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All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Multispacecraft observations of microscale fluctuations in the solar wind

Data from the Explorer 33 and 35 satellites were used to study Alfvenic fluctuations (i.e., fluctuations with a high correlation between perturbation in velocity and magnetic field) in the solar wind. It was found that the average minimum variance method does not give a good estimate of the phase front direction of these fluctuations. There is a distinct class of Alfvenic fluctuations with phase planes nearly parallel to the mean field B sub 0. The characteristic length of the phase fronts of the fluctuations is probably significantly greater than 50 R-E. It is concluded that since tangential discontinuities and possibly other types of static structures appear in Alfvenic fluctuations, these fluctuations are not solely Alfven waves.

Denskat, K. U.↗
NASA NTRS1983

Crop area estimation based on remotely-sensed data with an accurate but costly subsample

Alternatives to sampling-theory stratified and regression estimators of crop production and timber biomass were examined. An alternative estimator which is viewed as especially promising is the errors-in-variable regression estimator. Investigations established the need for caution with this estimator when the ratio of two error variances is not precisely known.

Gunst, R. F.↗
NASA NTRS1984

Wave normal directions of chorus near the equatorial source region

OGO 5 triaxial search coil magnetometer data are used to determine the wave propagation directions of postmidnight chorus in the near-equatorial region at L shells of 6 to 7. The methods used to estimate the wave normal directions involved minimum variance, the imaginary part of the cross-spectral matrix, the eigenvector of the Hermitian cross-spectral matrix, and a fitting of dispersion relations for one-wave and two-wave models to the cross-spectral matrix. Wave propagation at all frequencies within chorus tones is found to occur most frequently along the magnetic field with median and average cone angles of 9.1 deg and 12.2 deg, respectively. It is concluded that for waves propagating parallel to B, wave growth is maximum.

Goldstein, B. E.↗
NASA NTRS1989

Estimation of velocity perturbations in satellite fragmentation events

The magnitude, variance and directionality of the velocity perturbations of the fragments of a satellite can shed valuable information regarding the nature and intensity of the fragmentation. Up until now, the only method used to calculate the three orthogonal components of the velocity change consisted of inverting the process of evaluating the changes in the orbital elements of the fragments due to velocity perturbing forces. But the traditional method failed in five different cases: (1) when the parent satellite's orbit was circular; (2) and (3) when the true anomaly of the parent was either 0 deg or 180 deg; and (4) and (5) when the argument of latitude of the parent was 90 deg or 270 deg. Described here is a new method of calculating the velocity perturbations which is free from the shortcomings of the traditional method and could be used in all occasions, provided the fragmentation data and the orbital elements data are consistent with one another.

Tan, Arjun↗
NASA NTRS2007

Unbalanced and Minimal Point Equivalent Estimation Second-Order Split-Plot Designs

Restricting the randomization of hard-to-change factors in industrial experiments is often performed by employing a split-plot design structure. From an economic perspective, these designs minimize the experimental cost by reducing the number of resets of the hard-to- change factors. In this paper, unbalanced designs are considered for cases where the subplots are relatively expensive and the experimental apparatus accommodates an unequal number of runs per whole-plot. We provide construction methods for unbalanced second-order split- plot designs that possess the equivalence estimation optimality property, providing best linear unbiased estimates of the parameters; independent of the variance components. Unbalanced versions of the central composite and Box-Behnken designs are developed. For cases where the subplot cost approaches the whole-plot cost, minimal point designs are proposed and illustrated with a split-plot Notz design.

Parker, Peter A.↗
NASA NTRS2019

Star Tracker Accuracy Improvement and Optimization for Attitude Measurement in Three-Axis

High precision attitude measurement systems obviate the need for the beacon from the receiver making it possible for the spacecraft to beam a laser communications signal to a ground station without the ground station advertising its location. The research presented targets new detection and estimation methods to improve the accuracy in locating stars on a focal plane detector, and an understanding of the effects of changes in the optics design parameters and aberration, including defocus, on the navigation solution itself. This understanding can lead to an optimization of the attitude solution with respect to those optics realm parameter changes. The methodology discussed includes the development of a model of a current star tracker system. Using this model, multiple algorithms are implemented, including a multi-hypothesis method (MHT), to detect and estimate the position of the stars on the focal plane detector. It will be shown that using the MHT for detection and estimation, a greater accuracy can be found for each star estimation from more traditional detection and estimation algorithms. The approach then uses the model to develop statistics of the star tracker and the attitude estimation outputs to understand the accuracy, or variance, of the system's attitude solution. This solution is repeated for a range of defocus aberration, and a lower limit to the variance of the attitude solution is shown. A Cramer Rao lower bound solution is derived for the star tracker system and the results are compared to the Monte Carlo analysis from the model and shown to correlate very well. The approach uses a star image not as a Gaussian spot on the focal plane as done in previous work, and use of an image that includes the effects of aberrations of the optic system, and the effects of under-sampling and noise from the focal plane detector as well. Analysis includes exploring a star tracker's accuracy improvement through the combination of focus error and under-sampling effects alone, possibly contradicting conventional wisdom and approaches.

