Results for “Variability analysis” — Page 75

NASA NTRS2004

Aeroelastic Stability and Response of Rotating Structures

A summary of the work performed under NASA grant is presented. More details can be found in the cited references. This grant led to the development of relatively faster aeroelastic analysis methods for predicting flutter and forced response in fans, compressors, and turbines using computational fluid dynamic (CFD) methods. These methods are based on linearized two- and three-dimensional, unsteady, nonlinear aerodynamic equations. During the period of the grant, aeroelastic analysis that includes the effects of uncertainties in the design variables has also been developed.

Keith, Theo G., Jr.↗

NASA NTRS2004

The X-Ray Variable Sky

A novel approach to search for rapid time variability of every source, whether persistent or transient, within the entire ROSAT detector field has been developed. Semi-automated software statistically tests the photon arrival time event list for source variability and reports significant (greater than 5 sigma) variable enhancement in the photon count rate on time scales ranging from 5-500 seconds. The computational algorithms have been thoroughly tested, and are able to discriminate between false detections induced by instrumental effects, and real X-ray variable sources (XRVs); when carefully scrutinized by the PI. The analysis has proven to be successful, with both periodic and transient XRVs having been found. Some of these are entirely new discoveries, while others have been detected in previous X-ray missions, yet their nature remained elusive since source identification and analysis had yet to be performed. On average, one new (unidentified) XRV is found per ROSAT PSPC field analyzed. In some cases the XRVs show only a transient signature (a burst type event) with no persistent X-ray or other known (optical) counterpart. The ambitious goal of this project was to process as much of the ROSAT PSPC archive data as feasibly possible to discover XRVs and analyze this data.

Stringfellow, Guy↗

NASA NTRS2002

Autonomic neural control of dynamic cerebral autoregulation in humans

BACKGROUND: The purpose of the present study was to determine the role of autonomic neural control of dynamic cerebral autoregulation in humans. METHODS AND RESULTS: We measured arterial pressure and cerebral blood flow (CBF) velocity in 12 healthy subjects (aged 29+/-6 years) before and after ganglion blockade with trimethaphan. CBF velocity was measured in the middle cerebral artery using transcranial Doppler. The magnitude of spontaneous changes in mean blood pressure and CBF velocity were quantified by spectral analysis. The transfer function gain, phase, and coherence between these variables were estimated to quantify dynamic cerebral autoregulation. After ganglion blockade, systolic and pulse pressure decreased significantly by 13% and 26%, respectively. CBF velocity decreased by 6% (P<0.05). In the very low frequency range (0.02 to 0.07 Hz), mean blood pressure variability decreased significantly (by 82%), while CBF velocity variability persisted. Thus, transfer function gain increased by 81%. In addition, the phase lead of CBF velocity to arterial pressure diminished. These changes in transfer function gain and phase persisted despite restoration of arterial pressure by infusion of phenylephrine and normalization of mean blood pressure variability by oscillatory lower body negative pressure. CONCLUSIONS: These data suggest that dynamic cerebral autoregulation is altered by ganglion blockade. We speculate that autonomic neural control of the cerebral circulation is tonically active and likely plays a significant role in the regulation of beat-to-beat CBF in humans.

Non-NASA Center↗

NASA NTRS2007

Relativistic Iron K Emission and Absorption in the Seyfert 1.9 Galaxy MCG-05-23-16

We present the results of the simultaneous deep XMM-Newton and Chandra observations of the bright Seyfert 1.9 galaxy MCG-5-23-16, which is thought to have one of the best known examples of a relativistically broadened iron Kalpha line. We detected a narrow sporadic absorption line at 7.7 keV which appears to be variable on a time-scale of 20 ksec. If associated with FeXXVI this absorption is indicative of a possible variable high ionization, high velocity outflow. The time averaged spectral analysis shows that the iron K-shell complex is best modeled with an unresolved narrow emission component (FWHM less than 5000 kilometers per second, EW approx. 60 eV) plus a broad component. This latter component has FWHM approx. 44000 kilometers per second, an EW approx. 50 eV and its profile is well described with an emission line originating from the accretion disk viewed with an inclination angle approx. 40 deg. and with the emission arising from within a few tens of gravitational radii of the central black hole. The time-resolved spectral analysis of the XMM-Newton EPIC-pn spectrum shows that both the narrow and broad components of the Fe K emission line appear to be constant within the errors. The analysis of the XMM-Newton/RGS spectrum reveals that the soft X-ray emission of MCG-5-23-16 is likely dominated by several emission lines superimposed on an unabsorbed scattered power-law continuum. The lack of strong Fe L shell emission together with the detection of a strong forbidden line in the O VII triplet supports a scenario where the soft X ray emission lines are produced in a plasma photoionized by the nuclear emission.

