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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Hierarchical Linear Regression (Rev. 1)

We describe an algorithm for making inferences in a hierarchical linear model. The model allows different slopes and intercepts for different groups, and ties together the different slopes by representing them as samples from a higher level distribution. (The intercepts are treated as statistically independent.) Our model and code permit many options for the variance of this hierarchical distribution for the slopes, including gamma distributions on the precision, t-distributions on the standard error, pooled slopes (all equal), and independent slopes. The algorithm is described in the paper; an implementation of the algorithm in R is available on request.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

A Diamond Micro-strip Electron Detector for Compton Polarimetry

The Qweak experiment in Hall C at Jefferson Lab aims to measure the weak charge of the proton with a precision of 4.1{\%} by measuring the parity violating asymmetry in polarized electron-proton elastic scattering. Beam polarimetry is the largest experimental contribution to the error budget. A new Compton polarimeter was installed for a non-invasive and continuous monitoring of the electron beam polarization with a goal of 1{\%} systematic and 1{\%} per hour statistical precision. The Compton-scattered electrons are detected in four planes of diamond micro-strip detectors. These detectors are read out using custom built electronic modules that include a pre-amplifier, a pulse shaping amplifier and a discriminator for each detector micro-strip. We use Field Programmable Gate Array based general purpose logic modules for event selection and histogramming. The polarimeter was commissioned during the first run period of the Qweak experiment. We will show the preliminary results from the electron detector obtained during the first run period of Qweak experiment.

Narayan, Amrendra↗
DOE OSTI2015

Inter- and Intrafraction Target Motion in Highly Focused Single Vocal Cord Irradiation of T1a Larynx Cancer Patients

Purpose: The purpose of this study was to verify clinical target volume–planning target volume (CTV-PTV) margins in single vocal cord irradiation (SVCI) of T1a larynx tumors and characterize inter- and intrafraction target motion. Methods and Materials: For 42 patients, a single vocal cord was irradiated using intensity modulated radiation therapy at a total dose of 58.1 Gy (16 fractions × 3.63 Gy). A daily cone beam computed tomography (CBCT) scan was performed to online correct the setup of the thyroid cartilage after patient positioning with in-room lasers (interfraction motion correction). To monitor intrafraction motion, CBCT scans were also acquired just after patient repositioning and after dose delivery. A mixed online-offline setup correction protocol (“O2 protocol”) was designed to compensate for both inter- and intrafraction motion. Results: Observed interfraction, systematic (Σ), and random (σ) setup errors in left-right (LR), craniocaudal (CC), and anteroposterior (AP) directions were 0.9, 2.0, and 1.1 mm and 1.0, 1.6, and 1.0 mm, respectively. After correction of these errors, the following intrafraction movements derived from the CBCT acquired after dose delivery were: Σ = 0.4, 1.3, and 0.7 mm, and σ = 0.8, 1.4, and 0.8 mm. More than half of the patients showed a systematic non-zero intrafraction shift in target position, (ie, the mean intrafraction displacement over the treatment fractions was statistically significantly different from zero; P<.05). With the applied CTV-PTV margins (for most patients 3, 5, and 3 mm in LR, CC, and AP directions, respectively), the minimum CTV dose, estimated from the target displacements observed in the last CBCT, was at least 94% of the prescribed dose for all patients and more than 98% for most patients (37 of 42). The proposed O2 protocol could effectively reduce the systematic intrafraction errors observed after dose delivery to almost zero (Σ = 0.1, 0.2, 0.2 mm). Conclusions: With adequate image guidance and CTV-PTV margins in LR, CC, and AP directions of 3, 5, and 3 mm, respectively, excellent target coverage in SVCI could be ensured.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-C-BRD-03: Analysis of Accelerator Generated Text Logs for Preemptive Maintenance

