SEARCH · Engineering Papers

Results for “Correlation coefficient”

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.

SourceResearch connectionFrom yearThrough year

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

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS1979

The prediction of AE, ap, and Dst at time lags between 0 and 30 hours

The magnetic activity indexes AE, ap, and Dst are correlated with approximately 35,000 hours of interplanetary plasma and magnetic field measurements acquired near the Earth (assembled by NASA/NSSDC into a composite data sat). Lag times between the indexes and solar wind parameters ranged from 0 to 30 hours. Correlations at lags less than 6 hours yield results in agreement with previous studies. At greater lags, the correlation coefficients between the solar wind parameters and AE and ap approach these parameters' autocorrelation (persistence) values. For Dst the correlation with solar wind parameters is lower than that with AE and ap in the 3 to 4 hour lag range whereas the autocorrelation of Dst is significantly higher over the entire 0 to 30 hour lag range. The implications of these differences between AE, ap, and Dst are discussed in terms of persistence of solar wind structure.

Smart, D. F.↗

NASA NTRS1982

Reduction in peak oxygen uptake after prolonged bed rest

The hypothesis that the magnitude of the reduction in peak oxygen uptake (VO2) after bed rest is directly proportional to the level of pre-bed rest peak VO2 is tested. Complete pre and post-bed rest working capacity and body weight data were obtained from studies involving 24 men (19-24 years old) and 8 women (23-34 years old) who underwent bed rest for 14-20 days with no remedial treatments. Results of regression analyses of the present change in post-bed rest peak VO2 on pre-bed rest peak VO2 with 32 subjects show correlation coefficients of -0.03 (NS) for data expressed in 1/min and -0.17 for data expressed in ml/min-kg. In addition, significant correlations are found that support the hypothesis only when peak VO2 data are analyzed separately from studies that utilized the cycle ergometer, particularly with subjects in the supine position, as opposed to data obtained from treadmill peak VO2 tests. It is concluded that orthostatic factors, associated with the upright body position and relatively high levels of physical fitness from endurance training, appear to increase the variability of pre and particularly post-bed rest peak VO2 data, which would lead to rejection of the hypothesis.

Greenleaf, J. E.↗

NASA NTRS1987

The correlation between far-IR and radio continuum emission from spiral galaxies

A sample of 30 galaxies selected for their intense IRAS flux at 60 and 100 micron using the Arecibo telescope at 21 cm to measure the continuum and HI line luminosities were observed. The centimeter wave continuum correlates very well with the far-infrared flux, with a correlation coefficient as high as that found for other samples, and the same ratio between FIR and radio luminosities. Weaker correlations are seen between the FIR and optical luminosity and between the FIR and radio continuum. There is very little correlation between the FIR and the HI mass deduced from the integral of the 21 cm line. The strength of the radio continuum correlation suggests that there is little contribution to either the radio and FIR from physical processes not affecting both. If they each reflect time integrals of the star formation rate then the time constants must be similar, or the star formation rate must change slowly in these galaxies.

Dickey, John M.↗

NASA NTRS1995

Performance of residual carrier array-feed combining in correlated noise

An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory's 34-meter DSS-13 antenna. In this system, the defocused signal field captured by a focal plane array feed is recovered using real-time signal-processing and signal-combining techniques. The current signal-processing and signal-combining algorithms are optimum under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. Experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The main result of this article is an analytical derivation of the actual SNR performance of the current suboptimal signal-combining algorithm in this correlated-noise environment. The analysis here shows that the combined signal SNR can either be improved or degraded depending on the relation between the array signal and noise correlation coefficient phases. Further performance improvement will require the development of signal-combining methods that take into account the correlated noises.

Tan, H. H.↗

NASA NTRS2015

Comparisons of Characteristics of Magnetic Clouds and Cloud-Like Structures During 1995-2012