Lichter, Michael J.↗
DOE OSTI2017

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report April 1-June 30, 2017

Individual datastreams from instrumentation at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research observatories (sites) are collected and routed to the ARM Data Center (ADC). The Data Management Facility (DMF), a component of the ADC, executes datastream processing in near-real time. Processed data are then delivered approximately daily to the ARM Data Archive, also a component of the ADC, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. DOE requires national user facilities to report time-based operating data. The requirements involve: Actual hours of operation (ACTUAL)—24 hours per day, 91 days or 2184 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1–[ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

Aerosol↗
DOE OSTI2017

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report January 1-March 31, 2017

Individual datastreams from instrumentation at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research observatories (sites) are collected and routed to the ARM Data Center (ADC). The Data Management Facility (DMF), a component of the ADC, executes datastream processing in near-real time. Processed data are then delivered approximately daily to the ARM Data Archive, also a component of the ADC, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. DOE requires national user facilities to report time-based operating data. The requirements involve: Actual hours of operation (ACTUAL)—24 hours per day, 90 days or 2160 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1–[ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

Eastern North Atlantic, Southern Great Plains, Nor↗
DOE OSTI2017

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report July 1-September 30, 2016

Individual datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research sites are collected and routed to the Data Management Facility (DMF) for processing in near-real time. Instrument and processed data are then delivered approximately daily to the ARM Data Archive, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. The results are tabulated by 1) individual datastream, site, and month for the current year, and 2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements involve the: Actual hours of operation (ACTUAL) – 24 hours per day, 92 days or 2208 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1 – [ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

Southern Great Plains, North Slope of Alaska, East↗
DOE OSTI2016

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report April 1-June 30, 2016

Individual datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research sites are collected and routed to the Data Management Facility (DMF) for processing in near-real time. Instrument and processed data are then delivered approximately daily to the ARM Data Archive, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. The results are tabulated by 1) individual datastream, site, and month for the current year, and 2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements involve the: Actual hours of operation (ACTUAL) – 24 hours per day, 91 days or 2184 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1 – [ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

North Slope of Alaska, Eastern North Atlantic, Sou↗
DOE OSTI2017

Exploring the Use of Muon Momentum for Detection of Nuclear Material Within Shielded Spent Nuclear Fuel Dry Casks

The inspection of the storage containers that house used nuclear fuel is an important issue facing the nuclear industry; currently, there are limited options available to provide for even minimal inspections. During the long storage life of the fuel, intermediate handling and transportation activities may take place that can create concerns regarding fuel integrity (safety) and continuity of knowledge (safeguards and security). Accidents and natural disasters also contribute to this concern. The reliable and safe management of used nuclear fuel is among the critical tasks to be addressed for the advancement of fission-based nuclear energy in the United States and elsewhere. Since the early 1950's, when the first nuclear power plant began to produce electricity, approximately 65,000 metric tons of used nuclear fuel have been generated in the United States. The postponement of the opening of a permanent repository until 2048 will lead to increased used fuel accumulation at reactor sites. A rapid increase in storage installations with more than 9,000 casks storing {approx}420,000 assemblies is anticipated by 2050 even if no new nuclear power plants are built. After used nuclear fuel has been placed inside a cask, the cask is sealed, not allowing for visual inspection. Conventional methods, e.g., x-rays, are limited in that they cannot penetrate dense, well-shielded objects. More sophisticated techniques, such as penetrating neutrons or proton radiography, require the use of an expensive accelerator. Efforts by Ziock et al. using neutron and gamma-ray imagers concluded that '...the signatures are deemed insufficient to uniquely identify individual casks of the same type...'. It was found that the gamma-ray and neutron images were dominated by diffusion and thermalization effects resulting from the large amount of shielding. One promising mode of inspection would use cosmic-ray muons. These muons are naturally generated, are able to penetrate dense materials, and are incident from all directions above the horizon. Tomography performed using these muons could potentially provide efficient, inexpensive, remote assessment of used nuclear fuel. However, current muon applications are limited in that they have not included momentum measurement. If momentum measurement could be incorporated, that would represent a big step forward because it would allow more accurate estimation of the muon observables, e.g., scattering variance. This approach has the potential to reconstruct the contents of a cask with improved resolution and identify partial defects, fuel assemblies, and individual fuel rods.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Measurements of the E-mode polarization and temperature-E-mode correlation of the CMB from SPT-3G 2018 data

