Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Uncertainty modeling”

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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Early Estimation of Solar Activity Cycle: Potential Capability and Limits

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and longterm sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Kitiashvili, Irina N.↗
NASA NTRS2017

Using Data Assimilation Methods of Prediction of Solar Activity

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Prediction↗
NASA NTRS2017

Using Data Assimilation Methods for Prediction of Solar Activity

The variability of solar magnetic activity known as the 11-­‐year solar cycles has the longest history of observations. These solar cycles dramatically affect conditions in the heliosphere and the Earth’s space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-­‐term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model complemented by the equation of magnetic helicity conservation and long-­‐term sunspot data series. This approach has allowed us to reproduce the general properties of the solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Solar Activity↗
NASA NTRS1993

Topex Microwave Radiometer thermal control - Post-system-test modifications and on-orbit performance

The Topex Microwave Radiometer has had an excellent thermal performance since launch. The instrument, however, went through a hardware modification right before launch to correct for a thermal design inadequacy that was uncovered during the spacecraft thermal vacuum test. This paper reports on how the initially obscure problem was tracked down, and how the thermal models were revised, validated, and utilized to investigate the solution options and guide the hardware modification decisions. Details related to test data interpretation, analytical uncertainties, and model-prediction vs. test-data correlation, are documented. Instrument/spacecraft interface issues, where the problem originated and where in general pitfalls abound, are dealt with specifically. Finally, on-orbit thermal performance data are presented, which exhibit good agreement with flight predictions, and lessons learned are discussed.

Lin, Edward I.↗
NASA NTRS2002

Deuterium Abundance Toward G191-B2B: Results from the Far Ultraviolet Spectroscopic Explorer (FUSE) Mission

High-resolution spectra of the hot white dwarf G191-B2B covering the wavelength region 905-1187A were obtained with the Far Ultraviolet Spectroscopic Explorer (FUSE). This data was used in conjunction with existing high-resolution Hubble Space Telescope STIS observations to evaluate the total H(sub I), D(sub I), O(sub I) and N(sub I) column densities along the line of sight. Previous determinations of N(D(sub I)) based upon GHRS (Goddard High Resolution Spectrograph) and STIS (Space Telescope Imaging Spectrograph) observations were controversial due to the saturated strength of the D(sub I) Lyman alpha line. In the present analysis the column density of D(sub I) has been measured using only the unsaturated Lyman beta and Lyman gamma lines observed by FUSE. A careful inspection of possible systematic uncertainties tied to the modeling of the stellar continuum or to the uncertainties in the FUSE instrumental character series has been performed. The column densities derived are: log N(D(sub I)) = 13.40+/-0.07, log N(O(sub I)) = 14.86+/-0.07, and log N(N(sub I)) = 13.87+/-0.07 quoted with 2sigma, uncertainties. The measurement of the H(sub I) column density by profile fitting of the Lyman alpha line has been found to be unsecure. If additional weak hot interstellar components are added to the three detected clouds along the line of sight, the H(sub I)) column density can be reduced quite significantly, even though the signal-to-noise ratio and spectral resolution at Lyman alpha are excellent. The new estimate of N(H(sub I)) toward G191-B2B reads: logN(H (sub I)) = 18.18+/-0.18 (2sigma uncertainty), so that the average (D/H) ratio on the line of sight is: (D/H)= 1.66(+0.9/-0.6) x 10(exp -5) (2sigma uncertainty).

Lemoine, M.↗
NASA NTRS2005

Cosmic Infrared Background and Early Galaxy Evolution

The cosmic infrared background (CIB) reflects the sum total of galactic luminosities integrated over the entire age of the universe. From its measurement the red-shifted starlight and dust-absorbed and re-radiated starlight of the CIB can be used to determine (or constrain) the rates of star formation and metal production as a function of time and deduce information about objects at epochs currently inaccessible to telescopic studies. This review discusses the state of current CIB measurements and the (mostly space-based) instruments with which these measurements have been made, the obstacles (the various foreground emissions) and the physics behind the CIB and its structure. Theoretical discussion of the CIB levels can now be normalized to the standard cosmological model narrowing down theoretical uncertainties. We review the information behind and theoretical modeling of both the mean (isotropic) levels of the CIB and their fluctuations. The CIB is divided into three broad bands: near-IR (NIR), mid-IR (MIR) and far-IR (FIR). For each of the bands we review the main contributors to the CIB flux and the epochs at which the bulk of the flux originates. We also discuss the data on the various quantities relevant for correct interpretation of the CIB levels: the star-formation history, the present-day luminosity function measurements, resolving the various galaxy contributors to the CIB, etc. The integrated light of all galaxies in the deepest NIR galaxy counts to date fails to match the observed mean level of the CIB, probably indicating a significant high-redshift contribution to the CIB. Additionally, Population III stars should have left a strong and measurable signature via their contribution to the CIB anisotropies for a wide range of their formation scenarios, and measuring the excess CIB anisotropies coming from high z would provide direct information on the epoch of the first stars.

