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At least 1,099 records · Page 61
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NASA NTRS2019

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗
NASA NTRS2018

Thermal Modeling and Correlation of the Space Environments Complex Vacuum Chamber and Cryoshroud

A thermal model of the Space Environments Complex (SEC) vacuum chamber and cryoshroud has been developed in support of upcoming thermal vacuum/thermal balance testing for Orion EM-1. The model was developed in Thermal Desktop and includes the vacuum chamber itself, a fluid model of the gaseous nitrogen flowing through the cryoshroud and the chamber piping, the Heat Flux System (HFS) within the cryoshroud, and the mechanical ground support equipment (MGSE) that interfaces with the vehicle. It has been correlated with steady state data from three tests. Two tests ran the cryoshroud in hot mode at 170 °F, and one test ran the cryoshroud in cold mode at -263 °F. Correlation was done using an optimization algorithm to find values of unknown contact conductances that minimized the RMS error between the model predictions and the test data. Overall, model quality was very good with a total RMS error of 2.6 °F.

Stalcup, Erik J.↗
NASA NTRSDate not supplied

Identifying Human Errors and Error Mechanisms From Accident Reports Using Large Language Models

Emerging operational concepts for aviation hinge on novel paradigms for human machine interaction. Critical to their safe operation is early consideration of human error into the design process. Existing methods for consideration of human error require significant expert input, which is challenging both in early design and in novel systems for which there is little existing safety expertise. In this research, we propose a methodology for identifying human error, error producing factors, and mechanisms in early design from historical incident reports. Additionally, we hypothesize that cross-domain sharing of lessons learned can aid with early design human considerations in circumstances where data is not relevant or incomplete. This is addressed by identifying causes of human error in aviation and railway domains through applying state-of-the art natural language processing techniques to historical incident reports. Using this method, it is possible to extract extensive reports on human error from past incidents. Using the proposed approach, we identify nine human errors from railway reports and fourteen from aviation reports, with three errors common to both domains. There is at least one error producing conditions for each human error while a majority of the errors have more than one error mechanism. We also found that a majority of the human errors, error producing factors, and error mechanisms (even if they are not common between the domains) can be used to inform safe operations across domains as long as the errors are not domain specific and are interpreted and contextualized using engineering judgement.

Human Errors↗
NASA NTRS1990

Longwave cloud radiative forcing at the surface from ISCCP-C1 data

A method for deriving one component of the total cloud forcing picture, namely, the LW cloud forcing at the surface, is presented. The method is based on a validated radiative transfer technique and utilizes meteorological data available from the International Satellite Cloud Climatology Project. The radiative transfer model used was validated earlier and the TOVS-derived temperature and water vapor data used were generally reasonable. On a monthly-average basis, random error was estimated to be in the 5-10 W/sq m range, but biases as large as 10-20 W/sq m can occur in some regions. The lack of information on cloud-base heights were found to be the largest source of errors in the models and the meteorological data.

Gupta, Shashi K.↗
NASA NTRS2005

Reduced-Order Modeling of a Heaving Airfoil

A reduced-order model of a flapping airfoil is developed using Proper Orthogonal Decomposition (POD). The proper basis functions, developed from snapshots of full Navier-Stokes simulations, are used for a Galerkin projection of the governing equations. The resulting coupled, nonlinear ordinary di.erential equations have a low dimension because the first few basis members capture most of the energy of the flow. The reduced-order model is used to simulate heaving motions that are both similar to and different from the motion(s) used to generate the basis functions, and the errors in the model are quantified. Several methods are used to generate mode sets that can be used over a range of heaving parameters, including snapshots from one, two, and multiple Navier-Stokes simulations. As snapshots from additional simulations are added to the decomposition, the mode sets become richer and can simulate a wider range of parameter space, at some computational cost. Whereas the POD method is fully applicable in three dimensions, the simulation technique based on a body-fixed and body-fitted grid suffers large overhead when extended to three dimensions. To reduce the overhead, an embedding technique is discussed which embeds the solid wing into a fixed Cartesian grid. The wing, which can now have multiple pieces and also be flexible, is represented by a distribution of body forces. This distribution is determined to give exactly the flow around a flapping wing.

