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At least 1,189 records · Page 66

Airframe noise: A design and operating problem

A critical assessment of the state of the art in airframe noise is presented. Full-scale data on the intensity, spectra, and directivity of this noise source are evaluated in light of the comprehensive theory developed by Ffowcs Williams and Hawkings. Vibration of panels on the aircraft is identified as a possible additional source of airframe noise. The present understanding and methods for prediction of other component sources - airfoils, struts, and cavities - are discussed. Operating problems associated with airframe noise as well as potential design methods for airframe noise reduction are identified.

Hardin, J. C.↗

Close-mode identification performance of the ITD algorithm

Results of Monte Carlo numerical simulations conducted to study the close-mode performance of the Ibrahim Time-Domain (ITD) modal identification algorithm are presented. The ITD technique is a matrix eigensolution method for obtaining structural modal parameters directly from free-response test data without using the FFT. Thus, the well-known resolution and leakage limitations of the FFT procedure, that are particularly significant with short records, are avoided. As an example, one of several experimental data analyses where close modes have been accurately identified using very short records is shown. Although the identification scatter is found to increase as the square of reductions in frequency separation at small separations, the ability to differentiate modes spaced at fractions of the FFT resolution is substantiated.

Pappa, R. S.↗

The relationship between gravity and bathymetry in the Pacific Ocean

The study of the earth's gravitational field has provided one of the principal methods for the determination of the structure of the outer layers of the earth. A project has been undertaken which involves the systematic examination of the relationship between the earth's gravity field and topography in each of the earth's major ocean basins. The first part of the project was concerned with the compilation, reduction, and analysis of the available surface-ship gravity and bathymetry and satellite-derived geoid data in the oceans of the earth. The present paper has the objective to summarize the principal results which have been obtained so far in the Pacific Ocean.

Watts, A. B.↗

Dynamically stratified Monte Carlo forecasting

A new method for performing Monte Carlo forecasts is introduced. The method, called dynamic stratification, selects initial perturbations based on a stratification of the error distribution. A simple implementation is presented in which the error distribution used for the stratification is estimated from a linear model derived from a large ensemble of 12-h forecasts with the full dynamic model. The stratification thus obtained is used to choose a small subsample of initial states with which to perform the dynamical Monte Carlo forecasts. Several test cases are studied using a simple two-level general circulation model with uncertain initial conditions. It is found that the method provides substantial reductions in the sampling error of the forecast mean and variance when compared to the more traditional approach of choosing the initial perturbations at random. The degree of improvement, however, is sensitive to the nature of the initial error distribution and to the base state. In practice the method may be viable only if the computational burden involved in obtaining an adequate estimate of the error distribution is shared with the data-assimilation procedure.

Schubert, Siegfried↗

A simple node and conductor data generator for SINDA

This paper presents a simple, automated method to generate NODE and CONDUCTOR DATA for thermal match modes. The method uses personal computer spreadsheets to create SINDA inputs. It was developed in order to make SINDA modeling less time consuming and serves as an alternative to graphical methods. Anyone having some experience using a personal computer can easily implement this process. The user develops spreadsheets to automatically calculate capacitances and conductances based on material properties and dimensional data. The necessary node and conductor information is then taken from the spreadsheets and automatically arranged into the proper format, ready for insertion directly into the SINDA model. This technique provides a number of benefits to the SINDA user such as a reduction in the number of hand calculations, and an ability to very quickly generate a parametric set of NODE and CONDUCTOR DATA blocks. It also provides advantages over graphical thermal modeling systems by retaining the analyst's complete visibility into the thermal network, and by permitting user comments anywhere within the DATA blocks.

Gottula, Ronald R.↗

Transverse cracking and stiffness reduction in composite laminates

A study of transverse cracking mechanism in composite laminates is presented using a singular hybrid finite element model. The model provides the global structural response as well as the precise local crack-tip stress fields. An elasticity basis for the problem is established by employing Lekhnitskii's complex variable potentials and method of eigenfunction expansion. Stress singularities associated with the transverse crack are obtained by decomposing the deformation into the symmetric and antisymmetric modes and proper boundary conditions. A singular hybrid element is thereby formulated based on the variational principle of a modified hybrid functional to incorporate local crack singularities. Axial stiffness reduction due to transverse cracking is studied. The results are shown to be in very good agreement with the existing experimental data. Comparison with simple shear lag analysis is also given. The effects of stress intensity factors and strain energy density on the increase of crack density are analyzed. The results reveal that the parameters approach definite limits when crack densities are saturated, an evidence of the existence of characteristic damage state.

