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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

An Overview of Measurement Comparisons from the INTEX-B/MILAGRO Airborne Field Campaign

As part of the NASA's INTEX-B mission, the NASA DC-8 and NSF C-130 conducted three wing-tip to wing-tip comparison flights. The intercomparison flights sampled a variety of atmospheric conditions (polluted urban, non-polluted, marine boundary layer, clean and polluted free troposphere). These comparisons form a basis to establish data consistency, but also should also be viewed as a continuation of efforts aiming to better understand and reduce measurement differences as identified in earlier field intercomparison exercises. This paper provides a comprehensive overview of 140 intercomparisons of data collected as well as a record of the measurement consistency demonstrated during INTEX-B. It is the primary goal to provide necessary information for the future research to determine if the observations from different INTEX-B platforms/instrument are consistent within the PI reported uncertainties and used in integrated analysis. This paper may also contribute to the formulation strategy for future instrument developments. For interpretation and most effective use of these results, the reader is strongly urged to consult with the instrument principle investigator.

Kleb, Mary M.↗
NASA NTRS2003

Radiation Risk Projections for Space Travel

Space travelers are exposed to solar and galactic cosmic rays comprised of protons and heavy ions moving with velocities close to the speed of light. Cosmic ray heavy ions are known to produce more severe types of biomolecular damage in comparison to terrestrial forms of radiation, however the relationship between such damage and disease has not been fully elucidated. On Earth, we are protected from cosmic rays by atmospheric and magnetic shielding, and only the remnants of cosmic rays in the form of ground level muons and other secondary radiations are present. Because human epidemiology data is lacking for cosmic rays, risk projection must rely on theoretical understanding and data from experimental models exposed to space radiation using charged particle accelerators to simulate space radiation. Although the risks of cancer and other late effects from cosmic rays are currently believed to present a severe challenge to space travel, this challenge is centered on our lack of confidence in risk projections methodologies. We review biophysics and radiobiology data on the effects of the cosmic ray heavy ions, and the current methods used to project radiation risks . Cancer risk projections are described as a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Risk projections for space travel are described using Monte-Carlo sampling from subjective error di stributions that represent the lack of knowledge in each factor that contributes to the projection model in order to quantify the overall uncertainty in risk projections. This analysis is applied to space mi ssion scenarios including lunar colony, deep space outpost, and a Mars mission. Results suggest that the number of days in space where cancer mortality risks can be assured at a 95% confidence level to be below the maximum acceptable risk for radi ation workers on Earth or the International Space Station is only on the order of 100-200 days. Approaches to reduce these unceI1ainties and mitigate risks are described.

Cucinotta, Francis↗
NASA NTRS2012

Reliability Impacts in Life Support Architecture and Technology Selection

Quantitative assessments of system reliability and equivalent system mass (ESM) were made for different life support architectures based primarily on International Space Station technologies. The analysis was applied to a one-year deep-space mission. System reliability was increased by adding redundancy and spares, which added to the ESM. Results were thus obtained allowing a comparison of the ESM for each architecture at equivalent levels of reliability. Although the analysis contains numerous simplifications and uncertainties, the results suggest that achieving necessary reliabilities for deep-space missions will add substantially to the life support ESM and could influence the optimal degree of life support closure. Approaches for reducing reliability impacts were investigated and are discussed.

Lange Kevin E.↗
NASA NTRS2014

Assessment of Satellite Radiometry in the Visible Domain

Marine reflectance and chlorophyll-a concentration are listed among the Essential Climate Variables by the Global Climate Observing System. To contribute to climate research, the satellite ocean color data records resulting from successive missions need to be consistent and well characterized in terms of uncertainties. This chapter reviews various approaches that can be used for the assessment of satellite ocean color data. Good practices for validating satellite products with in situ data and the current status of validation results are illustrated. Model-based approaches and inter-comparison techniques can also contribute to characterize some components of the uncertainty budget, while time series analysis can detect issues with the instrument radiometric characterization and calibration. Satellite data from different missions should also provide a consistent picture in scales of variability, including seasonal and interannual signals. Eventually, the various assessment approaches should be combined to create a fully characterized climate data record from satellite ocean color.

