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At least 415 records · Page 23

Advanced probabilistic method of development

Advanced structural reliability methods are utilized on the Probabilistic Structural Analysis Methods (PSAM) project to provide a tool for analysis and design of space propulsion system hardware. The role of the effort at the University of Arizona is to provide reliability technology support to this project. PSAM computer programs will provide a design tool for analyzing uncertainty associated with thermal and mechanical loading, material behavior, geometry, and the analysis methods used. Specifically, reliability methods are employed to perform sensitivity analyses, to establish the distribution of a critical response variable (e.g., stress, deflection), to perform reliability assessment, and ultimately to produce a design which will minimize cost and/or weight. Uncertainties in the design factors of space propulsion hardware are described by probability models constructed using statistical analysis of data. Statistical methods are employed to produce a probability model, i.e., a statistical synthesis or summary of each design variable in a format suitable for reliability analysis and ultimately, design decisions.

Wirsching, P. H.↗

Stark-profile calculations for Lyman-series lines of one-electron ions in dense plasmas

The frequency distributions of the first six Lyman lines of hydrogenlike carbon, oxygen, neon, magnesium, aluminum, and silicon ions broadened by the local fields of both ions and electrons are calculated for dense plasmas. The electron collisions are treated by an impact theory allowing (approximately) for level splittings caused by the ion fields, finite duration of the collisions, and screening of the electron fields. These calculations are fully quantum mechanical and include the full Coulomb interaction. Ion effects are calculated in the quasistatic, linear-Stark-effect approximation, using distribution functions of Hooper and Tighe which include correlation and shielding effects. Theoretical uncertainties from the various approximations are estimated, and the scaling of the profiles with density, temperature, and nuclear charge is discussed. A correction for the effects caused by low-frequency field fluctuations is suggested.

Griem, H. R.↗

He 584 A dayglow at Neptune

The Voyager 2 Ultraviolet Spectrometer measured the emission intensity of the He resonance line at 584 A to be 0.34 + 0.2 or - 0.15 R on the day side of Neptune. Calculations of the He 584 A intensity at Neptune using partial frequency redistribution and inhomogeneous atmospheric models show that the product of the volume mixing ratio (mole fraction), fHe, and the eddy diffusion coefficient at the homopause, Kh, is fHeKh = 10 to the 7th sq cm/s with upper and lower bounds to the uncertainty of about a factor of 3 and 9, respectively. If fHe is taken as the current Infrared Interferometer Spectrometer working value, fHe = 0.19, then Kh = 5 x 10 to the 7th sq cm/s with a similar uncertainty. This range of K overlaps that obtained from analysis of the hydrocarbon distributions on Neptune (Broadfoot et al., 1989).

Parkinson, Christopher D.↗

Measurement of thermoelectric inhomogeneity of thermocouples

In a thermocouple probe that has significantly inhomogeneous legs, the relationship between emf and temperature is indefinite and depends on temperature distribution along the circuit. An inhomogeneous thermocouple cannot be calibrated to arbitrarily small uncertainty. Therefore, testing for inhomogeneities is a necessary preliminary to meaningful calibration. As most significant inhomogeneity that does occur is introduced during use (and sometimes during calibration) a post-test inhomogeneity measurement should also be employed to detect degradation that might have substantially affected the data. This paper presents a practical test method that is being developed for the observation, interpretation, and application of thermoelectric inhomogeneity as a routine quality assurance measurement that is an essential complement to traditional sheathed thermocouple calibration.

Reed, R. P.↗

HZE reactions and data-base development

The primary cosmic rays are dispersed over a large range of linear energy transfer (LET) values and their distribution over LET is a determinant of biological response. This LET distribution is modified by radiation shielding thickness and shield material composition. The current uncertainties in nuclear cross sections will not allow the composition of the shield material to be distinguished in order to minimize biological risk. An overview of the development of quantum mechanical models of heavy ion reactions will be given and computational results compared with experiments. A second approach is the development of phenomenological models from semi-classical considerations. These models provide the current data base in high charge and energy (HZE) shielding studies. They will be compared with available experimental data. The background material for this lecture will be available as a review document of over 30 years of research at Langley but will include new results obtained over the last year.