Yuan, F. G.↗

Theoretical study of thermodynamic properties and reaction rates of importance in the high-speed research program

One of the primary goals of NASA's high-speed research program is to determine the feasibility of designing an environmentally safe commercial supersonic transport airplane. The largest environmental concern is focused on the amount of ozone destroying nitrogen oxides (NO(x)) that would be injected into the lower stratosphere during the cruise portion of the flight. The limitations placed on NO(x) emission require more than an order of magnitude reduction over current engine designs. To develop strategies to meet this goal requires first gaining a fundamental understanding of the combustion chemistry. To accurately model the combustor requires a computational fluid dynamics approach that includes both turbulence and chemistry. Since many of the important chemical processes in this regime involve highly reactive radicals, an experimental determination of the required thermodynamic data and rate constants is often very difficult. Unlike experimental approaches, theoretical methods are as applicable to highly reactive species as stable ones. Also our approximation of treating the dynamics classically becomes more accurate with increasing temperature. In this article we review recent progress in generating thermodynamic properties and rate constants that are required to understand NO(x) formation in the combustion process. We also describe our one-dimensional modeling efforts to validate an NH3 combustion reaction mechanism. We have been working in collaboration with researchers at LeRC, to ensure that our theoretical work is focused on the most important thermodynamic quantities and rate constants required in the chemical data base.

Langhoff, Stephen↗

Robust Combining of Disparate Classifiers Through Order Statistics

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

Tumer, Kagan↗

Image Mapping and Visual Attention on the Sensory Ego-Sphere

The Sensory Ego-Sphere (SES) is a short-term memory for a robot in the form of an egocentric, tessellated, spherical, sensory-motor map of the robot s locale. Visual attention enables fast alignment of overlapping images without warping or position optimization, since an attentional point (AP) on the composite typically corresponds to one on each of the collocated regions in the images. Such alignment speeds analysis of the multiple images of the area. Compositing and attention were performed two ways and compared: (1) APs were computed directly on the composite and not on the full-resolution images until the time of retrieval; and (2) the attentional operator was applied to all incoming imagery. It was found that although the second method was slower, it produced consistent and, thereby, more useful APs. The SES is an integral part of a control system that will enable a robot to learn new behaviors based on its previous experiences, and that will enable it to recombine its known behaviors in such a way as to solve related, but novel, task problems with apparent creativity. The approach is to combine sensory-motor data association and dimensionality reduction to learn navigation and manipulation tasks as sequences of basic behaviors that can be implemented with a small set of closed-loop controllers. Over time, the aggregate of behaviors and their transition probabilities form a stochastic network. Then given a task, the robot finds a path in the network that leads from its current state to the goal. The SES provides a short-term memory for the cognitive functions of the robot, association of sensory and motor data via spatio-temporal coincidence, direction of the attention of the robot, navigation through spatial localization with respect to known or discovered landmarks, and structured data sharing between the robot and human team members, the individuals in multi-robot teams, or with a C3 center.

Fleming, Katherine Achim↗

Mass Spectrometric Studies of Oxides

Current studies at NASA Glenn on oxide thermodynamics are discussed. Previous studies on the vaporization of B2O3 in reducing atmospheres led to inconsistent studies when B was used as a reductant. It is shown that liquid B2O3 does not wet B and a clear phase separation was noted in the Knudsen cell. This problem was solved by using FeB and Fe2B to supply a different and constant activity of B. The thermodynamic data thus derived are compared to quantum chemical composite calculations. A major problem in high temperature mass spectrometry is the determination of accurate ionization cross sections, particularly for molecules. The method of Deutsch and Mark shows promise and some sample calculations are discussed. Finally current studies on the thermodynamics of rare earth silicates are discussed. Here the problems are obtaining a measurable signal from SiO2 vaporization and non-equilibrium vaporization. The use of a Ta reducing agent provides a stronger signal, which is related to silica activity. The Whitman-Motzfeld relation adapted to KEMS measurements is applied to obtain equilibrium pressures.

