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Results for “uncertainty analysis”

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NASA NTRS2002

Probabilistic and Possibilistic Analyses of the Strength of a Bonded Joint

The effects of uncertainties on the predicted strength of a single lap shear joint are examined. Probabilistic and possibilistic methods are used to account for uncertainties. A total of ten variables are assumed to be random, with normal distributions. Both Monte Carlo Simulation and the First Order Reliability Method are used to determine the probability of failure. Triangular membership functions with upper and lower bounds located at plus or minus three standard deviations are used to model uncertainty in the possibilistic analysis. The alpha cut (or vertex) method is used to evaluate the possibility of failure. Linear and geometrically nonlinear finite element analyses are used calculate the response of the joint; fracture in the adhesive and material strength failure in the strap are used to evaluate its strength. Although probabilistic and possibilistic analyses provide significantly more information than do conventional deterministic analyses, they are computationally expensive. A novel scaling approach is developed and used to substantially reduce the computational cost of the probabilistic and possibilistic analyses. The possibilistic approach for treating uncertainties appears to be viable during the conceptual and preliminary design stages when limited data are available and high accuracies are not needed. However, this viability is mixed with several cautions that are discussed herein.

Stroud, W. Jefferson↗

NASA NTRS2023

Calibration of the SNPP and NOAA 20 VIIRS Sensors for Continuity of the MODIS Climate Data Records

Accurate long-term sensor calibration and periodic re-processing to ensure consistency and continuity of atmospheric, land and ocean geophysical retrievals from space within the mission period and across different missions is a major requirement of climate data records. In this work, we applied the Multi-Angle Implementation of Atmospheric Correction (MAIAC)-based vicarious calibration technique over Libya-4 desert site to perform calibration analysis of Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 satellites. For both VIIRS sensors we characterized residual linear calibration trends and cross-calibrated both sensors to MODerate resolution Imaging Spectroradiometer (MODIS) Aqua regarded as a calibration standard. The relative spectral response (RSR) differences were accounted for using the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) hyperspectral surface reflectance data. Our results agree with independent vicarious calibration results of both the MODIS/VIIRS Characterization Support Team as well as the CERES Imager and Geostationary Calibration Group within estimated uncertainty of 1–2%. Analysis of MAIAC geophysical products with the new calibration shows a high level of agreement of MAIAC aerosol, surface reflectance and NDVI records between MODIS and VIIRS. Excluding high aerosol optical depth (AOD), all three sensors agree in AOD with mean difference (MD) less than 0.01 and residual mean squared difference rmsd ∼ 0.04. Spectral geometrically normalized surface reflectance agrees within rmsd of 0.003–0.005 in the visible and 0.01–0.012 at longer wavelengths. The residual surface reflectance differences are fully explained by differences in spectral filter functions. Finally, difference in NDVI is characterized by rmsd ∼ 0.02 and MD less than 0.003 for NDVI based on VIIRS imagery bands I1/I2 and less than 0.01 for NDVI based on VIIRS radiometric bands M5/M7. In practical sense, these numbers indicate consistency and continuity in MAIAC records ensuring the smooth transition from MODIS to VIIRS.

MAIAC↗

NASA NTRS1972

Determination of aerothermodynamic environment uncertainties with application to space shuttle vehicles

In an effort to minimize the cost of the thermal protection system (TPS) for space shuttles, an analysis is made of environmental uncertainties. The basic categories of these uncertainties include aerodynamic heating, trajectory dispersions, atmospheric variations, and vehicle attitude variations. Also discussed are TPS design sensitivity to environmental uncertainties, and uncertainty profiles. Preliminary results indicate moderate TPS cost for a high confidence level environment may be obtained.

Scottoline, C. A.↗

NASA NTRS2016

Influence of Measurement Uncertainties on Fractional Solubility of Iron in Mineral Aerosols over the Oceans

The atmospheric supply of mineral dust iron (Fe) plays a crucial role in the Earths biogeochemical cycle and is of specific importance as a micronutrient in the marine environment. Observations show several orders of magnitude variability in the fractional solubility of Fe in mineral dust aerosols, making it hard to assess the role of mineral dust for the global ocean biogeochemical Fe cycle. In this study we compare the operational solubility of mineral dust aerosol Fe associated with the flow-through leaching protocol to the results of the global 3-D chemical transport model GEOS-Chem. According to the protocol, aerosol Fe is defined as soluble by first deionized water leaching of mineral dust through a 0.45 m pore size membrane followed by acidification and storage of the leachate over a long period of time prior to analysis. To estimate the uncertainty in soluble Fe results introduced by the flow-through leaching protocol, we prescribe an average 50 (range of 30 to 70) fractional solubility to sub-0.45 m sized mineral dust particles that may inadvertently pass the filter and end up in the acidified (at pH1.7) leachate for a couple of month period. In the model, the fractional solubility of Fe is either explicitly calculated using a complex mineral aerosol Fe dissolution module, or prescribed to be 1 and 4. Calculations show that the fractional solubility of Fe derived through the flow-through leaching is higher compared to the model results. The largest differences (40) are predicted to occur farther away from the dust source regions, over the areas where sub-0.45 m sized mineral dust particles contribute a larger fraction of the total mineral dust mass. This study suggests that different methods used in soluble Fe measurements and inconsistences in the operational definition of filterable Fe in marine environment and soluble Fe in atmospheric aerosols are likely to contribute to the wide range of fractional solubility of aerosol Fe reported in the literature.

