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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Acoustic flight tests of rotorcraft noise-abatement approaches using local differential GPS guidance

This paper presents the test design, instrumentation set-up, data acquisition, and the results of an acoustic flight experiment to study how noise due to blade-vortex interaction (BVI) may be alleviated. The flight experiment was conducted using the NASA/Army Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) research helicopter. A Local Differential Global Positioning System (LDGPS) was used for precision navigation and cockpit display guidance. A laser-based rotor state measurement system on board the aircraft was used to measure the main rotor tip-path-plane angle-of-attack. Tests were performed at Crows Landing Airfield in northern California with an array of microphones similar to that used in the standard ICAO/FAA noise certification test. The methodology used in the design of a RASCAL-specific, multi-segment, decelerating approach profile for BVI noise abatement is described, and the flight data pertaining to the flight technical errors and the acoustic data for assessing the noise reduction effectiveness are reported.

Chen, Robert T. N.↗
NASA NTRS1997

Women in Flight Research at NASA Dryden Flight Research Center from 1946 to 1995: Monographs in Aerospace History - Number 6

This monograph discusses the working and living environment of women involved with flight research at NASA Dryden Flight Research Center during the late 1940s and early 1950s. The women engineers, their work and the airplanes they worked on from 1960 to December 1995 are highlighted. The labor intensive data gathering and analysis procedures and instrumentation used before the age of digital computers are explained by showing and describing typical instrumentation found on the X-series aircraft from the X-1 through the X-15. The data reduction technique used to obtain the Mach number position error curve for the X-1 aircraft and which documents the historic first flight to exceed the speed of sound is described and a Mach number and altitude plot from an X-15 flight is shown.

Powers, Sheryll Goecke↗
NASA NTRS1998

A Station Tethered Express Payload System (STEPS)

Most capsules designed to return payloads from earth orbit use rockets for deorbit. They have modest payload mass & volume fractions. Active attitude control raises costs, and the deorbit rocket imposes risks which increase development and operational costs. This note describes an alternative concept now being developed under NASA funding. It uses a tether to both deorbit and orient the capsule. This allows simultaneous reduction of capsule complexity, cost, loads, hazards, and reentry errors. The flight of SEDS-1 in 1993 proved out the basic concepts. A 20 km tether slung a 26 kg payload back to earth from a 74O x 19O km orbit, accurately enough for a pre-positioned observer to videotape the reentry. As air drag built up just before reentry, the tether was blown back and became a kite-tail, with tension increasing as predicted before flight. The tether was still attached at approx. 110 km, when telemetry was lost.

Carroll, Joseph A.↗
NASA NTRS1997

Experimental Investigation of Jet Impingement Heat Transfer Using Thermochromic Liquid Crystals

Jet impingement cooling of a hypersonic airfoil leading edge is experimentally investigated using thermochromic liquid crystals (TLCS) to measure surface temperature. The experiment uses computer data acquisition with digital imaging of the TLCs to determine heat transfer coefficients during a transient experiment. The data reduction relies on analysis of a coupled transient conduction - convection heat transfer problem that characterizes the experiment. The recovery temperature of the jet is accounted for by running two experiments with different heating rates, thereby generating a second equation that is used to solve for the recovery temperature. The resulting solution requires a complicated numerical iteration that is handled by a computer. Because the computational data reduction method is complex, special attention is paid to error assessment. The error analysis considers random and systematic errors generated by the instrumentation along with errors generated by the approximate nature of the numerical methods. Results of the error analysis show that the experimentally determined heat transfer coefficients are accurate to within 15%. The error analysis also shows that the recovery temperature data may be in error by more than 50%. The results show that the recovery temperature data is only reliable when the recovery temperature of the jet is greater than 5 C, i.e. the jet velocity is in excess of 100 m/s. Parameters that were investigated include nozzle width, distance from the nozzle exit to the airfoil surface, and jet velocity. Heat transfer data is presented in graphical and tabular forms. An engineering analysis of hypersonic airfoil leading edge cooling is performed using the results from these experiments. Several suggestions for the improvement of the experimental technique are discussed.