Jacobson, Nathan S.↗

Multifidelity uncertainty quantification with models based on dissimilar parameters

Multifidelity uncertainty quantification (MF UQ) sampling approaches have been shown to significantly reduce the variance of statistical estimators while preserving the bias of the highest-fidelity model, provided that the low-fidelity models are well correlated. However, maintaining a high level of correlation can be challenging, especially when models depend on different input uncertain parameters, which drastically reduces the correlation. Existing MF UQ approaches do not adequately address this issue. In this work, we propose a new sampling strategy that exploits a shared space to improve the correlation among models with dissimilar parameterization. We achieve this by transforming the original coordinates onto an auxiliary manifold using the adaptive basis (AB) method (Tipireddy and Ghanem, 2014). The AB method has two main benefits: (1) it provides an effective tool to identify the low-dimensional manifold on which each model can be represented, and (2) it enables easy transformation of polynomial chaos representations from high- to low-dimensional spaces. This latter feature is used to identify a shared manifold among models without requiring additional evaluations. Here we present two algorithmic flavors of the new estimator to cover different analysis scenarios, including those with legacy and non-legacy high-fidelity (HF) data. We provide numerical results for analytical examples, a direct field acoustic test, and a finite element model of a nuclear fuel assembly. For all examples, we compare the proposed strategy against both single-fidelity and MF estimators based on the original model parameterization.

42 ENGINEERING↗

Tracking the PACE of household energy usage: Energy usage impacts of projects financed through Property Assessed Clean Energy programs in California

This report examines the household-level energy impacts of residential property assessed clean energy (R-PACE) projects using normalized metered energy consumption methods. Our analysis covers projects that occurred through an R-PACE program between 2009 and 2017 and includes more than 25,000 electricity meters and 15,000 gas meters. We employ a comparison group, drawn from other R-PACE households with similar locational and usage characteristics whose projects were implemented at different times, to control for some non-project and non-weather factors that may impact energy use. We find that projects consisting of energy efficiency technologies save, on average, about 3% of household electricity usage and 3.5% of household gas usage. R-PACE financing, however, can be used to install central heating or air conditioning equipment for the first time. These projects would be expected to increase energy consumption. Since our data do not directly indicate which projects are new installations, we develop a simple algorithm for identifying them. Removing these inferred installation projects yields average savings of about 5% for electricity and 6% for gas for those households that remain in the sample. Given the mild California climate and the results of another study of similar California projects using similar methods, these results are in line with expectations. Solar PV projects yield large reductions in grid electricity use, averaging 69% of household consumption. We estimate that, collectively, all R-PACE projects installed in California through 2019 would generate annual reductions in grid-tied electricity consumption of 506 GWh (mostly due to solar PV) and gas consumption reductions of 2 million therms in a normal weather year. These impacts are equivalent to the electricity consumption of about 74,000 California households (including both efficiency and PV generation) and the gas consumption of about 4700 California households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Some methods of computing platform transmitter terminal location estimates

A position estimation algorithm was developed to track a humpback whale tagged with an ARGOS platform after a transmitter deployment failure and the whale's diving behavior precluded standard methods. The algorithm is especially useful where a transmitter location program exists; it determines the classical keplarian elements from the ARGOS spacecraft position vectors included with the probationary file messages. A minimum of three distinct messages are required. Once the spacecraft orbit is determined, the whale is located using standard least squares regression techniques. Experience suggests that in instances where circumstances inherent in the experiment yield message data unsuitable for the standard ARGOS reduction, (message data may be too sparse, span an insufficient period, or include variable-length messages). System ARGOS can still provide much valuable location information if the user is willing to accept the increased location uncertainties.

Hoisington, C. M.↗

Free-decay time-domain modal identification for large space structures

Concept definition studies for the Modal Identification Experiment (MIE), a proposed space flight experiment for the Space Station Freedom (SSF), have demonstrated advantages and compatibility of free-decay time-domain modal identification techniques with the on-orbit operational constraints of large space structures. Since practical experience with modal identification using actual free-decay responses of large space structures is very limited, several numerical and test data reduction studies were conducted. Major issues and solutions were addressed, including closely-spaced modes, wide frequency range of interest, data acquisition errors, sampling delay, excitation limitations, nonlinearities, and unknown disturbances during free-decay data acquisition. The data processing strategies developed in these studies were applied to numerical simulations of the MIE, test data from a deployable truss, and launch vehicle flight data. Results of these studies indicate free-decay time-domain modal identification methods can provide accurate modal parameters necessary to characterize the structural dynamics of large space structures.