Purpose: To develop a model to analyze medical accelerator generated parameter and performance data that will provide an early warning of performance degradation and impending component failure. Methods: A robust 6 MV VMAT quality assurance treatment delivery was used to test the constancy of accelerator performance. The generated text log files were decoded and analyzed using statistical process control (SPC) methodology. The text file data is a single snapshot of energy specific and overall systems parameters. A total of 36 system parameters were monitored which include RF generation, electron gun control, energy control, beam uniformity control, DC voltage generation, and cooling systems. The parameters were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and the parameter/system specification. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: the value of 1 standard deviation from the mean operating parameter of 483 TB systems, a small fraction (≤ 5%) of the operating range, or a fraction of the minor fault deviation. Results: There were 34 parameters in which synthetic errors were introduced. There were 2 parameters (radial position steering coil, and positive 24V DC) in which the errors did not exceed the limit of the I/MR chart. The I chart limit was exceeded for all of the remaining parameters (94.2%). The MR chart limit was exceeded in 29 of the 32 parameters (85.3%) in which the I chart limit was exceeded. Conclusion: Statistical process control I/MR evaluation of text log file parameters may be effective in providing an early warning of performance degradation or component failure for digital medical accelerator systems. Research is Supported by Varian Medical Systems, Inc.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

Background based Gaussian mixture model lesion segmentation in PET

Purpose: Quantitative {sup 18}F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. Methods: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previous analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). Results: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was demonstrated. The inclusion of the spatial prior improved segmentation accuracy only for lesions surrounded by heterogeneous background: in the relevant simulation subset, the median VE significantly decreased from 13% to 7%. Results on clinical data were found in accordance with simulations, with absolute VE <7%, Dice >0.85, CE <0.30, and HD <0.81. Conclusions: The sole introduction of constraints based on background modeling outperformed standard GMM and the other tested algorithms. Insertion of a spatial prior improved the accuracy for realistic cases of objects in heterogeneous backgrounds. Moreover, robustness against initialization supports the applicability in a clinical setting. In conclusion, application-driven constraints can generally improve the capabilities of GMM and statistical clustering algorithms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Systematic and statistical uncertainties of the hilbert-transform based high-precision FID frequency extraction method

Pulsed nuclear magnetic resonance (NMR) is widely used in high-precision magnetic field measurements. The absolute value of the magnetic field is determined from the precession frequency of nuclear magnetic moments. The Hilbert transform is widely used to extract the phase function from the observed free induction decay (FID) signal and then its frequency. In this paper, a detailed implementation of a Hilbert-transform based FID frequency extraction method is described. How artifacts and noise level in the FID signal affect the extracted phase function are derived analytically. A method of mitigating the artifacts in the extracted phase function of an FID is discussed. Correlations between noises of the phase function samples are studied for different noise spectra. We discovered that the error covariance matrix for the extracted phase function is nearly singular and improper for constructing the $\chi^2$ used in the fitting routine. A down-sampling method for fixing the singular covariance matrix has been developed, so that the minimum $\chi^2$-fit yields properly the statistical uncertainty of the extracted frequency. Other practical methods of obtaining the statistical uncertainty are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Neutrino Interactions

The neutrino group of the University of Tennessee, Knoxville was involved from 05/01/2013 to 04/30/2015 in the neutrino physics research funded by DOE-HEP grant DE-SC0009861. Contributions were made to the Double Chooz nuclear reactor experiment in France where second detector was commissioned during this period and final series of measurements has been started. Although Double Chooz was smaller experimental effort than competitive Daya Bay and RENO experiments, its several advantages make it valuable for understanding of systematic errors in measurements of neutrino oscillations. Double Chooz was the first experiment among competing three that produced initial result for neutrino angle θ 13 measurement, giving other experiments the chance to improve measured value statistically. Graduate student Ben Rybolt defended his PhD thesis on the results of Double Chooz experiment in 2015. UT group has fulfilled all the construction and analysis commitments to Double Chooz experiment, and has withdrawn from the collaboration by the end of the mentioned period to start another experiment. Larger effort of UT neutrino group during this period was devoted to the participation in another DOE-HEP project - NOvA experiment. The 14,000-ton "FAR" neutrino detector was commissioned in northern Minnesota in 2014 together with 300-ton "NEAR" detector located at Fermilab. Following that, the physics measurement program has started when Fermilab accelerator complex produced the high-intensity neutrino beam propagating through Earth to detector in MInnessota. UT group contributed to NOvA detector construction and developments in several aspects. Our Research Associate Athanasios Hatzikoutelis was managing (Level 3 manager) the construction of the Detector Control System. This work was successfully accomplished in time with the commissioning of the detectors. Group was involved in the development of the on-line software and study of the signatures of the cosmic ray backgrounds. Flumerfelt and another graduate student Philip Mason were also studying the non-linearity properties of the NOvA liquid scintillator - information that will be essential at the final stages of NOvA data analysis. Philip Mason also studied the response of the FAR NOvA detector in correlation with solar flares. Flumerfelt and Mason successfully defended their PhD in 2015. Also, undergraduate student Cameron Blake Erickson has defended his undergraduate thesis on the NOvA liquid scintillator studies with Compton gamma spectrometer at UT.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Verification of Calculated Skin Doses in Postmastectomy Helical Tomotherapy