Kashlinsky, Alexander↗
NASA NTRS2016

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk, and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results, and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods, such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty, are rendered obsolete, since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods. This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper describes how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

Novack, Steven D.↗
NASA NTRS2016

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty are rendered obsolete since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods.This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper shows how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

Novack, Steven D.↗
NASA NTRS2019

Approach for Propagating Radiometric Data Uncertainties Through NASA Ocean Color Algorithms

Spectroradiometric satellite observations of the ocean are commonly referred to as “ocean color” remote sensing. NASA has continuously collected, processed, and distributed ocean color datasets since the launch of the Sea-viewing Wide-field-of-view Sensor (SeaWiFS) in 1997. While numerous ocean color algorithms have been developed in the past two decades that derive geophysical data products from sensor-observed radiometry, few papers have clearly demonstrated how to estimate measurement uncertainty in derived data products. As the uptake of ocean color data products continues to grow with the launch of new and advanced sensors, it is critical that pixel-by-pixel data product uncertainties are estimated during routine data processing. Knowledge of uncertainties can be used when studying long-term climate records, or to assist in the development and performance appraisal of bio-optical algorithms. In this method paper we provide a comprehensive overview of how to formulate first-order first-moment (FOFM) calculus for propagating radiometric uncertainties through a selection of bio-optical models. We demonstrate FOFM uncertainty formulations for the following NASA ocean color data products: chlorophyll-a pigment concentration (Chl), the diffuse attenuation coefficient at 490 nm (K(sub d,490)), particulate organic carbon (POC), normalized fluorescent line height (nflh), and inherent optical properties (IOPs). Using a quality-controlled in situ hyperspectral remote sensing reflectance (R(sub rs,i)) dataset, we show how computationally inexpensive, yet algebraically complex, FOFM calculations may be evaluated for correctness using the more computationally expensive Monte Carlo approach. We compare bio-optical product uncertainties derived using our test R(sub rs) dataset assuming spectrally-flat, uncorrelated relative uncertainties of 1, 5, and 10%. We also consider spectrally dependent, uncorrelated relative uncertainties in R(sub rs). The importance of considering spectral covariances in R(sub rs), where practicable, in the FOFM methodology is highlighted with an example SeaWiFS image. We also present a brief case study of two POC algorithms to illustrate how FOFM formulations may be used to construct measurement uncertainty budgets for ecologically-relevant data products. Such knowledge, even if rudimentary, may provide useful information to end-users when selecting data products or when developing their own algorithms.

Bio-optics↗
NASA NTRS1993

TOPEX Microwave Radiometer Thermal Control: Post-System-Test Modifications and On-Orbit Performance

The Topex Microwave Radiometer has had an excellent thermal performance since launch. The instrument, however, went through a hardware modification right before launch to correct for athermal design inadequacy that was uncovered during the spacecraft thermal vacuum test. This paper reports on how the initially obscure problem was tracked down, and how the thermal models were revised, validated, and utilized to investigate the solution options and guide the hardware modification decisions. Details related to test data interpretation, analytical uncertainties, and model-prediction vs. test-data correlation, are documented. Instrument/spacecraft interface issues, where the problem originated and where in general pitfalls abound, are dealt with specifically. Finally, on-orbit thermal performance data are presented, which exhibit good agreement with flight predictions, and lessons learned are discussed.

Lin, Edward I.↗
NASA NTRS2000

Trajectory Hunting: A Case Study of Rapid Chlorine Activation in December 1992 as Seen by UARS

Trajectory hunting (i.e., a technique to find air parcels sampled at least twice over the course of a few days) is applied to analyze Upper Atmosphere Research Satellite (UARS) measurements in conjunction with the Atmospheric and Environmental Research, Inc. (AER) photochemical box model. As a case study, we investigate rapid chlorine activation in the Arctic lower stratosphere on December 29, 1992 associated with a polar stratospheric cloud (PSC) event. Eleven air parcels that have been sampled several times along five-day trajectories at the 465 K (approx. 46 hPa), 520 K (approx. 31 hPa), and 585 K (approx. 22 hPa) levels were investigated. For the first time, the latest versions of the Cryogenic Limb Array Etalon Spectrometer (CLAES, version 9) and Microwave Limb Sounder (MLS, version 5) data sets are analyzed, and their consistency is assessed. A detailed sensitivity study with the AER photochemical box model along these trajectories leads to the conclusion that for the December 24-29, 1992 episode: (1) the individual CLAES ClONO2 and MLS ClO measurements are self-consistent within their uncertainties; and (2) most of the time, UARS measurements of ClO, ClONO2, HNO3, and aerosol extinction at 780 cm(exp -1) agree within the range of their uncertainties with the model calculations. It appears that the HNO3 and aerosol extinction measurements for four parcels at 520 K look more supportive for the nitric acid trihydrate (NAT) scheme, However, the uncertainties in the individual UARS measurements and UK Meteorological Office temperature do not allow a definite discrimination between the NAT and supercooled ternary solution (STS) PSC schemes for this chlorine activation episode in December 1992.

