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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

TRIPOLI-4{sup R} version 9 Shielding for the Shielding Community: Overview, Relevant Benchmarking for Shielding and Licensing Policy - Paper 49

This is a review paper of the Shielding only version of TRIPOLI-4. TRIPOLI-4 and TRIPOLI-4 S: TRIPOLI{sup R} represents a family of radiation transport codes using the Monte Carlo method (1,2). It has been continuously developed at CEA since the mid 60's. TRIPOLI-4{sup R}, being the fourth generation, has been developed starting from the mid 90's in C++. It tracks neutrons from 20 MeV down to 10{sup -5} eV, photons, electrons and positrons from 100 MeV to 1 keV, in 3D arbitrary geometries either in TRIPOLI{sup R} proprietary format or ROOT(4) format. It reads its continuous energy nuclear data from any evaluation in ENDF format, including but not limited to JEFF-3.1.1 and ENDF/BVII.0. It has various simulation modes, fixed-source (with or without fission), criticality, or both of them chained. A variety of tallies are available: averaged flux in a volume (track length and collision estimators), surface flux and current, point flux, reaction rates, deposited energy, dpa, pka, gamma spectroscopy, mesh tallies, tallies for criticality (k{sub eff}, beta eff, kinetic parameters). It provides the user with embedded response functions from IRDF and EAF as well. Several variance reduction techniques (3), including automated ones, make it particularly suitable to deep penetration problems (implicit capture, Russian roulette, exponential biasing with automatic estimation of the importance map). It may run in parallel, on single multi-core machines as well as heterogeneous networks of stations or massively parallel machines. It comes with productivity tools designed to speed-up the elaboration and verification of the input deck as well as the output analysis: 2D interactive display of geometry; 2D display of mesh tallies and collision sites; 3D input deck modeler; compatibility with ROOT tools to post-process TRIPOLI{sup R} outputs. Its V and V test base is made of more than 1000 internationally accepted benchmarks from ICSBEP and SINBAD (REPLICA, ASPIS, NESDIP) and covers all its application domains, including several shielding cases which will be detailed in the talk. TRIPOLI-4{sup R} is the reference Monte Carlo code for CEA, EDF, and also for AREVA for a number of applications. A 'Shielding-only' version has been designed to specifically answer the needs of the shielding community. It is distributed through the NEA Databank with a license for R and D, covering the fusion applications, whose terms are detailed in the paper.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Co-registered Topographical, Band Excitation Nanomechanical, and Mass Spectral Imaging Using a Combined Atomic Force Microscopy/Mass Spectrometry Platform

The advancement of a hybrid atomic force microscopy/mass spectrometry imaging platform demonstrating for the first time co-registered topographical, band excitation nanomechanical, and mass spectral imaging of a surface using a single instrument is reported. The mass spectrometry-based chemical imaging component of the system utilized nanothermal analysis probes for pyrolytic surface sampling followed by atmospheric pressure chemical ionization of the gas phase species produced with subsequent mass analysis. We discuss the basic instrumental setup and operation and the multimodal imaging capability and utility are demonstrated using a phase separated polystyrene/poly(2-vinylpyridine) polymer blend thin film. The topography and band excitation images showed that the valley and plateau regions of the thin film surface were comprised primarily of one of the two polymers in the blend with the mass spectral chemical image used to definitively identify the polymers at the different locations. Data point pixel size for the topography (390 nm x 390 nm), band excitation (781 nm x 781 nm), mass spectrometry (690 nm x 500 nm) images was comparable and submicrometer in all three cases, but the data voxel size for each of the three images was dramatically different. The topography image was uniquely a surface measurement, whereas the band excitation image included information from an estimated 10 nm deep into the sample and the mass spectral image from 110-140 nm in depth. Moreover, because of this dramatic sampling depth variance, some differences in the band excitation and mass spectrometry chemical images were observed and were interpreted to indicate the presence of a buried interface in the sample. The spatial resolution of the mass spectral image was estimated to be between 1.5 m 2.6 m, based on the ability to distinguish surface features in that image that were also observed in the other images.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

