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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12

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NASA NTRS2012

A Systems Modeling Approach for Risk Management of Command File Errors

The main cause of commanding errors is often (but not always) due to procedures. Either lack of maturity in the processes, incompleteness of requirements or lack of compliance to these procedures. Other causes of commanding errors include lack of understanding of system states, inadequate communication, and making hasty changes in standard procedures in response to an unexpected event. In general, it's important to look at the big picture prior to making corrective actions. In the case of errors traced back to procedures, considering the reliability of the process as a metric during its' design may help to reduce risk. This metric is obtained by using data from Nuclear Industry regarding human reliability. A structured method for the collection of anomaly data will help the operator think systematically about the anomaly and facilitate risk management. Formal models can be used for risk based design and risk management. A generic set of models can be customized for a broad range of missions.

probabilistic risk↗

NASA NTRS1985

Dynamics explorer guest investigator

The use of Dynamics Explorer (DE) data sets to model the auroral inputs for the time dependent ionospheric model (TDIM) is reported. The modelling requires DE-1 SAI images and simultaneous DE-2 LAPI particle data. The data sets allow the large scale relative auroral variations and local absolute energy flexes and characteristics energies to be defined. The images enabled global scale auroral modelling with 12 min. time resolution and the LAPI data presented a detailed energy flux and characteristic energy calibration of the image model. The auroral model is used as an input to the TDIM and studies ionospheric storms.

Sojka, J. J.↗

NASA NTRS2016

Consistent Evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC Through Comparisons to TCCON

Consistent validation of satellite CO2 estimates is a prerequisite for using multiple satellite CO2 measurements for joint flux inversion, and for establishing an accurate long-term atmospheric CO2 data record. Harmonizing satellite CO2 measurements is particularly important since the differences in instruments, observing geometries, sampling strategies, etc. imbue different measurement characteristics in the various satellite CO2 data products. We focus on validating model and satellite observation attributes that impact flux estimates and CO2 assimilation, including accurate error estimates, correlated and random errors, overall biases, biases by season and latitude, the impact of coincidence criteria, validation of seasonal cycle phase and amplitude, yearly growth, and daily variability. We evaluate dry-air mole fraction (X(sub CO2)) for Greenhouse gases Observing SATellite (GOSAT) (Atmospheric CO2 Observations from Space, ACOS b3.5) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) (Bremen Optimal Estimation DOAS, BESD v2.00.08) as well as the CarbonTracker (CT2013b) simulated CO2 mole fraction fields and the Monitoring Atmospheric Composition and Climate (MACC) CO2 inversion system (v13.1) and compare these to Total Carbon Column Observing Network (TCCON) observations (GGG2012/2014). We find standard deviations of 0.9, 0.9, 1.7, and 2.1 parts per million vs. TCCON for CT2013b, MACC, GOSAT, and SCIAMACHY, respectively, with the single observation errors 1.9 and 0.9 times the predicted errors for GOSAT and SCIAMACHY, respectively. We quantify how satellite error drops with data averaging by interpreting according to (error(sup 2) equals a(sup 2) plus b(sup 2) divided by n (with n being the number of observations averaged, a the systematic (correlated) errors, and b the random (uncorrelated) errors). a and b are estimated by satellites, coincidence criteria, and hemisphere. Biases at individual stations have year-to-year variability of 0.3 parts per million, with biases larger than the TCCON predicted bias uncertainty of 0.4 parts per million at many stations. We find that GOSAT and CT2013b under-predict the seasonal cycle amplitude in the Northern Hemisphere (NH) between 46 and 53 degrees North latitude, MACC over-predicts between 26 and 37 degrees North latitude, and CT2013b under-predicts the seasonal cycle amplitude in the Southern Hemisphere (SH). The seasonal cycle phase indicates whether a data set or model lags another data set in time. We find that the GOSAT measurements improve the seasonal cycle phase substantially over the prior while SCIAMACHY measurements improve the phase significantly for just two of seven sites. The models reproduce the measured seasonal cycle phase well except for at Lauder_125HR (CT2013b) and Darwin (MACC). We compare the variability within 1 day between TCCON and models in June-July-August; there is correlation between 0.2 and 0.8 in the NH, with models showing 10-50 percent the variability of TCCON at different stations and CT2013b showing more variability than MACC. This paper highlights findings that provide inputs to estimate flux errors in model assimilations, and places where models and satellites need further investigation, e.g., the SH for models and 45-67 degrees North latitude for GOSAT and CT2013b.

