Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data Reasoning”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Faults Discovery By Using Mined Data

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Lee, Charles↗
DOE OSTI2024

Multi-fidelity Fourier neural operator for fast modeling of large-scale geological carbon storage

Deep learning-based surrogate models have been widely applied in geological carbon storage (GCS) problems to accelerate the prediction of reservoir pressure and CO2 plume migration. Large amounts of data from physics-based numerical simulators are required to train a model to accurately predict the complex physical behaviors associated with this process. In practice, the available training data are always limited in large-scale 3D problems due to the high computational cost. Therefore, we propose to use a multi-fidelity Fourier neural operator (FNO) to solve large-scale GCS problems with more affordable multi-fidelity training datasets. FNO has a desirable grid-invariant property, which simplifies the transfer learning procedure between datasets with different discretization. Here, we first test the model efficacy on a GCS reservoir model being discretized into 110 k grid cells. The multi-fidelity model can predict with accuracy comparable to a high-fidelity model trained with the same amount of high-fidelity data with 81% less data generation costs. We further test the generalizability of the multi-fidelity model on a same reservoir model with a finer discretization of 1 million grid cells. This case was made more challenging by employing high-fidelity and low-fidelity datasets generated by different geostatistical models and reservoir simulators. We observe that the multi-fidelity FNO model can predict pressure fields with reasonable accuracy even when the high-fidelity data are extremely limited. The findings of this study can help for better understanding of the transferability of multi-fidelity deep learning surrogate models.

58 GEOSCIENCES↗
NASA NTRS2010

On the Scaling of Small, Heat Simulated Jet Noise Measurements to Moderate Size Exhaust Jets

Modern military aircraft jet engines are designed with variable geometry nozzles to provide optimum thrust in different operating conditions, depending on the flight envelope. However, the acoustic measurements for such nozzles are scarce, due to the cost involved in making full scale measurements and the lack of details about the exact geometry of these nozzles. Thus the present effort at The Pennsylvania State University and the NASA Glenn Research Center- in partnership with GE Aviation is aiming to study and characterize the acoustic field produced by supersonic jets issuing from converging-diverging military style nozzles. An equally important objective is to validate methodology for using data obtained from small and moderate scale experiments to reliably predict the most important components of full scale engine noise. The experimental results presented show reasonable agreement between small scale and moderate scale jet acoustic data, as well as between heated jets and heat-simulated ones. Unresolved issues however are identified that are currently receiving our attention, in particular the effect of the small bypass ratio airflow. Future activities will identify and test promising noise reduction techniques in an effort to predict how well such concepts will work with full scale engines in flight conditions.

McLaughlin, Dennis K.↗
DOE OSTI2021

Physiological Characterization of Language Comprehension

In this project, our goal was to develop methods that would allow us to make accurate predictions about individual differences in human cognition. Understanding such differences is important for maximizing human and human-system performance. There is a large body of research on individual differences in the academic literature. Unfortunately, it is often difficult to connect this literature to applied problems, where we must predict how specific people will perform or process information. In an effort to bridge this gap, we set out to answer the question: can we train a model to make predictions about which people understand which languages? We chose language processing as our domain of interest because of the well- characterized differences in neural processing that occur when people are presented with linguistic stimuli that they do or do not understand. Although our original plan to conduct several electroencephalography (EEG) studies was disrupted by the COVID-19 pandemic, we were able to collect data from one EEG study and a series of behavioral experiments in which data were collected online. The results of this project indicate that machine learning tools can make reasonably accurate predictions about an individual?s proficiency in different languages, using EEG data or behavioral data alone.

42 ENGINEERING↗
NASA NTRS1996

Transonic Turbulent Flow Predictions With Two-Equation Turbulence Models

Solutions of the Favre-averaged Navier-Stokes equations for two well-documented transonic turbulent flows are compared in detail with existing experimental data. While the boundary layer in the first case remains attached, a region of extensive flow separation has been observed in the second case. Two recently developed k-epsilon, two-equation, eddy-viscosity models are used to model the turbulence field. These models satisfy the realizability constraints of the Reynolds stresses. Comparisons with the measurements are made for the wall pressure distribution, the mean streamwise velocity profiles, and turbulent quantities. Reasonably good agreement is obtained with the experimental data.

Liou, William W.↗
NASA NTRS1987

A canopy reflectance model based on an analytical solution to the multiple scattering equation

An approximation to the radiative transfer equation for solar radiation in relatively full, homogeneous plant canopies is presented and solved analytically for solar zenith angles less than 60 deg. The model predicts reflectance at any depth in the canopy and in any direction and may be inverted with bidirectional reflectance measurements. The model was fit to data at two sun angles and two wavebands (visible and NIR) to within the assumed errors on the reflectance data. The calculated albedos are insensitive to achievable measurement errors. Some of the parameter values themselves found by the inversion agree reasonably well with independent measurements, but the uncertainties introduced by the data noise are rather large. However, the agreement is good enough to demonstrate that the model is physically realistic.