Analysis of modified SMI method for adaptive array weight control

An adaptive array is applied to the problem of receiving a desired signal in the presence of weak interference signals which need to be suppressed. A modification, suggested by Gupta, of the sample matrix inversion (SMI) algorithm controls the array weights. In the modified SMI algorithm, interference suppression is increased by subtracting a fraction F of the noise power from the diagonal elements of the estimated covariance matrix. Given the true covariance matrix and the desired signal direction, the modified algorithm is shown to maximize a well-defined, intuitive output power ratio criterion. Expressions are derived for the expected value and variance of the array weights and output powers as a function of the fraction F and the number of snapshots used in the covariance matrix estimate. These expressions are compared with computer simulation and good agreement is found. A trade-off is found to exist between the desired level of interference suppression and the number of snapshots required in order to achieve that level with some certainty. The removal of noise eigenvectors from the covariance matrix inverse is also discussed with respect to this application. Finally, the type and severity of errors which occur in the covariance matrix estimate are characterized through simulation.

Dilsavor, R. L.↗
DOE OSTI2016

A priori filtered chemical source term modeling for LES of high Karlovitz number premixed flames

Assumptions behind closure models for the filtered source term are studied a priori using results from DNS of turbulent n-heptane/air premixed flames at varying Karlovitz numbers. Simulations with both detailed chemistry and tabulated chemistry, as well as unity and non-unity Lewis numbers, are used to determine if finite-rate chemistry and differential diffusion effects affect the filtered chemical source terms. While the unfiltered source term shows large fluctuations, the filtered source terms from detailed chemistry and tabulated chemistry are in good agreement at sufficiently large filter widths (Δ ≳ l F ). Using the concept of optimal estimators, it is shown that a tabulation approach using the filtered progress variable and its variance can predict accurately the filtered chemical source terms. Finally, the filtered source terms from the DNS are compared to predictions from two commonly assumed sub-filter probability density function models. Both models show deviations from the filtered DNS source terms but predict accurately the mean turbulent flame speed. In conclusion, the results illustrate the potential of using simple tabulated chemistry approaches based on presumed PDFs for LES of premixed flames in the thin and distributed reaction zones regimes.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

NO TIME FOR DEAD TIME: TIMING ANALYSIS OF BRIGHT BLACK HOLE BINARIES WITH NuSTAR

Timing of high-count-rate sources with the NuSTAR Small Explorer Mission requires specialized analysis techniques. NuSTAR was primarily designed for spectroscopic observations of sources with relatively low count rates rather than for timing analysis of bright objects. The instrumental dead time per event is relatively long (∼2.5 msec) and varies event-to-event by a few percent. The most obvious effect is a distortion of the white noise level in the power density spectrum (PDS) that cannot be easily modeled with standard techniques due to the variable nature of the dead time. In this paper, we show that it is possible to exploit the presence of two completely independent focal planes and use the cospectrum, the real part of the cross PDS, to obtain a good proxy of the white-noise-subtracted PDS. Thereafter, one can use a Monte Carlo approach to estimate the remaining effects of dead time, namely, a frequency-dependent modulation of the variance and a frequency-independent drop of the sensitivity to variability. In this way, most of the standard timing analysis can be performed, albeit with a sacrifice in signal-to-noise ratio relative to what would be achieved using more standard techniques. We apply this technique to NuSTAR observations of the black hole binaries GX 339–4, Cyg X-1, and GRS 1915+105.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

An approach to the analysis of performance of quasi-optimum digital phase-locked loops.

An approach to the analysis of performance of quasi-optimum digital phase-locked loops (DPLL's) is presented. An expression for the characteristic function of the prior error in the state estimate is derived, and from this expression an infinite dimensional equation for the prior error variance is obtained. The prior error-variance equation is a function of the communication system model and the DPLL gain and is independent of the method used to derive the DPLL gain. Two approximations are discussed for reducing the prior error-variance equation to finite dimension. The effectiveness of one approximation in analyzing DPLL performance is studied.

Polk, D. R.↗
NASA NTRS1976

Performance analysis of digital FM demodulators for fading channels in the threshold region

The quasi-optimum digital FM demodulators for fading channels reported earlier (1975) reflected the system performance accurately under high signal to noise ratio conditions. In this paper, the prediction of the system performance for low SNR values is considered. A new set of error variance algorithms is developed from the filter algorithm assuming a Gaussian distribution for the state estimation errors and taking the effect of high frequency terms into consideration. Simulation analysis for an FM system with Rician fading channel shows that these algorithms predict the system performance accurately in the threshold region.