Townsend, Lawrence W.↗

Probabilistic Analysis of Gas Turbine Field Performance

A gas turbine thermodynamic cycle was computationally simulated and probabilistically evaluated in view of the several uncertainties in the performance parameters, which are indices of gas turbine health. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design, enhance performance, increase system availability and make it cost effective. The analysis leads to the selection of the appropriate measurements to be used in the gas turbine health determination and to the identification of both the most critical measurements and parameters. Probabilistic analysis aims at unifying and improving the control and health monitoring of gas turbine aero-engines by increasing the quality and quantity of information available about the engine's health and performance.

Gorla, Rama S. R.↗

Bounding the Failure Probability Range of Polynomial Systems Subject to P-box Uncertainties

This paper proposes a reliability analysis framework for systems subject to multiple design requirements that depend polynomially on the uncertainty. Uncertainty is prescribed by probability boxes, also known as p-boxes, whose distribution functions have free or fixed functional forms. An approach based on the Bernstein expansion of polynomials and optimization is proposed. In particular, we search for the elements of a multi-dimensional p-box that minimize (i.e., the best-case) and maximize (i.e., the worst-case) the probability of inner and outer bounding sets of the failure domain. This technique yields intervals that bound the range of failure probabilities. The offset between this bounding interval and the actual failure probability range can be made arbitrarily tight with additional computational effort.

Crespo, Luis G.↗

Microfilament-Eruption Mechanism for Solar Spicules

Recent studies indicate that solar coronal jets result from eruption of small-scale filaments, or "minifilaments" (Sterling et al. 2015, Nature, 523, 437; Panesar et al. ApJL, 832L, 7). In many aspects, these coronal jets appear to be small-scale versions of long-recognized large-scale solar eruptions that are often accompanied by eruption of a large-scale filament and that produce solar flares and coronal mass ejections (CMEs). In coronal jets, a jet-base bright point (JBP) that is often observed to accompany the jet and that sits on the magnetic neutral line from which the minifilament erupts, corresponds to the solar flare of larger-scale eruptions that occurs at the neutral line from which the large-scale filament erupts. Large-scale eruptions are relatively uncommon (approximately 1 per day) and occur with relatively large-scale erupting filaments (approximately 10 (sup 5) kilometers long). Coronal jets are more common (approximately 100s per day), but occur from erupting minifilaments of smaller size (approximately 10 (sup 4) kilometers long). It is known that solar spicules are much more frequent (many millions per day) than coronal jets. Just as coronal jets are small-scale versions of large-scale eruptions, here we suggest that solar spicules might in turn be small-scale versions of coronal jets; we postulate that the spicules are produced by eruptions of "microfilaments" of length comparable to the width of observed spicules (approximately 300 kilometers). A plot of the estimated number of the three respective phenomena (flares/CMEs, coronal jets, and spicules) occurring on the Sun at a given time, against the average sizes of erupting filaments, minifilaments, and the putative microfilaments, results in a size distribution that can be fitted with a power-law within the estimated uncertainties. The counterparts of the flares of large-scale eruptions and the JBPs of jets might be weak, pervasive, transient brightenings observed in Hinode/CaII images, and the production of spicules by microfilament eruptions might explain why spicules spin, as do coronal jets. The expected small-scale neutral lines from which the microfilaments would be expected to erupt would be difficult to detect reliably with current instrumentation, but might be apparent with instrumentation of the near future. A full report on this work appears in Sterling and Moore 2016, ApJL, 829, L9.