Haj-Hariri, H.↗
NASA NTRS2014

Development, Validation, and Application of OSSEs at NASA-GMAO

The GMAO OSSE framework has two general classes of applications. One is to estimate the potential improvements to weather forecasting and analysis by using new proposed instruments that are not as yet built or deployed. This exploits the simulated nature of the OSSE. The other is to assess various aspects of the GMAO data assimilation system. This exploits the availability of truth provided by the OSSE. Two examples of the first class of application will be offered. One concerns deployment of constellations of passive MW sounders on small CUBESATs placed in very low orbits. The other concern is increasing the frequency of radiosonde observations to 4-times daily at all current stations. Several examples of the second class will also be presented. One is an estimation of analysis error characteristics. Another is a comparison between covariances directly determined from explicitly known background errors and those estimated by computing differences between lagged forecasts using the NMC-method prior to tuning. A third is a comparison of effects of model and observation errors on analysis and forecast skill. The last is an examination of spectra of forecast errors in a study of predictability. This latter is an ongoing study.

OSSE↗
NASA NTRS2021

Reducing Risk of InSight Surface Operations Through High-Fidelity Command Sequence Modeling

Simulating spacecraft behavior is crucial for the success of deep space missions, and failure to do so may result in damages to or the loss of the spacecraft. Many previous deep space missions have made use of ground-simulation of sequenced commanding, at speeds far greater than real time, to predict spacecraft state over time through the execution of onboard sequences. This type of modeling can be done at any fidelity, and most missions have opted to decrease fidelity to reduce cost and complexity. However, NASA’s Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission expanded the scope of ground modeling considerably, which has led to numerous benefits over past implementations. This paper will discuss the process and products that InSight created, as well as the lessons learned from successfully operating the spacecraft on Mars. InSight is the first JPL mission to expand the scope of ground modeling to include the uplink of files from Earth to the spacecraft, rather than making the simplification that any command sequences already exist onboard the spacecraft. The advantages of modeling the uplink of files are numerous. First, it allows for accurate modeling of the onboard filesystem of the spacecraft at all points in time, meaning that all file loads and deletions throughout the mission are modeled at the exact moment they are predicted to actually happen. Second, operators can be more certain that dependencies between sequences are not broken due to the dynamic nature of the filesystem as files are deleted, copied, and uplinked. Lastly, spacecraft filesystem tracking allows for management of sequences prior to uplink, limiting the uplink to only new sequences. The onboard filesystem model became crucial to mission success, emphasizing the importance of investing in accurate models before the need for them arises. During daily tactical operations of a spacecraft on Mars, a model is only useful if the results can be interpreted quickly. In this fast-paced environment, it is essential that command products are modeled and reviewed, errors are found and diagnosed, and new command products are redelivered, remodeled, re-reviewed in a timely manner. It is impossible to review the entire model and therefore the results of the model must be condensed and presented in a fashion that is intuitive, easy-to-navigate, complete, and trustworthy. InSight developed a number of innovative sequence review products that are designed to provide operators with the information required to quickly assess the validity of command products and diagnose potential issues. Together, these products provide a complete, yet succinct picture of the command and sequence model to the operators and facilitate a quick assessment of all sequence command products. This paper will cover planning and sequencing innovations made during InSight surface operations, and will compare the tools, processes, and results to those on other missions. Additionally, the paper will cover the flexible, yet robust nature of the planning and sequencing system architecture and how that flexibility allowed for rapid development and response to the unpredictability of Mars.

Cloutier, Kyle↗
NASA NTRS2001

Estimates of M2 Tidal Energy Dissipation from TOPEX/Poseidon Altimeter Data

Most of the tidal energy dissipation in the ocean occurs in shallow seas, as has long been recognized. However, recent work has suggested that a significant fraction of the dissipation, perhaps 1 TW or more, occurs in the deep ocean. This paper builds further evidence for that conclusion. More than 6 years of data from the TOPEX/Poseidon satellite altimeter are used to map the tidal dissipation rate throughout the world ocean. The dissipation rate is estimated as a balance between the rate of working by tidal forces and the energy flux divergence, computed using currents derived by least squares fitting of the altimeter data and the shallow water equations. Such calculations require dynamical assumptions, in particular about the nature of dissipation. To assess sensitivity of dissipation estimates to input assumptions, a large suite of tidal inversions based on a wide range of drag parameterizations and employing both real and synthetic altimeter data are compared. These experiments and Monte Carlo error fields from a generalized inverse model are used to establish error uncertainties for the dissipation estimates. Owing to the tight constraints on tidal elevation fields provided by the altimeter, area integrals of the energy balance are remarkably insensitive to required dynamical assumptions. Tidal energy dissipation is estimated for all major shallow seas (excluding individual polar seas) and compared with previous model and data-based estimates. Dissipation in the open ocean is significantly tnhanced around major bathymetric features, in a manner consistent with simple theories the generation of baroclinic tides.