Braito, V.↗

NASA NTRS2012

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Koster, Randal↗

NASA NTRS2012

Validation of MODIS FLH and In Situ Chlorophyll a from Tampa Bay, Florida (USA)

Satellite observation of phytoplankton concentration or chlorophyll-a (chla) is an important characteristic, critically integral to monitoring coastal water quality. However, the optical properties of estuarine and coastal waters are highly variable and complex and pose a great challenge for accurate analysis. Constituents such as suspended solids and dissolved organic matter and the overlapping and uncorrelated absorptions in the blue region of the spectrum renders the blue-green ratio algorithms for estimating chl-a inaccurate. Measurement of suninduced chlorophyll fluorescence, on the other hand, which utilizes the near infrared portion of the electromagnetic spectrum may, provide a better estimate of phytoplankton concentrations. While modelling and laboratory studies have illustrated both the utility and limitations of satellite algorithms based on the sun induced chlorophyll fluorescence signal, few have examined the empirical validity of these algorithms or compared their accuracy against bluegreen ratio algorithms . In an unprecedented analysis using a long term (2003-2011) in situ monitoring data set from Tampa Bay, Florida (USA), we assess the validity of the FLH product from the Moderate Resolution Imaging Spectrometer against a suite of water quality parameters taken in a variety of conditions throughout this large optically complex estuarine system. . Overall, the results show a 106% increase in the validity of chla concentration estimation using FLH over the standard chla estimate from the blue-green OC3M algorithm. Additionally, a systematic analysis of sampling sites throughout the bay is undertaken to understand how the FLH product responds to varying conditions in the estuary and correlations are conducted to see how the relationships between satellite FLH and in situ chlorophyll-a change with depth, distance from shore, from structures like bridges, and nutrient concentrations and turbidity. Such analysis illustrates that the correlations between FLH and in situ chla measurements increases with increasing distance between monitoring sites and structures like bridges and shore. Due probably to confounding factors, expected improvement in the FLH- chla relationship was not clearly noted when increasing depth and distance from shore alone (not including bridges). Correlations between turbidity and nutrient concentrations are discussed further and principle component analyses are employed to address the relationships between the multivariate data sets. A thorough understanding of how satellite FLH algorithms relate to in situ water quality parameters will enhance our understanding of how MODIS s global FLH algorithm can be used empirically to monitor coastal waters worldwide.

Fischer, Andrew↗

NASA NTRS2012

Psychophysiological Assessment of Fatigue in Commercial Aviation Operations

The overall goal of this study is to improve our understanding of crew work hours, workload, sleep, fatigue, and performance, and the relationships between these variables on actual flight deck performance. Specifically, this study will provide objective measures of physiology and performance, which may benefit investigators in identifying fatigue levels of operators in commercial aviation and provide a way to better design strategies to limit crew fatigue. This research was supported by an agreement between NASA Ames Research Center and easyJet Airline Company, Ltd., Luton, UK. Twenty commercial pilots volunteered to participant in the study that included 15 flight duty days. Participants wore a Zephyr Bioharness ambulatory physiological monitor each flight day, which measured their heart rate, respiration rate, skin temperature, activity and posture. In addition, pilots completed sleep log diaries, self-report scales of mood, sleepiness and workload, and a Performance Vigilance Task (PVT). All data were sent to NASA researchers for processing and analyses. Heart rate variability data of several subjects were subjected to a spectral analysis to examine power in specific frequency bands. Increased power in low frequency band was associated with reports of higher subjective sleepinesss in some subjects. Analyses of other participants data are currently underway.

Hernandez, Norma↗

NASA NTRS2014

Estimating Uncertainty in Long Term Total Ozone Records from Multiple Sources

Total ozone measurements derived from the TOMS and SBUV backscattered solar UV instrument series cover the period from late 1978 to the present. As the SBUV series of instruments comes to an end, we look to the 10 years of data from the AURA Ozone Monitoring Instrument (OMI) and two years of data from the Ozone Mapping Profiler Suite (OMPS) on board the Suomi National Polar-orbiting Partnership satellite to continue the record. When combining these records to construct a single long-term data set for analysis we must estimate the uncertainty in the record resulting from potential biases and drifts in the individual measurement records. In this study we present a Monte Carlo analysis used to estimate uncertainties in the Merged Ozone Dataset (MOD), constructed from the Version 8.6 SBUV2 series of instruments. We extend this analysis to incorporate OMI and OMPS total ozone data into the record and investigate the impact of multiple overlapping measurements on the estimated error. We also present an updated column ozone trend analysis and compare the size of statistical error (error from variability not explained by our linear regression model) to that from instrument uncertainty.