spicule↗

Evaluating CERES TOA Fluxes using ARISE aircraft observations

Uncertainty in observations of top-of-atmosphere (TOA) radiation fluxes are larger in the Arctic than in other regions. The magnitude of these uncertainties limit our understanding of the Arctic surface energy budget and its variability. The significant uncertainties are due to the low sun angles and wide range of highly reflecting, anisotropic, and highly heterogeneous surface conditions. Therefore, quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with measurements from the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) flow in September 2014. A key objective of ARISE was to evaluate and attribute uncertainty in CERES footprint and gridded TOA radiative fluxes. In this study, we first compare the CERES TOA flux with those obtained from the broadband radiometer measurements from the aircraft using instantaneously matched footprint with the flight track and as the hourly gridded fluxes. This comparison indicates an agreement within uncertainty in the longwave (2 Wm-2 ) for all five grid boxes and agreement in the shortwave (10 Wm-2) for four-out-of-five grid boxes. While not a statistically significant results given the small sample size, the hourly, gridded and the instantaneously matched footprint comparison suggest a -10 Wm-2 bias for CERES in the shortwave. To explore whether this is a robust feature or a statistical artifact, we quantify the individual sources of uncertainty in the differences (temporal and spatial sampling differences, scene evolution, accuracy, angular distribution models, and scene id) to see if any of these differences account for the shortwave bias.

CERES↗

Attitude stability of LDEF: Refinement of results from the silver pinhole camera

A measurement was previously described of the angular offset and attitude stability of the LDEF spacecraft using a simple pinhole camera device in the UAH experiment A0114. This device uses a silver surface to record the impact zone of atmospheric atomic oxygen passing through a small pinhole on the front surface of the satellite. The shape and size of this zone are well defined if the satellite velocity and gas temperature are known. The circular symmetry of the zone would be distorted by oscillation of the LDEF about its stable attitude, or by the effect of the co-rotation of the Earth's atmosphere for cases of satellites in nonequatorial orbits. The observed ellipticity of 1.05 with the major axis in the yaw direction is equivalent to an oscillation of + or - 0.2 deg about the stable attitude. The uncertainty in that measurement was estimated at about 0.1 deg. A refined analysis based on summing distributions of flux versus incidence angle for a large number of orbital positions, and including a co-rotating atmosphere, indicates that the combined distributions produce a result consistent with the measured exposed spot. It is suggested that, within the precision of the measurements, no actual oscillation of the LDEF is required to produce the results. Thus, the LDEF may have maintained a stable attitude to better than 0.1 deg, even under conditions of maximum aerodynamic perturbation when the silver oxygen record was made. This error is some two orders of magnitude lower than the predicted uncertainty in yaw oscillation and may indicate that the predict methodologies are too conservative.

Peters, P. N.↗

Comparison of Statistical Estimation Techniques for Mars Entry, Descent, and Landing Reconstruction from MEDLI-like Data Sources

Flight data from an entry, descent, and landing (EDL) sequence can be used to reconstruct the vehicle's trajectory, aerodynamic coefficients and the atmospheric profile experienced by the vehicle. Past Mars missions have contained instruments that do not provide direct measurement of the freestream atmospheric conditions. Thus, the uncertainties in the atmospheric reconstruction and the aerodynamic database knowledge could not be separated. The upcoming Mars Science Laboratory (MSL) will take measurements of the pressure distribution on the aeroshell forebody during entry and will allow freestream atmospheric conditions to be partially observable. This data provides a mean to separate atmospheric and aerodynamic uncertainties and is part of the MSL EDL Instrumentation (MEDLI) project. Methods to estimate the flight performance statistically using on-board measurements are demonstrated here through the use of simulated Mars data. Different statistical estimators are used to demonstrate which estimator best quantifies the uncertainties in the flight parameters. The techniques demonstrated herein are planned for application to the MSL flight dataset after the spacecraft lands on Mars in August 2012.

Dutta, Soumyo↗

Determination of lunar ilmenite abundances from remotely sensed data

The mineral ilmenite (FeTiO3) was found in abundance in lunar mare soils returned during the Apollo project. Lunar ilmenite often contains greater than 50 weight-percent titanium dioxide (TiO2), and is a primary potential resource for oxygen and other raw materials to supply future lunar bases. Chemical and spectroscopic analysis of the returned lunar soils produced an empirical function that relates the spectral reflectance ratio at 400 and 560 nm to the weight percent abundance of TiO2. This allowed mapping of the lunar TiO2 distribution using telescopic vidicon multispectral imaging from the ground; however, the time variant photometric response of the vidicon detectors produced abundance uncertainties of at least 2 to 5 percent. Since that time, solid-state charge-coupled device (CCD) detector technology capable of much improved photometric response has become available. An investigation of the lunar TiO2 distribution was carried out utilizing groundbased telescopic CCD multispectral imagery and spectroscopy. The work was approached in phases to develop optimum technique based upon initial results. The goal is to achieve the best possible TiO2 abundance maps from the ground as a precursor to lunar orbiter and robotic sample return missions, and to produce a better idea of the peak abundances of TiO2 for benefaction studies. These phases and the results are summarized.

