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NASA NTRS2013

Estimating the Properties of Hard X-Ray Solar Flares by Constraining Model Parameters

We wish to better constrain the properties of solar flares by exploring how parameterized models of solar flares interact with uncertainty estimation methods. We compare four different methods of calculating uncertainty estimates in fitting parameterized models to Ramaty High Energy Solar Spectroscopic Imager X-ray spectra, considering only statistical sources of error. Three of the four methods are based on estimating the scale-size of the minimum in a hypersurface formed by the weighted sum of the squares of the differences between the model fit and the data as a function of the fit parameters, and are implemented as commonly practiced. The fourth method is also based on the difference between the data and the model, but instead uses Bayesian data analysis and Markov chain Monte Carlo (MCMC) techniques to calculate an uncertainty estimate. Two flare spectra are modeled: one from the Geostationary Operational Environmental Satellite X1.3 class flare of 2005 January 19, and the other from the X4.8 flare of 2002 July 23.We find that the four methods give approximately the same uncertainty estimates for the 2005 January 19 spectral fit parameters, but lead to very different uncertainty estimates for the 2002 July 23 spectral fit. This is because each method implements different analyses of the hypersurface, yielding method-dependent results that can differ greatly depending on the shape of the hypersurface. The hypersurface arising from the 2005 January 19 analysis is consistent with a normal distribution; therefore, the assumptions behind the three non- Bayesian uncertainty estimation methods are satisfied and similar estimates are found. The 2002 July 23 analysis shows that the hypersurface is not consistent with a normal distribution, indicating that the assumptions behind the three non-Bayesian uncertainty estimation methods are not satisfied, leading to differing estimates of the uncertainty. We find that the shape of the hypersurface is crucial in understanding the output from each uncertainty estimation technique, and that a crucial factor determining the shape of hypersurface is the location of the low-energy cutoff relative to energies where the thermal emission dominates. The Bayesian/MCMC approach also allows us to provide detailed information on probable values of the low-energy cutoff, Ec, a crucial parameter in defining the energy content of the flare-accelerated electrons. We show that for the 2002 July 23 flare data, there is a 95% probability that Ec lies below approximately 40 keV, and a 68% probability that it lies in the range 7-36 keV. Further, the low-energy cutoff is more likely to be in the range 25-35 keV than in any other 10 keV wide energy range. The low-energy cutoff for the 2005 January 19 flare is more tightly constrained to 107 +/- 4 keV with 68% probability.

X-rays↗

NASA NTRSDate not supplied

Compression of Solar Spectroscopic Observations: a Case Study of MgII k Spectral Line Profiles Observed by NASA’s IRIS Satellite

In this study we extract the deep features and investigate the compression of the MgII k spectral line profiles observed in quiet Sun regions by NASA’s IRIS satellite. The data set of line profiles used for the analysis was obtained on April 20th, 2020, at the center of the solar disc, and contains almost 300,000 individual MgII k line profiles after data cleaning. The data are separated into train and test subsets. The train subset was used to train the autoencoder of the varying embedding layer size. The early stopping criterion was implemented on the test subset to prevent the model from overfitting. Our results indicate that it is possible to compress the spectral line profiles more than 27 times (which corresponds to the reduction of the data dimensionality from 110 to 4) while having a 4DN average reconstruction error, which is comparable to the variations in the line continuum. The mean squared error and the reconstruction error of even statistical moments sharply decrease when the dimensionality of the embedding layer increases from 1 to 4 and almost stop decreasing for higher numbers. The observed occasional improvements in training for values higher than 4 indicate that a better compact embedding may potentially be obtained if other training strategies and longer training times are used. The features learned for the critical four-dimensional case can be interpreted. In particular, three of these four features mainly control the line width, line asymmetry, and line dip formation respectively. The presented results are the first attempt to obtain a compact embedding for spectroscopic line profiles and confirm the value of this approach, in particular for feature extraction, data compression, and denoising.

