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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Uncertainty Analysis of Historical Hurricane Data

An analysis of variance (ANOVA) study was conducted for historical hurricane data dating back to 1851 that was obtained from the U. S. Department of Commerce National Oceanic and Atmospheric Administration (NOAA). The data set was chosen because it is a large, publicly available collection of information, exhibiting great variability which has made the forecasting of future states, from current and previous states, difficult. The availability of substantial, high-fidelity validation data, however, made for an excellent uncertainty assessment study. Several factors (independent variables) were identified from the data set, which could potentially influence the track and intensity of the storms. The values of these factors, along with the values of responses of interest (dependent variables) were extracted from the data base, and provided to a commercial software package for processing via the ANOVA technique. The primary goal of the study was to document the ANOVA modeling uncertainty and predictive errors in making predictions about hurricane location and intensity 24 to 120 hours beyond known conditions, as reported by the data set. A secondary goal was to expose the ANOVA technique to a broader community within NASA. The independent factors considered to have an influence on the hurricane track included the current and starting longitudes and latitudes (measured in degrees), and current and starting maximum sustained wind speeds (measured in knots), and the storm starting date, its current duration from its first appearance, and the current year fraction of each reading, all measured in years. The year fraction and starting date were included in order to attempt to account for long duration cyclic behaviors, such as seasonal weather patterns, and years in which the sea or atmosphere were unusually warm or cold. The effect of short duration weather patterns and ocean conditions could not be examined with the current data set. The responses analyzed were the storm latitude, longitude and intensity, as recorded in the data set, 24 or 120 hours beyond the current state. Several ANOVA modeling schemes were examined. Two forms of validation were used: 1) comparison with official hurricane prediction performance metrics and 2) cases studies conducted on hurricanes from the 2005 season, which were not included within the model construction and ANOVA assessment. In general, the ANOVA technique did not perform as well as the established official prediction performance metrics published by NOAA; still, the technique did remarkably well in this demonstration with a difficult data set and could probably be made to perform better with more knowledge of hurricane development and dynamics applied to the problem. The technique provides a repeatable prediction process that eliminates the need for judgment in the forecast.

Green, Lawrence L.↗
NASA NTRS1996

Modelling System Processes to Support Uncertainty Analysis and Robustness Evaluation

In the use of advanced systems control techniques in the development of a dynamic system, results from effective mathematical modelling is required. Historically, in some cases the use of a model which only reflects the "expected" or "nominal" important -information about the system's internal processes has resulted in acceptable system performance, but it should be recognized that for those cases success was due to a combination of the remarkable inherent potential of feedback control for robustness and fortuitously wide margins between system performance requirements and system performance capability. In the cases of a CELSS development, no such fortuitous combinations should be expected, and it should be expected that the uncertainty in the information on the system's processes will have to be taken into account in order to generate a performance robust design. In this paper, we develop one perspective of the issue of providing robustness as mathematical modelling impacts it, and present some examples of model formats which serve the needed purpose.

Blackwell, Charles↗
NASA NTRS1999

Antarctic Photochemistry: Uncertainty Analysis

Understanding the photochemistry of the Antarctic region is important for several reasons. Analysis of ice cores provides historical information on several species such as hydrogen peroxide and sulfur-bearing compounds. The former can potentially provide information on the history of oxidants in the troposphere and the latter may shed light on DMS-climate relationships. Extracting such information requires that we be able to model the photochemistry of the Antarctic troposphere and relate atmospheric concentrations to deposition rates and sequestration in the polar ice. This paper deals with one aspect of the uncertainty inherent in photochemical models of the high latitude troposphere: that arising from imprecision in the kinetic data used in the calculations. Such uncertainties in Antarctic models tend to be larger than those in models of mid to low latitude clean air. One reason is the lower temperatures which result in increased imprecision in kinetic data, assumed to be best characterized at 298K. Another is the inclusion of a DMS oxidation scheme in the present model. Many of the rates in this scheme are less precisely known than are rates in the standard chemistry used in many stratospheric and tropospheric models.

Stewart, Richard W.↗
NASA NTRS2016

Isokinetic TWC Evaporator Probe: Calculations and Systemic Uncertainty Analysis

A new Isokinetic Total Water Content Evaporator (IKP2) was downsized from a prototype instrument, specifically to make airborne measurements of hydrometeor total water content (TWC) in deep tropical convective clouds to assess the new ice crystal Appendix D icing envelope. The probe underwent numerous laboratory and wind tunnel investigations to ensure reliable operation under the difficult high altitude/speed/TWC conditions under which other TWC instruments have been known to either fail, or have unknown performance characteristics and the results are presented in a companion paper. This paper presents the equations used to determine the total water content (TWC) of the sampled atmosphere from the values measured by the IKP2 or necessary ancillary data from other instruments. The uncertainty in the final TWC is determined by propagating the uncertainty in the measured values through the calculations to the final result. Two techniques were used and the results compared. The first is a typical analytical method of propagating uncertainty and the second performs a Monte Carlo simulation. The results are very similar with differences that are insignificant for practical purposes. The uncertainty is between 2 percent and 3 percent at most practical operating conditions. The capture efficiency of the IKP2 was also examined based on a computational fluid dynamic simulation of the original IKP and scaled down to the IKP2. Particles above 24 microns were found to have a capture efficiency greater than 99 percent at all operating conditions.