Using eighteen years (1995 - 2012) of solar wind plasma and magnetic field data (observed by the Wind spacecraft), solar activity (e.g. sunspot number: SSN), and the geomagnetic activity index (Dst), we have identified 168 magnetic clouds (MCs) and 197 magnetic cloud - like structures (MCLs), and we have made relevant comparisons. The following features are found during seven different periods (TP: Total period during 1995 - 2012, P1 and P2: first and second half period during 1995 - 2003 and 2004 - 2012, Q1 and Q2: quiet periods during 1995 - 1997 and 2007 - 2009, A1 and A2: active periods during 1998 - 2006 and 2010 - 2012). (1) During the total period the yearly occurrence frequency is 9.3 for MCs and 10.9 for MCLs. (2) In the quiet periods Q1 > Q1 and Q2 > Q2, but in the active periods A1 < A1 and A2 < A2. (3) The minimum Bz (Bzmin) inside of a MC is well correlated with the intensity of geomagnetic activity, Dstmin (minimum Dst found within a storm event) for MCs (with a Pearson correlation coefficient, c.c. = 0.75, and the fitting function is Dstmin = 0.90+7.78Bzmin), but Bzmin for MCLs is not well correlated with the Dst index (c.c. = 0.56, and the fitting function is Dstmin = -9.40+ 4.58 Bzmin). (4) MCs play a major role in producing geomagnetic storms: the absolute value of the average Dstmin ( MC = -70 nT) for MCs associated geomagnetic storms is two times stronger than that for MCLs ( MCL = -35 nT), due to the difference in the IMF (interplanetary magnetic field) strength. (5) The SSN is not correlated with MCs ( TP, c.c. = 0.27), but is well associated with MCLs ( TP, c.c. = 0.85). Note that the c.c. for SSN vs. P2 is higher than that for SSN vs. P2. (6) Averages of IMF, solar wind speed, and density inside of the MCs are higher than those inside of the MCLs. (7) The average of MC duration (approx. = 18.82 hours) is approx. = 20 % longer than the average of MCL duration (approx. = 15.69 hours). (8) There are more MCs than MCLs in the quiet solar period, and more MCLs than MCs in the active solar period, probably due to the interaction between a MC and another significant interplanetary disturbance (including another MC) which could obviously change the character of a MC, but we speculate that some MCLs are no doubt due to other factors such as complex birth conditions at the Sun.

CME↗

NASA NTRS2019

Scenario Complexity for Unmanned Aircraft System Traffic

This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time apA quick and accurate assessment of complexity for a given traffic scenario can help plan and schedule flights to alleviate traffic bottleneck and mitigate operation risks, especially for unmanned aerial system traffic management where high traffic density or complexity is expected. This work introduces a traffic scenario complexity metric that was constructed based on the number of potential conflicts weighted by the conflict resolution cost associated. The cost associated with a conflict is calculated based on the corresponding conflict resolution maneuvers. To obtain the conflict resolution maneuvers, a MILP-based optimization was formulated with the vehicle model and conflict management parameters incorporated. To evaluate the complexity metrics, an approach of using measurements from high-fidelity simulations was proposed. The scenario complexity measurements for 920 random-generated scenarios were obtained through high-fidelity simulations and treated as the ground truth. Two statistics methods: Pearson and Alternative Conditional Expectations were applied for analysis. The results showed that the number of flights has low correlation with the scenario complexity according to the correlation coefficients calculated by both methods. The Alternative Conditional Expectations method shows that the proposed scenario complexity metric has better correlation with the ground truth than the number of potential conflicts.plications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.

traffic complexity↗

NASA NTRS1975

Application of LANDSAT to the Surveillance and Control of Lake Eutrophication in the Great Lakes Basin

The author has identified the following significant results. Computer techniques developed for mapping water quality parameters from LANDSAT data were demonstrated, using ground truth collected in an ongoing survey of water quality in Saginaw Bay (Lake Huron), Michigan. Regression correlation coefficients varied from 0.99 for total phosphorus to 0.72 for chlorophyll-a corrected. Five water quality parameters are best correlated with LANDSAT band 6 alone. Temperature relates to band 5 alone and only two bands are justified for mapping the remaining six parameters. LANDSAT CCTs were used as a basis for inventorying land use within each of the Ohio-Kentucky-Indiana regional commissions, 225 drainage areas, and nine counties. Sixteen categories were merged into ten categories and mapped at a scale of 1 in. = 5,000 ft, with detail to 0.44 hectares for the 2,700 sq mi region. These products were produced in less than 90 days at a cost of one cent an acre. LANDSAT CCTS were also used as a basis for inventorying land cover within the Triangle J council of governments 1,750 sq mi study area. The complete inventory was accomplished within a period of 60 days at a cost of about one half cent per acre.