ocean color↗
NASA NTRS2018

Halpha Emitting Galaxies at Z ~ 0.6 in the Deep and Wide Narrow-Band Survey

We present new measurements of the Hα luminosity function (LF) and star formation rate (SFR) volume density for galaxies at z∼0.62 in the COSMOS field. Our results are part of the Deep And Wide Narrow-band Survey (DAWN), a unique infrared imaging program with large areal coverage (∼1.1 deg2 over five fields) and sensitivity (9.9 x 10(exp -18) erg cm(exp -2) s(exp -1) at 5σ). The present sample, based on a single DAWN field, contains 116 Hα emission line candidates at z∼0.62, 25% of which have spectroscopic confirmations. These candidates have been selected through the comparison of narrow and broad-band images in the infrared and through matching with existing catalogs in the COSMOS field. The dust-corrected LF is well described by a Schechter function with L* = 10 (exp 42.64 +/- 0.92) erg s (exp −1), Phi* = 10 (exp -3.320.93)Mpc(exp −3), L*Phi* = L 10(exp 39.40) 0.15 erg s(exp −1)Mpc(exp −3), and α=−1.75+/-0.09. From this LF, we calculate a SFR density of ρSFR=10(exp −1.37+/-0.08)solar mass yr(exp −1)Mpc(exp −3). We expect an additional cosmic variance uncertainty of ∼20%. Both the faint end slope and luminosity density that we derive are consistent with prior results at similar redshifts, with reduced uncertainties. We also present an analysis of these Hα emitters' sizes, which shows a direct correlation between the galaxies' sizes and their Hα emission.

Coughlin, Alicia↗
NASA NTRS2017

B-plane Evolution Under Highly Non-Keplerian Dynamics

Juno is the second of a series of New Frontiers missions and was launched in 2011. The spacecraft was set en route to Jupiter, and its Jupiter Orbit Insertion occurred on 2016-07-04 after a five-year cruise in deep space. The mission phase just prior to this large maneuver is called approach. As navigation team, we were responsible for precise orbit determination of the Juno spacecraft to ensure a successful orbit insertion. To evaluate the navigation performance we employed the B-plane mapping, where the incoming hyperbolic velocity defines the plane perpendicular to it, and the time to go to hit the plane will directly map into the uncertainties of the target point. The B-plane is a convenient tool when assessing the navigation performance as it is not affected by non-linearities due to the gravitational pull of the targeted body. However, as the Jupiter Orbit Insertion approached we started to realize that the B-plane mapping uncertainties were significantly larger than expected. We found that the B-plane mapping time had tremendous influence on the covariance inflation in the B-plane. Because of the close approach distance during the Jupiter Orbit Insertion and the strong interaction with J2 spherical harmonic coefficient, the Juno dynamics were too far from a Keplerian one assumed for the B-plane mapping. We first discuss the analytical approach of the B-plane mapping uncertainty and perform a numerical analysis to isolate the components of the Juno dynamics that cause the B-plane covariance inflation.

Bordi, John↗
NASA NTRS2000

An Approach to Experimental Design for the Computer Analysis of Complex Phenomenon

The ability to make credible system assessments, predictions and design decisions related to engineered systems and other complex phenomenon is key to a successful program for many large-scale investigations in government and industry. Recently, many of these large-scale analyses have turned to computational simulation to provide much of the required information. Addressing specific goals in the computer analysis of these complex phenomenon is often accomplished through the use of performance measures that are based on system response models. The response models are constructed using computer-generated responses together with physical test results where possible. They are often based on probabilistically defined inputs and generally require estimation of a set of response modeling parameters. As a consequence, the performance measures are themselves distributed quantities reflecting these variabilities and uncertainties. Uncertainty in the values of the performance measures leads to uncertainties in predicted performance and can cloud the decisions required of the analysis. A specific goal of this research has been to develop methodology that will reduce this uncertainty in an analysis environment where limited resources and system complexity together restrict the number of simulations that can be performed. An approach has been developed that is based on evaluation of the potential information provided for each "intelligently selected" candidate set of computer runs. Each candidate is evaluated by partitioning the performance measure uncertainty into two components - one component that could be explained through the additional computational simulation runs and a second that would remain uncertain. The portion explained is estimated using a probabilistic evaluation of likely results for the additional computational analyses based on what is currently known about the system. The set of runs indicating the largest potential reduction in uncertainty is then selected and the computational simulations are performed. Examples are provided to demonstrate this approach on small scale problems. These examples give encouraging results. Directions for further research are indicated.