Kim, Hyoung M.↗

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗

Novel Engineering and Fabrication Techniques Tested in Low-Noise- Research Fan Blades

A major source of fan noise in commercial turbofan engines is the interaction of the wake from the fan blades with the stationary vanes (stators) directly behind them. The Trailing Edge Blowing (TEB) project team at the NASA Glenn Research Center designed and fabricated new fan blades to study the effects of fan trailing edge blowing as a potential noise-reduction concept. The intent is to fill the rotor wake by supplying air to the rotor blade trailing edge at the proper conditions to minimize the wake deficit, and thus generate less noise. The TEB hardware is designed for the Active Noise Control Fan (ANCF) test rig in Glenn's Aeroacoustic Propulsion Laboratory. For this test, the air is fed from an external supply through the shaft of the rig. It is distributed to the base of each blade through an impeller, where it is forced into a plenum at the core of each blade. In actual engine configuration, air would most likely be bled from the compressor, but only at times when noise is an issue, such as takeoffs and landings. Glenn researchers designed and manufactured the blades in-house, using new techniques and concepts. The skins, which were designed for maximum strength in the directions of highest stress, were molded from multiple layers of carbon fiber. Considerable use was made of rapid prototyping techniques, such as laser sintering. The core was sintered from a lightweight polymer, and the retainer was CNC-machined (computer numerical control machined) from aluminum. All the components were joined with a cold-cure aerospace adhesive. These techniques and processes reduced the overall cost and allowed the new concept to be studied much sooner than would be possible using traditional fabrication methods. Since this test rig did not support the use of blade-monitoring techniques such as strain gauges, extensive bench testing was required to qualify the design. The blades were examined using a variety of methods including holography, pull tests (cyclic and failure), shake tests, rap tests, and nondestructive inspection. Acoustic testing of the ANCF fan using TEB has been ongoing since January of 2001. The fan has completed about 100 hr of testing with no structural, vibrational, or fatigue problems. Far-field acoustic measurements, in-duct mode measurements, precise hot wire surveys, and detailed performance measurements are providing data for evaluating the concept. The far-field noise data show that tone noise was reduced significantly with the initial ANCF TEB fan design. In addition, a significant reduction in unsteady stator loading has been measured, indicating the potential for stator broadband noise reduction. The acoustic benefits will be assessed and important design parameters identified to improve the ability to fully exploit any benefit provided by this technique. On the basis of the success of trailing edge blowing, Glenn plans to continue this research with a higher speed, higher pressure ratio fan operating in an acoustic wind tunnel to simulate flight conditions.

Cunningham, Cameron C.↗

Nuclear Astrophysics in the Storage Ring: Background Suppressed Simultaneous Measurement of (p,γ) and (p,n) Reactions

We report the application of the new elimination of Rutherford elastic scattering technique for the measurement of proton-induced reaction cross sections utilizing stored ions decelerated to astrophysical energies. This approach results in a background reduction factor of about 1 order of magnitude, enabling the first measurement of a (p, n) cross section in a storage ring. Here, the reaction channels 124 Xe⁢(p,n) and 124 Xe⁢(p,γ) have been studied just above the neutron threshold energy. The new data provide valuable constraints for Hauser-Feshbach theory and extrapolation of the (p,γ) cross section to lower energies. Most importantly, for nuclei of limited availability, the method represents a powerful improvement to efficiently study proton-induced reactions at energies within or close to the astrophysical Gamow window, bringing many reaction measurements within reach that were previously inaccessible in the laboratory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Conditional replenishment using motion prediction

Conditional replenishment is an interframe video compression method that uses correlation in time to reduce video transmission rates. This method works by detecting and sending only the changing portions of the image and by having the receiver use the video data from the previous frame for the non-changing portion. The amount of compression that can be achieved through this technique depends to a large extent on the rate of change within the image, and can vary from 10 to 1 to less than 2 to 1. An additional 3 to 1 reduction in rate is obtained by the intraframe coding of data blocks using a 2-dimensional variable rate Hadamard transform coder. A further additional 2 to 1 rate reduction is achieved by using motion prediction. Motion prediction works by measuring the relative displacements of a subpicture from one frame to the next. The subpicture can then be transmitted by sending only the value of the 2-dimensional displacement. Computer simulations have demonstrated that data rates of 2 to 4 Mega-bits/second can be achieved while still retaining good fidelity in the image.

Hein, D. N.↗