SMD↗

NASA NTRS2020

First-Order Runtime Verification using BDDs

Runtime Verification (RV) expedites the analyses of execution traces for detecting system errors and for statistical and quality analysis. Having started modestly, with checking temporal properties that are based on propositional (yes/no) values, the current practice of RV often involves properties that are parametrized by the data observed in the input trace. The specifications are based on various formalisms, such as automata, temporal logics, rule systems, and stream processing. Checking execution traces that are data intensive against a specification that imposes strong dependencies between the data, poses a nontrivial challenges; in particular if runtime verification has to be performed online, while many events that carry data appear within small time proximities. Towards achieving this goal, it was recently suggested to represent relations over the observed data values, based on BDDs, where data elements are enumerated and then converted into bit vectors. This representation provided a very simple and natural extension of an RV algorithm from propositional to first-order LTL, but more importantly, was shown to contribute to the memory compactness and to the speed, as was demonstrated using a corresponding implementation. We extend here the capabilities of BDD-based RV with the ability to express timing constraints, where the monitored events include (integer) clock values. We show how to efficiently operate on BDDs that represent both relations on (enumerations of) values and time dependencies, as required by the addition of the time constraints. We demonstrate our algorithm with an efficient implementation and provide experimental results.

Peled, Doron↗

DOE OSTI2015

Overview of the Fermilab Muon g-2 Experiment

The measurement of the anomalous magnetic moment of muon provides a precision test of the Standard Model. The Brookhaven muon g-2 experiment (E821) measured the muon magnetic moment anomaly with 0.54 ppm precision, a more than 3 deviation from the Standard Model predictions, spurring speculation about the possibility of new physics. The new g-2 experiment at Fermilab (E989) will reduce the combined statistical and systematic error of the BNL experiment by a factor of 4. An overview of the new experiment is described in this article.

Kim, SeungCheon↗

DOE OSTI2015

The Early Physics Program with Eta Decays in JLab¿s Hall D

The eta decay program in Hall D using the GlueX detector will begin with the copious eta --> 3pibranches to better determine the quark mass ratio. Improving on the state of the art requires statistical and systematic errors below 0.1% corresponding to several years of data-taking. A precise new Dalitz distribution for the charged branch will also improve direct constraints on C violating, P conserving interactions. Ultimately, our eta working group intends to upgrade the forward calorimeter to improve the sensitivity for extremely challenging rare, neutral eta decays by 2 orders of magnitude.

Mack, David↗

DOE OSTI2025

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗

DOE OSTI2016

SU-F-J-126: Influence of Six Dimensional Motions in Frameless Stereotactic Dosimetry Incorporating Rotational Shifts as Equivalent Translational Shifts: A Feasibility Study for Elekta-BrainLAB Stereotactic System

Purpose: Six dimensional positional shifts (translational and rotational) determined by a volumetric imaging system were mathematically combined and incorporated as simple translational shifts and the resultant impact on dose characteristics was studied. Methods: Thirty patients who underwent either single fraction (12 Gy) or five fractions (5 Gy per fraction) stereotactic treatments were included in this study. They were immobilized using a double layered thermoplastic mask from BrainLAB. Isocenter matching was done using infrared marker of ExacTrac. An initial cone beam CT (CBCT) gave positional shifts in 6-dimensions that were applied through 6-D motion enabled couch. A verification CBCT was done following corrections before treatment. These 6-D positional shifts determined at each imaging session from the first CBCT were mathematically combined to give three simple translational shifts. Doses were recalculated in the patient matrix with these positional errors present by moving the whole image dataset. Doses were also recalculated after second CBCT with only residual errors present. PTV dose statistics were compared. Results: For the approved plans V100%(PTV), V100%(GTV), D95%(PTV), D95%(GTV), D1%(PTV) and D1%(GTV) were 96.2±3.0%, 98.2±1.4%, 102%±1.7%, 103±1.2%, 107.9±8.9% and 109.3±7.5% of prescription dose respectively. With the positional errors present (after 1st CBCT) the corresponding values were 86.7±4.9%, 91.3±2.9%, 89.6±4.2%, 95.9±3.7%, 108.3±9.9% and 108.6±4.5%. Post-correction (after 2nd CBCT) with only residual errors present, values were 94.5±5.7%, 97.3±2.9%, 99.3%±3.2%, 102%±2.1%, 107.6±8.5% and 109.0±7.6% respectively. Significant and nominal OAR dose variation was observed between pre- and post-table corrections. Conclusion: Positional errors significantly affect PTV dose statistics. They need to be corrected before delivery of stereotactic treatments although the magnitude of dose changes can vary from patient-to-patient depending on the tumor location. As expected after the table corrections, residual errors result in insignificant dose deviations. For frameless stereotactic treatments having a six-dimensional motion enabled couch is highly recommended to reduce quantum of dose deviations.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1989

Photon statistical limitations for daytime optical tracking

Tracking of interplanetary spacecraft equipped with optical communication systems by using astrometric instruments is being investigated by JPL. Existing instruments are designed to work at night and, for bright sources, are limited by tropospheric errors. To provide full coverage of the solar system, astrometric tracking instruments must either be capable of daytime operation or be space-based. The integration times necessary for the ground-based daytime photon statistical errors to reach a given accuracy level (5 to 50 nanoradians) were computed for an ideal astrometric instrument. The required photon statistical integration times are found to be shorter than the tropospheric integrations times for the ideal detector. Since the astrometric need not be limited by photon statistics even under daytime conditions, it may be fruitful to investigate instruments for daytime optical tracking.