Rogers, R. H.↗

NASA NTRS2023

Heliocentric Distance and Solar Activity Dependence of Sustained Quasi-radial Interplanetary Magnetic Field Occurrence

Planets close to their stars experience an interplanetary magnetic field (IMF) that is dominantly quasi-radial. Our solar system serves as a laboratory to study how the occurrence of quasi-radial IMF varies away from the star and under different stellar activities. Furthermore, on time and spatial scales relevant to magnetospheric physics, solar wind variability prevails in the form of structures generated both at the Sun and locally in the interplanetary space. The stationary Parker spiral model only approximates the large-scale structure of the IMF. Deviations from the Parker spiral often result in strongly radial magnetic fields that give rise to kinetic foreshock turbulence, which in turn can impact planetary magnetospheres. The relative significance of this type of interaction can be estimated statistically based on the occurrence rate of cases where the IMF is directed along the radial direction, leading to the entire day-side magnetosphere being downstream of the ion foreshock. We use observations covering radial distances from 0.1 to 10 au and more than 2 solar cycles to quantify the prevalence of radial IMFs throughout the heliosphere. Near Earth's orbit, it is found that the occurrence rates of quasi-radial and southward IMF orientations are similar, and that the Pearson correlation coefficient is ${{ \mathcal R }}_{{xy}}\sim -0.7$ calculated between quasi-radial IMF occurrence rate and solar activity. A negative correlation is demonstrated for radial distances extending to at least Mars but not to Saturn.

Brandon L Burkholder↗

NASA NTRS1982

A procedure for testing the quality of LANDSAT atmospheric correction algorithms

There are two basic methods for testing the quality of an algorithm to minimize atmospheric effects on LANDSAT imagery: (1) test the results a posteriori, using ground truth or control points; (2) use a method based on image data plus estimation of additional ground and/or atmospheric parameters. A procedure based on the second method is described. In order to select the parameters, initially the image contrast is examined for a series of parameter combinations. The contrast improves for better corrections. In addition the correlation coefficient between two subimages, taken at different times, of the same scene is used for parameter's selection. The regions to be correlated should not have changed considerably in time. A few examples using this proposed procedure are presented.

Dias, L. A. V.↗

NASA NTRS2022

Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations

The COVID-19 lockdown had a large impact on anthropogenic emissions of air pollutants and particularly on nitrogen dioxide (NO 2 ). While the overall NO 2 decline over some large cities is well-established, understanding the details remains a challenge since multiple source categories contribute. In this study, a new method of isolation of three components (background NO 2 , NO 2 from urban sources, and NO 2 from industrial point sources) is applied to estimate the impact of the COVID-19 lockdown on each of them. The approach is based on fitting satellite data by a statistical model with empirical plume dispersion functions driven by a meteorological reanalysis. Population density and surface elevation data as well as coordinates of industrial sources were used in the analysis. The tropospheric NO 2 vertical column density (VCD) values measured by the Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor over 261 urban areas for the period from 16 March to 15 June 2020 were compared with the average VCD values for the same period in 2018 and 2019. While the background NO 2 component remained almost unchanged, the urban NO 2 component declined by −18 % to −28 % over most regions. India, South America, and a part of Europe (particularly, Italy, France, and Spain) demonstrated a −40 % to −50 % urban emission decline. In contrast, the decline over urban areas in China, where the lockdown was over during the analysed period, was, on average, only -4.4± 8 %. Emissions from large industrial sources in the analysed urban areas varied greatly from region to region from -4.8 ± 6 % for China to -40 ± 10 % for India. Estimated changes in urban emissions are correlated with changes in Google mobility data (the correlation coefficient is 0.62) confirming that changes in traffic were one of the key elements in the decline in urban NO2 emissions. No correlation was found between changes in background NO2 and Google mobility data. On the global scale, the background and urban components were remarkably stable in 2018, 2019, and 2021, with averages of all analysed areas all being within ±2.5 % and suggesting that there were no substantial drifts or shifts in TROPOMI data. The 2020 data are clearly an outlier: in 2020, the mean background component for all analysed areas (without China) was -6.0 % ± 1.2 % and the mean urban component was -26.7 ± 2.6 % or 20σ below the baseline level from the other years.

COVID-19↗

NASA NTRS1981

Analysis of GASP carbon monoxide data

Atmospheric carbon monoxide in the upper troposphere and lower stratosphere for the period March 1977 through October 1978 was analyzed. The CO data are summarized and the distribution and variations in space and time of this gas are presented. The data show that the CO mixing ratios are higher in the troposphere than those in the stratosphere. In the Northern Hemisphere the highest value of CO mixing ratio occurs in spring, although more data are needed to verify these findings. Correlation coefficients among CO, O3, air temperature (T) and winds were calculated for different regions under different seasons. It was found that the CO correlates negatively with O3 above 20 degrees latitude and positively below that latitude. Case studies using the data of CO, O3, and T measured simultaneously were performed. Discussions and suggestions are made. Ozone data on seasonal basis is also summarized.