TOMS and SBUV↗

NASA NTRS2013

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

remote sensing↗

NASA NTRS2020

The European Russia Drought Atlas (1400-2016 CE)

We present the European Russia Drought Atlas (ERDA) that covers the East European Plain to the Ural Mountains from 1400–2016 CE. Like the Old World Drought Atlas (OWDA) for the Euro-Mediterranean region, the ERDA is a one-half degree gridded reconstruction of summer Palmer Drought Severity Indices estimated from a network of annual tree-ring chronologies. Ensemble point-by-point regression is used to generate the ERDA with the identical protocols used for developing the OWDA. Split calibration/validation tests of the ERDA indicate that it has significant skill over most of its domain and is much more skillful than the OWDA where they overlap in the western part of ERDA domain. Comparisons to historical droughts over European Russia additionally support the ERDA’s overall validity. The ERDA has been spatially smoothed and infilled using a local regression method to yield a spatially complete drought atlas back to 1400 CE. EOF analysis indicates that there are three principal modes of hydroclimatic variability in the ERDA. After Varimax rotation, these modes correlate significantly with independent climate data sets extending back to the late nineteenth century in a physically interpretable way and relate to atmospheric circulation dynamics of droughts and heatwaves over European Russia based on more recent instrumental data.

Cook, Edward R.↗

NASA NTRS2020

Particulate backscattering in the global ocean: A comparison of independent assessements

How well do we know the particulate backscattering coefficient (bbp) in the global ocean? Satellite lidar bbp has never been validated globally and few studies have compared lidar bbp to bbp derived from reflectances (via ocean color) or in-situ observations. Here we validate lidar bbp with autonomous biogeochemical Argo floats using a decorrelation analysis to identify relevant spatiotemporal matchup scales inspired by geographical variability in the Rossby radius of deformation. We compare lidar, float, and ocean color bbp at the same locations and times to assess performance. Lidar bbp outperforms ocean color, with a median percent error of 18% compared to 24% in the best case and a relative bias of -11% compared to -21%, respectively. Phytoplankton carbon calculated from ocean color and lidar exhibits basin-scale differences that can reach ± 50%.

ocean color↗

NASA NTRSDate not supplied

Aeroelastic Trim Drag Optimization of Mach 0.8 TransonicTruss-Braced Wing Aircraft with Variable Camber ContinuousTrailing Edge Flap

This paper presents an aeroelastic trim drag optimization study of the Mach 0.8 Tran-sonic Truss-Braced Wing (TTBW) aircraft with the Variable Camber Continuous TrailingEdge Flap (VCCTEF). An aero-structural analysis solver VSPAERO with transonic small dis-turbance, integral boundary-layer, and wing-strut interference corrections coupled to modeshapes computed by NASTRAN using the Galerkin method is developed to provide a rapidaircraft aeroelastic performance evaluation. Aeroelastic trim drag optimization studies areconducted for a VCCTEF configuration with 6-spanwise sections. Three different flight condi-tions corresponding to Mach 0.8 are selected for the aeroelastic trim drag optimization at thedesign and off-design cruise lift coefficients. The preliminary optimization results show thatthe TTBW aircraft with the optimized VCCTEF deflection achieves a drag reduction of about 9.2 counts, 9.6 counts, and 12.3 counts corresponding to the lift coefficients 0.661, 0.695, and0.729, respectively. When accounting for the actuator weight penalty, the corresponding dragreductions are 1.77%, 1.82%, 2.41%. A high-fidelity CFD solver FUN3D is used to validatethe aeroelastic trim drag optimization.