Camillo, Peter↗
NASA NTRS1995

Finding the forest in the trees: The challenge of combining diverse environmental data

It has become increasingly important to conduct interdisciplinary environmental research assessments, both nationally and internationally. For this reason, the Committee for a Pilot Study on Database Interfaces was charged to review and advise on data interfacing activities. The committee used six case studies (1) to identify and understand the most important problems associated with collecting, integrating, and analyzing environmental data from local to global spatial scales and over a very wide range of temporal scales; and (2) to elaborate the common barriers to interfacing data of disparate sources and types. Consistent with the committee's charge, the primary focus was the interfacing of geophysical and ecological data. The case studies used by the committee were: The Impact Assessment Project for Drought Early Warning in the Sahel, The National Acid Precipitation Assessment Program, The H.J. Andrew Experimental Forest Long-Term Ecological Research Site, The Carbon Dioxide Information Analysis Center, The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment, and The California Cooperative Oceanic Fisheries Investigation. The committee derived a number of lessons from the case studies, and these lessons are summarized at the end of each case study and analyzed in the last chapter. Some are generic in nature; others are more specific to a discipline or project. The conclusions and recommendations are based on the committee's analysis of the case studies and additional research. They are organized according to four major areas of barriers or challenges to the effective interfacing of diverse environmental data. In the final section the committee offers a set of broadly applicable principles (Ten Keys to Success) that can be used by scientists and data managers in planning and conducting interfacing activities.

Source record↗
NASA NTRS2003

Data and Modeling of Dendrites Subject to A Step Change in Pressure (TDSE)

There is considerable interest in dendritic solidification because of the influence dendrites have in the determination of microstructure, and thereby in the physical properties of cast metals and alloys. Current theories and models of dendritic growth generally couple diffusion effects in the melt with the physics of the interface. Data and subsequent analysis prior of the tip growth speed and radii of thermal succinonitrile dendrites in the near-convection free, on-orbit, free-fall environment demonstrate that these theories yield predictions that are reasonably in agreement with the results of experiment. However, data and analysis for assessing the interfacial physics component of theory are not sufficiently detailed or definitive. To study fundamental aspects of dendritic interface stability, we are measuring and modeling the kinetics and morphology of dendrites as they evolve from one well-defined steady state at a pre-set supercooling, through a transient stage, to a different well-defined steady state. More specifically, we subject succinonitrile dendrites, growing under steady-state conditions, to a rapid change in pressure. This leads to a rapid change in thermal driving force from the corresponding change in both the equilibrium melting temperature due to the Clapeyron effect, and a change in the far-field temperature due to adiabatic temperature changes in the bulk liquid and solid. Subsequently, we observe transformations from a well-characterized initial state into a new steady-state. Initial data reveal that the dendrite tip velocity changes almost as fast as the pressure charges, while the tip radius changes occur more slowly, taking from 10 60 seconds depending on the size of the step change and the final supercooling. Computer modeling of this process shows both agreements and disagreements with the experimental data. In making these observations and measurements, we are gaining new understandings of interfacial dynamics and state-selection physics.

Koss, Matthew B.↗
NASA NTRS1986

Comparison of analytical and experimental performance of a wind-tunnel diffuser section

Wind tunnel diffuser performance is evaluated by comparing experimental data with analytical results predicted by an one-dimensional integration procedure with skin friction coefficient, a two-dimensional interactive boundary layer procedure for analyzing conical diffusers, and a two-dimensional, integral, compressible laminar and turbulent boundary layer code. Pressure, temperature, and velocity data for a 3.25 deg equivalent cone half-angle diffuser (37.3 in., 94.742 cm outlet diameter) was obtained from the one-tenth scale Altitude Wind Tunnel modeling program at the NASA Lewis Research Center. The comparison is performed at Mach numbers of 0.162 (Re = 3.097x19(6)), 0.326 (Re = 6.2737x19(6)), and 0.363 (Re = 7.0129x10(6)). The Reynolds numbers are all based on an inlet diffuser diameter of 32.4 in., 82.296 cm, and reasonable quantitative agreement was obtained between the experimental data and computational codes.