ACOS-GOSAT↗

NASA NTRS1986

Theoretical study of the X-ray emission from astrophysical shock waves

Theoretical X-ray emission spectra are needed to interpret the X-ray emission observed by many low and moderate resolution X-ray instruments, and to provide diagnosis of physical conditions for high resolution spectra. Over the past decade, a set of model codes which compute the X-ray and XUV emission for a wide set of physical conditions, including high or low densities, photoionized gas, and time-dependent ionization balance was developed. In the past year, the atomic rate coefficients in the code was improved. Further capabilities were added, and applied to several astrophysical problems.

Raymond, J.↗

NASA NTRS1999

Wind-Tunnel Overpressure Signatures From a Low-Boom HSCT Concept With Aft-Fuselage-Mounted Engines

A 1:300 scale wind-tunnel model of a conceptual High-Speed Civil Transport (HSCT) designed to generate a shaped, low-boom pressure signature on the ground was tested to obtain sonic-boom pressure signatures in the Langley Research Center Unitary Plan Wind Tunnel at a Mach number of 1.8 and a separation distance of about two body lengths or four wing-spans from the model. Two sets of engine nacelles representing two levels of engine technology were used on the model to determine the effects of increased nacelle volume. Pressure signatures were measured for (model lift)/(design lift) ratios of 0.5, 0.63, 0.75, and 1.0 so that the effect of lift on the pressure signature could be determined. The results of these tests were analyzed and used to discuss the agreement between experimental data and design expectations.

Mack, Robert J.↗

NASA NTRS2008

Wake Vortex Inverse Model User's Guide

NorthWest Research Associates (NWRA) has developed an inverse model for inverting landing aircraft vortex data. The data used for the inversion are the time evolution of the lateral transport position and vertical position of both the port and starboard vortices. The inverse model performs iterative forward model runs using various estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Forward model predictions of lateral transport and altitude are then compared with the observed data. Differences between the data and model predictions guide the choice of vortex parameter values, crosswind profile and circulation evolution in the next iteration. Iterations are performed until a user-defined criterion is satisfied. Currently, the inverse model is set to stop when the improvement in the rms deviation between the data and model predictions is less than 1 percent for two consecutive iterations. The forward model used in this inverse model is a modified version of the Shear-APA model. A detailed description of this forward model, the inverse model, and its validation are presented in a different report (Lai, Mellman, Robins, and Delisi, 2007). This document is a User's Guide for the Wake Vortex Inverse Model. Section 2 presents an overview of the inverse model program. Execution of the inverse model is described in Section 3. When executing the inverse model, a user is requested to provide the name of an input file which contains the inverse model parameters, the various datasets, and directories needed for the inversion. A detailed description of the list of parameters in the inversion input file is presented in Section 4. A user has an option to save the inversion results of each lidar track in a mat-file (a condensed data file in Matlab format). These saved mat-files can be used for post-inversion analysis. A description of the contents of the saved files is given in Section 5. An example of an inversion input file, with preferred parameters values, is given in Appendix A. An example of the plot generated at a normal completion of the inversion is shown in Appendix B.

Lai, David↗

NASA NTRS1987

Fuzzy sets and autonomous navigation

The use of fuzzy sets in modeling the human expert for certain Space Shuttle navigation problems is discussed with particular reference to onboard and ground console data monitoring tasks traditionally performed by astronauts and engineers. Specific problems include determining the quality of sensor data and of the filter state. The results obtained in this study indicate that fuzzy sets can be successfully used in modeling human reaction to rules in decision-making processes. They can also be used within software systems where guidelines have traditionally been used to set strict tolerances.