Aircraft Icing↗
NASA NTRS1981

The two-dimensional diagnostic model for tropospheric OH - An uncertainty analysis

Tropospheric OH is believed to play a major role in atmospheric photochemistry, and, via its chemical interactions OH ultimately may affect the climate, stratospheric ozone levels, and the pH of rain. A valuable tool for predicting the global OH abundance as a function of latitude and altitude is the two-dimensional diagnostic model for tropospheric OH. This model can also be applied to budget studies of species which interact with OH, such as CH4, CO, and O3. In addition to laboratory-obtained kinetic data, important variables include the rate constants for several reactions, the rate of heterogeneous removal of soluble species, and the global abundance and spatial variability in H2O, O3, CO, and NOx. The uncertainties in these parameters imply over a factor of 3 variability in the calculated global OH concentration as well as significant uncertainties in the latitudinal and vertical OH distribution.

Chameides, W. L.↗
NASA NTRS2016

Isokinetic TWC Evaporator Probe: Calculations and Systemic Uncertainty Analysis

A new Isokinetic Total Water Content Evaporator (IKP2) was downsized from a prototype instrument, specifically to make airborne measurements of hydrometeor total water content (TWC) in deep tropical convective clouds to assess the new ice crystal Appendix D icing envelope. The probe underwent numerous laboratory and wind tunnel investigations to ensure reliable operation under the difficult high altitude/speed/TWC conditions under which other TWC instruments have been known to either fail, or have unknown performance characteristics and the results are presented in a companion paper (Ref. 1). This paper presents the equations used to determine the total water content (TWC) of the sampled atmosphere from the values measured by the IKP2 or necessary ancillary data from other instruments. The uncertainty in the final TWC is determined by propagating the uncertainty in the measured values through the calculations to the final result. Two techniques were used and the results compared. The first is a typical analytical method of propagating uncertainty and the second performs a Monte Carlo simulation. The results are very similar with differences that are insignificant for practical purposes. The uncertainty is between 2 and 3 percent at most practical operating conditions. The capture efficiency of the IKP2 was also examined based on a computational fluid dynamic simulation of the original IKP and scaled down to the IKP2. Particles above 24 micrometers were found to have a capture efficiency greater than 99 percent at all operating conditions.

Meteorological Instrument↗
NASA NTRSDate not supplied

PACE OCI Short-Wave Infrared Detection Assembly frequency-dependent linearity characterization and uncertainty analysis

The Ocean Color Instrument (OCI), the primary payload of the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)observatory, will collect data to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared(SWIR) Detection Assembly (SDA) was built and characterized by the Utah State University Space DynamicsLaboratory (SDL) and is a subsystem of OCI. The SDA measures seven bands centered at 940, 1038, 1250, 1378,1615, 2130, and 2260 nm, with standard- and high-gain varieties for the 1250 and 1615 nm bands, resulting in nine total detection configurations in the SWIR. The delivery of high-quality science data is critically dependent upon accurately characterizing the linearity of the SDA. Two metrology techniques were employed to measure the linearity and characterize the frequency-dependent linearity uncertainty of the system. The first technique used superposition linearity measurements to determine the DC linearity, and the second technique involved an oscillating small-signal response at seven frequencies to determine the frequency-dependent linearity. Discrepancies between the DC and frequency-dependent linearities constrain the uncertainty between the two. Examining the difference between these two methods for all SDA channels, we find most channels experience an uncertainty below0.2% with a worst-case measurement uncertainty of 0.31%. Averaging SDA channels with similar detectors, optical filters, and electronics to simulate the flight-like data products yields a worst-case frequency-dependence linearity uncertainty of 0.12%, demonstrating minimal frequency dependence, implying an excellent linearity knowledge.Detailed performance knowledge, including linearity performance, verifies data quality and builds confidence in the success of the PACE mission.

