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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 847 records · Page 47

Ionospheric Slant Total Electron Content Analysis Using Global Positioning System Based Estimation

A method, system, apparatus, and computer program product provide the ability to analyze ionospheric slant total electron content (TEC) using global navigation satellite systems (GNSS)-based estimation. Slant TEC is estimated for a given set of raypath geometries by fitting historical GNSS data to a specified delay model. The accuracy of the specified delay model is estimated by computing delay estimate residuals and plotting a behavior of the delay estimate residuals. An ionospheric threat model is computed based on the specified delay model. Ionospheric grid delays (IGDs) and grid ionospheric vertical errors (GIVEs) are computed based on the ionospheric threat model.

Sparks, Lawrence C.↗

Motion Estimation System Utilizing Point Cloud Registration

A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.

Chen, Qi↗

The use of multiwavelets for uncertainty estimation in seismic surface wave dispersion.

This report describes a new single-station analysis method to estimate the dispersion and uncer- tainty of seismic surface waves using the multiwavelet transform. Typically, when estimating the dispersion of a surface wave using only a single seismic station, the seismogram is decomposed into a series of narrow-band realizations using a bank of narrow-band filters. By then enveloping and normalizing the filtered seismograms and identifying the maximum power as a function of frequency, the group velocity can be estimated if the source-receiver distance is known. However, using the filter bank method, there is no robust way to estimate uncertainty. In this report, I in- troduce a new method of estimating the group velocity that includes an estimate of uncertainty. The method is similar to the conventional filter bank method, but uses a class of functions, called Slepian wavelets, to compute a series of wavelet transforms of the data. Each wavelet transform is mathematically similar to a filter bank, however, the time-frequency tradeoff is optimized. By taking multiple wavelet transforms, I form a population of dispersion estimates from which stan- dard statistical methods can be used to estimate uncertainty. I demonstrate the utility of this new method by applying it to synthetic data as well as ambient-noise surface-wave cross-correlelograms recorded by the University of Nevada Seismic Network.

58 GEOSCIENCES↗

Data acquisition and path selection decision making for an autonomous roving vehicle

Problems related to the guidance of an autonomous rover for unmanned planetary exploration were investigated. Topics included in these studies were: simulation on an interactive graphics computer system of the Rapid Estimation Technique for detection of discrete obstacles; incorporation of a simultaneous Bayesian estimate of states and inputs in the Rapid Estimation Scheme; development of methods for estimating actual laser rangefinder errors and their application to date provided by Jet Propulsion Laboratory; and modification of a path selection system simulation computer code for evaluation of a hazard detection system based on laser rangefinder data.

Frederick, D. K.↗

A hybrid technique for spacecraft attitude interpolation with arbitrary attitude data gaps

An algorithm for obtaining sufficiently accurate estimates of a system parameter Y, given a data record of the parameter in which at arbitrary times no direct observations of Y exist, and describing the variance of these estimates, is proposed. The method provides estimates at all requested times, and the variance of the estimates is maintained as close to the variance of directly measured data as the quality of input information will allow. Three classes of information are used: (1) the measured data record of Y and the statistical extension of this record into time intervals of no direct measurement, obtained by a modification of standard autocorrelation techniques; (2) an a priori indicator of the behavior of Y; and (3) one or more indirect indicators of Y based on observation of other system parameters. The application of the algorithm to the SEASAT-A attitude determination under conditions of sensor field-of-view limitations and sun occultations is presented.

Treder, A. J.↗

The methods of paired comparisons and magnitude estimation in judging the noisiness of aircraft

The point of subjective equality in regard to perceived noisiness for each of 14 pairs of aircraft noises was obtained using both magnitude estimation technique and the method of paired comparisons. Both methods gave approximately the same estimates of the points of subjective equality for the noise pairs, and both showed similar correspondence to predictive physical measures. Nevertheless, the two methods appear to have greater face validity to the listeners. However, the magnitude estimation technique appears to be more efficient; for a given level of reliability it requires approximately 50% of the testing time required by the paired comparison method. The functions relating physical intensity to the estimated magnitude of subjective noisiness had slopes ranging from about .61 to .29 for the aircraft noises employed in this study, indicating a required change of about 5 to 10 db for a doubling in subjective magnitude. Some physical units of noise measurement were found to be very predictive (standard errors of estimate as low as 1.9 db) of the subjective judgements of noisiness.