Wu, M. F.↗

NASA NTRS1986

Dynamically supported geoid highs over hotspots: Observation and theory

Hotspots are associated with long wavelength geoid highs, an association that is even stronger when the geoid highs associated with subduction zones are removed. These associations are quantified by expanding the hotspot distribution in spherical harmonics and calculating correlation coefficients as a function of harmonic degree. The hotspot distribution spectrum is essentially white, with peaks at degrees 2 and 6. It is correlated positively with the slab residual geoid for degrees 2 to 6, with low seismic velocity in the lower mantle at degree 2, and with low seismic velocity in the upper mantle at degree 6. A variety of fluid mechanical models were tested for hotspots, including lithospheric delamination and hot plumes, by calculating their predicted dynamic geoid responses and comparing them to the observations. These models include the effects of temperature dependent rheology. The preferred hotspot model, based on observations of the geoid and seismic tomography, has plumes preferentially occurring in regions of large scale background temperature highs in a mantle with substantial viscosity increase with depth, although other models are possible.

Richards, M. A.↗

NASA NTRS1988

Dynamically supported geoid highs over hotspots - Observation and theory

Richards, Mark A.↗

NASA NTRS2006

Using CO2:CO Correlations to Improve Inverse Analyses of Carbon Fluxes

Observed correlations between atmospheric concentrations of CO2 and CO represent potentially powerful information for improving CO2 surface flux estimates through coupled CO2-CO inverse analyses. We explore the value of these correlations in improving estimates of regional CO2 fluxes in east Asia by using aircraft observations of CO2 and CO from the TRACE-P campaign over the NW Pacific in March 2001. Our inverse model uses regional CO2 and CO surface fluxes as the state vector, separating biospheric and combustion contributions to CO2. CO2-CO error correlation coefficients are included in the inversion as off-diagonal entries in the a priori and observation error covariance matrices. We derive error correlations in a priori combustion source estimates of CO2 and CO by propagating error estimates of fuel consumption rates and emission factors. However, we find that these correlations are weak because CO source uncertainties are mostly determined by emission factors. Observed correlations between atmospheric CO2 and CO concentrations imply corresponding error correlations in the chemical transport model used as the forward model for the inversion. These error correlations in excess of 0.7, as derived from the TRACE-P data, enable a coupled CO2-CO inversion to achieve significant improvement over a CO2-only inversion for quantifying regional fluxes of CO2.

Palmer, Paul I.↗

NASA NTRS2011

El Nino-Southern Oscillation Correlated Aerosol Angstrom Exponent Anomaly Over the Tropical Pacific Discovered in Satellite Measurements

El Nino.Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical atmosphere. ENSO could potentially impact local and global aerosol properties through atmospheric circulation anomalies and teleconnections. By analyzing aerosol properties, including aerosol optical depth (AOD) and Angstrom exponent (AE; often used as a qualitative indicator of aerosol particle size) from the Moderate Resolution Imaging Spectrometer, the Multiangle Imaging Spectroradiometer and the Sea ]viewing Wide Field ]of ]view Sensor for the period 2000.2011, we find a strong correlation between the AE data and the multivariate ENSO index (MEI) over the tropical Pacific. Over the western tropical Pacific (WTP), AE increases during El Nino events and decreases during La Nina events, while the opposite is true over the eastern tropical Pacific (ETP). The difference between AE anomalies in the WTP and ETP has a higher correlation coefficient (>0.7) with the MEI than the individual time series and could be considered another type of ENSO index. As no significant ENSO correlation is found in AOD over the same region, the change in AE (and hence aerosol size) is likely to be associated with aerosol composition changes due to anomalous meteorological conditions induced by the ENSO. Several physical parameters or mechanisms that might be responsible for the correlation are discussed. Preliminary analysis indicates surface wind anomaly might be the major contributor, as it reduces sea ]salt production and aerosol transport during El Nino events. Precipitation and cloud fraction are also found to be correlated with tropical Pacific AE. Possible mechanisms, including wet removal and cloud shielding effects, are considered. Variations in relative humidity, tropospheric ozone concentration, and ocean color during El Nino have been ruled out. Further investigation is needed to fully understand this AE ]ENSO covariability and the underlying physical processes responsible for it.