Larson, Stephen M.↗

A probabilistic fracture mechanics approach for structural reliability assessment of space flight systems

A probabilistic fracture mechanics approach for predicting the failure life distribution due to subcritical crack growth is presented. A state-of-the-art crack propagation method is used in a Monte Carlo simulation to generate a distribution of failure lives. The crack growth failure model expresses failure life as a function of stochastic parameters including environment, loads, material properties, geometry, and model specification errors. A stochastic crack growth rate model that considers the uncertainties due to scatter in the data and mode misspecification is proposed. The rationale for choosing a particular type of probability distribution for each stochastic input parameter and for specifying the distribution parameters is presented. The approach is demonstrated through a probabilistic crack growth failure analysis of a welded tube in the Space Shuttle Main Engine. A discussion of the results from this application of the methodology is given.

Sutharshana, S.↗

A Nanometer Aerosol Size Analyzer (nASA) for Rapid Measurement of High-Concentration Size Distributions

We have developed a fast-response Nanometer Aerosol Size Analyzer (nASA) that is capable of scanning 30 size channels between 3 and 100 nm in a total time of 3 seconds. The analyzer includes a bipolar charger (P0210), an extended-length Nanometer Differential Mobility Analyzer (Nano-DMA), and an electrometer (TSI 3068). This combination of components provides particle size spectra at a scan rate of 0.1 second per channel free of uncertainties caused by response-time-induced smearing. The nASA thus offers a fast response for aerosol size distribution measurements in high-concentration conditions and also eliminates the need for applying a de-smearing algorithm to resulting data. In addition, because of its thermodynamically stable means of particle detection, the nASA is useful for applications requiring measurements over a broad range of sample pressures and temperatures. Indeed, experimental transfer functions determined for the extended-length Nano-DMA using the Tandem Differential Mobility Analyzer (TDMA) technique indicate the nASA provides good size resolution at pressures as low as 200 Torr. Also, as was demonstrated in tests to characterize the soot emissions from the J85-GE engine of a T38 aircraft, the broad dynamic concentration range of the nASA makes it particularly suitable for studies of combustion or particle formation processes. Further details of the nASA performance as well as results from calibrations, laboratory tests and field applications are presented.

Han, Hee-Siew↗

Gaussian Process Regression Method for Costing SmallSat Bus Capabilities

NASA is responding to the growing interest in, andcapabilities of, small satellites for science applications with an increasingnumber and frequency of Announcements of Opportunityfor small satellite space missions. Estimating the probabilitythat these mission concepts will fit within the small cost capsof these opportunities is largely driven by the probability thatone of the burgeoning number of small satellite providers will beable to meet the payload’s accommodation requirements withinthe budget for the spacecraft. JPL has collected a databasecontaining technical specifications and cost of commerciallyavailable Smallsat buses across various vendors. The primarypurpose of the database is for use in JPL’s Team X architecturestudies to inform cost estimates of a spacecraft bus which fitsthe customer’s technical requirements for their payload andmission. Customer needs are often unique and don’t alignperfectly with an off-the-shelf commercial spacecraft bus, whichmotivates the need to develop a cost model across the continuoustechnical parameter space.Al’s Bus Cost Distribution Estimator (ABCDE) uses Gaussianprocess regression (GPR) to predict commercial Smallsat spacecraftbus cost based on a subset of a customer’s technicalrequirements (payload mass, payload power, delta V, pointingcontrol, and downlink rate). GPR is implemented in ABCDE asa Bayesian method which fits an implied multivariate regressionon the technical parameters and uses kriging to intentionally“overfit” the residuals. Overfitting the residuals allows costestimates to collapse in uncertainty closer to the data pointswhile maintaining larger uncertainty intervals in regions of parameterspace with fewer data records. The data used to fit thismodel is sensitive and represents cost estimates for off-the-shelfcommercial buses. GPR simultaneously protects the sensitivityof the database and uses the sparse nature of the database toaccount for uncertainty in cost in a useful way. For a givenset of customer technical requirements, the tool provides a costestimate distribution, the percentiles of which can be interpretedas a confidence level of finding a commercial bus under a specifiedcost cap. ABCDE dramatically pushes the boundaries ofspacecraft cost estimation models due to its Bayesian methodology(accounting for the maximum uncertainty in the underlyingregression), the mathematically advanced kriging methodology,and the novelty of its application in Team X architecture tradestudies.