Soluble Iron↗

NASA NTRS2008

The X-43A Six Degree of Freedom Monte Carlo Analysis

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A inflight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

Baumann, Ethan↗

NASA NTRS2007

The X-43A Six Degree of Freedom Monte Carlo Analysis

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A in-flight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

Baumann, Ethan↗

NASA NTRSDate not supplied

Three-Dimensional Nonequilibrium Boundary Layer Stability & Transition Analysis For Martian Entry

In this work, we apply the boundary layer stability code LASTRAC, modified to include chemical and thermal nonequilibrium capabilities, to a simulated test case based on literature, with three-dimensional effects. LASTRAC provides Parabolized Stability Equations (PSE)as well as Linear Stability Theory (LST) to predict the stability of a boundary layer and transition with semiempirical eN methods. Tests of the Mars Science Laboratory (MSL)indicated a range of laminar to transitional flow conditions. In order to reduce the weight of Thermal Protection Systems (TPS), reliable prediction of transition and an understanding of the environmental factors that contribute to transition are necessary. This work is a step towards addressing this need, including the effects of thermochemical nonequilibrium but neglecting radiation, ablation, and ionization effects. Our results indicate that an oblique first mode produces maximum N-Factors on the symmetry plane, however with N-Factors too small to explain transition. Although we are able to show nonequilibrium three-dimensional PSE results inCO2, further study with improved mean flow solutions, accounting for some of the uncertainties inherent in this analysis, or evaluation of alternative transition mechanisms is needed to explain transition in the wind tunnel cases examined here.

H L Kline↗

NASA NTRS1977

Space shuttle engineering and operations support: Dispersion analysis for the first orbital flight test (OFT-1) mission

A dispersion analysis considering 3—sigma (3σ) uncertainties (or perturbations) in platform, vehicle, and environmental parameters has been performed for the first orbital flight test (OFT-1) mission. The dispersion analysis is based on the nominal trajectory for the OFT-1 reference flight profile (RFP) which is described in Reference 1. The analysis has been performed to determine state vector and performance dispersions (or variations) which result from the indicated 3σ uncertainties. The dispersions are determined at major mission events and fixed times from Liftoff (time slices). The dispersion results will be used to evaluate the capability of the vehicle to perform the mission within a 3σ Level of confidence and to determine flight performance reserves. (FPR).

L.S. Snow↗

NASA NTRS1971

L-/S-band calibration error analysis.

Results of a statistical error analysis performed to determine the degree of uncertainty encountered when calibrating steerable receiving antennas with the solar calibration method. The analysis considers the propagation of precision error indices. It is shown that a worst-case one-sigma (1 sigma) uncertainty of plus or minus 0.8 dB in system noise temperature occurs for a solar calibration at L-band. Somewhat better precision can be achieved by monitoring the antenna gain-to-noise temperature ratio at a station; a worst-case uncertainty of plus or minus 0.5 dB (1 sigma) can be realized. An error analysis is made of a method to determine absolute antenna gain based upon solar flux density. The uncertainty in this type of measurement is plus or minus 0.7 dB (1 sigma) at L- and S-band frequencies.

Taylor, R. E.↗

NASA NTRS1985

A panel method study of vortex sheets with special emphasis on sheets of axisymmetric geometry

The self induced evolution of a vortex sheet was simulated by modeling the sheet using an integration of discrete elements of vorticity. Replacing small sections of a vortex sheet by flat panels of constant vorticity is found to reproduce more accurately the initial conditions for the Lagrangian simulation technique than replacement by point vortices. The flat panel method for the vortex sheet was then extended to model axisymmetric vortex sheets. The local and far field velocities induced by the axisymmetric panels were obtained using matched asymptotic analysis, and some of the uncertainties involved in other models of the axisymmetric vortex sheet have been eliminated. One important result of this analysis is the determination of the proper choice of core size for a circular vortex filament which may replace a section of an axisymmetric vortex sheet. Roll-up of both two dimensional and axisymmetric vortex sheets was computed using the panel methods developed in the report.