Dempsey, Brian Paul↗
NASA NTRS2000

Error Sources in Asteroid Astrometry

Asteroid astrometry, like any other scientific measurement process, is subject to both random and systematic errors, not all of which are under the observer's control. To design an astrometric observing program or to improve an existing one requires knowledge of the various sources of error, how different errors affect one's results, and how various errors may be minimized by careful observation or data reduction techniques.

Owen, William M., Jr.↗
NASA NTRS2002

Design and Stress Analysis of Low-Noise Adjusted Bearing Contact Spiral Bevel Gears

An integrated computerized approach for design and stress analysis of low-noise spiral bevel gear drives with adjusted bearing contact is proposed. The procedure of computations is an iterative process that requires four separate procedures and provide: (a) a parabolic function of transmission errors that is able to reduce the effect of errors of alignment on noise and vibration, and (b) reduction of the shift of bearing contact caused by misalignment. Application of finite element analysis enables us to determine the contact and bending stresses and investigate the formation of the bearing contact. The design of finite element models and boundary conditions is automated and does not require intermediate CAD computer programs for application of general purpose computer program for finite element analysis.

Fuentes, A.↗
NASA NTRS2016

Summary of Full-Scale Blade Displacement Measurements of the UH- 60A Airloads Rotor

Blade displacement measurements using multi-camera photogrammetry techniques were acquired for a full-scale UH-60A rotor, tested in the National Full-Scale Aerodynamic Complex 40-Foot by 80-Foot Wind Tunnel. The measurements, acquired over the full rotor azimuth, encompass a range of test conditions that include advance ratios from 0.15 to 1.0, thrust coefficient to rotor solidity ratios from 0.01 to 0.13, and rotor shaft angles from -10.0 to 8.0 degrees. The objective was to measure the blade displacements and deformations of the four rotor blades and provide a benchmark blade displacement database to be utilized in the development and validation of rotorcraft prediction techniques. An overview of the blade displacement measurement methodology, system development, and data analysis techniques are presented. Sample results based on the final set of camera calibrations, data reduction procedures and estimated corrections that account for registration errors due to blade elasticity are shown. Differences in blade root pitch, flap and lag between the previously reported results and the current results are small. However, even small changes in estimated root flap and pitch can lead to significant differences in the blade elasticity values.

Displacement↗
NASA NTRS2016

Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model Ensembles

To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.

damage assessment↗
DOE OSTI2020

Rapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ 1 -regularization

We develop a new data-driven paradigm for efficient model reduction of a broad class of nonlinear dynamical systems. Our model reduction method directly enables the interpretation of key components of the dynamical system, unlike traditional projection-based model reduction methods that focus on reducing computational complexity more than interpretability. Our method is not application specific and is simple to implement on nonlinear dynamical systems arising from a variety of different fields. It requires minimal parameterization using a single parameter to trade-off between model complexity and estimation error. We use a data-driven paradigm to formulate model reduction as an efficient convex optimization problem that scales polynomially in the original size of the complex system, enabling systems with as many as thousands of components to be reduced in a matter of minutes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

On the equivalence of Gaussian elimination and Gauss-Jordan reduction in solving linear equations

A novel general approach to round-off error analysis using the error complexity concepts is described. This is applied to the analysis of the Gaussian Elimination and Gauss-Jordan scheme for solving linear equations. The results show that the two algorithms are equivalent in terms of our error complexity measures. Thus the inherently parallel Gauss-Jordan scheme can be implemented with confidence if parallel computers are available.

Tsao, Nai-Kuan↗
NASA NTRS2011

A Starshade Petal Error Budget for Exo-Earth Detection and Characterization

We present a starshade error budget with engineering requirements that are well within the current manufacturing and metrology capabilities. The error budget is based on an observational scenario in which the starshade spins about its axis on timescales short relative to the zodi-limited integration time, typically several hours. The scatter from localized petal errors is smoothed into annuli around the center of the image plane, resulting in a large reduction in the background flux variation while reducing thermal gradients caused by structural shadowing. Having identified the performance sensitivity to petal shape errors with spatial periods of 3-4 cycles/petal as the most challenging aspect of the design, we have adopted and modeled a manufacturing approach that mitigates these perturbations with 1-meter-long precision edge segments positioned using commercial metrology that readily meets assembly requirements. We have performed detailed thermal modeling and show that the expected thermal deformations are well within the requirements as well. We compare the requirements for four cases: a 32 meter diameter starshade with a 1.5 meter telescope, analyzed at 75 and 90 milliarcseconds, and a 40 meter diameter starshade with a 4 meter telescope, analyzed at 60 and 75 milliarcseconds.