Folkner, W. M.↗

NASA NTRS1975

Some statistical analysis techniques for the effect of systematic instrument errors on the results of measurements in a space experiment

Mathematical models of certain systematic telemetry signal errors arising during the passage of the signal through the recording and transmitting blocks of the physical instruments aboard the spacecraft are classified and constructed. Statistical analysis methods are used to determine the background function and relative sensitivity coefficients of the channels of a charged particle detector. Results are presented. A block diagram for a method taking into account the effect of distortions is given.

Kondakov, S. P.↗

DOE OSTI2015

TOMOGRAPHY OF THE FERMI -LAT γ -RAY DIFFUSE EXTRAGALACTIC SIGNAL VIA CROSS CORRELATIONS WITH GALAXY CATALOGS

Building on our previous cross-correlation analysis (Xia et al. 2011) between the isotropic γ-ray background (IGRB) and different tracers of the large-scale structure of the universe, we update our results using 60 months of data from the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope (Fermi). For this study, we perform a cross-correlation analysis both in configuration and spherical harmonics space between the IGRB and objects that may trace the astrophysical sources of the IGRB: QSOs in the Sloan Digital Sky Survey (SDSS) DR6, the SDSS DR8 Main Galaxy Sample, luminous red galaxies (LRGs) in the SDSS catalog, infrared-selected galaxies in the Two Micron All Sky Survey (2MASS), and radio galaxies in the NRAO VLA Sky Survey (NVSS). The benefit of correlating the Fermi-LAT signal with catalogs of objects at various redshifts is to provide tomographic information on the IGRB, which is crucial in separating the various contributions and clarifying its origin. The main result is that, unlike in our previous analysis, we now observe a significant (>3.5σ) cross-correlation signal on angular scales smaller than 1° in the NVSS, 2MASS, and QSO cases and, at lower statistical significance (~3.0σ), with SDSS galaxies. The signal is stronger in two energy bands, E > 0.5 GeV and E > 1 GeV, but it is also seen at E > 10 GeV. No cross-correlation signal is detected between Fermi data and the LRGs. These results are robust against the choice of the statistical estimator, estimate of errors, map cleaning procedure, and instrumental effects. Finally, we test the hypothesis that the IGRB observed by Fermi-LAT originates from the summed contributions of three types of unresolved extragalactic sources: BL Lacertae objects (BL Lacs), flat spectrum radio quasars (FSRQs), and star-forming galaxies (SFGs). Finally, we find that a model in which the IGRB is mainly produced by SFGs ($72_{-37}^{+23}$% with 2σ errors), with BL Lacs and FSRQs giving a minor contribution, provides a good fit to the data. We also consider a possible contribution from misaligned active galactic nuclei, and we find that, depending on the details of the model and its uncertainty, they can also provide a substantial contribution, partly degenerate with the SFG one.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1998

Evaluation of the 29-km Eta Model: Objective Verification at Three Selected Stations - Part 1

This paper describes an objective verification of the National Centers for Environmental Prediction (NCEP) 29-km eta model from May 1996 through January 1998. The evaluation was designed to assess the model's surface and upper-air point forecast accuracy at three selected locations during separate warm (May - August) and cool (October - January) season periods. In order to enhance sample sizes available for statistical calculations, the objective verification includes two consecutive warm and cool season periods. Systematic model deficiencies comprise the larger portion of the total error in most of the surface forecast variables that were evaluated. The error characteristics for both surface and upper-air forecasts vary widely by parameter, season, and station location. At upper levels, a few characteristic biases are identified. Overall however, the upper-level errors are more nonsystematic in nature and could be explained partly by observational measurement uncertainty. With a few exceptions, the upper-air results also indicate that 24-h model error growth is not statistically significant. In February and August 1997, NCEP implemented upgrades to the eta model's physical parameterizations that were designed to change some of the model's error characteristics near the surface. The results shown in this paper indicate that these upgrades led to identifiable and statistically significant changes in forecast accuracy for selected surface parameters. While some of the changes were expected, others were not consistent with the intent of the model updates and further emphasize the need for ongoing sensitivity studies and localized statistical verification efforts. Objective verification of point forecasts is a stringent measure of model performance, but when used alone, is not enough to quantify the overall value that model guidance may add to the forecast process. Therefore, results from a subjective verification of the meso-eta model over the Florida peninsula are discussed in the companion paper by Manobianco and Nutter. Overall verification results presented here and in part two should establish a reasonable benchmark from which model users and developers may pursue the ongoing eta model verification strategies in the future.