Danilin, M. Y.↗
NASA NTRS1986

A new sunspot umbral model and its variation with the solar cycle

Semiempirical model atmospheres are presented for the darkest parts of large sunspot umbrae, regions have called umbral cores. The approach is based on general-purpose computational procedures that are applicable to different types of stellar atmospheres. It is shown that recent umbral intensity measurements of the spectral energy distribution may be accounted for by an umbral core atmospheric model that varies with time during the solar cycle; the observed center-limb variation can be accounted for by the properties of the model. Three umbral core models are presented, corresponding to the early, middle, and late phases of the solar cycle. These three models also may be regarded as having the properties of dark, average, and bright umbral cores respectively. The effects of atomic, opacity, and abundance data uncertainties on the model calculations are briefly discussed. For comparison, a new reference model for the average quiet solar photosphere is given.

Maltby, P.↗
NASA NTRS1988

X-band noise temperature near the Sun at a 34-meter high efficiency antenna

The X-band system noise temperature near the Sun was measured at the DSS 15, a 34 meter high efficiency (HEF) antenna, in November 1987. Data was taken at angles off the center of the Sun from 0 to 4 degrees. At angles greater than 0.5 degree, the measured results agree with Voyager tracking data taken at solar conjunction in late December 1987. Within the solar disk, at angles lower than 0.27 degree, the temperature measured was lower than the prediction of a model by 30 percent, after adjusting for known receiver nonlinearities. The discrepancy in this extreme case is probably caused by unknown nonlinearities in the receiver, uncertainties in the model, or both. The measurement is nevertheless credible for practically all Sun-Earth-probe angles of interest to deep space missions.

Rebold, T. A.↗
NASA NTRS2002

Improving the Accuracy of Satellite Sea Surface Temperature Measurements by Explicitly Accounting for the Bulk-Skin Temperature Difference

The focus of this research was to determine whether the accuracy of satellite measurements of sea surface temperature (SST) could be improved by explicitly accounting for the complex temperature gradients at the surface of the ocean associated with the cool skin and diurnal warm layers. To achieve this goal, work was performed in two different major areas. The first centered on the development and deployment of low-cost infrared radiometers to enable the direct validation of satellite measurements of skin temperature. The second involved a modeling and data analysis effort whereby modeled near-surface temperature profiles were integrated into the retrieval of bulk SST estimates from existing satellite data. Under the first work area, two different seagoing infrared radiometers were designed and fabricated and the first of these was deployed on research ships during two major experiments. Analyses of these data contributed significantly to the Ph.D. thesis of one graduate student and these results are currently being converted into a journal publication. The results of the second portion of work demonstrated that, with presently available models and heat flux estimates, accuracy improvements in SST retrievals associated with better physical treatment of the near-surface layer were partially balanced by uncertainties in the models and extra required input data. While no significant accuracy improvement was observed in this experiment, the results are very encouraging for future applications where improved models and coincident environmental data will be available. These results are included in a manuscript undergoing final review with the Journal of Atmospheric and Oceanic Technology.

Wick, Gary A.↗
NASA NTRS2002

Problems in Assessment of the UV Penetration into Natural Waters from Space-based Measurements

Satellite instruments currently provide global maps of surface UV (ultraviolet) irradiance by combining backscattered radiance data with radiative transfer models. The models are often limited by uncertainties in physical input parameters of the atmosphere and surface. Global mapping of the underwater UV irradiance creates further challenges for the models. The uncertainties in physical input parameters become more serious because of the presence of absorbing and scattering quantities caused by biological processes within the oceans. In this paper we summarize the problems encountered in the assessment of the underwater UV irradiance from space-based measurements, and propose approaches to resolve the problems. We have developed a radiative transfer scheme for computation of the UV irradiance in the atmosphere-ocean system. The scheme makes use of input parameters derived from satellite instruments such as TOMS (Total Ozone Mapping Spectrometer) and SeaWiFS (Sea-viewing Wide Field-of-view Sensor). The major problem in assessment of the surface UV irradiance is to accurately quantify the effects of clouds. Unlike the standard TOMS UV algorithm, we use the cloud fraction products available from SeaWiFS and MODIS (Moderate Resolution Imaging Spectrometer) to calculate instantaneous surface flux at the ocean surface. Daily UV doses can be calculated by assuming a model of constant cloudiness throughout the day. Both SeaWiFS and MODIS provide some estimates of seawater optical properties in the visible. To calculate the underwater UV flux the seawater optical properties must be extrapolated down to shorter wavelengths. Currently, the problem of accurate extrapolation of visible data down to the UV spectral range is not solved completely, and there are few available measurements. The major difficulty is insufficient correlation between photosynthetic and photoprotective pigments of phytoplankton absorbing in the visible and UV respectively. We propose to empirically parameterize seawater absorption in the UV on a basis of available data sets of bio-optical measurements from a variety of ocean waters. Another problem is the lack of reliable data on pure seawater absorption in the UV. Laboratory measurements of the UV absorption of both pure water and pure seawater are required.

