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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Machine Learning-Based Energy Estimation for Sterile Neutrino Searches in the NOνA Experiment

This dissertation presents a search for sterile neutrinos using Monte Carlo datasets and experimental data from the NOνA experiment. This work introduces novel machine learning techniques for energy reconstruction in neutral current events. A deep learning-based energy estimator was developed and integrated into the analysis framework. Using this new energy estimator, the sensitivity to sterile neutrino-induced oscillations is evaluated and presented. Furthermore, the dissertation explores potential methods for further improvement of the analysis.

43 PARTICLE ACCELERATORS↗
NASA NTRS2017

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

manual control↗
NASA NTRS2019

Prior biosphere model impact on global terrestrial CO2 fluxes estimated from OCO-2 retrievals

This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC/yr). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

Sajeev Philip↗
NASA NTRS1985

An Algorithm for Efficient Maximum Likelihood Estimation and Confidence Interval Determination in Nonlinear Estimation Problems

An algorithm for maximum likelihood (ML) estimation is developed with an efficient method for approximating the sensitivities. The algorithm was developed for airplane parameter estimation problems but is well suited for most nonlinear, multivariable, dynamic systems. The ML algorithm relies on a new optimization method referred to as a modified Newton-Raphson with estimated sensitivities (MNRES). MNRES determines sensitivities by using slope information from local surface approximations of each output variable in parameter space. The fitted surface allows sensitivity information to be updated at each iteration with a significant reduction in computational effort. MNRES determines the sensitivities with less computational effort than using either a finite-difference method or integrating the analytically determined sensitivity equations. MNRES eliminates the need to derive sensitivity equations for each new model, thus eliminating algorithm reformulation with each new model and providing flexibility to use model equations in any format that is convenient. A random search technique for determining the confidence limits of ML parameter estimates is applied to nonlinear estimation problems for airplanes. The confidence intervals obtained by the search are compared with Cramer-Rao (CR) bounds at the same confidence level. It is observed that the degree of nonlinearity in the estimation problem is an important factor in the relationship between CR bounds and the error bounds determined by the search technique. The CR bounds were found to be close to the bounds determined by the search when the degree of nonlinearity was small. Beale's measure of nonlinearity is developed in this study for airplane identification problems; it is used to empirically correct confidence levels for the parameter confidence limits. The primary utility of the measure, however, was found to be in predicting the degree of agreement between Cramer-Rao bounds and search estimates.

Murphy, Patrick Charles↗
NASA NTRS1984

Estimation of parameters in linear structural relationships: Sensitivity to the choice of the ratio of error variances

Maximum likelihood estimation of parameters in linear structural relationships under normality assumptions requires knowledge of one or more of the model parameters if no replication is available. The most common assumption added to the model definition is that the ratio of the error variances of the response and predictor variates is known. The use of asymptotic formulae for variances and mean squared errors as a function of sample size and the assumed value for the error variance ratio is investigated.

Lakshminarayanan, M. Y.↗
NASA NTRS1984

Estimation of parameters in linear structural relationships Sensitivity to the choice of the ratio of error variances

Maximum likelihood estimation of parameters in linear structural relationships under normality assumptions requires knowledge of one or more of the model parameters if no replication is available. The most common assumption added to the model definition is that the ratio of the error variances of the response and predictor variates is known. This paper investigates the use of asymptotic formulae for variances and mean squared errors as a function of sample size and the assumed value for the error variance ratio.

Lakshminarayanan, M. Y.↗
NASA NTRS1997

Adaptation of a Fast Optimal Interpolation Algorithm to the Mapping of Oceangraphic Data

A fast, recently developed, multiscale optimal interpolation algorithm has been adapted to the mapping of hydrographic and other oceanographic data. This algorithm produces solution and error estimates which are consistent with those obtained from exact least squares methods, but at a small fraction of the computational cost. Problems whose solution would be completely impractical using exact least squares, that is, problems with tens or hundreds of thousands of measurements and estimation grid points, can easily be solved on a small workstation using the multiscale algorithm. In contrast to methods previously proposed for solving large least squares problems, our approach provides estimation error statistics while permitting long-range correlations, using all measurements, and permitting arbitrary measurement locations. The multiscale algorithm itself, published elsewhere, is not the focus of this paper. However, the algorithm requires statistical models having a very particular multiscale structure; it is the development of a class of multiscale statistical models, appropriate for oceanographic mapping problems, with which we concern ourselves in this paper. The approach is illustrated by mapping temperature in the northeastern Pacific. The number of hydrographic stations is kept deliberately small to show that multiscale and exact least squares results are comparable. A portion of the data were not used in the analysis; these data serve to test the multiscale estimates. A major advantage of the present approach is the ability to repeat the estimation procedure a large number of times for sensitivity studies, parameter estimation, and model testing. We have made available by anonymous Ftp a set of MATLAB-callable routines which implement the multiscale algorithm and the statistical models developed in this paper.