Dharamsi, M. T.↗
NASA NTRS1977

Evaluation of signature extension algorithms

The author has identified the following significant results. One of the major findings was that nearly all of the bias in the proportion estimates of the multisegment training and classification procedure resulted from the particular configuration of the signature set used for classification, rather than from peculiarities of the recognition sample segments. This meant that the proportion estimation bias could be accurately corrected simply by estimating the bias on the original six training segments. The bias corrected proportion estimates of the multisegment training and classification procedure were extremely accurate and had a low variance when compared to local training and classification. This finding may have important ramifications for reducing the cost and increasing the accuracy of bias correction procedures.

Nalepka, R. F.↗
NASA NTRS2018

ATMS Radiometric Noise Characterization

The Advanced Technology Microwave Sounder (ATMS), on SNPP and NOAA-20, provides vertical atmospheric temperature and moisture profiles that are a key input to numerical weather prediction. Full characterization of radiometric noise is critical to error modeling, algorithm development and the potential development of performance requirements and product improvements. This paper presents estimates of white noise and low-frequency 1/f noise as derived from the Allan variance and scan-to-scan autocorrelations of data from the internal hot calibration. This approach allows direct comparison of on-orbit performance of the two units as well as comparison between ground calibration test data and on-orbit performance. The autocorrelation at multiple scan intervals is used as input to a theoretical model of the NET of inferred scene brightness temperature, when using weighted samples of calibration data over multiple scans. This will support selection of optimized calibration weighting functions for each channel, as well as providing further insight into the striping phenomenon. These measured autocorrelations are also compared to the autocorrelations derived from the 1/f spectra obtained both in special ground and on-orbit tests that characterize gain fluctuation. Channel cross-correlations are also presented, which can have a significant impact on effectiveness of direct assimilation performance.

instrument calibration↗
DOE OSTI2016

DESIGN CHARACTERISTICS OF THE IDAHO NATIONAL LABORATORY HIGH-TEMPERATURE GAS-COOLED TEST REACTOR

Uncertainty and sensitivity analysis is an indispensable element of any substantial attempt in reactor simulation validation. The quantification of uncertainties in nuclear engineering has grown more important and the IAEA Coordinated Research Program (CRP) on High-Temperature Gas Cooled Reactor (HTGR) initiated in 2012 aims to investigate the various uncertainty quantification methodologies for this type of reactors. The first phase of the CRP is dedicated to the estimation of cell and lattice model uncertainties due to the neutron cross sections co-variances. Phase II is oriented towards the investigation of propagated uncertainties from the lattice to the coupled neutronics/thermal hydraulics core calculations. Nominal results for the prismatic single block (Ex.I-2a) and super cell models (Ex.I-2c) have been obtained using the SCALE 6.1.3 two-dimensional lattice code NEWT coupled to the TRITON sequence for cross section generation. In this work, the TRITON/NEWT-flux-weighted cross sections obtained for Ex.I-2a and various models of Ex.I-2c is utilized to perform a sensitivity analysis of the MHTGR-350 core power densities and eigenvalues. The core solutions are obtained with the INL coupled code PHISICS/RELAP5-3D, utilizing a fixed-temperature feedback for Ex. II-1a.. It is observed that the core power density does not vary significantly in shape, but the magnitude of these variations increases as the moderator-to-fuel ratio increases in the super cell lattice models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1989

Probabilities and statistics for backscatter estimates obtained by a scatterometer with applications to new scatterometer design data

The values of the Normalized Radar Backscattering Cross Section (NRCS), sigma (o), obtained by a scatterometer are random variables whose variance is a known function of the expected value. The probability density function can be obtained from the normal distribution. Models for the expected value obtain it as a function of the properties of the waves on the ocean and the winds that generated the waves. Point estimates of the expected value were found from various statistics given the parameters that define the probability density function for each value. Random intervals were derived with a preassigned probability of containing that value. A statistical test to determine whether or not successive values of sigma (o) are truly independent was derived. The maximum likelihood estimates for wind speed and direction were found, given a model for backscatter as a function of the properties of the waves on the ocean. These estimates are biased as a result of the terms in the equation that involve natural logarithms, and calculations of the point estimates of the maximum likelihood values are used to show that the contributions of the logarithmic terms are negligible and that the terms can be omitted.