Vasilkov, Alexander P.↗
NASA NTRS2022

Assimilation of Sea Ice Thickness Derived from Cryosat-2 Along-Track Freeboard Measurements into the Met Office's Forecast Ocean Assimilation Model (FOAM)

The feasibility of assimilating sea ice thickness (SIT) observations derived from CryoSat-2 along-track measurements of sea ice freeboard is successfully demonstrated using a 3D-Var assimilation scheme, NEMOVAR, within the Met Office's global, coupled ocean–sea-ice model, Forecast Ocean Assimilation Model (FOAM). The CryoSat-2 Arctic freeboard measurements are produced by the Centre for Polar Observation and Modelling (CPOM) and are converted to SIT within FOAM using modelled snow depth. This is the first time along-track observations of SIT have been used in this way, with other centres assimilating gridded and temporally averaged observations. The assimilation leads to improvements in the SIT analysis and forecast fields generated by FOAM, particularly in the Canadian Arctic. Arctic-wide observation-minus-background assimilation statistics for 2015–2017 show improvements of 0.75 m mean difference and 0.41 m root-mean-square difference (RMSD) in the freeze-up period and 0.46 m mean difference and 0.33 m RMSD in the ice break-up period. Validation of the SIT analysis against independent springtime in situ SIT observations from NASA Operation IceBridge (OIB) shows improvement in the SIT analysis of 0.61 m mean difference (0.42 m RMSD) compared to a control without SIT assimilation. Similar improvements are seen in the FOAM 5 d SIT forecast. Validation of the SIT assimilation with independent Beaufort Gyre Exploration Project (BGEP) sea ice draft observations does not show an improvement, since the assimilated CryoSat-2 observations compare similarly to the model without assimilation in this region. Comparison with airborne electromagnetic induction (Air-EM) combined measurements of SIT and snow depth shows poorer results for the assimilation compared to the control, despite covering similar locations to the OIB and BGEP datasets. This may be evidence of sampling uncertainty in the matchups with the Air-EM validation dataset, owing to the limited number of observations available over the time period of interest. This may also be evidence of noise in the SIT analysis or uncertainties in the modelled snow depth, in the assimilated SIT observations, or in the data used for validation. The SIT analysis could be improved by upgrading the observation uncertainties used in the assimilation. Despite the lack of CryoSat-2 SIT observations available for assimilation over the summer due to the detrimental effect of melt ponds on retrievals, it is shown that the model is able to retain improvements to the SIT field throughout the summer months due to prior, wintertime SIT assimilation. This also results in regional improvements to the July modelled sea ice concentration (SIC) of 5 % RMSD in the European sector, due to slower melt of the thicker sea ice.

Emma K. Fiedler↗
NASA NTRS1974

Observations of He I 584 A nighttime radiation - Evidence for an interstellar source of neutral helium

The intensity and spatial variations of the He I 584 A radiation in the night sky were measured to an altitude of 264 km from a sounding rocket launched from Thumba, India. The flux varied in intensity with look angle from a high of 16 plus or minus 5 rayleighs to a low of less than 1 rayleigh. The data obtained are presented in the form of an all-sky map. Since the peak flux levels observed are approximately two orders of magnitude larger than that expected from geocoronal resonant scattering, we have compared our results with those expected from two interplanetary sources of neutral helium: the penetration of the local interstellar medium into the solar neighborhood and the dust deionization of solar-wind alpha particles. The dust deionization-model predictions using currently accepted input parameters appear to be inconsistent with the observations. The interstellar helium source is compatible with the data to within the uncertainties of the models.

Paresce, F.↗
NASA NTRS2017

IceCube SWIRP

Clouds, ice clouds in particular, are a major source of uncertainty in climate models. Submm-wave sensors fill the sensitivity gap between MW and IR.Cloud microphysical properties (particle size and shape) account for large (200 and 40) measurement uncertainty.

Wu, Dongliang L.↗