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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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NASA NTRS2005

Key Reliability Drivers of Liquid Propulsion Engines and A Reliability Model for Sensitivity Analysis

This paper is to address the in-flight reliability of a liquid propulsion engine system for a launch vehicle. We first establish a comprehensive list of system and sub-system reliability drivers for any liquid propulsion engine system. We then build a reliability model to parametrically analyze the impact of some reliability parameters. We present sensitivity analysis results for a selected subset of the key reliability drivers using the model. Reliability drivers identified include: number of engines for the liquid propulsion stage, single engine total reliability, engine operation duration, engine thrust size, reusability, engine de-rating or up-rating, engine-out design (including engine-out switching reliability, catastrophic fraction, preventable failure fraction, unnecessary shutdown fraction), propellant specific hazards, engine start and cutoff transient hazards, engine combustion cycles, vehicle and engine interface and interaction hazards, engine health management system, engine modification, engine ground start hold down with launch commit criteria, engine altitude start (1 in. start), Multiple altitude restart (less than 1 restart), component, subsystem and system design, manufacturing/ground operation support/pre and post flight check outs and inspection, extensiveness of the development program. We present some sensitivity analysis results for the following subset of the drivers: number of engines for the propulsion stage, single engine total reliability, engine operation duration, engine de-rating or up-rating requirements, engine-out design, catastrophic fraction, preventable failure fraction, unnecessary shutdown fraction, and engine health management system implementation (basic redlines and more advanced health management systems).

Huang, Zhao-Feng↗

NASA NTRS2006

Towards a Framework for Modeling Space Systems Architectures

Topics covered include: 1) Statement of the problem: a) Space system architecture is complex; b) Existing terrestrial approaches must be adapted for space; c) Need a common architecture methodology and information model; d) Need appropriate set of viewpoints. 2) Requirements on a space systems model. 3) Model Based Engineering and Design (MBED) project: a) Evaluated different methods; b) Adapted and utilized RASDS & RM-ODP; c) Identified useful set of viewpoints; d) Did actual model exchanges among selected subset of tools. 4) Lessons learned & future vision.

cost savings↗

NASA NTRS2010

Locating and Quantifying Broadband Fan Sources Using In-Duct Microphones

In-duct beamforming techniques have been developed for locating broadband noise sources on a low-speed fan and quantifying the acoustic power in the inlet and aft fan ducts. The NASA Glenn Research Center's Advanced Noise Control Fan was used as a test bed. Several of the blades were modified to provide a broadband source to evaluate the efficacy of the in-duct beamforming technique. Phased arrays consisting of rings and line arrays of microphones were employed. For the imaging, the data were mathematically resampled in the frame of reference of the rotating fan. For both the imaging and power measurement steps, array steering vectors were computed using annular duct modal expansions, selected subsets of the cross spectral matrix elements were used, and the DAMAS and CLEAN-SC deconvolution algorithms were applied.

Dougherty, Robert P.↗

NASA NTRS2017

Effect of Ice Shape Fidelity on Swept-Wing Aerodynamic Performance

Low-Reynolds number testing was conducted at the 7 ft. x 10 ft. Walter H. Beech Memorial Wind Tunnel at Wichita State University to study the aerodynamic effects of ice shapes on a swept wing. A total of 17 ice shape configurations of varying geometric detail were tested. Simplified versions of an ice shape may help improve current ice accretion simulation methods and therefore aircraft design, certification, and testing. For each configuration, surface pressure, force balance, and fluorescent mini-tuft data were collected and for a selected subset of configurations oil-flow visualization and wake survey data were collected. A comparison of two ice shape geometries and two configurations with simplified geometric detail for each ice shape geometry is presented in this paper.

Scale models↗

NASA NTRS2018

Air Traffic Management Technology Demonstration - 3 (ATD-3): Operational Concept for the Integration of ATD-3 Capabilities Version 1.0

ATD-3 has developed four capabilities to address its goal and objectives. The four ATD-3 capabilities include: Dynamic Weather Routes (DWR), Multi-Flight Common Routes (MFCR), Traffic Aware Strategic Aircrew Requests (TASAR), and Dynamic Routes for Arrivals in Weather (DRAW). This document describes the long-term, mature vision for the use and incorporation of the ATD-3 capabilities into the National Airspace System (NAS). This vision describes their complementary interaction and the benefit capture that accrues from use. Recognizing that all capabilities are unlikely to be implemented in unison, each of the capabilities is designed and able to be implemented independently. As discrete portions of the integrated capabilities are planned, additional integration efforts should be undertaken to validate the complementary interactions and benefit pool are realized from the selected subset.