Pierson, Willard J., Jr.↗
NASA NTRS2006

Studies in Software Cost Model Behavior: Do We Really Understand Cost Model Performance?

While there exists extensive literature on software cost estimation techniques, industry practice continues to rely upon standard regression-based algorithms. These software effort models are typically calibrated or tuned to local conditions using local data. This paper cautions that current approaches to model calibration often produce sub-optimal models because of the large variance problem inherent in cost data and by including far more effort multipliers than the data supports. Building optimal models requires that a wider range of models be considered while correctly calibrating these models requires rejection rules that prune variables and records and use multiple criteria for evaluating model performance. The main contribution of this paper is to document a standard method that integrates formal model identification, estimation, and validation. It also documents what we call the large variance problem that is a leading cause of cost model brittleness or instability.

data mining↗
DOE OSTI2017

THE NANOGRAV NINE-YEAR DATA SET: EXCESS NOISE IN MILLISECOND PULSAR ARRIVAL TIMES

Gravitational wave (GW) astronomy using a pulsar timing array requires high-quality millisecond pulsars (MSPs), correctable interstellar propagation delays, and high-precision measurements of pulse times of arrival. Here we identify noise in timing residuals that exceeds that predicted for arrival time estimation for MSPs observed by the North American Nanohertz Observatory for Gravitational Waves. We characterize the excess noise using variance and structure function analyses. We find that 26 out of 37 pulsars show inconsistencies with a white-noise-only model based on the short timescale analysis of each pulsar, and we demonstrate that the excess noise has a red power spectrum for 15 pulsars. We also decompose the excess noise into chromatic (radio-frequency-dependent) and achromatic components. Associating the achromatic red-noise component with spin noise and including additional power-spectrum-based estimates from the literature, we estimate a scaling law in terms of spin parameters (frequency and frequency derivative) and data-span length and compare it to the scaling law of Shannon and Cordes. We briefly discuss our results in terms of detection of GWs at nanohertz frequencies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

TH-A-18C-09: Ultra-Fast Monte Carlo Simulation for Cone Beam CT Imaging of Brain Trauma

Purpose: Application of cone-beam CT (CBCT) to low-contrast soft tissue imaging, such as in detection of traumatic brain injury, is challenged by high levels of scatter. A fast, accurate scatter correction method based on Monte Carlo (MC) estimation is developed for application in high-quality CBCT imaging of acute brain injury. Methods: The correction involves MC scatter estimation executed on an NVIDIA GTX 780 GPU (MC-GPU), with baseline simulation speed of ~1e7 photons/sec. MC-GPU is accelerated by a novel, GPU-optimized implementation of variance reduction (VR) techniques (forced detection and photon splitting). The number of simulated tracks and projections is reduced for additional speed-up. Residual noise is removed and the missing scatter projections are estimated via kernel smoothing (KS) in projection plane and across gantry angles. The method is assessed using CBCT images of a head phantom presenting a realistic simulation of fresh intracranial hemorrhage (100 kVp, 180 mAs, 720 projections, source-detector distance 700 mm, source-axis distance 480 mm). Results: For a fixed run-time of ~1 sec/projection, GPU-optimized VR reduces the noise in MC-GPU scatter estimates by a factor of 4. For scatter correction, MC-GPU with VR is executed with 4-fold angular downsampling and 1e5 photons/projection, yielding 3.5 minute run-time per scan, and de-noised with optimized KS. Corrected CBCT images demonstrate uniformity improvement of 18 HU and contrast improvement of 26 HU compared to no correction, and a 52% increase in contrast-tonoise ratio in simulated hemorrhage compared to “oracle” constant fraction correction. Conclusion: Acceleration of MC-GPU achieved through GPU-optimized variance reduction and kernel smoothing yields an efficient (<5 min/scan) and accurate scatter correction that does not rely on additional hardware or simplifying assumptions about the scatter distribution. The method is undergoing implementation in a novel CBCT dedicated to brain trauma imaging at the point of care in sports and military applications. Research grant from Carestream Health. JY is an employee of Carestream Health.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

