluation, recording their impression of fracture presence or absence. Results of the examination were compared with routine plain or computer aided radiography (CT). RESULTS: 58 patients were examined. The sensitivity and specificity of US were 92.9% and 83.3%, and of the physical examination were 78.6% and 90.0%, respectively. US provided improved sensitivity with less specificity compared with physical examination in the detection of fractures in long bones. CONCLUSION: Ultrasound scans by minimally trained clinicians may be used to rule out a long-bone fracture in patients with a medium to low probability of fracture.

Validation Studies↗

NASA NTRSDate not supplied

Recent Progress and Development of Self-Aligned Focusing Schlieren

A broad range of developments and applications of self-aligned focusing schlieren (SAFS)systems is presented. The replacement of the Ronchi ruling (RR) with a𝜇LCD was demonstrated with digital SAFS, which provides the ability to modulate the pattern and orientation without physical intervention. Additionally, replacement of the traditional RR with spectral-spatial filters was demonstrated to yield the ability to simultaneously image horizontal and vertical index of refraction gradients using two separate wavelengths. The application of the Scheimpflug principle to SAFS systems enables off-axis imaging and allowed for extended fields-of-view to be captured using a two-camera system. The addition of a plenoptic camera to a baseline SAFS system enables refocusing capabilities, which is demonstrated on two jets offset along the optical axis. Furthermore, application of an event-based camera to SAFS was shown to enable acquisition of sparse, spatio-temporal data. Beyond the listed developments, SAFS was applied to difficult and constraining facilities, such as the National Full-Scale Aerodynamics Complex(NFAC) 80- by 120-ft Wind Tunnel and the Thermal Acoustic Engines (TAE) rig at NASA Ames Research Center and NASA Glenn Research Center, respectively. Behavior of Ronchi rulings, Rochon prisms, and the use of quarter-wave plates versus quarter-wave films are evaluated to provide insight for future experimental design of SAFS-systems.

Self-Aligned Focusing Schlieren↗

NASA NTRSDate not supplied

Recent Progress and Development of Self-Aligned Focusing Schlieren

A broad range of developments and applications of self-aligned focusing schlieren (SAFS)systems is presented. The replacement of the Ronchi ruling (RR) with a𝜇LCD was demonstrated with digital SAFS, which provides the ability to modulate the pattern and orientation without physical intervention. Additionally, replacement of the traditional RR with spectral-spatial filters was demonstrated to yield the ability to simultaneously image horizontal and vertical index of refraction gradients using two separate wavelengths. The application of the Scheimpflug principle to SAFS systems enables off-axis imaging and allowed for extended fields-of-view to be captured using a two-camera system. The addition of a plenoptic camera to a baseline SAFS system enables refocusing capabilities, which is demonstrated on two jets offset along the optical axis. Furthermore, application of an event-based camera to SAFS was shown to enable acquisition of sparse, spatio-temporal data. Beyond the listed developments, SAFS was applied to difficult and constraining facilities, such as the National Full-Scale Aerodynamics Complex(NFAC) 80- by 120-ft Wind Tunnel and the Thermal Acoustic Engines (TAE) rig at NASA Ames Research Center and NASA Glenn Research Center, respectively. Behavior of Ronchi rulings, Rochon prisms, and the use of quarter-wave plates versus quarter-wave films are evaluated to provide insight for future experimental design of SAFS-systems.

Self-Aligned Focusing Schlieren↗

NASA NTRS2014

Neutrino Physics from the Cosmic Microwave Background and Large Scale Structure

This is a report on the status and prospects of the quantification of neutrino properties through the cosmological neutrino background for the Cosmic Frontier of the Division of Particles and Fields Community Summer Study long-term planning exercise. Experiments planned and underway are prepared to study the cosmological neutrino background in detail via its influence on distance-redshift relations and the growth of structure. The program for the next decade described in this document, including upcoming spectroscopic galaxy surveys eBOSS and DESI and a new Stage-IV CMB polarization experiment CMB-S4, will achieve sigma (sigma*mass(sub v)= 16 meV and sigma (Effective number of neutrino species) = 0.020. Such a mass measurement will produce a high significance detection of non-zero sigma*mass(sub v), whose lower bound derived from atmospheric and solar neutrino oscillation data is about 58 meV. If neutrinos have a minimal normal mass hierarchy, this measurement will definitively rule out the inverted neutrino mass hierarchy, shedding light on one of the most puzzling aspects of the Standard Model of particle physics - the origin of mass. This precise a measurement of Neff will allow for high sensitivity to any light and dark degrees of freedom produced in the big bang and a precision test of the standard cosmological model prediction that the effective number of neutrino species = 3.046.

Neutrinos↗

NASA NTRS1990

New radio detections of early-type pre-main-sequence stars

Results of VLA radio continuum observations of 13 early-type pre-main-sequence stars selected from the 1984 catalog of Finkenzeller and Mundt are presented. The stars HD 259431 and MWC 1080 were detected at 3.6 cm, while HD 200775 and TY CrA were detected at both 3.6 and 6 cm. The flux density of HD 200775 has a frequency dependence consistent with the behavior expected for free-free emission originating in a fully ionized wind. However, an observation in A configuration suggests that the source geometry may not be spherically symmetric. In contrast, the spectral index of TY CrA is negative with a flux behavior implying nonthermal emission. The physical mechanism responsible for the nonthermal emission has not yet been identified, although gyrosynchrotron and synchrotron processes cannot be ruled out.