Purpose: To verify the accuracy of calculated skin doses in helical tomotherapy for postmastectomy radiation therapy (PMRT). Methods and Materials: In vivo thermoluminescent dosimeters (TLDs) were used to measure the skin dose at multiple points in each of 14 patients throughout the course of treatment on a TomoTherapy Hi.Art II system, for a total of 420 TLD measurements. Five patients were evaluated near the location of the mastectomy scar, whereas 9 patients were evaluated throughout the treatment volume. The measured dose at each location was compared with calculations from the treatment planning system. Results: The mean difference and standard error of the mean difference between measurement and calculation for the scar measurements was -1.8% {+-} 0.2% (standard deviation [SD], 4.3%; range, -11.1% to 10.6%). The mean difference and standard error of the mean difference between measurement and calculation for measurements throughout the treatment volume was -3.0% {+-} 0.4% (SD, 4.7%; range, -18.4% to 12.6%). The mean difference and standard error of the mean difference between measurement and calculation for all measurements was -2.1% {+-} 0.2% (standard deviation, 4.5%: range, -18.4% to 12.6%). The mean difference between measured and calculated TLD doses was statistically significant at two standard deviations of the mean, but was not clinically significant (i.e., was <5%). However, 23% of the measured TLD doses differed from the calculated TLD doses by more than 5%. Conclusions: The mean of the measured TLD doses agreed with TomoTherapy calculated TLD doses within our clinical criterion of 5%.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy

Purpose: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. Methods and Materials: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. Results: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. Conclusions: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Regression of exchangeable relational arrays

Relational arrays represent measures of association between pairs of actors, often in varied contexts or over time. Trade flows between countries, financial transactions between individuals, contact frequencies between school children in classrooms and dynamic protein-protein interactions are all examples of relational arrays. Elements of a relational array are often modelled as a linear function of observable covariates. Uncertainty estimates for regression coefficient estimators, and ideally the coefficient estimators themselves, must account for dependence between elements of the array, e.g., relations involving the same actor. Existing estimators of standard errors that recognize such relational dependence rely on estimating extremely complex, heterogeneous structure across actors. This paper develops a new class of parsimonious coefficient and standard error estimators for regressions of relational arrays. Here we leverage an exchangeability assumption to derive standard error estimators that pool information across actors, and are substantially more accurate than existing estimators in a variety of settings. This exchangeability assumption is pervasive in network and array models in the statistics literature, but not previously considered when adjusting for dependence in a regression setting with relational data. We demonstrate improvements in inference theoretically, via a simulation study, and by analysis of a dataset involving international trade.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Forecasting constraints on the mean free path of ionizing photons at z ≥ 5.4 from the Lyman-α forest flux autocorrelation function

ABSTRACT Fluctuations in Lyman-α (Ly α) forest transmission towards high-z quasars are partially sourced from spatial fluctuations in the ultraviolet background, the level of which are set by the mean free path of ionizing photons (λmfp). The autocorrelation function of Ly α forest flux characterizes the strength and scale of transmission fluctuations and, as we show, is thus sensitive to λmfp. Recent measurements at z ∼ 6 suggest a rapid evolution of λmfp at z > 5.0 which would leave a signature in the evolution of the autocorrelation function. For this forecast, we model mock Ly α forest data with properties similar to the XQR-30 extended data set at 5.4 ≤ z ≤ 6.0. At each z, we investigate 100 mock data sets and an ideal case where mock data matches model values of the autocorrelation function. For ideal data with λmfp = 9.0 cMpc at z = 6.0, we recover $\lambda _{\text{mfp}}=12^{+6}_{-3}$ cMpc. This precision is comparable to direct measurements of λmfp from the stacking of quasar spectra beyond the Lyman limit. Hypothetical high-resolution data leads to a $\sim 40~{{\ \rm per\ cent}}$ reduction in the error bars over all z. The distribution of mock values of the autocorrelation function in this work is highly non-Gaussian for high-z, which should caution work with other statistics of the high-z Ly α forest against making this assumption. We use a rigorous statistical method to pass an inference test, however future work on non-Gaussian methods will enable higher precision measurements.