Egbert, Gary D.↗
NASA NTRS1995

A count probability cookbok: Spurious effects and the scaling model

We study the errors brought by finite volume effects and dilution effects on the practical determination of the count probability distribution function P(sub N)(n,l), which is the probability of having N objects in a cell of volume l cubed for a set of average number density n. Dilution effects are particularly revelant to the so-called sparse sampling strategy. This work is mainly done in the framework of the Bailan & Schaeffer scaling model, which assumes that the Q-body correlation functions obey the scaling relation Xi(sub Q)(lambda r(sub l),....lambda r(sub Q) = lambda(exp -(Q-1)gamma) Xi(sub Q)(r(sub 1),....r(sub Q)). We use three synthetic samples as references to perform our analysis: a fractal generated by a Rayleigh-Levy random walk with approximately 3 x 10(exp 4) objects, a sample dominated by a spherical power-law cluster with approximately 3 x 10(exp 4) objects and a cold dark matter (CDM) universe involving approximately 3 x 10(exp 5) matter particles.

Colombi, S.↗
NASA NTRS1983

The influence of rain and clouds on a satellite dual frequency radar altimeter system operating at 13 and 35 GHz

The effects of inhomogeneous spatial attenuation resulting from clouds and rain on the altimeter estimate of the range to mean sea level are modelled. It is demonstrated that typical cloud and rain attenuation variability at commonly expected spatial scales can significantly degrade altimeter range precision. Rain cell and cloud scale sizes and attenuations are considered as factors. The model simulation of altimeter signature distortion is described, and the distortion of individual radar pulse waveforms by different spatial scales of attenuation is considered. Examples of range errors found for models of a single cloud, a rain cell, and cloud streets are discussed.

Walsh, E. J.↗
NASA NTRS1989

Total dose effect on soft error rate for dynamic metal-oxide-semiconductor memory cells

A simple model for the soft error rate for dynamic metal-oxide-semiconductor random access memories due to normal galactic radiation was devised and then used to calculate the rate of decrease of the single-event-upset rate with total radiation dose. The computation shows that the decrease in the soft error rate is less than 10 percent per day if the shielding is 0.5 g/sq cm and the spacecraft is in a geosynchronous orbit. The decrease is considerably less in a polar orbiting device.

Benumof, Reuben↗
NASA NTRS2006

A Comparison of Various Stress Rupture Life Models for Orbiter Composite Pressure Vessels and Confidence Intervals

In conjunction with a recent NASA Engineering and Safety Center (NESC) investigation of flight worthiness of Kevlar Ovenvrapped Composite Pressure Vessels (COPVs) on board the Orbiter, two stress rupture life prediction models were proposed independently by Phoenix and by Glaser. In this paper, the use of these models to determine the system reliability of 24 COPVs currently in service on board the Orbiter is discussed. The models are briefly described, compared to each other, and model parameters and parameter error are also reviewed to understand confidence in reliability estimation as well as the sensitivities of these parameters in influencing overall predicted reliability levels. Differences and similarities in the various models will be compared via stress rupture reliability curves (stress ratio vs. lifetime plots). Also outlined will be the differences in the underlying model premises, and predictive outcomes. Sources of error and sensitivities in the models will be examined and discussed based on sensitivity analysis and confidence interval determination. Confidence interval results and their implications will be discussed for the models by Phoenix and Glaser.

stress ratios↗
NASA NTRS2008

Forecasting Lightning Threat using Cloud-Resolving Model Simulations

Two new approaches are proposed and developed for making time and space dependent, quantitative short-term forecasts of lightning threat, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the WRF model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models. One method is based on upward fluxes of precipitating ice hydrometeors in the mixed phase region at the-15 C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash rate proxy fields against domain-wide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. Our blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Exploratory tests for selected North Alabama cases show that, because WRF can distinguish the general character of most convective events, our methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models,the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of forecasts become available.