Menemenlis, Dimitris↗
NASA NTRS1977

Emission measures, electron densities, and nonthermal velocities from optically thin UV lines near a quiet solar limb

Calibrated intensities and line widths are presented for 45 optically thin chromospheric and transition-zone UV lines observed in a quiet area near the solar limb. The observations were made over the wavelength range from 1175 to 1915 A with the slit spectrograph on the Skylab Apollo Telescope Mount. Three nonthermal-velocity components are derived from the transition-zone line widths: a main component of 23 km/s and two high-velocity components of 45 and 75 km/s, respectively, which contribute 5% to 10% of the averaged intensity. Absolute intensities are determined as a function of height, emission measures are obtained as functions of height as well as temperature, and electron densities are estimated from density-sensitive line ratios. The densities estimated from different sets of lines are found not to agree with each other, but the values obtained from the Si III multiplet between 1297 and 1301 A are considered to be the most reliable. An atmospheric model with inhomogeneous structures extending high above the solar surface is suggested.

Moe, O. K.↗
NASA NTRS2010

Why Hasn't Earth Warmed as Much as Expected?

The observed increase in global mean surface temperature (GMST) over the industrial era is less than 40% of that expected from observed increases in long-lived greenhouse gases together with the best-estimate equilibrium climate sensitivity given by the 2007 Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Possible reasons for this warming discrepancy are systematically examined here. The warming discrepancy is found to be due mainly to some combination of two factors: the IPCC best estimate of climate sensitivity being too high and/or the greenhouse gas forcing being partially offset by forcing by increased concentrations of atmospheric aerosols; the increase in global heat content due to thermal disequilibrium accounts for less than 25% of the discrepancy, and cooling by natural temperature variation can account for only about 15 %. Current uncertainty in climate sensitivity is shown to preclude determining the amount of future fossil fuel CO2 emissions that would be compatible with any chosen maximum allowable increase in GMST; even the sign of such allowable future emissions is unconstrained. Resolving this situation, by empirical determination of the earth's climate sensitivity from the historical record over the industrial period or through use of climate models whose accuracy is evaluated by their performance over this period, is shown to require substantial reduction in the uncertainty of aerosol forcing over this period.

Schwartz, Stephen E.↗
NASA NTRS1997

A Statistical Simulation Approach to Safe Life Fatigue Analysis of Redundant Metallic Components

This paper introduces a dual active load path fail-safe fatigue design concept analyzed by Monte Carlo simulation. The concept utilizes the inherent fatigue life differences between selected pairs of components for an active dual path system, enhanced by a stress level bias in one component. The design is applied to a baseline design; a safe life fatigue problem studied in an American Helicopter Society (AHS) round robin. The dual active path design is compared with a two-element standby fail-safe system and the baseline design for life at specified reliability levels and weight. The sensitivity of life estimates for both the baseline and fail-safe designs was examined by considering normal and Weibull distribution laws and coefficient of variation levels. Results showed that the biased dual path system lifetimes, for both the first element failure and residual life, were much greater than for standby systems. The sensitivity of the residual life-weight relationship was not excessive at reliability levels up to R = 0.9999 and the weight penalty was small. The sensitivity of life estimates increases dramatically at higher reliability levels.

Matthews, William T.↗
NASA NTRS1991

Temperature sensitivity of differential absorption lidar measurements of water vapor in the 720-nm region

Recently measured properties of water vapor (H2O) absorption lines have been used in calculations to evalute the temperature sensitivity of differential absorption lidar (Dial) H2O measurements. This paper estimates the temperature sensitivity of H2O lines in the 717-733-nm region for both H2O mixing ratio and number density measurements, and discusses the influence of the H2O line ground state energies E-double-prime, the H2O absorption linewidths, the linewidth temperature dependence parameter, and the atmospheric temperature and pressure variations with altitude and location on the temperature sensitivity calculations. Line parameters and temperature sensitivity calculations for 67 H2O lines in the 720-nm band are given which can be directly used in field experiments. Water vapor lines with E-double-prime values in the 100-300/cm range were found to be optimum for Dial measurements of H2O number densities, while E-double-prime values in the 250-500/cm range were found to be optimum for H2O mixing ratio measurements.

Browell, Edward V.↗
NASA NTRS1983

Simulation fidelity and numerosity effects in CDTI experimentation

Twenty pilot workload assessment techniques were compared using a simulated flying task in which three levels of psychomotor workload were imposed. The experiment was conducted in a three degree of freedom motion base simulator. Opinion measures, spare mental capacity measures, physiological measures, eye movement behavior and primary task performance measures were evaluated. The primary task was an instrument landing system (ILS) approach and landing. All measures were recorded between the outer and middle markers on the approach. Three levels of psychomotor load were obtained by the combined manipulation of wind gust disturbance level and simulated aircraft pitch stability. Six instrument rated general aviation pilots participated in the experiment. Cooper-Harper ratings, WCI/TE ratings, time estimation standard deviation, pulse rate mean, and control movements per unit time demonstrated sensitivity to psychomotor load. No intrusion into primary task performance was found that the sensitivities of workload estimation techniques vary widely, and that only a few techniques appear to be sensitive to psychomotor load.