Astronomy & Astrophysics↗
DOE OSTI2025

Lanczos algorithm for lattice QCD matrix elements

Recent work [M. L. Wagman, Lanczos, the transfer matrix, and the signal-to-noise problem, .] found that an analysis formalism based on the Lanczos algorithm allows energy levels to be extracted from Euclidean correlation functions with faster ground-state convergence than effective masses, convergent estimators for multiple states from a single correlator, and two-sided error bounds. After filtering out spurious eigenvalues and using outlier-robust estimators within a nested bootstrap framework, Lanczos estimators behave more like multistate fit results than effective masses—but without involving statistical fitting. We extend this formalism to the determination of matrix elements from three-point correlation functions and provide a physical picture of “spurious-state filtering” involving restriction to a Hermitian subspace. We demonstrate similar advantages for matrix elements as for spectroscopy through example applications to noiseless mock-data and (bare) forward matrix elements of the strange scalar current between both ground and excited states with the quantum numbers of the nucleon.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Fast-neutron Multiplicity Counter for Passive and Active Measurements of Special Nuclear Material

We developed a fast-neutron multiplicity counter (FNMC) based on organic scintillators (liquid and stilbene). The system is able to detect correlated photon and neutron multiplets emitted by fission reactions. We tested the system both in passive and active operation mode, and present the results of the experiments, both carried out at the Zero Power Physics Reactor of Idaho National Laboratory. The system was operated in coincidence mode (with a gate time of 50 nanoseconds) and two calibration-based approaches were used to estimate the 240Pu effective (240Pueff) and 235U mass of the samples. In passive mode, we assayed two types of plutonium metal plates, i.e. PAHN and PANN, with a 240Pueff mass of 4.7 g and 25.05 g per plate, respectively. The 239Pu mass percentage was 74% for the PAHN and 95% for the PANN series. We measured neutrons emitted in coincidence by several plate assemblies, having an overall 240Pueff mass in the 4.7 g to 500 g range. In active mode, we characterized several uranium samples. We used two AmLi sources (~50000 neutrons emitted per second) to induce fission in the samples. The first six measured samples were certified reference materials (CRM, set 149), having a constant enrichment, i.e. 93.2 wt%, and mass in the range between 0.5 and 4 kg. Additionally, we assayed three CRM-146 samples, with constant total mass of 500 g and an enrichment of 20.1 wt%, 52.8 wt% and 93.2 wt%. In both configurations, the system succeeded in estimating the fissile mass of an unknown sample with a statistical uncertainty lower than 1% (4-minute assay) and 7% (10-minute assay), in passive and active mode, respectively. In passive mode, the statistical uncertainty is lower than the one achieved by standard 3He counters for plutonium metal samples of similar mass. The difference between the estimated and the declared 240Pueff mass, i.e., the bias error, measured by the fast neutron multiplicity counter was consistently lower compared to the bias error of a standard thermal system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Self-shielding models of MICROX-2 code

The MICROX-2 is a transport theory code that solves for the neutron slowing-down and thermalization equations of a two-region lattice cell. In the previous study, a new fine-group cross section library of the MICROX-2 was generated and tested against reference calculations and measurement data. In this study, existing physics models of the MICROX-2 are reviewed and updated to improve the physics calculation performance of the MICROX-2 code, including the resonance self-shielding model and spatial self-shielding factor. The updated self-shielding models have been verified through a series of benchmark calculations against the Monte Carlo code, using homogeneous and pin cell models selected for this study. The results have shown that the updates of the self-shielding factor calculation model are correct and improve the physics calculation accuracy even though the magnitude of error reduction is relatively small. Compared to the existing models, the updates reduced the prediction error of the infinite multiplication factor by approximately 0.1 % and 0.2% for the homogeneous and pin cell models, respectively, considered in this study. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic Data-Driven Multiscale Modeling for Predicting Microstructure and Mechanical Properties of 316L Stainless Steel

We have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