On the uncertainty of estimating photovoltaic soiling using nearby soiling data

The accumulation of dust on the surface of photovoltaic modules can reduce their performance and affect the cost competitiveness of this technology. This phenomenon is known as soiling and can be mitigated through appropriate corrective and/or preventive actions. In order to maximize its effectiveness, it is important to plan the soiling mitigation strategy even before the PV system is operational. This is typically done through a nearest neighbor approach, by estimating soiling using data from the nearest operational photovoltaic system. This work focuses on understanding the uncertainty related to this practice. For this purpose, the semi-variance function is used to study the dissimilarity between the soiling losses of two locations in California depending on their distance. The results show that, when the soiling loss at a nearby system is used to estimate soiling of a site, the uncertainty can be approximated to increase linearly at a rate of 0.08-0.10%/km up to 60 or 80 km. After this distance, the use of a nearest neighbor approach is no longer justified, as it produces an uncertainty as big as the average soiling loss of the sites in the dataset used in this study. In some conditions, uncertainties > 0% are found also for sites located within 25 km, meaning that even close-by systems might soil differently.

14 SOLAR ENERGY↗
DOE OSTI2023

A Machine Learning–Based Tire Life Prediction Framework for Increasing Life of Commercial Vehicle Tires

In the commercial freight industry, tire retreading decisions are often conservative due to limited knowledge of a tire’s remaining service life. This practice leads to increased costs and material waste. This paper proposes a machine learning–based approach for estimating tire casing life and retreadability, focusing on usage data rather than wear information. This approach could extend the tire’s lifespan and reduce landfill waste. Data integration from diverse tire casing measurement sources presents challenges, including imbalanced removal data. Our methodology addresses these challenges by using historical inspection, telematics, and finite element modeling (FEM) datasets. We introduce “Tire Casing Energy” as a comprehensive usage input and apply a Variance-Reduction Synthetic Minority Oversampling Technique (VR-SMOTE) for data imbalance rectification. A random forest model is used to estimate the state of the tire casing and the casing removal probability, with Bayesian optimization applied for hyperparameter tuning, enhancing model accuracy. Here, the proposed prediction framework is able to differentiate different truck fleets and tire locations based on their usage parameters. With the aid of this machine learning model, the importance and sensitivity of different tire usage parameters can be obtained, which is beneficial to maximize tire life.

Data balancing↗
NASA NTRS1978

Kalman filter divergence and aircraft motion estimators

Kalman filters designed for many aerospace systems turn out to be unsatisfactory. The estimate errors become large compared to the errors predicted by the theory ('divergence'). One of the principal causes of this failure is that the system model contains states or modes that are undisturbed by the modeled process noise, and are neutrally stable (NS). One cure for such problems is periodic restarting of a time-varying Kalman filter. Other cures include minimum variance observers with eigenvalue constraints, added noise, pole-shifting, and destabilization. Several examples are given, including effective time-invariant estimators for the longitudinal and lateral motions of an airplane where several NS modes are undisturbed by wind gusts. An interpretation of these estimators as a 'strapdown IMU' without accelerometers, gimbaled gyros, or servos is given.

Bryson, A. E., Jr.↗
DOE OSTI2016

A novel approach to assess the treatment response using Gaussian random field in PET

Purpose: The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robust approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects. Methods: The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (128{sup 2} pixels) with lesions of various diameters (2–6 mm), multiple tumor-to-background contrasts (3–10), and different changes in intensity (6.25%–30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response assessment utilizing local average method based on random field. The accuracy of the estimation was validated in terms of Euler distance and correlation coefficient. Results: It is shown that the performance of therapy response assessment is significantly improved by the introduction of variance with a higher area under the curve (97.3%) than SUVmean (91.4%) and SUVmax (82.0%). In addition, the FPR estimation serves as a good prediction for the specificity of the proposed method, consistent with simulation outcome with ∼1 correlation coefficient. Conclusions: In this work, the authors developed a method to evaluate therapy response from PET images, which were modeled as Gaussian random field. The digital phantom simulations demonstrated that the proposed method achieved a large reduction in statistical variability through incorporating knowledge of the variance of the original Gaussian random field. The proposed method has the potential to enable prediction of early treatment response and shows promise for application to clinical practice. In future work, the authors will report on the robustness of the estimation theory for application to clinical practice of therapy response evaluation, which pertains to binary discrimination tasks at a fixed location in the image such as detection of small and weak lesion.

61 RADIATION PROTECTION AND DOSIMETRY↗