Clarke, F. R.↗

Quantum eigenvalue estimation via time series analysis

We present an efficient method for estimating the eigenvalues of a Hamiltonian H from the expectation values of the evolution operator for various times. For a given quantum state ρ, our method outputs a list of eigenvalue estimates and approximate probabilities. Each probability depends on the support of ρ in those eigenstates of H associated with eigenvalues within an arbitrarily small range. The complexity of our method is polynomial in the inverse of a given precision parameter ε, which is the gap between eigenvalue estimates. Unlike the well-known quantum phase estimation algorithm that uses the quantum Fourier transform, our method does not require large ancillary systems, large sequences of controlled operations, or preserving coherence between experiments, and is therefore more attractive for near-term applications. The output of our method can be used to estimate spectral properties of H and other expectation values efficiently, within additive error proportional to ε.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Locating the Isolator Shock-Train Leading Edge with Limited Pressure Information

Real-time detection and control of the isolator shock-train leading edge (STLE) is important to the performance of high-speed air-breathing engines, such as dual-mode scramjets. Typically, the STLE location is determined using wall static-pressure measurements, but there are often restrictions on the placement and overall number of the pressure transducers, reducing the viability and accuracy of such approaches. To address these issues, we introduce the adaptive pressure profile (APP) method for estimating the STLE location. This method does not require extensive prior characterization of the isolator or engine model. Instead, it uses real-time pressure measurements from a small number of transducers to adaptively learn the isolator pressure profile and subsequently uses this deduced profile to estimate the STLE location in a data-driven manner. The APP method works well in situations with sparse transducer placement. It produces accurate estimates when the STLE location is 1) not bounded by two or more transducers or 2) between two transducers that are several isolator duct heights apart. We demonstrate the efficacy of the APP method using simulations and experimental data from direct-connect isolator models. This validation shows that the APP method is accurate and robust for different flow regimes, transducer configurations, and model geometries.

Gregory J. Hunt↗

Completely monotone regression estimates of software failure rates

A method for estimating the present failure rate of a program is presented. A crude nonparameter estimate of the failure rate function is obtained from past failure times. This estimate is then smoothed by fitting a completely monotonic function, which is the solution of a quadratic programming problem. The value of the smoothed function at present time is used as the estimate of present failure rate. Results of a Monte Carlo study of performance are given.

Miller, D. R.↗

Estimating Electron Content Of The Ionosphere

Method for estimation total electron content of ionosphere. Based on measurements of signals transmitted from global positioning satellites (GPS's). Ionospheric delays obtained by measuring differential arrival times of signals at two different frequencies. Since GPS observations cover certain regions of sky, location of space probe to be calibrated might not overlap GPS field of view. Certain assumptions made about behavior of ionosphere so total electron content estimated in any direction from receiver.

Lanyi, G. E.↗

Estimating Atmospheric Turbulence From Flight Records

Method for estimation of atmospheric turbulence encountered by airplanes utilizes wealth of data captured by multichannel digital flight-data recorders and air-traffic-control radar. Developed as part of continuing effort to understand how airplanes respond to such potentially hazardous phenomena as: clear-air turbulence generated by destabilized wind-shear layers above mountains and thunderstorms, and microbursts (intense downdrafts striking ground), associated with thunderstorms. Reconstructed wind fields used to predict and avoid future hazards.

Wingrove, R. C.↗

A reevaluation of the interrupter technique for airway resistance measurement

An attempt was made to obtain a better insight into the actual transient response of airway opening pressure (Pao) following rapid occlusion. With this knowledge it was hoped to be able to clarify the reason for the overestimations found by other investigators, and possibly to obtain a more accurate method of estimating alveolar pressure just prior to interruption. This would result in an improved method for estimating airway resistance. Use of an extrapolation method was found to provide an improved correlation between resistances determined by the interruptor technique and those found by the plethysmograph in normal subjects.

Jackson, A. C.↗

Incorporating spatial context into statistical classification of multidimensional image data

Compound decision theory is employed to develop a general statistical model for classifying image data using spatial context. The classification algorithm developed from this model exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. A key input to this contextural classifier is a quantitative characterization of this tendency: the context function. Several methods for estimating the context function are explored, and two complementary methods are recommended. The contextural classifier is shown to produce substantial improvements in classification accuracy compared to the accuracy produced by a non-contextural uniform-priors maximum likelihood classifier when these methods of estimating the context function are used. An approximate algorithm, which cuts computational requirements by over one-half, is presented. The search for an optimal implementation is furthered by an exploration of the relative merits of using spectral classes or information classes for classification and/or context function estimation.