Nutter, Paul A.↗

NASA NTRS2010

Error Representation in Time For Compressible Flow Calculations

Time plays an essential role in most real world fluid mechanics problems, e.g. turbulence, combustion, acoustic noise, moving geometries, blast waves, etc. Time dependent calculations now dominate the computational landscape at the various NASA Research Centers but the accuracy of these computations is often not well understood. In this presentation, we investigate error representation (and error control) for time-periodic problems as a prelude to the investigation of feasibility of error control for stationary statistics and space-time averages. o These statistics and averages (e.g. time-averaged lift and drag forces) are often the output quantities sought by engineers. o For systems such as the Navier-Stokes equations, pointwise error estimates deteriorate rapidly which increasing Reynolds number while statistics and averages may remain well behaved.

Barth, Timothy J.↗

DOE OSTI2025

Type Ia Supernova Growth-rate Measurement with LSST Simulations: Intrinsic Scatter Systematics

Measurement of the growth rate of structures (fσ 8 ) with Type Ia supernovae (SNe Ia) will improve our understanding of the nature of dark energy and enable tests of general relativity. In this paper, we generate simulations of the 10 yr SN Ia data set of the Rubin-LSST survey, including a correlated velocity field from an N-body simulation and realistic models of SNe Ia properties and their correlations with host-galaxy properties. We find, similar to SN Ia analyses that constrain the dark energy equation-of-state parameters w 0 w a , that constraints on fσ 8 can be biased depending on the intrinsic scatter of SNe Ia. While for the majority of intrinsic scatter models we recover fσ 8 with a precision of ∼13%–14%, for the most realistic dust-based model, we find that the presence of non-Gaussianities in Hubble diagram residuals leads to a bias on fσ 8 of ∼ −20%. When trying to correct for the dust-based intrinsic scatter, we find that the propagation of the uncertainty on the model parameters does not significantly increase the error on fσ 8 . We also find that while the main component of the error budget of fσ 8 is the statistical uncertainty (>75% of the total error budget), the systematic error budget is dominated by the uncertainty on the damping parameter, σ u , that gives an empirical description of the effect of redshift space distortions on the velocity power spectrum. Our results motivate a search for new methods to correct for the non-Gaussian distribution of the Hubble diagram residuals, as well as an improved modeling of the damping parameter.

Carreres, Bastien [Duke Univ., Durham, NC (United ↗

NASA NTRS1962

Application of Statistical Filter Theory to the Optimal Estimation of Position and Velocity on Board a Circumlunar Vehicle

Concepts from statistical filter theory are applied to the problem of in-flight determination of the position and velocity of a space vehicle for the purposes of midcourse guidance. The source of information is assumed to be an arbitrary sequence of measurements of any desired set of "observables" (e.g., space angles), the measurements being corrupted by additive errors so that the position and velocity are never known perfectly. A state transition approach is employed which leads naturally to a computational scheme that is readily implemented by a digital computer. The scheme can be regarded as a dynamical time-varying filter which weights the incoming observations in an optimal sense for use in producing an up-to-date optimal estimate of position and velocity. The advantages of the scheme are (1) it provides the best possible estimate (minimum error) based upon ensemble statistics of injection conditions and measurement errors; (2) it is extremely versatile, not requiring adherence to a predetermined observation schedule or reference trajectory; and (3) the computations are sufficiently simple to be practical in an on-board computer. A digital computer simulation of the proposed system is employed to demonstrate the feasibility of an all on-board system and to illustrate the performance attainable in a hypothetical physical situation.

SPACE VEHICLE↗

NASA NTRS1974

A Markov model for NASA's Ground Communications Facility

A 'natural' way of constructing finite-state Markov chains (FSMC) is presented for those noise burst channels that can be modeled by them. In particular, a five-state Markov chain is given as a model of errors occurring at the Ground Communications Facility (GCF). A maximum likelihood procedure applicable to any FSMC is developed for estimating all the model parameters starting from the data of error runs. A few of the statistics important for estimating the performance of error control strategies on the channel are provided.