error budget↗
DOE OSTI2015

The source-lens clustering effect in the context of lensing tomography and its self-calibration

Cosmic shear can only be measured where there are galaxies. This source-lens clustering (SLC) effect has two sources, intrinsic source clustering and cosmic magnification (magnification/size bias). Lensing tomography can suppress the former. However, this reduction is limited by the existence of photo-z error and nonzero redshift bin width. Furthermore, SLC induced by cosmic magnification cannot be reduced by lensing tomography. Through N-body simulations, we quantify the impact of SLC on the lensing power spectrum in the context of lensing tomography. We consider both the standard estimator and the pixel-based estimator. We find that none of them can satisfactorily handle both sources of SLC. (1) For the standard estimator, SLC induced by both sources can bias the lensing power spectrum by O(1)–O(10)%. Intrinsic source clustering also increases statistical uncertainties in the measured lensing power spectrum. However, the standard estimator suppresses intrinsic source clustering in the cross-spectrum. (2) In contrast, the pixel-based estimator suppresses SLC through cosmic magnification. However, it fails to suppress SLC through intrinsic source clustering and the measured lensing power spectrum can be biased low by O(1)–O(10)%. In short, for typical photo-z errors (σ{sub z}/(1+z)=0.05) and photo-z bin sizes (Δz{sup P}=0.2), SLC alters the lensing E-mode power spectrum by 1–10%, with ℓ∼10{sup 3} and z{sub s}∼1 being of particular interest to weak lensing cosmology. Therefore the SLC is a severe systematic for cosmology in Stage-IV lensing surveys. We present useful scaling relations to self-calibrate the SLC effect.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The Reduction of Random Uncertainty in Differential Temperature Measurements Using Common Leg Thermocouples

The uncertainty quantification of random error is considered for common leg thermocouples (i.e., where one thermoelement is shared along the length of the TC for all other TC junctions present). The uncertainty is presented for both a common leg and individual, separate leg thermocouples. For Type K thermocouples a reduction in uncertainty by up to 3x is capable when differential temperatures, ?T, are within 150°C, and diminishes to little to no improvement above 150°C.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2019

Achieving Verifiable and High Integrity Instrumentation and Control Systems through Complexity Awareness and Constrained Design. Final Report

While most process control industries have been able to embrace digital Instrumentation and Control (I&C) technology to improve performance, reliability, maintainability, and efficiency of production, the nuclear industry has been relatively slow to adopt digital I&C for safety critical plant functions. There are a variety of reasons for this, but in general the nuclear industry takes a conservative stance that new technologies must mature before adoption. A deeper underlying reason for not fully realizing digital I&C and automation in nuclear power is associated with the complexity that can manifest in software-based systems that is different in nature from the complexity of their analog predecessors. Accordingly, this research pursued the development of innovative architectures and methods to “constrain complexity” to enhance verifiability of digital I&C devices. These constraints can positively impact the reduction of Software Common Cause Failures (SCCF) and other systematic errors. The architectural concept developed in this research effort is called SymPLe. SymPLe is specifically aimed at safety critical functions within Nuclear Power Plants and other critical infrastructure where constraining device complexity to support verifiability and safety case arguments is important. The SymPLe architecture is designed to promote “accessible verification” between OEM/utility engineers and the regulatory agencies who review and license nuclear power plant I&C systems. The major contributions of this work to the nuclear industry are: Demonstration of SymPLe as a viable approach to “complexity aware” I&C systems and Embedded Digital Devices.Comprehensive use of model-based design and engineering to produce verifiable I&C systems for the nuclear industry with clear findings on the usability of model-based engineering. Employ comprehensive use of model-based engineering, testing, and verification in an IEC 61508 workflow in support of design assurance. Gathered evidence of “difficult to find” design flaws found using model-based design and testing methods. Detailed the nature of these SCCFs including where they were introduced, the triggers, and how they were found. Gathered evidence on the synergistic use of practical formal methods and testing and how these methods can be used to significantly increase assurance of reduction and avoidance of design flaws.