Rutherford, Brian↗
NASA NTRS1980

Uncertainties in predicting turbine blade metal temperatures

An analysis is presented of the effects of the hot-gas and coolant temperatures, the gas-to-blade and blade-to-coolant heat transfer coefficients, and the thermal conductances of a metal wall and a ceramic thermal-barrier coating on the prediction of local turbine-blade surface temperatures. The analysis was applied to the conditions of an advanced turbofan engine and a 1700 K, 40 atm turbine test rig, and to conditions that simulated the engine at 756 K and 15.6 atm. The results showed that with current information on boundary conditions, geometry, heat-transfer coefficients, and material thermal properties, the uncertainty in predicting and verifying local turbine-blade surface temperatures in an average engine is 98 kelvins or 7.6% of the reference metal absolute temperature for uncoated blades, and 62 kelvins or 5.7% for ceramic-thermal-barrier-coated blades.

Stepka, F. S.↗
NASA NTRS2004

The Micro-Pulse Lidar Network (MPLNET): A Federated Network of Micro-pulse Lidars and AERONET Sunphotometers

We present the formation of a new global-ground based eye-safe lidar network, the NASA Micro-Pulse Lidar Network (MPLNET). The aim of MPLNET is to acquire long- term observations of aerosol and cloud vertical profiles at unique geographic sites within the NASA Aerosol Robotic Network (AERONET). MPLNET utilizes standard instrumentation and data processing algorithms for efficient network operations and direct comparison of data between each site. The micro-pulse lidar is eye-safe, compact, and commercially available, and most easily allows growth of the network without sacrificing standardized instrumentation goals. Network growth follows a federated approach, pioneered by AERONET, wherein independent research groups may join MPLNET with their own instrument and site. MPLNET sites produce not only vertical profile data, but also column-averaged products already available from AERONET (aerosol optical depth, sky radiance, size distributions). Algorithms are presented for each MPLNET data product. Real-time Level 1 data products (next-day) include daily lidar signal images from the surface to -2Okm, and Level 1.5 aerosol extinction profiles at times co-incident with AERONET observations. Quality assured Level 2 aerosol extinction profiles are generated after screening the Level 1.5 results and removing bad data. Level 3 products include continuous day/night aerosol extinction profiles, and are produced using Level 2 calibration data. Rigorous uncertainty calculations are presented for all data products. Analysis of MPLNET data show the MPL and our analysis routines are capable of successfully retrieving aerosol profiles, with the strenuous accounting of uncertainty necessary for accurate interpretation of the results.

Welton, Ellsworth J.↗
NASA NTRS2008

Orbit Determination for the 2007 Mars Phoenix Lander

The Phoenix mission is designed to study the arctic region of Mars. To achieve this goal, the spacecraft must be delivered to a narrow corridor at the top of the Martian atmosphere, which is approximately 20 km wide. This paper will discuss the details of the Phoenix orbit determination process and the effort to reduce errors below the level necessary to achieve successful atmospheric entry at Mars. Emphasis will be placed on properly modeling forces that perturb the spacecraft trajectory and the errors and uncertainties associated with those forces. Orbit determination covariance analysis strongly influenced mission operations scenarios, which were chosen to minimize errors and associated uncertainties.