Shyne, R. J.↗
NASA NTRS1992

NASA's astrophysics archives at the National Space Science Data Center

NASA maintains an archive facility for Astronomical Science data collected from NASA's missions at the National Space Science Data Center (NSSDC) at Goddard Space Flight Center. This archive was created to insure the science data collected by NASA would be preserved and useable in the future by the science community. Through 25 years of operation there are many lessons learned, from data collection procedures, archive preservation methods, and distribution to the community. This document presents some of these more important lessons, for example: KISS (Keep It Simple, Stupid) in system development. Also addressed are some of the myths of archiving, such as 'scientists always know everything about everything', or 'it cannot possibly be that hard, after all simple data tech's do it'. There are indeed good reasons that a proper archive capability is needed by the astronomical community, the important question is how to use the existing expertise as well as the new innovative ideas to do the best job archiving this valuable science data.

Vansteenberg, M. E.↗
NASA NTRS2017

RFI Statistical Distribution and Missed Detection in Aquarius Radiometer Measurements

Aquarius is an microwave active/passive sensor whose main goal is to globally estimate sea surface salinity from space. Two instruments, a radar scatterometer and a radiometer, operate at L-band observing the same surface footprint almost simultaneously. The sensitivity to sea surface salinity (SSS) is given by the radiometer, while the scatterometer measurements provide a correction for sea surface roughness. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. Radio Frequency Interference (RFI) can occur in both the radiometer and the scatterometer bands of operation, and for this reason detection and mitigation of RFI was included in the data processing of both active and passive instruments. This paper will focus on the RFI processing for the Aquarius radiometer only and provide an update on the efforts to reduce the amount of missed RFI detection.

RFI↗
DOE OSTI2025

Analyze the real-time performance of the optimized fiber-PTR instrument

An instrument to perform in-reactor, real-time thermal property measurements of nuclear fuels and materials was recently designed, optimized, and tested at Massachusetts Institute of Technology Research Reactor. It was the second insertion experiments of a total of two rounds. Here we report the collection and analysis of the real-time captured thermal diffusivity data on the preloaded SiC. With the optimized design, the instrument temperature had been successfully raised as we expected. Only one probe (the top one) returned real-time thermal diffusivity in a time span of approximately two days. Measured thermal diffusivity of the preloaded SiC was significantly lower than the literature value at the same temperature, indicating a significant influence from the irradiation induced microstructure damage. Meanwhile, the real-time thermal diffusivity value continuously reduced with time, indicating the dynamic microstructure evolution. The possible reasons of the probes that did not return data were hypothesized. The further optimization of the instrument with the objective to improve the measurement accuracy and instrument survivability is also discussed.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Dunes and microdunes on Venus: Why were so few found in the Magellan data?

A search through cycle 1, 2, and 3 Magellan radar data covering 98% of the surface of Venus revealed very few dunes. Only two possible dune fields and several areas that may contain microdunes smaller than the resolution of the images (75 m) were identified. The Aglaonice dune field was identified in the cycle 1 images by the specular returns characteristic of dune faces oriented perpendicular to the radar illumination. Cycle 1 and 2 data of the Fortuna-Meshkenet dune field indicate that there has been no noticeable movement of the dunes over an 8-month period. The dunes, which are oriented both parallel and perpendicular to the radar illumination, appear to be dark features on a brighter substrate. Bright and dark patches that were visible in either cycle 1 or 2 data, but not both, allowed identification of several regions in the southern part of Venus that may contain microdunes. The microdunes are associated with several parabolic crater deposits in the region and are probably similar to those formed in wind tunnel experiments under Venus-like conditions. Bragg scattering and/or subpixel relfections from the near-normal face on asymmetric microdunes may account for these bright and dark patches. Look-angle effects and the lack of sufficient sand-size particles seem to be most likely reasons so few dunes were identified in Magellan data. Insufficient wind speeds, thinness of sand cover, and difficulty in identifying isolated dunes may also be contributors to the scarcity of dunes.

Weitz, Catherine M.↗
NASA NTRS1994

Dunes and Microdunes on Venus: Why Were So Few Found in the Magellan Data?

A search through cycle 1, 2, and 3 Magellan radar data covering 98% of the surface of Venus revealed very few dunes. Only two possible dune fields and several areas that may contain microdunes smaller than the resolution of the images (75 m) were identified. The Aglaonice dune field was identified in the cycle I images by the specular returns characteristic of dune faces oriented perpendicular to the radar illumination. Cycle 1 and 2 data of the Fortuna-Meshkenet dune field indicate that there has been no noticeable movement of the dunes over an 8-month period. The dunes, which are oriented both parallel and perpendicular to the radar illumination, appear to be dark features on a brighter substrate. Bright and dark patches that were visible in either cycle 1 or 2 data, but not both, allowed identification of several regions in the southern part of Venus that may contain microdunes. The microdunes are associated with several parabolic crater deposits in the region and are probably similar to those formed in wind tunnel experiments under Venus-like conditions. Bragg scattering and/or subpixel reflections from the near-normal face on asymmetric microdunes may account for these bright and dark patches. Look-angle effects and the lack of sufficient sand-size particles seem to be the most likely reasons so few dunes were identified in Magellan data. Insufficient wind speeds, thinness of sand cover, and difficulty in identifying isolated dunes may also be contributors to the scarcity of dunes.