Sugioka, I.↗

NASA NTRS2022

Uncertainty Estimation for SMAP Level-1 Brightness Temperature Assimilation at Different Timescales

Soil Moisture Active Passive (SMAP) mission brightness temperature (T(b) ) observations are assimilated into NASA’s Catchment Land Surface Model using an Ensemble Kalman filter to update simulations of surface and root-zone soil moisture. Different time series components of the T(b) observations are assimilated including anomalies, inter-annual variations, and high frequency variations. To optimize the weights that the data assimilation (DA) puts on the observations, the ratio between the uncertainties of modeled and observed T(b) is approximated using modeled and observed soil moisture uncertainties estimated using triple collocation analysis. In a benchmark experiment, T(b) observations are assimilated using a spatially constant 4 Kelvin (K) observation uncertainty, as in the operational SMAP Level-4 algorithm. All DA experiments exhibit notable skill improvements in most regions. Improvements are largest for the inter-annual variations in the simulations of both surface and root-zone soil moisture (mean improvements in terms of Pearson correlation (-) are 0.08 and 0.06, respectively). Anomaly simulations improve similarly (0.07), and improvements in the high-frequency variations are only observed for surface soil moisture simulations (0.06). No notable difference in skill - neither improvement nor deterioration - is observed between the experiments that use optimized observation uncertainty parameters and the 4 K benchmark experiment. This may be explained by the presence of large observation operator errors, which are analytically shown to have the potential to render post-update uncertainty insensitive to inaccuracies in estimates of the Kalman gain. These results have important implications for the design of soil moisture DA systems, in particular for parameterizing model and observation uncertainties.

Hydrology↗

NASA NTRSDate not supplied

Synergy of Satellite Radiation, Precipitation, and Other Meteorological Variable Observations for Global Mean Sea Surface Turbulent Heat Flux Estimation

Sea surface turbulent heat flux is one of the key components in global freshwater and energy balances and plays an important role in atmospheric dynamics, thermodynamics and general circulation. This turbulent heat flux is dominantly decided by sea surface latent heat release with some contribution from sensible heat exchange. The flux and its anomaly could significantly affect ocean heat storage and ocean circulation. They are part of and have great impacts on climate variability. Though the turbulent heat flux is extremely important for the climate and weather systems, only very limited ship and buoy observations of the flux are available over open oceans. There are no global, operational, direct measurements of this crucial meteorological variable. Global estimates are, basically, indirectly calculated from bulk turbulent flux parameterization with a combination of satellite column water vapor, sea surface water temperature, and wind speed observations. Critical parameters such as sea surface air temperature and humidity are estimated from empirical relations of theses variables with the water vapor and sea surface water temperature, respectively. Lacking accurate knowledge on surface air temperature and humidity, uncertainties in the parameterization and potential changes in the non-linear turbulent processes with long-term climate variations could cause large errors in estimated long-term turbulent fluxes from the indirect method as shown in current global sea surface turbulent flux datasets. This study uses synergized data of satellite global radiation, precipitation, and other meteorological variable observations to estimate sea surface turbulent heat fluxes. The radiation observations are made by the satellite Clouds and the Earth’s Radiant Energy System (CERES) sensors, while the global precipitation data is from NASA’s satellite Global Precipitation Climatology Project (GPCP). Other data includes satellite sea surface water temperature and wind speed observations. These datasets are obtained from a wide range of space sensors from passive to active instruments and from visible and near infrared to thermal infrared and microwave spectral sounders. One significant feature of these datasets is that they have multi-decades long climate records. Top-of-atmosphere (TOA) radiation and its anomaly represents the net heat energy input to the climate system, and the oceanic precipitation and ocean-land moisture transport can be used to quantify sea surface latent heat release. Based on the synergized datasets and the principle of global water and energy balances, global mean turbulent heat fluxes are estimated. The turbulent heat anomalies for the first two decades of the 21st century are, then, obtained mainly from global CERES radiation and GPCP precipitation anomalies, along with CERES derived ocean-land heat transports. Analysis indicates that the uncertainties in the estimated turbulent flux anomalies may be reduced considerably. The results suggest a strong needs in synchronized and synergized observations of atmospheric radiation, precipitation, and oceanic meteorological variables for long-term climate studies.