Lea, Robert N.↗

NASA NTRS2019

Lifetimes and Occurrence Rates of Dark Vortices on Neptune from 25 Years of Hubble Space Telescope Images

We scoured the full set of blue-wavelength Hubble Space Telescope images of Neptune, finding one additional dark spot in new Hubble data beyond those discovered in 1989, 1994, 1996, and 2015. We report the complete disappearance of the SDS-2015 dark spot, using new Hubble data taken on 2018 September 9–10, as part of the Outer Planet Atmospheres Legacy (OPAL) program. Overall, dark spots in the full Hubble data set have lifetimes of at least one to two years, and no more than six years. We modeled a set of dark spots randomly distributed in time over the latitude range on Neptune that is visible from Earth, finding that the cadence of archival Hubble images would have detected about 70% of these spots if their lifetimes are only one year, or about 85%–95% of simulated spots with lifetimes of two or more years. Based on the Hubble data set, we conclude that dark spots have average occurrence rates of one dark spot every four to six years. Many numerical models to date have simulated much shorter vortex lifetimes, so our findings provide constraints that may lead to improved understanding of Neptune’s wind field, stratification, and humidity.

Hsu, Andrew I.↗

NASA NTRS2015

Simulating the X-Ray Image Contrast to Set-Up Techniques with Desired Flaw Detectability

The paper provides simulation data of previous work by the author in developing a model for estimating detectability of crack-like flaws in radiography. The methodology is being developed to help in implementation of NASA Special x-ray radiography qualification, but is generically applicable to radiography. The paper describes a method for characterizing X-ray detector resolution for crack detection. Applicability of ASTM E 2737 resolution requirements to the model are also discussed. The paper describes a model for simulating the detector resolution. A computer calculator application, discussed here, also performs predicted contrast and signal-to-noise ratio calculations. Results of various simulation runs in calculating x-ray flaw size parameter and image contrast for varying input parameters such as crack depth, crack width, part thickness, x-ray angle, part-to-detector distance, part-to-source distance, source sizes, and detector sensitivity and resolution are given as 3D surfaces. These results demonstrate effect of the input parameters on the flaw size parameter and the simulated image contrast of the crack. These simulations demonstrate utility of the flaw size parameter model in setting up x-ray techniques that provide desired flaw detectability in radiography. The method is applicable to film radiography, computed radiography, and digital radiography.

Koshti, Ajay M.↗

NASA NTRS1971

On a programming language for graph algorithms

An algorithmic language, GRAAL, is presented for describing and implementing graph algorithms of the type primarily arising in applications. The language is based on a set algebraic model of graph theory which defines the graph structure in terms of morphisms between certain set algebraic structures over the node set and arc set. GRAAL is modular in the sense that the user specifies which of these mappings are available with any graph. This allows flexibility in the selection of the storage representation for different graph structures. In line with its set theoretic foundation, the language introduces sets as a basic data type and provides for the efficient execution of all set and graph operators. At present, GRAAL is defined as an extension of ALGOL 60 (revised) and its formal description is given as a supplement to the syntactic and semantic definition of ALGOL. Several typical graph algorithms are written in GRAAL to illustrate various features of the language and to show its applicability.

Rheinboldt, W. C.↗

NASA NTRS1988

The pros and cons of code validation

Computational and wind tunnel error sources are examined and quantified using specific calculations or experimental data, and a substantial comparison of theoretical and experimental results, or a code validation, is discussed. Wind tunnel error sources considered include wall interference, sting effects, Reynolds number effects, flow quality and transition, and instrumentation such as strain gage balances, electronically scanned pressure systems, hot film gages, hot wire anemometers, and laser velocimeters. Computational error sources include math model equation sets, the solution algorithm, artificial viscosity/dissipation, boundary conditions, the uniqueness of solutions, grid resolution, turbulence modeling, and Reynolds number effects. It is concluded that although improvements in theory are being made more quickly than in experiments, wind tunnel research has the advantage of the more realistic transition process of a right turbulence model in a free-transition test.