Austin, Alex↗

Bayesian Rules of Thumb: Robust Uncertainty Quantification in Early Project Cost Estimation

Systems engineers often make use of cost Rules ofThumb in order to estimate cost during early phases of projectformulation. These Rules of Thumb typically take the form ofa sequence of percentages over which a total cost is allocatedacross NASA WBS elements. Rules of Thumb can then be usedto extrapolate cost from one or more known WBS elements tothe remaining unknown WBS elements, assisting early projectformulation architecture studies (such as those in JPL’s Team Xand A Team).A number of issues can arise when generating and using costRules of Thumb. For example, many records of project costsconsist of incomplete data. Typical methods of dealing withincomplete cost allocation data include (a) ignoring missionswith incomplete data, or (b) taking averages of the non-zero percentagesacross missions, but both of these methods can result inbiased estimates if the existence of incomplete data correlateswith total mission cost or any particular WBS element. Anothercommon example is cost reported in one or more incorrect WBSelements. This is especially prevalent in smaller missions whereit is more common for engineers to perform tasks that fall underthe purview of multiple WBS elements.Furthermore, a Rule of Thumb estimate is typically reported asa point estimate; there is no reported uncertainty around thepercentages used to generate an allocation. Even in the rarecase in which confidence intervals around mean percentages areprovided, there may be positive or negative correlations betweenWBS elements which can skew estimates.Here we attempt to address these problems by formulatingprobabilistic Rules of Thumb in which a distribution of allocationschemes, rather than a single allocation scheme, is generated.We use a bootstrap imputation method to simultaneouslyaccount for uncertainty in the missing data while using allavailable information contained in the dataset. The imputeddatasets are then input into a multivariate Bayesian modelwhich accounts for correlations between WBS elements andproperly accounts for uncertainty in the final Rule of Thumbpercentages and predictions. We describe the mathematicalmodel and provides snippets of R code utilizing the brms(Bayesian Regression Models using Stan) package. To illustratethis model, we generate a Bayesian Level 2 WBS Cost Rule ofThumb for MIDEX (Medium-Class Explorers) missions withdata extracted from NASA’s CADRe. We then compare thismethod’s performance with the classical Rule of Thumb method.

Hooke, Melissa A↗

Modeling of mineral dust in the atmosphere: Sources, transport, and optical thickness

A global three-dimensional model of the atmospheric mineral dust cycle is developed for the study of its impact on the radiative balance of the atmosphere. The model includes four size classes of minearl dust, whose source distributions are based on the distributions of vegetation, soil texture and soil moisture. Uplift and deposition are parameterized using analyzed winds and rainfall statistics that resolve high-frequency events. Dust transport in the atmosphere is simulated with the tracer transport model of the Goddard Institute for Space Studies. The simulated seasonal variations of dust concentrations show general reasonable agreement with the observed distributions, as do the size distributions at several observing sites. The discrepancies between the simulated and the observed dust concentrations point to regions of significant land surface modification. Monthly distribution of aerosol optical depths are calculated from the distribution of dust particle sizes. The maximum optical depth due to dust is 0.4-0.5 in the seasonal mean. The main uncertainties, about a factor of 3-5, in calculating optical thicknesses arise from the crude resolution of soil particle sizes, from insufficient constraint by the total dust loading in the atmosphere, and from our ignorance about adhesion, agglomeration, uplift, and size distributions of fine dust particles (less than 1 micrometer).

Tegen, Ina↗

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↗