Testing↗
NASA NTRS1985

Simulation studies of time-control procedures for the advanced air traffic control system

The problem of mixing aircraft equipped with time-controlled guidance systems and unequipped aircraft in the terminal area has been investigated via a real-time air traffic control simulation. These four-dimensional (4D) guidance systems can predict and control the touchdown time of an aircraft to an accuracy of a few seconds throughout the descent. The objectives of this investigation were to (1) develop scheduling algorithms and operational procedures for various traffic mixes that ranged from 25% to 75% 4D-equipped aircraft; (2) examine the effect of time errors at 120 n. mi. from touchdown on touchdown time scheduling of the various mix conditions; and (3) develop efficient algorithms and procedures to null the initial time errors prior to reaching the final control sector, 30 n. mi. from touchdown. Results indicate substantial reduction in controller workload and an increase in orderliness when more than 25% of the aircraft are equipped with 4D guidance systems; initial random errors of up to + or - 2 min can be handled via a single speed advisory issued in the arrival control sector, thus avoiding disruption of the time schedule.

Tobias, L.↗
NASA NTRS2022

Vision-based Velocimetry over Unknown Terrain with a Low-Noise IMU

This paper presents a novel approach to terrain-relative navigation with a visual camera and Inertial Measurement Unit (IMU). The proposed algorithm uses an Extended Kalman Filter (EKF) to combine an IMU propagated state estimate with batch correction estimates computed over a sliding window of measurements. The batch correction algorithm follows the Maximum Likelihood Estimation (MLE) approach used in other Bundle Adjustment systems. Unlike other systems, the proposed system parameterizes the state over the entire window in terms of the state at a single epoch. By ignoring IMU error over the window duration, we obtain a state epoch MLE that jointly estimates the epoch state and terrain parameters with drastically reduced computationally cost. This paper presents the general architecture which can be adapted for various state parameterizations and measurement inputs. For space applications with high-accuracy IMUs, the reduction in computational cost comes with only a modest increase in estimation errors. The increase in error is quantified via a linear covariance analysis presented in this paper. Furthermore, we present simulation results which show the applicability of this algorithm to planetary landing problems.

San Martin, A. Miguel↗
NASA NTRS1999

Data Assimilation in the Presence of Forecast Bias: The GEOS Moisture Analysis

We describe the application of the unbiased sequential analysis algorithm developed by Dee and da Silva (1998) to the GEOS DAS moisture analysis. The algorithm estimates the persistent component of model error using rawinsonde observations and adjusts the first-guess moisture field accordingly. Results of two seasonal data assimilation cycles show that moisture analysis bias is almost completely eliminated in all observed regions. The improved analyses cause a sizable reduction in the 6h-forecast bias and a marginal improvement in the error standard deviations.

Dee, Dick P.↗
DOE OSTI2023

PROTEUS: Machine Learning Driven Resilience for Extreme-scale Systems

The objective of this project is to design, develop, and evaluate scalable software to enhance resilience, data checkpointing, program restart, and analysis. The proposed tasks are to 1) develop scalable machine learning techniques to learn temporal change patterns in a scalable and in-situ manner, and to minimize data movement and maximize learning locally closest to data; 2) design a concise data representation and indexing mechanism to capture the distribution of changes in data that can guarantee point-wise user-defined tolerable errors while reducing the data storage requirements by an order of magnitude or more; 3) develop data reduction techniques as library modules; 4) exploit local SSD for minimizing data movement in storage hierarchy; 5) develop anomaly detection algorithms that can predict corruptions based on learning of emerging patterns; 6) develop software libraries to be incorporated within widely used data formats and APIs; and 7) evaluate the proposed software using DOE scientific applications. The outcomes of the proposed work are to satisfy many synergistic data reduction and resilience requirements for large-scale data intensive applications executed on extreme-scale computing systems. The developed mechanism for error-bound data approximation is directly applicable to existing scientific applications. Through machine learning from historical events and change distribution, this work will enable anomaly detection for DOE computer facility.

97 MATHEMATICS AND COMPUTING↗