Bobbitt, Percy J.↗

NASA NTRS1988

The pros and cons of code validation

Computational and wind tunnel error sources are examined and quantified using specific calculations of experimental data, and a substantial comparison of theoretical and experimental results, or a code validation, is discussed. Wind tunnel error sources considered include wall interference, sting effects, Reynolds number effects, flow quality and transition, and instrumentation such as strain gage balances, electronically scanned pressure systems, hot film gages, hot wire anemometers, and laser velocimeters. Computational error sources include math model equation sets, the solution algorithm, artificial viscosity/dissipation, boundary conditions, the uniqueness of solutions, grid resolution, turbulence modeling, and Reynolds number effects. It is concluded that, although improvements in theory are being made more quickly than in experiments, wind tunnel research has the advantage of the more realistic transition process of a right turbulence model in a free-transition test.

Bobbitt, Percy J.↗

NASA NTRS1990

Atmospheric dynamics of the outer planets

Despite major differences in the solar and internal energy inputs, the atmospheres of the four Jovian planets all exhibit latitudinal banding and high-speed jet streams. Neptune and Saturn are the windiest planets, Jupiter is the most active, and Uranus is a tipped-over version of the others. Large oval storm systems exhibit complicated time-dependent behavior that can be simulated in numerical models and laboratory experiments. The largest storm system, the Great Red Spot of Jupiter, has survived for more than 300 years in a chaotic shear zone where smaller structures appear and dissipate every few days. Future space missions will add to the understanding of small-scale processes, chemical composition, and vertical structure. Theoretical hypotheses about the interiors provide input for fluid dynamical models that reproduce many observed features of the winds, temperatures, and cloud patterns. In one set of models the winds are confined to the thin layer where clouds form. In other models, the winds extend deep into the planetary fluid interiors. Hypotheses will be tested further as observations and theories become more exact and detailed comparisons are made.

Ingersoll, Andrew P.↗

NASA NTRSDate not supplied

DDFRG: Double Differential FRaGmentation Models for Proton and Light Ion Production in High Energy Nuclear Collisions: Closed Form, Analytic Formulas for Transport Codes and other Applications

New models for Double-Differential FRaGmentation (DDFRG) cross sections for proton and light ion production from high energy nucleus-nucleus collisions are developed. The proton model employs thermal production from the projectile, central fireball and target sources, and also quasi-elastic direct knockout production. Light ion production cross sections employ a hybrid coalescence model. The models are able to describe a wide range of experimental data with only a limited set of model parameters. Closed form analytic formulas for double-differential cross sections as well as single-differential energy cross sections are developed. The analytic formulas enable highly efficient computation for space radiation transport codes and other applications.

John W Norbury↗

NASA NTRS2022

X-59 Sonic Boom Test Results from the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel

A wind tunnel test was conducted to investigate near-field sonic boom pressure signatures from a model of the X-59 Low-Boom Flight Demonstrator aircraft. A 1.62%-scale model of the aircraft in the C612A configuration was fabricated for the wind tunnel test, which took place in the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel in September and October 2021. The model had provisions for two different mounting options: a swept blade strut that attached at the top of model ahead of the inlet, and rear-entry sting that was made as one piece with a dummy nacelle, and which had a 2”-long cylindrical segment aft of the nozzle exit before tapering up in size. The blade strut allowed for a clean aft end of the model for evaluation of the shocks from that region, while the sting avoided the significant distortions of the flow and shocks from the blade strut along the top of the model. Both the sting and the strut had adapters that attached to a force balance. The model had alternate parts for ±0.5° deflections of the flaps, ailerons, and stabilator, and ±1° deflections of the T-tail horizontal surface. Off-body static pressure measurements of the flow field below the model were made by use of a pressure rail which had 420 orifices along its tip. The model was positioned at various heights from the rail by vertical movement of the wind tunnel strut, and at various longitudinal stations relative to the rail by means of a linear actuator mounted between the tunnel strut and the balance. The longitudinal positioning allowed multiple pressure signatures to be obtained along different portions of the rail. These signatures were aligned by accounting for the model longitudinal movement and then averaged to take out the effects of tunnel flow distortions and the interference of the rail flow field and shocks on the model pressure signatures. The test was run at approximate Mach numbers of 1.36, 1.4, and 1.47, and the model was set at various angles of attack and roll relative to the rail. Plots of the model signatures for all the variations of Mach number, model angles, control deflections, and height relative to the rail are provided throughout the report. Repeatability was generally very good and gave confidence in the quality of the measurements. The signatures measured at various heights from the rail provided insight into the aging of the model shocks as they propagated from 1.2 to 3 body lengths from the model. Off-track signatures up to 45° from centerline obtained by rolling the model gave indications of the shock flow fields across the width of the sonic boom carpet. The deflections of the various control surfaces allowed assessment of the boom sensitivity to the control surface movements.