We present measurements of the E -mode ( E E ) polarization power spectrum and temperature- E -mode ( T E ) cross-power spectrum of the cosmic microwave background using data collected by SPT-3G, the latest instrument installed on the South Pole Telescope. This analysis uses observations of a 1500 deg 2 region at 95, 150, and 220 GHz taken over a four-month period in 2018. We report binned values of the E E and T E power spectra over the angular multipole range 300 ≤ ℓ < 3000 , using the multifrequency data to construct six semi-independent estimates of each power spectrum and their minimum-variance combination. These measurements improve upon the previous results of SPTpol across the multipole ranges 300 ≤ ℓ ≤ 1400 for E E and 300 ≤ ℓ ≤ 1700 for T E , resulting in constraints on cosmological parameters comparable to those from other current leading ground-based experiments. We find that the SPT-3G data set is well fit by a Λ CDM cosmological model with parameter constraints consistent with those from Planck and SPTpol data. From SPT-3G data alone, we find H 0 = 68.8 ± 1.5 km s - 1 Mpc - 1 and σ 8 = 0.789 ± 0.016 , with a gravitational lensing amplitude consistent with the Λ CDM prediction ( A L = 0.98 ± 0.12 ). We combine the SPT-3G and the Planck data sets and obtain joint constraints on the Λ CDM model. The volume of the 68% confidence region in six-dimensional Λ CDM parameter space is reduced by a factor of 1.5 compared to Planck-only constraints, with no significant shifts in central values. We note that the results presented here are obtained from data collected during just half of a typical observing season with only part of the focal plane operable, and that the active detector count has since nearly doubled for observations made with SPT-3G after 2018.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Unbiased Ratio Estimator for k-Eigenvalue in Monte Carlo Criticality Calculations

In criticality calculations, the effective multiplication factor (k{sub eff}) is an important parameter for reactor analysis. It can be interpreted as the ratio of the neutron production rate to the loss rate in a reactor core. In Monte Carlo (MC) criticality calculations, k{sub eff} is obtained for each active cycle i as: k-i = P{sub i}/L{sub i} for I = 1 to I where P{sub i} and L{sub i} are the production rate and the loss rate at cycle i, respectively, and they are normalized by the nominal source size for cycle. Since all neutron particles in a cycle will be absorbed or leaks out at the end, the loss rate, L{sub i}, can be set as the source rate, which is the unity. Thus, in MCNP5, k{sub i} is simply calculated with P{sub i} by using three conventional estimators; collision, absorption, and track-length estimators. In domain decomposed MC criticality calculations based on the fission and surface source (FSS) iteration method, k{sub i} is calculated by a ratio of P{sub i} and L{sub i}, where both P{sub i} and L{sub i} are random variables, sampled by using the same particle histories. When the numerator and the denominator are correlated, the variance of the ratio can be smaller than that of the numerator. Then, the final estimate of k{sub eff} is provided as the sample mean of k{sub i}, which will be referred as 'simple' ratio estimator in this paper. In Ref., it is shown that this ratio estimator converges faster and fluctuates less than the conventional estimator. A similar ratio estimator is also used in Serpent 2, as an implicit estimate of k{sub eff}. However, this type of 'simple' ratio estimator is biased, which means that the expectation of the ratio is different from the ratio of the expectation of the numerator and that of the denominator. In this paper, an unbiased ratio estimator which was originally derived in the cytometry analysis is introduced to estimate k{sub eff} and is tested on a continuous-energy UO{sub 2} pin-cell problem. In this test problem, it is shown that the variance of the unbiased ratio estimator is smaller than those of the conventional estimators provided by MCNP5, while the simple ratio estimator can be significantly biased when the number of histories per cycle is too small. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2014

Use of an OSSE to Evaluate Background Error Covariances Estimated by the 'NMC Method'

The NMC method has proven utility for prescribing approximate background-error covariances required by variational data assimilation systems. Here, untunedNMCmethod estimates are compared with explicitly determined error covariances produced within an OSSE context by exploiting availability of the true simulated states. Such a comparison provides insights into what kind of rescaling is required to render the NMC method estimates usable. It is shown that rescaling of variances and directional correlation lengths depends greatly on both pressure and latitude. In particular, some scaling coefficients appropriate in the Tropics are the reciprocal of those in the Extratropics. Also, the degree of dynamic balance is grossly overestimated by the NMC method. These results agree with previous examinations of the NMC method which used ensembles as an alternative for estimating background-error statistics.