Ryne, Mark S.↗
NASA NTRS2016

Estimating the Rate of Occurrence of Renal Stones in Astronauts

Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidence of renal stones in US astronauts exists and the question "How much does this risk change with space flight?" remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone presentation. The modeling process utilizes a Population Balance Equation based model developed in the companion IWS abstract by Kassemi et al. (2016) to evaluate the maximum growth and agglomeration potential from a specified set of urine chemistry values. Changes in renal stone occurrence rates are obtained from this model in a probabilistic simulation that interrogates the range of possible urine chemistries using Monte Carlo techniques. Subsequently, each randomly sampled urine chemistry undergoes speciation analysis using the well-established Joint Expert Speciation System (JESS) code to calculate critical values, such as ionic strength and relative supersaturation. The Kassemi model utilizes this information to predict the mean and maximum stone size. We close the assessment loop by using a transfer function that estimates the rate of stone formation from combining the relative supersaturation and both the mean and maximum free stone growth sizes. The transfer function is established by a simulation analysis which combines population stone formation rates and Poisson regression. Training this transfer function requires using the output of the aforementioned assessment steps with inputs from known non-stone-former and known stone-former urine chemistries. Established in a Monte Carlo system, the entire renal stone analysis model produces a probability distribution of the stone formation rate and an expected uncertainty in the estimate. The utility of this analysis will be demonstrated by showing the change in renal stone occurrence predicted by this method using urine chemistry distributions published in Whitson et al. 2009. A comparison to the model predictions to previous assessments of renal stone risk will be used to illustrate initial validation of the model.

gravitational physiology↗
NASA NTRS1979

Ramp time synchronization

A new method of intercontinental clock synchronization has been developed and proposed for possible use by NASA's Deep Space Network (DSN), using a two-way/three-way radio link with a spacecraft. Analysis of preliminary data indicates that the real-time method has an uncertainty of 0.6 microsec, and it is very likely that further work will decrease the uncertainty. Also, the method is compatible with a variety of nonreal-time analysis techniques, which may reduce the uncertainty down to the tens of nanosecond range.

Hietzke, W.↗
NASA NTRS1993

Specifying design conservatism: Worst case versus probabilistic analysis

Design conservatism is the difference between specified and required performance, and is introduced when uncertainty is present. The classical approach of worst-case analysis for specifying design conservatism is presented, along with the modern approach of probabilistic analysis. The appropriate degree of design conservatism is a tradeoff between the required resources and the probability and consequences of a failure. A probabilistic analysis properly models this tradeoff, while a worst-case analysis reveals nothing about the probability of failure, and can significantly overstate the consequences of failure. Two aerospace examples will be presented that illustrate problems that can arise with a worst-case analysis.

Miles, Ralph F., Jr.↗
NASA NTRS2019

Uncertainty of Observation Impact Estimation in an Adjoint Model Investigated with an Observing System Simulation Experiment

Adjoint models are often used to estimate the impact of different observations on short-term forecast skill. A common difficulty with the evaluation of short term forecast quality is the choice of verification fields. The use of self-analysis fields for verification is typical but incestuous, and introduces uncertainty due to biases and errors in the analysis field. In this study, an observing system simulation experiment (OSSE) is used to explore the uncertainty in adjoint model estimations of observation impact. The availability of the true state for verification in the OSSE framework in the form of the Nature Run allows calculation of the observation impact without the uncertainties present in self-analysis verification. These impact estimates are compared to estimates calculated using self-analysis verification. The Global Earth Observing System version 5 (GEOS-5) forecast model with Gridpoint Statistical Interpolation (GSI) is used with the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) OSSE capability. The adjoint model includes moist processes, with total wet energy selected as the norm for evaluation of observation impacts. The results show that there are measurable but small discrepancies in the adjoint model estimation of observation impact. In general, observations of temperature and winds tend to have overestimated impacts with self-analysis verification, while observations of humidity and moisture-affected observations tend to have underestimated impacts. The small magnitude of the differences in impact estimates supports the robustness of the adjoint method of estimating observation impacts.

N C Prive↗
NASA NTRSDate not supplied

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design

UQ↗
NASA NTRSDate not supplied

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design.

UQ↗
NASA NTRS1986

Description of data on the Nimbus 7 LIMS map archive tape: Temperature and geopotential height

The process by which the analysis of the Limb Infared Monitor of the Stratosphere (LIMS) experiment data were used to produce estimates of synoptic maps of temperature and geopotential height is described. In addition to a detailed description of the analysis procedure, several interesting features in the data are discussed and these features are used to demonstrate how the analysis procedure produced the final maps and how one can estimate the uncertainties in the maps. In addition, features in the analysis are noted that would influence how one might use, or interpret, the results. These include subjects such as smoothing and the interpretation of wave components. While some suggestions are made for an improved analysis of the data, it is shown that, in general, the maps are an excellent estimation of the synoptic fields.

Haggard, K. V.↗