Adeyemi, O.↗

NASA NTRS1987

A technique for evaluating the application of the pin-level stuck-at fault model to VLSI circuits

Accurate fault models are required to conduct the experiments defined in validation methodologies for highly reliable fault-tolerant computers (e.g., computers with a probability of failure of 10 to the -9 for a 10-hour mission). Described is a technique by which a researcher can evaluate the capability of the pin-level stuck-at fault model to simulate true error behavior symptoms in very large scale integrated (VLSI) digital circuits. The technique is based on a statistical comparison of the error behavior resulting from faults applied at the pin-level of and internal to a VLSI circuit. As an example of an application of the technique, the error behavior of a microprocessor simulation subjected to internal stuck-at faults is compared with the error behavior which results from pin-level stuck-at faults. The error behavior is characterized by the time between errors and the duration of errors. Based on this example data, the pin-level stuck-at fault model is found to deliver less than ideal performance. However, with respect to the class of faults which cause a system crash, the pin-level, stuck-at fault model is found to provide a good modeling capability.

Palumbo, Daniel L.↗

DOE OSTI2016

High Accuracy Signal Validation Framework for Sensor Calibration Assessment in NPPs

Effective and efficient health management of sensing channels and instrumentation supports reliable and accurate process monitoring capacities in any industry. Current practice in the nuclear industry relies on periodic calibration assessment and correction activities. This time based maintenance technique consists of three steps: i) removal of sensor to a test environment, ii) testing and recalibration, and iii) reinstallation of sensor into its working environment. This procedure is highly labor intensive, adds to the outage cost and timeline, and contributes to worker radiation exposure and ALARA requirements. Furthermore, the human element contributes to error factors in all stages of the procedure. The effectiveness of this calibration procedure after sensors are returned to working environmental variables also raises concerns, and the practicability of this periodic approach is uncertain for future reactor designs with longer operating cycles between refueling outages. Studies indicate that periodic calibration assessment find only 10% of sensing instrumentations with calibration issues during a single outage (18- 24 months), meaning at least 90% of sensors are undergoing unnecessary maintenance actions. This provides an opportunity to maintain the current levels of safety and functional integrity with fewer, more targeted maintenance actions and lower economic burden. Performance-based maintenance planning shows much promise over current periodic maintenance approaches. Specifically, online monitoring (OLM) utilizes the continually collected process data to non-intrusively monitor the calibration status of process instrumentation and detect the onset of de-calibration, thereby minimizing the number of recalibration procedures required. Ultimately, this can lead to termination of time based recalibration at NPPs. OLM utilizes the process measurements made for process monitoring and control to evaluate the calibration status of the sensors and instrumentation making the measurements. OLM can detect and differentiate sensor faults and process anomalies, thus providing a valuable tool to suit the industry's and regulatory body's requirements. Though supported by more than a decade of research, OLM for sensor calibration assessment is yet to be implemented in the US fleet due to regulatory requirements and constraints. As shown in Figure 1, OLM utilizes process data to train statistical models that predict normal, error-free process behavior. Measured process values are compared with error-corrected predictions to ascertain the presence of faults. The reliability of OLM is dependent on the quality of its predictions, measured in part by the uncertainty in these predictions. This research develops a framework to accurately quantify the prediction uncertainty based on Bayesian inference techniques to provide the required confidence levels for OLM systems. The expected outcomes include signal validation by high-accuracy, high-confidence uncertainty quantification for variable sensor types and operating ranges. Furthermore, the framework will facilitate fault detection capacities and so-called virtual sensors, a capability to replace faulty sensor measurements with error-corrected values when a sensor fault is detected. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Large-eddy simulation of heavy particle dispersion in wall-bounded turbulent flows

Capabilities and accuracy issues in Lagrangian tracking of heavy particles in velocity fields obtained from large-eddy simulations (LES) of wall-bounded turbulent flows are reviewed. In particular, it is shown that, if no subgrid scale (SGS) model is added to the particle motion equations, particle preferential concentration and near-wall accumulation are significantly underestimated. Results obtained with SGS modeling for the particle motion equations based on approximate deconvolution are briefly recalled. Then, the error purely due to filtering in particle tracking in LES flow fields is singled out and analyzed. The statistical properties of filtering errors are characterized in turbulent channel flow both from an Eulerian and a Lagrangian viewpoint. Implications for stochastic SGS modeling in particle motion equations are briefly outlined.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