Data Assimilation↗
NASA NTRS1971

Design of optimal probing signals for vector parameter estimation.

In the design of optimal inputs or probing signals for parameter estimation, it is more natural to consider functions of the Fisher information matrix as the criterion of optimality instead of some function of the error covariance matrix. The input which maximizes the Fisher information measure for efficient estimation of a scalar parameter also provides the minimum error variance. The information is thus a logical choice for the optimality criterion in scalar problems. No such obvious choice is apparent for vector parameter estimation. A number of performance measures are examined and compared in the present study, and a useful criterion is selected. The design of an optimal probing signal using this criterion is shown to be equivalent to an optimal control problem in which certain equality constraints must be satisfied. This problem may be solved by conventional techniques of deterministic or stochastic optimal control.

Nahi, N. E.↗
DOE OSTI2021

Proof that Combining the Forced-collision and DXTRAN Monte Carlo Variance-reduction Techniques is Fair

This report provides mathematical proof that the MCNP DXTRAN (also known in other codes as forced-flight) and forced-collision variance-reduction techniques do not bias the expected value of Monte Carlo simulation estimates when combined. Proof is also provided that the techniques are unbiased when used independently. To prove that the techniques are unbiased, this report derives the first History Score Moment Equation (HSME) for non-multiplying media employing only forced collisions, only DXTRAN, and then both the variance-reduction techniques combined, as defined next. The HSMEs are found by forming the History Score Probability Density Functions (HSPDFs) and then taking the first score moment. Following its derivation, each HSME with a variance-reduction technique employed is reduced to the HSME for an analog simulation. Because the HSME represents the expected contribution to estimators in the simulation, reducing the HSME with variance reduction to the analog HSME shows that the simulation is unbiased despite the variance-reduction technique considered in the HSME. Analysis regarding higher-score moments of each technique is the subject of prior work and is not addressed herein. Throughout this work, the phase space p is defined to be the particle position x, direction-of-flight unit vector $\hat{Ω}$, energy E, and statistical weight w, $$p ≡ (x; \hat{Ω}; E; w).$$ A reduced phase-space excluding the statistical weight of the particle, $$r ≡ (x; \hat{Ω}; E),$$ is also used.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Uncertainty Error Modeling for Non-Linear State Estimation With Unsynchronized SCADA and µPMU Measurements

Distribution systems of the future smart grid require enhancements to the reliability of distribution system state estimation (DSSE) in the face of low measurement redundancy, unsynchronized measurements, and dynamic load profiles. Micro phasor measurement units (µPMUs) facilitate co-synchronized measurements with high granularity, albeit at an often prohibitively expensive installation cost. Supervisory control and data acquisition (SCADA) measurements can supplement µPMU data, although they are received at a slower sampling rate. Further complicating matters is the uncertainty associated with load dynamics and unsynchronized measurements–not only are the SCADA and µPMU measurements not synchronized with each other, but the SCADA measurements themselves are received at different time intervals with respect to one another. This paper proposes a non-linear state estimation framework which models dynamic load uncertainty error by updating the variances of the unsynchronized measurements, leading to a time-varying system of weights in the weighted least squares state estimator. Case studies are performed on the 33-Bus Distribution System in MATPOWER, using Ornstein–Uhlenbeck stochastic processes to simulate dynamic load conditions.

Cooper, Austin↗
DOE OSTI2018

A Minimum Variance Algorithm for Overdetermined TOA Equations with an Altitude Constraint.

We present a direct (non-iterative) method for solving for the location of a radio frequency (RF) emitter, or an RF navigation receiver, using four or more time of arrival (TOA) measurements and an assumed altitude above an ellipsoidal earth. Both the emitter tracking problem and the navigation application are governed by the same equations, but with slightly different interpreta- tions of several variables. We treat the assumed altitude as a soft constraint, with a specified noise level, just as the TOA measurements are handled, with their respective noise levels. With 4 or more TOA measurements and the assumed altitude, the problem is overdetermined and is solved in the weighted least squares sense for the 4 unknowns, the 3-dimensional position and time. We call the new technique the TAQMV (TOA Altitude Quartic Minimum Variance) algorithm, and it achieves the minimum possible error variance for given levels of TOA and altitude estimate noise. The method algebraically produces four solutions, the least-squares solution, and potentially three other low residual solutions, if they exist. In the lightly overdermined cases where multiple local minima in the residual error surface are more likely to occur, this algebraic approach can produce all of the minima even when an iterative approach fails to converge. Algorithm performance in terms of solution error variance and divergence rate for bas eline (iterative) and proposed approach are given in tables.

97 MATHEMATICS AND COMPUTING↗