Li, Jing↗

NASA NTRS1992

Correlation, Cost Risk, and Geometry

The geometric viewpoint identifies the choice of a correlation matrix for the simulation of cost risk with the pairwise choice of data vectors corresponding to the parameters used to obtain cost risk. The correlation coefficient is the cosine of the angle between the data vectors after translation to an origin at the mean and normalization for magnitude. Thus correlation is equivalent to expressing the data in terms of a non orthogonal basis. To understand the many resulting phenomena requires the use of the tensor concept of raising the index to transform the measured and observed covariant components into contravariant components before vector addition can be applied. The geometric viewpoint also demonstrates that correlation and covariance are geometric properties, as opposed to purely statistical properties, of the variates. Thus, variates from different distributions may be correlated, as desired, after selection from independent distributions. By determining the principal components of the correlation matrix, variates with the desired mean, magnitude, and correlation can be generated through linear transforms which include the eigenvalues and the eigenvectors of the correlation matrix. The conversion of the data to a non orthogonal basis uses a compound linear transformation which distorts or stretches the data space. Hence, the correlated data does not have the same properties as the uncorrelated data used to generate it. This phenomena is responsible for seemingly strange observations such as the fact that the marginal distributions of the correlated data can be quite different from the distributions used to generate the data. The joint effect of statistical distributions and correlation remains a fertile area for further research. In terms of application to cost estimating, the geometric approach demonstrates that the estimator must have data and must understand that data in order to properly choose the correlation matrix appropriate for a given estimate. There is a general feeling by employers and managers that the field of cost requires little technical or mathematical background. Contrary to that opinion, this paper demonstrates that a background in mathematics equivalent to that needed for typical engineering and scientific disciplines at the masters or doctorate level is appropriate within the field of cost risk.

Dean, Edwin B.↗

NASA NTRS2017

Synchronization of Human Autonomic Nervous System Rhythms with Geomagnetic Activity in Human Subjects

A coupling between geomagnetic activity and the human nervous system's function was identified by virtue of continuous monitoring of heart rate variability (HRV) and the time-varying geomagnetic field over a 31-day period in a group of 10 individuals who went about their normal day-to-day lives. A time series correlation analysis identified a response of the group's autonomic nervous systems to various dynamic changes in the solar, cosmic ray, and ambient magnetic field. Correlation coefficients and p values were calculated between the HRV variables and environmental measures during three distinct time periods of environmental activity. There were significant correlations between the group's HRV and solar wind speed, Kp, Ap, solar radio flux, cosmic ray counts, Schumann resonance power, and the total variations in the magnetic field. In addition, the time series data were time synchronized and normalized, after which all circadian rhythms were removed. It was found that the participants' HRV rhythms synchronized across the 31-day period at a period of approximately 2.5 days, even though all participants were in separate locations. Overall, this suggests that daily autonomic nervous system activity not only responds to changes in solar and geomagnetic activity, but is synchronized with the time-varying magnetic fields associated with geomagnetic field-line resonances and Schumann resonances.

Magnetic Fields↗

NASA NTRS2020

The Importance of Star Formation Intensity in Lyα Escape from Green Pea Galaxies and Lyman Break Galaxy Analogs

We have studied ultraviolet images of 40 Green Pea galaxies and 15 local Lyman Break Galaxy Analogs to understand the relation between Lyα photon escape and central UV photometric properties. We measured star formation intensity (SFI; star formation rate per unit area) from the central 250 pc region (S250 pc) using Cosmic Origins Spectrograph near-ultraviolet images from the Hubble Space Telescope. The measured S250 pc of our sample Green Peas ranges from 2.3–46M☉ yr−1 kpc−2, with a geometric mean of 15M☉ yr−1 kpc−2 and a standard deviation of 0.266 dex, forming a relatively narrow distribution. The Lyman Break Galaxy Analogs show a similarly narrow distribution of S250 pc (0.271 dex), though with a larger mean of 28M☉ yr−1 kpc−2. We show that while the Lyα equivalent width (EW(Lyα)) and the Lyα escape fraction ( f a esc Lyα) are not significantly correlated with the central SFI (S250 pc), both are positively correlated with the ratio of surface brightness to galaxy stellar mass (S250 pc/Mstar), with correlation coefficients (p-values) of 0.702 (1 × 10−8) and 0.529 (5 × 10−4) with EW(Lyα) and f a esc Lyα, respectively. These correlations suggest a scenario where intense central star formation can drive a galactic wind in galaxies with relatively shallow gravitational potential wells, thus clearing channels for the escape of Lyα photons.

Compact galaxies↗