Bing Lin↗

NASA NTRS2021

Challenges to Aboveground Biomass Prediction from Waveform Lidar

Accurate accounting of aboveground biomass density (AGBD) is crucial for carbon cycle, biodiversity, and climate change science. The Global Ecosystem Dynamics Investigation (GEDI), which maps global AGBD from waveform lidar, is the first of a new generation of Earth observation missions designed to improve carbon accounting. This paper explores the possibility that lidar waveforms may not be unique to AGBD—that forest stands with different AGBD may produce highly similar waveforms—and we hypothesize that non-uniqueness may contribute to the large uncertainties in AGBD predictions. Our analysis integrates simulated GEDI waveforms from 428 in situ stem maps with output from an individual-based forest gap model, which we use to generate a database of potential forest stands and simulate GEDI waveforms from those stands. We use this database to predict the AGBD of the 428 in situ stem maps via two different methods: a linear regression from waveform metrics, and a waveform-matching approach that accounts for waveform-AGBD non-uniqueness. We find that some in situ waveforms are more unique to AGBD than others, which notably impacts AGBD prediction uncertainty (7–411 Mg ha−1, average of 167 Mg ha−1). We also find that forest structure complexity may influence the non-uniqueness effect; stands with low structural complexity are more unique to AGBD than more mature stands with multiple cohorts and canopy layers. These findings suggest that the non-uniqueness phenomena may be introduced by the measuring characteristics of waveform lidar in combination with how forest structure manifests at small scales, and we discuss how this complexity may complicate uncertainty estimation in AGBD prediction. This analysis suggests a limit to the accuracy and precision of AGBD predictions from lidar waveforms seen in empirical studies, and underscores the need for further exploration of the relationships between lidar remote sensing measurements, forest structure, and AGBD.

GEDI↗

NASA NTRS1996

Six Degree-of-Freedom Entry Dispersion Analysis for the METEOR Recovery Module

The present study performs a six degree-of-freedom entry dispersion analysis for the Multiple Experiment Transporter to Earth Orbit and Return (METEOR) mission. METEOR offered the capability of flying a recoverable science package in a microgravity environment. However, since the Recovery Module has no active control system, an accurate determination of the splashdown position is difficult because no opportunity exists to remove any errors. Hence, uncertainties in the initial conditions prior to deorbit burn initiation, during deorbit burn and exo-atmospheric coast phases, and during atmospheric flight impact the splashdown location. This investigation was undertaken to quantify the impact of the various exo-atmospheric and atmospheric uncertainties. Additionally, a Monte-Carlo analysis was performed to statistically assess the splashdown dispersion footprint caused by the multiple mission uncertainties. The Monte-Carlo analysis showed that a 3-sigma splashdown dispersion footprint with axes of 43.3 nm (long), -33.5 nm (short), and 10.0 nm (crossrange) can be constructed. A 58% probability exists that the Recovery Module will overshoot the nominal splashdown site.

Desai, Prasun N.↗

NASA NTRS1973

New radiometric techniques and solar constant measurements.

A series of absolute cavity radiometers, designed to measure solar irradiance, has been developed at the Jet Propulsion Laboratory. Analysis indicates the absolute uncertainty of irradiance measurements made by the most recent devices to be less than plus or minus 0.5 mW/sq cm. In a series of experiments the radiometric scale defined by the JPL instruments has been compared with the International Pyrheliometric Scale (IPS). A systematic 2.2% difference has been observed with the IPS producing consistently lower measurements. The solar constant and spectral distribution have been derived from high-altitude balloon flight measurements made by two types of JPL cavity radiometers. Measurements at 25 km in 1968 produced a solar constant value of 137.0 mW/sq cm. From 1969 measurements at 36 km, a value of 136.6 mW/sq cm was derived, with an estimated absolute uncertainty of plus or minus 0.5%. The solar spectrum information from these experiments agrees most closely with the solar spectrum model of Labs and Neckel (1968).

Willson, R. C.↗

NASA NTRS1974

Uncertainties in predicting solar panel power output

The problem of calculating solar panel power output at launch and during a space mission is considered. The major sources of uncertainty and error in predicting the post launch electrical performance of the panel are considered. A general discussion of error analysis is given. Examples of uncertainty calculations are included. A general method of calculating the effect on the panel of various degrading environments is presented, with references supplied for specific methods. A technique for sizing a solar panel for a required mission power profile is developed.

Anspaugh, B.↗

NASA NTRS1974

Calculations of the moon's heat history at different concentrations of radioactive elements taking account of the material differentiation with melting

A mathematical procedure for analyzing the heat conductivity of the lunar surface is discussed. The solution is based on homogeneous and laminated moon models and considers the effects of radioactive elements conveyed to the lunar surface by melting. The various parameters which introduce uncertainties into the numerical analysis are identified. The application of data obtained from radio astronomy and from analyses of lunar samples returned by the Apollo flights is explained. Tables of data are included to show the types and amounts of radioactive materials which have been identified.

Arnatskaya, O. I.↗

NASA NTRS1976

Zonal average earth radiation budget measurements from satellites for climate studies

Data from 29 months of satellite radiation budget measurements, taken intermittently over the period 1964 through 1971, are composited into mean month, season and annual zonally averaged meridional profiles. Individual months, which comprise the 29 month set, were selected as representing the best available total flux data for compositing into large scale statistics for climate studies. A discussion of spatial resolution of the measurements along with an error analysis, including both the uncertainty and standard error of the mean, are presented.

Ellis, J. S.↗