PACE↗
NASA NTRS2013

Trajectory Reconstruction and Uncertainty Analysis Using Mars Science Laboratory Pre-Flight Scale Model Aeroballistic Testing

As part of the Mars Science Laboratory (MSL) trajectory reconstruction effort at NASA Langley Research Center, free-flight aeroballistic experiments of instrumented MSL scale models was conducted at Aberdeen Proving Ground in Maryland. The models carried an inertial measurement unit (IMU) and a flush air data system (FADS) similar to the MSL Entry Atmospheric Data System (MEADS) that provided data types similar to those from the MSL entry. Multiple sources of redundant data were available, including tracking radar and on-board magnetometers. These experimental data enabled the testing and validation of the various tools and methodologies that will be used for MSL trajectory reconstruction. The aerodynamic parameters Mach number, angle of attack, and sideslip angle were estimated using minimum variance with a priori to combine the pressure data and pre-flight computational fluid dynamics (CFD) data. Both linear and non-linear pressure model terms were also estimated for each pressure transducer as a measure of the errors introduced by CFD and transducer calibration. Parameter uncertainties were estimated using a "consider parameters" approach.

Lugo, Rafael A.↗
NASA NTRS1996

Uncertainty Analysis for Oil-Film Interferometry Skin-Friction Measurement Techniques

Over the past 20 years, the use of oil-film interferometry to measure the skin friction coefficient (C(sub f) = tau/q where tau is the surface shear stress and q is the dynamic pressure) has increased. Different forms of this oil-film technique with various levels of accuracy and ease of use have been successfully applied in a wide range of flows. The method's popularity is growing due to its relative ease of implementation and minimal intrusiveness as well as an increased demand for C(sub f) measurements. Nonetheless, the accuracy of these methods has not been rigorously addressed to date. Most researchers have simply shown that the skin-friction measurements made using these techniques compare favorably with other measurements and theory, most of which are only accurate to within 5-20%. The use of skin-friction data in the design of commercial aircraft, whose drag at cruise is 50% skin-friction drag, and in the validation of computational fluid dynamics programs warrants better uncertainty estimates. Additional information is contained in the original extended abstract.

Naughton, Jonathan W.↗
NASA NTRS2018

Radiative Heating Indicators and Uncertainty Analysis for Mars 2020

This paper will present analysis to evaluate a functional form and associated parameters to determine the radiative heating at various back-shell locations of the Mars 2020 aeroshell. The radiative heating indicators are used for preliminary vehicle design, and to determine the worst-case trajectories for peak radiative heat flux and load. Historically, the functional form for radiative heating is based on free-stream parameters of density, velocity and a length scale, typically the nose-radius (or equivalent). However, a fit of this form has been shown to not provide significant enough accuracy when compared to simulation results. Therefore, a fit based on post-shock equilibrium calculations of CO and CO2 number density, temperature and pressure has been devised. The results from the TPS 15 01 trajectory were used to develop the fit. The fit was then applied to the MSL best estimated trajectory (BET). Furthermore, the paper will quantify the uncertainty in simulations of the radiative heating for Mars 2020.

Mars 2020↗
NASA NTRS2013

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.

remote sensing↗
NASA NTRS2000

Uncertainty Analysis of Stiffened Composite Panels

A study is made of the variability in the nonlinear response of three stiffened composite panels associated with variations in their geometric and material parameters. The three panels have a cylindrical skin with either four or five T-shaped stiffeners. Two of the panels have a notch and the third panel has a circular cutout. Hierarchical sensitivity analysis is used to identify the major parameters at the micro-mechanical, layer, laminate and sub-component levels. The major parameters are then taken to be fuzzy parameters, and a fuzzy set analysis is used to determine the range of variation of the response associated with pre-selected variations in the major parameters.

Noor, Ahmed K.↗
NASA NTRS2000

Uncertainty Analysis of Composite Structures

A two-phase approach and a computational procedure are presented for predicting the variability in the nonlinear response of composite structures associated with variations in the geometric and material parameters of the structure. In the first phase, hierarchical sensitivity analysis is used to identify the major parameters, which have the most effect on the response quantities of interest. In the second phase, the major parameters are taken to be fuzzy parameters, and a fuzzy set analysis is used to determine the range of variation of the response, associated with preselected variations in the major parameters. The effectiveness of the procedure is demonstrated by means of a numerical example of a cylindrical panel with four T-shaped stiffeners and a circular cutout.

Noor, Ahmed K.↗
NASA NTRS2018

Uncertainty Analysis of Coaxial Thermocouple Calorimeters Used in Arc Jets

Recent introduction of Coaxial Thermocouple type calorimeters into the NASA Ames arc jet facilities has inspired an analysis of 2D conduction effects internal to this type of calorimeter. The 1D finite slab inverse analysis (which is typically used to deduce the heat transfer to the calorimeter) relies on the assumption that lateral conduction (i.e., 2D effects) is negligible. Most calorimeter bodies have a spherical nose, which in itself is a violation of the 1D finite slab analysis assumption. Secondly most calorimeters experience a variation in heating across the face of the body which is also a violation of the 1D finite slab analysis assumption. It turns out that these two effects tend to cancel each other to some extent. This paper shows the extent to which error exists in the analysis of the Coaxial Thermocouple type calorimeters, and also offers analysis strategies for reducing the errors.

Lateral Conduction↗