ConOps↗

NASA NTRS2019

Evaluating the Uncertainty of Terrestrial Water Budget Components over High Mountain Asia

This study explores the uncertainties in terrestrial water budget estimation over High Mountain Asia (HMA) using a suite of uncoupled land surface model (LSM) simulations. The uncertainty in the water balance components of precipitation (P), evapotranspiration (ET), runoff (R), and terrestrial water storage (TWS) is significantly impacted by the uncertainty in the driving meteorology, with precipitation being the most important boundary condition. Ten gridded precipitation datasets along with a mix of model-, satellite-, and gauge-based products, are evaluated first to assess their suitability for LSM simulations over HMA. The datasets are evaluated by quantifying the systematic and random errors of these products as well as the temporal consistency of their trends. Though the broader spatial patterns of precipitation are generally well captured by the datasets, they differ significantly in their means and trends. In general, precipitation datasets that incorporate information from gauges are found to have higher accuracy with low Root Mean Square Errors and high correlation coefficient values. An ensemble of LSM simulations with selected subset of precipitation products is then used to produce the mean annual fluxes and their uncertainty over HMA in P, ET, and R to be 2.11 ± 0.45, 1.26 ± 0.11, and 0.85 ± 0.36 mm per day, respectively. The mean annual estimates of the surface mass (water) balance components from this model ensemble are comparable to global estimates from prior studies. However, the uncertainty/spread of P, ET, and R is significantly larger than the corresponding estimates from global studies. A comparison of ET, snow cover fraction, and changes in TWS estimates against remote sensing-based references confirms the significant role of the input meteorology in influencing the water budget characterization over HMA and points to the need for improving meteorological inputs.

Terrestrial water budget↗

NASA NTRSDate not supplied

Investigation of Physical Mechanisms for Jet Noise Reduction by Plug Nozzle Porosity

This paper presents the results of a computational study on porous-plug nozzles for their eventual application in reducing takeoff noise levels for supersonic civil transport. The study explores a wide range of porous-plug geometries, encompassing variations in hole size, plug length and porosity. Computational fluid dynamics (CFD) analyses are employed in concert with an advanced automated mesh refinement (AMR) scheme, Sketch-to-Solution (S2S), to investigate porous plug nozzle design strategies that may diminish shock strength, broad-band shock noise (BBSN), flow separation, and other undesirable characteristics associated with high takeoff noise levels. A selected subset of the porous-plug nozzles that were analyzed computationally were manufactured at subscale using stereolithography 3D printing. These nozzles were tested experimentally, obtaining far-field noise spectral data and schlieren flow visualization pictures. Detailed comparisons between CFD predictions and experimental results were conducted. These comparisons focus on gaining a better understanding of the underlying physical mechanisms responsible for noise reduction with the porous plugs relative to corresponding solid plugs.

computational fluid dynamics↗

NASA NTRSDate not supplied

Investigation of Physical Mechanisms for Jet Noise Reduction by Plug Nozzle Porosity

Nozzles↗

NASA NTRS1983

A minicomputer based software system for the selection of optimal subsets of Thematic Mapper channels

A software system has been developed and implemented on a minicomputer for feature selection based on two inter-dependent methods. The first is an enhancement of the traditional approach based on optimizing interclass average separabilities. The second is based on a Monte Carlo simulation of multispectral data and machine classification with subsequent estimation of classification accuracy as a function of channel subset. The two methods are mutually supportive - the first allows rapid screening whereas the second is based on the more solid theoretical foundation of maximizing classification accuracy.

Card, D. H.↗

NASA NTRS2017

Selection of a Representative Subset of Global Climate Models that Captures the Profile of Regional Changes for Integrated Climate Impacts Assessment

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

Climate Change; GCMs; Climate Model Subset; Repres↗

NASA NTRS2001

Input Decimated Ensembles

Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers' performance levels high is an important area of research. In this article, we explore input decimation (ID), a method which selects feature subsets for their ability to discriminate among the classes and uses them to decouple the base classifiers. We provide a summary of the theoretical benefits of correlation reduction, along with results of our method on two underwater sonar data sets, three benchmarks from the Probenl/UCI repositories, and two synthetic data sets. The results indicate that input decimated ensembles (IDEs) outperform ensembles whose base classifiers use all the input features; randomly selected subsets of features; and features created using principal components analysis, on a wide range of domains.

Tumer, Kagan↗

NASA NTRS1985

Retrieval of Geophysical Parameters From Radiometric Data

Rapid linear algorithm retrieves meteorological parameters from microwave radiometric data. Versatile 2-step, multiple-linear-regression algorithm examines all possible subsets of available channels and selects optimum subset for retrieving given geophysical or meteorological parameter.