Aeroelastic trim drag↗

NASA NTRSDate not supplied

Evaluating the Impact of Geostationary Sounders in the Context of International Coordination

The proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) program plans to include a hyperspectral infrared (IR) sounder (GXS) on its central satellite, joining international counterparts. Ahead of launch, the NASA Global Modeling and Assimilation Office (GMAO) assessed the potential effectiveness of GXS both as a lone sounder in a GEO orbit and as part of a global ring of such instruments. Using an observing system simulation experiment (OSSE) framework from a global numerical weather prediction (NWP) perspective, the ability of GXS and the global ring to improve weather prediction of thermodynamic variables was assessed both globally and regionally. GXS dominated regional analysis and forecast improvements and contributed significantly to global increases in forecast skill. However, more sustained global improvements on the order of 4 days rely on international partnerships. Over CONUS, the FSOI metric showed the GXS observations provide the strongest radiance impact on the moist energy error norm reduction. Additionally, GXS shows the capability to improve hurricane forecast track errors, resulting in improved forecast warnings. Overall, the persistent atmospheric profile information from GXS over much of the western hemisphere provide an opportunity to improve the representation of weather systems and their forecasts.

Erica L. McGrath-Spangler↗

NASA NTRSDate not supplied

Evaluating the Impact of Geostationary Sounders in the Context of International Coordination

The proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) program plans to include a hyperspectral infrared (IR) sounder (GXS) on its central satellite, joining international counterparts. Ahead of launch, the NASA Global Modeling and Assimilation Office (GMAO) assessed the potential effectiveness of GXS both as a lone sounder in a GEO orbit and as part of a global ring of such instruments. Using an observing system simulation experiment (OSSE) framework from a global numerical weather prediction (NWP) perspective, the ability of GXS and the global ring to improve weather prediction of thermodynamic variables was assessed both globally and regionally. GXS dominated regional analysis and forecast improvements and contributed significantly to global increases in forecast skill. However, more sustained global improvements on the order of 4 days rely on international partnerships. Over CONUS, the FSOI metric showed the GXS observations provide the strongest radiance impact on the moist energy error norm reduction. Additionally, GXS shows the capability to improve hurricane forecast track errors, resulting in improved forecast warnings. Overall, the persistent atmospheric profile information from GXS over much of the western hemisphere provide an opportunity to improve the representation of weather systems and their forecasts.

Erica McGrath-Spangler↗

NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗

NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗

NASA NTRSDate not supplied

Techniques in Assessing Random Uncertainty of Wind Tunnel Replicate Test Data

The preferred method to determine the random uncertainty of variables of interest during wind tunnel tests is by direct analysis of replicate data. However, current information is limited to analysis of a single replicate set condition that does not consider data covariance. This paper provides additional information on considerations for quantifying random uncertainty including the evaluation and correction of replicate data covariance, the selection of replicate set conditions for the test, and the interpolation of random uncertainty at other than replicate set conditions. The analysis and techniques are supported by data from a conventional aircraft configuration test at the Oran Nicks Low-Speed Wind Tunnel and an ASME nozzle flow characterization at the Propulsion Systems Laboratory.

Uncertainty↗

NASA NTRS2017

Influence of Mid-Latitude Cyclones on European Background Surface Ozone Investigated in Observations, MACC and MERRA-2 Reanalyses

The relationship between springtime mid-latitude cyclones and background ozone at two rural monitoring sites on the west coast of Europe -- Mace Head, Ireland and Monte Velho, Portugal -- is explored using a combination of observations and three reanalyses: 1) the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-Interim reanalysis, 2) the Monitoring Atmospheric Composition and Climate (MACC) reanalysis and 3) NASA's Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis. The ERA-Interim cyclone tracks are used here to establish the long-term relationship between cyclones and ozone observations (since 1988). The MACC reanalysis data set, which covers the period 2003-2012, is produced with the ECMWF integrated forecast system (IFS) model two-way coupled to a chemistry transport model (CTM). Since the MACC reanalysis uses a similar atmospheric model to ERA-Interim, MACC is used to explore the mechanisms within the case study cyclones that can influence surface ozone concentrations at Mace Head and Monte Velho. The MERRA-2 reanalysis also provides 3D distributions of ozone, although less ideal for analysis of surface ozone concentrations since MERRA-2 ozone under represents ozone variability outside the stratosphere as it does not have a detailed chemistry scheme or emission sources for the troposphere. The MERRA-2 reanalysis, which has the potential to identify more features within the cyclones as the resolution is higher than the MACC reanalysis, is used in conjunction with the MACC reanalysis to provide a measure of uncertainty to the case study analysis. We found the main source of high ozone to these two sites is from the stratosphere, which is well represented in both the MERRA-2 and the MACC reanalyses, either from direct injection into the cyclone or associated with aged airstreams from decaying downstream cyclones that can become entrained and descend toward the surface within new cyclones over the NA region.

MERRA-2↗