Bauer, M. E.↗

Implementation of a Battery Health Monitor and Vertical Lift Aircraft Testbed for the Application of an Electrochemisty-Based State of Charge Estimator

Prediction methods concerning remaining charge in lithium-ion batteries that power unmanned aerial vehicles are of critical concern for the safe fulfillment of mission objectives. In recent years, lithium-ion batteries have been the power source for both fixed wing and vertical lift electric vehicles. The purpose of this document is to describe in detail the implementation of a battery health monitor for estimating the state of charge of a lithium-ion battery and a lithium-ion polymer battery that is used to power a vertical lift aircraft test-bed. It will be demonstrated that an electro-chemistry based state of charge estimator effectively tracks battery discharge characteristics and may be employed as a useful tool in monitoring battery health.

Potteiger, Timothy R.↗

Quantification of uncertainties in thermoelectric properties of materials from a first-principles prediction method: An approach based on Gaussian process regression

We present the electron-phonon averaged via Gaussian process regression (EPA-GPR) method, in which the electron-phonon coupling matrix is represented as a function of two energies and is in turn modeled as a Gaussian process. The EPA-GPR method can be used as an efficient method to estimate thermoelectric properties of materials for fast-screening applications, comparable to the original electron-phonon averaged (EPA) method and the electron-phonon averaged via moving-least-squares (EPA-MLS) method. The EPA-GPR method does not require specification of any open parameter, unlike the other EPA-related methods, since all the hyperparameters in the model can be unambiguously estimated within the type II maximum likelihood (ML-II) approximation. Thus, the EPA-GPR method is a parameter-free estimation method. Additionally, the concept of Gaussian processes in the EPA-GPR method allows us to quantify the uncertainty in estimated properties of thermoelectric materials. One can randomly realize the electron-phonon coupling coefficients from the identified Gaussian process, and those realized samples can be further analyzed in the solution process of the semiclassical Boltzmann transport equation for charge carriers. The results of the semiclassical Boltzmann transport equation provide the statistical properties of the thermoelectric properties of interest. The means, standard deviations, histograms, and confidence intervals of the Seebeck coefficient, the electrical conductivity, and the power factor can be constructed and analyzed. Furthermore the proposed EPA-GPR method is applied to a p-type half-Heusler compound, i.e., HfCoSb, as a case example, the results of which clearly present the advantages of the method.

30 DIRECT ENERGY CONVERSION↗

Quasi-static shape estimation and control of adaptive truss structures

Methods for estimating the deformation of adaptive truss structures are proposed which employ internal displacement sensors to measure changes in the length of selected truss members. Based on the measured data from the instrumented truss member, the total truss deformation pattern can be estimated through direct interpolation. To verify the validity of the methods presented here, numerical simulations are carried out for simple plane trusses, a beam truss, and a tetrahedral truss.

Kuwao, Fumihiro↗

Quantifying adoption rates and energy savings over time for advanced energy-efficient manufacturing technologies

Energy-efficient manufacturing technologies can reduce energy consumption and lower operating costs for manufacturing facilities, but up-front costs and increased process complexity frequently lead to manufacturers being reluctant to adopt such technologies. To avoid overestimating the benefits of advanced energy-efficient manufacturing technologies, it is necessary to account for how quickly and how widely the technology will be adopted by manufacturers. This work develops a method for estimating manufacturing technology adoption rates using quantitative technology characteristics including energetic, economic, and technical criteria that capture both incentives (such as energy and cost savings) and disincentives (such as increased process complexity) for technology adoption. This method is unique in that it can be applied before or after a technology reaches the market; other adoption rate estimation methods require sales data and can only be applied post-market. Eleven technology characteristics are considered, with each characteristic weighted to reflect its impact on the overall technology adoption rate. Technology characteristic data is used to estimate model parameters for the Bass diffusion curve, which quantifies the change in the number of new technology adopters in a population over time. Finally, energy savings at the sector level are calculated over time by multiplying the number of new technology adopters at each time step with the technology’s facility-level energy savings. The proposed method is demonstrated with an application to glass industry manufacturing technologies using technology data obtained from the U.S. Department of Energy's 2017 bandwidth study. The potential energy savings for each technology and the rate at which each technology is adopted in the sector are quantified and used to identify the technologies which offer the greatest cumulative sector-level energy savings over a period of 20 years.

advanced manufacturing↗