McCaul, Eugene W., Jr.↗
NASA NTRS2006

Inspection and Verification of Domain Models with PlanWorks and Aver

When developing a domain model, it seems natural to bring the traditional informal tools of inspection and verification, debuggers and automated test suites, to bear upon the problems that will inevitably arise. Debuggers that allow inspection of registers and memory and stepwise execution have been a staple of software development of all sorts from the very beginning. Automated testing has repeatedly proven its considerable worth, to the extent that an entire design philosophy (Test Driven Development) has been developed around the writing of tests. Unfortunately, while not entirely without their uses, the limitations of these tools and the nature of the complexity of models and the underlying planning systems make the diagnosis of certain classes of problems and the verification of their solutions difficult or impossible. Debuggers provide a good local view of executing code, allowing a fine-grained look at algorithms and data. This view is, however, usually only at the level of the current scope in the implementation language, and the data-inspection capabilities of most debuggers usually consist of on-line print statements. More modem graphical debuggers offer a sort of tree view of data structures, but even this is too low-level and is often inappropriate for the kinds of structures created by planning systems. For instance, god or constraint networks are at best awkward when visualized as trees. Any any non-structural link between data structures, as through a lookup table, isn't captured at all. Further, while debuggers have powerful breakpointing facilities that are suitable for finding specific algorithmic errors, they have little use in the diagnosis of modeling errors.

Bedrax-Weiss, Tania↗
NASA NTRS2021

Physics-Based SNOWPACK Model Improves Representation of Near-Surface Antarctic Snow and Firn Density

Estimates of snow and firn density are required for satellite-altimetry-based retrievals of ice sheet mass balance that rely on volume-to-mass conversions. Therefore, biases and errors in presently used density models confound assessments of ice sheet mass balance and by extension ice sheet contribution to sea level rise. Despite this importance, most contemporary firn densification models rely on simplified semi-empirical methods, which are partially reflected by significant modeled density errors when compared to observations. In this study, we present a new drifting-snow compaction scheme that we have implemented into SNOWPACK, a physics-based land surface snow model. We show that our new scheme improves existing versions of SNOWPACK by increasing simulated near-surface (defined as the top 10 m) density to be more in line with observations (near-surface bias reduction from −44.9 to −5.4 kg m−3). Furthermore, we demonstrate high-quality simulation of near-surface Antarctic snow and firn density at 122 observed density profiles across the Antarctic ice sheet, as indicated by reduced model biases throughout most of the near-surface firn column when compared to two semi-empirical firn densification models (SNOWPACK mean bias=−9.7 kg m−3, IMAU-FDM mean bias=−32.5 kg m−3, GSFC-FDM mean bias=15.5 kg m−3). Notably, our analysis is restricted to the near surface where firn density is most variable due to accumulation and compaction variability driven by synoptic weather and seasonal climate variability. Additionally, the GSFC-FDM exhibits lower mean density bias from 7–10 m (SNOWPACK bias=−22.5 kg m−3, GSFC-FDM bias=10.6 kg m−3) and throughout the entire near surface at high-accumulation sites (SNOWPACK bias=−31.4 kg m−3, GSFC-FDM bias=−4.7 kg m−3). However, we found that the performance of SNOWPACK did not degrade when applied to sites that were not included in the calibration of semi-empirical models. This suggests that SNOWPACK may possibly better represent firn properties in locations without extensive observations and under future climate scenarios, when firn properties are expected to diverge from their present state.

Eric Keenan↗
NASA NTRS1990

Atmospheric drag perturbations on the Mars Observer Orbiter

The nominal launch date of the Mars Observer spacecraft is 09 - 16 - 02, with Mars encounter on 08 - 19 - 93 and the mapping orbit established on 12 - 06 - 93. Because this orbit is nearly circular at low altitude (361 km), both gravity and atmospheric drag will dominate the orbital evolution and are also the major error sources. This paper provides: (1) a summary of atmospheric density and errors for the Mars Observer orbit and time frame, (2) an assessment of spacecraft-position errors using current density estimates, and (3) an estimate of atmospheric density modeling improvement directly from the Doppler data acquired during flight operations. With an improved gravity field model, reconstructed spacecraft-position errors are at the level of 0.5 km (1sigma). However, when predicting the spacecraft's position over 14 days, the density error (at the 90-percent confidence level) dominates, yielding a down-track error of almost 70 km. By modeling the mean atmospheric density, this error can be reduced by at least a factor of two.

Esposito, P. B.↗