Kreifeldt, J. G.↗
NASA NTRS2000

Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by the light and heavy rain rates. This is useful in estimating the fraction of rainfall contributed by the rain rates that go undetected by the radar. The results at high rain rates provide a cross-check on the usual attenuation correction methods that are applied at the highest resolution of the instrument.

Meneghini, R.↗
NASA NTRS1989

A study on cloud-radiation interaction

Most empirical studies estimating the climate sensitivity due to cloud amount are based on calculating a cloud sensitivity parameter by means of satellite measurements. A different way to estimate the interaction between clouds and radiation is to determine the effect of radiative heating and cooling by clouds on the generation of available potential energy (GAPE). This provides a measure of the influence of clouds on the general circulation. The radiative contribution of clouds to the GAPE is given by the net cloud generated radiative heating (CGRH) and an efficiency factor. The CGRH, parameterized in terms of cloud type, height, and optical depth, can be estimated from satellite measurements. The efficiency factor is only a function of the temperature distribution of the atmosphere. Thus, taking satellite measurements as for instance those of the ISCCP, the radiative impact of clouds on the general circulation can be inferred.

Stuhlmann, R.↗
NASA NTRS2001

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

Aires, Filipe↗
NASA NTRS1986

A methodology for airplane parameter estimation and confidence interval determination in nonlinear estimation problems

An algorithm for maximum likelihood (ML) estimation is developed with an efficient method for approximating the sensitivities. The ML algorithm relies on a new optimization method referred to as a modified Newton-Raphson with estimated sensitivities (MNRES). MNRES determines sensitivities by using slope information from local surface approximations of each output variable in parameter space. With the fitted surface, sensitivity information can be updated at each iteration with less computational effort than that required by either a finite-difference method or integration of the analytically determined sensitivity equations. MNRES eliminates the need to derive sensitivity equations for each new model, and thus provides flexibility to use model equations in any convenient format. A random search technique for determining the confidence limits of ML parameter estimates is applied to nonlinear estimation problems for airplanes. The confidence intervals obtained by the search are compared with Cramer-Rao (CR) bounds at the same confidence level. The degree of nonlinearity in the estimation problem is an important factor in the relationship between CR bounds and the error bounds determined by the search technique. Beale's measure of nonlinearity is developed in this study for airplane identification problems; it is used to empirically correct confidence levels and to predict the degree of agreement between CR bounds and search estimates.

Murphy, P. C.↗
NASA NTRS2008

Laser Sounder for Measuring Atmospheric CO2 Concentrations: Progress Toward Ascends

The next generation of space-based, active remote sensing instruments for measurement of tropospheric CO2 promises a capability to quantify global carbon sources and sinks at regional scales. Active (laser) methods will extend CO2 measurement coverage in time, space, and perhaps precision such that the underlying mechanisms for carbon exchange at the surface can be understood with .sufficient detail to confidently project the future of carbon-climate interaction and the influence of remediative policy actions. The recent Decadal Survey for Earth Science by the US National Research Council has recommended such a mission called the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) for launch in 2013-2016. We have been developing a laser technique for measurement of tropospheric CO2 for a number of years. Our immediate goal is to develop and demonstrate the method and instrument technology that will permit measurements of the CO2 column abundance over a horizontal path and from aircraft at the few-ppmv level. Our longer-term goal is to demonstrate the required capabilities of the technique, develop a space mission approach, and design the instrument for an ASCENDS-type mission. Our approach is to use a dual channel laser absorption spectrometer (i.e., differential absorption in altimeter mode), which continuously measures from a near-polar circular orbit. We use several co-aligned tunable fiber laser transmitters allowing simultaneous measurement of the absorption from a CO2 line in the 1570 nm band, O2 extinction in the oxygen A-band (near 765 nm), and aerosol backscatter in the same measurement path. We measure the energy of the laser echoes at nadir reflected from land and water surfaces, day and night. The lasers have spectral widths much narrower than the gas absorption lines and are turned on and off the selected CO2 and O2 lines at kHz rates. The gas extinction and column densities for the CO2 and O2 gases are estimated from the ratio of the on and off-line singnals via the DIAL technique. We used pulsed laser signals, photon counting detectors, and time gating to isolate the laser returns from the surface, and to reject photons scattered from thin clouds and aerosols. High signal-to-noise ratios are required and the CO2 estimates can be sensitive to small drifts or other errors in the instrument, so the absorption estimates need to be quite stable for hours. We have constructed a breadboard version of the CO2 sensor that uses a low power fiber laser and a 20 cm diameter telescope. We have used it to make measurements of CO2 absorption in the laboratory and over 200-m to 2-km long open horizontal paths. These have been done in several sessions extending over multiple days, which allows us to assess the measurement stability and to compare absorption variations to readings from an external in situ CO2 sensor. We have also calculated characteristics of the technique for space including its expected measurement performance for different modulation types, and have performed an initial space mission accommodation study. We sill describe these results in the presentation.

Abshire, J. B.↗