Skinner, Stephen L.↗

NASA NTRS1994

Evidence for X-ray flux and spectral modulation by absorption in NGC 6814. 1: The nature of the most rapid variability

The Seyfert 1 galaxy NGC 6814 was observed using the Japanese X-ray astronomy satellite Ginga in 1990 April and October. The rapid variability characteristically associated with this source was reconfirmed. Specifically, three dips were found in the April observation in which the flux dropped to nearly zero in approximately 300 s. The doubling timescale was approximately 50 s. A similar but separated drop and rise in flux was observed in the October data, different in that the flux did not decrease completely to zero. A detailed analysis of the data around the structures of most rapid variability found spectral variability and lags in flux between different energy bands. Lags were on the order of a few to tens of seconds for the April data, and on the order of tens to a couple of hundred seconds for the October data. The sense of the lags was such that during flux decreases the hard flux lagged, while during flux increases the soft flux lagged. Associated significant apparent hardening of the spectrum at low flux was observed in the April data. Apparent hardening of the spectrum also occurred in the October flux decrease, to a photon index of GAMMA = 0.85; however, the spectrum softened at lowest flux to the index of the predecrease level, GAMMA = 1.54. In the April dips, the line flux was found to decrease significantly. A marginal decrease in line flux was also observed in the October data. The variability of the line flux reconfirmed the result of Kunieda et al. (1990), who found that the line production region must be within approximately 300 light-seconds from the source. To explain the observational results, a variable-absorption model was proposed, in which the column density was assumed to vary as a function of time. Other physical processes, including intrinsic spectral changes and warm absorber models, which could account for the fastest variability, could be ruled out by the results of the data analysis. A primary constraint found for geometrical models is that the material which is doing the absorption must have relatively low ionization (xi less than 100). This result leads to severe constraints on a general orbiting cloud model, requiring high densities (n approximately 10(exp 16)/cu cm) and sheetlike geometry.

Leighly, Karen↗

NASA NTRS2021

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

Airport configuration selection is a complex decision-making process that involves several operational and human factors. In this paper we propose a novel recursive multi-step machine learning (ML) approach to predict airport configuration. The multi-step approach guarantees stability of the predicted configuration by taking as input the configuration predicted at the previous time step. The features of the proposed model include weather data, future arrival and departure counts and current configuration. Due to the importance of arrival and departure counts in predicting the airport configuration, arrival counts are calculated using landing time predictions selected from physics-based landing time predictions available in FAA System Wide Information Management data feeds for each flight. The selection rules were developed and refined to select the most accurate time for different phases of flight. The proposed model predicts the airport configurations up to 6 hours ahead. In this paper we show the predictive performance of the proposed model for six major US airports, including Charlotte Douglas International Airport (CLT), Dallas/Fort Worth International Airport (DFW), John F. Kennedy International Airport (JFK), Newark Liberty International Airport (EWR), LaGuardia Airport (LGA) and Dallas Love Field Airport (DAL). We trained and evaluated models on 2019 and 2020 data in order to study the effect of the pandemic and how changes in traffic patterns affected the performance of the proposed model. Results are compared with a baseline assuming no airport configuration changes. In our results for DFW, we obtained a prediction accuracy of 89.3% for 3 hours ahead prediction, and 82.8% for 6 hours ahead when applied on 2019 data.

machine learning↗

NASA NTRS2021

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

Airport configuration selection is a complex decision-making process that involves several operational and human factors. In this paper we propose a novel recursive multi-step machine learning (ML) approach to predict airport configuration. The multi-step approach guarantees stability of the predicted configuration by taking as input the configuration predicted at the previous time step. The features of the proposed model include weather data, future arrival and departure counts and current configuration. Due to the importance of arrival and departure counts in predicting the airport configuration, arrival counts are calculated using landing time predictions selected from physics-based landing time predictions available in FAA System Wide Information Management data feeds for each flight. The selection rules were developed and refined to select the most accurate time for different phases of flight. The proposed model predicts the airport configurations up to 6 hours ahead. In this paper we show the predictive performance of the proposed model for six major US airports, including Charlotte Douglas International Airport (CLT), Dallas/Fort Worth International Airport (DFW), John F. Kennedy International Airport (JFK), Newark Liberty International Airport (EWR), LaGuardia Airport (LGA) and Dallas Love Field Airport (DAL). We trained and evaluated models on 2019 and 2020 data in order to study the effect of the pandemic and how changes in traffic patterns affected the performance of the proposed model. Results are compared with a baseline assuming no airport configuration changes. In our results for DFW, we obtained a prediction accuracy of 89.3% for 3 hours ahead prediction, and 82.8% for 6 hours ahead when applied on 2019 data.

machine learning↗

NASA NTRS1988

A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

Kautzmann, Frank N., III↗