Sonic boom↗

NASA NTRS2023

X-59 Sonic Boom Test Results from the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel

A wind tunnel test was conducted to investigate near-field sonic boom pressure signatures of the X-59 Low-Boom Flight Demonstrator aircraft. A 1.62%-scale model of the aircraft was fabricated for the wind tunnel test, which took place in the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel in September and October 2021. The model had provisions for being mounted by a swept blade strut that attached at top of model ahead of the inlet, or by a rear-entry sting that held the model at the location of the nacelle. The model had alternate parts for ±0.5° deflections of the flaps, ailerons, and stabilator, and ±1° deflections of the T-tail. Off-body static pressure measurements of the flow field below the model were made on a pressure rail which had 420 orifices along its tip. The model was positioned at various heights from the rail by vertical movement of the tunnel strut, and at various longitudinal stations relative to the rail by means of a linear actuator mounted between the wind tunnel strut and the balance. Spatial averaging of model pressure signatures acquired over a range of longitudinal positions reduced the effects of tunnel flow distortions and the interference of the rail flow field and shocks on the model pressure signatures. The test was run at approximate Mach numbers of 1.36, 1.4, and 1.47, and the model was set at various angles of attack and roll relative to the rail. Plots of the model signatures for representative variations of Mach number, model angles, control deflections, and height relative to the rail are provided throughout the report. Repeatability was generally very good and gave confidence in the quality of the measurements. The signatures measured at various heights from the rail provided insight into the aging of the model shocks as they propagated from 1.2 to 3 body lengths from the model. Off-track signatures up to 45° from centerline obtained by rolling the model gave indications of the shock flow fields across the width of the sonic boom carpet. The deflections of the various control surfaces allowed assessment of the boom sensitivity to the control surface movements.

Sonic boom↗

NASA NTRS2023

X-59 Sonic Boom Test Results from the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel

Sonic boom↗

DOE OSTI2025

ELM model simulations of Plum Island Ecosystems LTER low marsh site 2018-2020

Model simulations using the Department of Energy's Energy Exascale Earth System Model (E3SM) land model (ELM) with improved capabilities to represent vegetation response to salinity and inundation. The simulations were conducted for a tidal salt marsh at Plum Island Ecosystems Long Term Ecological Research (LTER) site near Rowley, Massachusetts, USA; the site is a low marsh dominated by Spartina alterniflora. The model was forced with site-specific meteorology, salinity and tidal cycles from 2018-2020. Four sets of model simulations are included and described below:1. Parameterization of the salinity response function. These simulations tested different combinations of values for optimal salinity and salinity tolerance.2. Model evaluation. This comparison conducted simulations using the default model, the salinity function only, the submergence function only, and both the salinity and submergence functions. 3. Salinity scenarios. These simulations used the 2018 salinity input data varied by -5 to +10 ppt salinity.4. Water level scenarios. These simulations used the tide height varied by -10 to +50 cm. These simulations were used to demonstrate how the salinity and submergence functions better represent carbon uptake by tidal salt marshes.The data package includes netCDF files used as forcing files for tide height and salinity, one for each year 2018-2020 at observed salinity concentrations, and an additional three forcing files in which salinity concentrations were varied 5 ppt lower, 5 ppt higher, and 10 ppt higher than the measured 2018 time series. Also included are python scripts for creating forcing files, plain text parameter and command files for running simulations, model outputs in netCDF format, and python scripts for visualizing outputs. Code for the modified E3SM model is archived in Sulman et al 2023 at doi:10.15485/1991625. More detail about files is provided in the README.md file.

54 ENVIRONMENTAL SCIENCES↗