Pandey, P. C.↗

NASA NTRS1982

Evaluation of the potential of one to three SEASAT-SMMR channels in retrieving sea surface temperature

The scanning multichannel microwave radiometer (SMMR) aboard the SEASAT satellite measured emitted radiation in both horizontal and vertical polarizations at microwave frequencies of 6.6, 10.69, 18.0, 21.0 and 37.0 GHz. Retrieval algorithms, for sea surface temperature (SST) determination, from subsets of one to three SMMR channels are obtained by a two step statistical technique. The technique first selects the best subsets of a given size defined by an R2 criterion (coefficient of determination), of a given size by the application of an efficient 'leaps and bounds' technique on a statistical data base. It then performs a regression analysis on the selected subsets. The statistical data base employed a large (600) set of seasonally and geographically diverse atmospheric and surface parameters for radiative transfer calculations. The results of the study of one to three channel subset retrieval algorithms indicate the possibility of using 6.6V, 6.6H and 18V channels for SST determination from SEASAT-SMMR data.

Pandey, P. C.↗

NASA NTRS1991

Algorithm For Solution Of Subset-Regression Problems

Reliable and flexible algorithm for solution of subset-regression problem performs QR decomposition with new column-pivoting strategy, enables selection of subset directly from originally defined regression parameters. This feature, in combination with number of extensions, makes algorithm very flexible for use in analysis of subset-regression problems in which parameters have physical meanings. Also extended to enable joint processing of columns contaminated by noise with those free of noise, without using scaling techniques.

Verhaegen, Michel↗

NASA NTRS2009

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Simon, Donald L.↗

NASA NTRS2003

Vector-Ordering Filter Procedure for Data Reduction

The vector-ordering filter (VOF) technique involves a procedure for sampling a large population of data vectors to select a subset of data vectors that fully characterize the state space of the large population. The VOF technique enables a large reduction of the volume of data that must be handled in the automated monitoring system and method discussed in the two immediately preceding articles. In so doing, the VOF technique enables the development of data-driven mathematical models of a monitored asset from sets of data that would otherwise exceed the memory capacities of conventional engineering computers. Data-driven mathematical models have been shown to offer high fidelity for purposes of control and monitoring of assets. In practice, a collection of asset-operating observations is acquired with the intention that the collection contain observations characteristic of the full dynamic range of operation of the asset. Often, such a collection contains an extremely large number of observations, many of which are redundant. The VOF technique fills the need for a means to extract, from the original collection of observational data, a reduced data matrix that excludes redundant data while maintaining the full statistical character and dynamic range of the original data. The reduced data matrix can then be used as the input data for development of a mathematical model of the monitored asset, or as training data for a neural-network substitute for an explicit mathematical model of the asset. Alternatively, the reduced data matrix can, itself, be used directly as a mathematical model of the monitored asset, as is commonly done in multivariate state-estimation techniques. The original data are collected from the asset over a range of operating states and are put in matrix form. Each column vector in the original data matrix represents the signal values acquired at a particular operational state of the asset. Thus, the number of columns of the original data matrix equals the number of observed states and the number of rows in this matrix equals the number of signals acquired at each observation. In the VOF technique, one extracts the reduced data matrix from the original data matrix through the selection of a representative subset of the column (state) vectors.

Bickford, Randall L.↗

NASA NTRS1973

Choice: 36 band feature selection software with applications to multispectral pattern recognition

Feature selection software was developed at the Earth Resources Laboratory that is capable of inputting up to 36 channels and selecting channel subsets according to several criteria based on divergence. One of the criterion used is compatible with the table look-up classifier requirements. The software indicates which channel subset best separates (based on average divergence) each class from all other classes. The software employs an exhaustive search technique, and computer time is not prohibitive. A typical task to select the best 4 of 22 channels for 12 classes takes 9 minutes on a Univac 1108 computer.

Jones, W. C.↗

NASA NTRS1985

An adaptive quantization method for burst mode synthetic aperture radar data

Synthetic aperture radar (SAR) has high data rate because it collects and processes the data coherently. The data rate limitation of the system has to be satisfied while maintaining good image quality. Thus, a quantizer with minimum data rate and high SNR should be employed. An adaptive quantization method is proposed for the burst mode SAR. This adaptive quantizer uses uniformly quantized data to select a subset of bits which is equivalent to changing the step size of the uniform quantizer. A simple implementation which uses the previous burst data to compute the local statistics for the bit selection is presented. The use of previous burst simplifies the implementation because it does not require storage or delay; however, an abrupt change in the terrain could result in incorrect bit selection. An error analysis of this implementation and comparison of two burst mode SAR images formed using the uniformly quantized and adaptively quantized data is presented.

Joo, T. H.↗