Weitz, Catherine M.↗
NASA NTRS1986

Atmospheric correction of TIMS data

The Thermal Infrared Multispectral Scanner (TIMS) is a unique sensor for two reasons, it is multispectral in the thermal-infrared and it has on board, active calibration sources. The existence of the calibration permits the recorded DNs to be converted unambiguously to absolute energy units. However, to relate the data to energy originating from a target on the ground it is necessary to remove the atmospheric contribution to the signal, specifically its transmittance and emittance. These can be obtained fairly easily by use of the atmospheric model provided by LOWTRAN-6 and the data from the U.S. Weather Service network of bidaily radiosondes. Using these data with the TIMS responsivity curves an equation can be obtained which permits the unambiguous correction of the TIMS data for the atmosphere.

Rickman, Doug↗
NASA NTRSDate not supplied

Analysis of Atmospheric Conditions Responsible for an Ozone Exceedance Event in Southeast Virginia on June 15, 2022

On June 15, 2022, the Virginia Department of Environmental Quality monitoring site at Suffolk/Holland, a rural site in southeast Virginia, recorded its first ozone exceedance since 2016. An ozone exceedance day occurs when the daily maximum 8-hour average surface ozone concentration is greater than 70 ppb. On this day, it was 75 ppb. This event is also noteworthy due to the rapid increase in surface ozone between 6 am and 9 am EDT as well as the hourly maximum ozone concentration of 82 ppb that was measured at 1 pm EDT. In this analysis, we utilize various observational and model data to determine the atmospheric conditions responsible for this ozone exceedance event. The analysis is conducted in two parts: (1) an evaluation of the accuracy of the GEOS-CF and WRF-Chem model forecasts and (2) an investigation of the mechanisms responsible for the high surface ozone at the Virginia DEQ Suffolk/Holland monitoring site. Comparisons of model forecasted ozone time-height cross sections with measured ozone by lidars from the Tropospheric Ozone Lidar Network (TOLNet) at NASA Langley and NASA Goddard reveal that both models forecasted ozone reasonably well near the surface. Model and observational data reveal that an upper-level ridge was present over much of the eastern United States, with a broad anticyclonic circulation near the surface, resulting in north-northeasterly flow over southeast Virginia. Back trajectory calculations using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) and model data suggest that a low-level plume rich in ozone and precursor species originating from the New York City and New Jersey region was transported along the east coast between June 14 and June 15, arriving in southeast Virginia around 6 am EDT on June 15. In the early morning hours, this plume mixed down to the surface, elevating the background ozone mixing ratio as well as the mixing ratios of several precursor species. Other potential contributions are also explored and discussed. Lastly, the authors note that this work represents the analysis of the authors and not the Virginia Department of Environmental Quality.

Daniel B Phoenix↗
NASA NTRS1983

Comet Halley ephemeris uncertainties in 1985-1986

For the planned flyby missions to Comet Halley in March 1986, the comet's ephemeris uncertainties completely dominate the spacecraft-comet miss distance. In an effort to determine realistic Comet Halley ephemeris uncertainties, a statistical covariance analysis was conducted using the actual data in 1909-1910-1911 and simulated data in 1984-1985-1986. In 1985-1986, Comet Halley's ephemeris uncertainties are very sensitive to the comet's orbital position, the optical data noise, data schedule, and whether or not the old data is included in the orbital solutions. The comet's ephemeris uncertainties in March 1986 are relatively insensitive to reasonable center of light/center of mass offsets and also to possible radar data taken in late November 1985. Accurate Space Telescope observations made in early March 1986 might significantly improve upon the comet's position uncertainties for the various intercepting spacecraft.

Yeomans, D. K.↗
NASA NTRS1988

Atomic oxygen modeling in the upper thermosphere

Empirical models of atomic oxygen in the earth's thermosphere are discussed, and calibration problems in satellite drag and in situ mass spectrometer measurements are reviewed. Models based on drag data and mass spectrometer data are found to agree on average to within 15 percent, suggesting that the absolute values are reasonably well known in the upper thermosphere. Comparison of different models with various data sources show residuals of at least 15 percent which are the results of unmodeled magnetic storm, EUV, and geographical variations and smaller scale variations caused by gravity waves.

Hedin, A. E.↗