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At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Immersion freezing of water and aqueous ammonium sulfate droplets initiated by humic-like substances as a function of water activity

Immersion freezing of water and aqueous (NH 4 ) 2 SO 4 droplets containing leonardite (LEO) and Pahokee peat (PP) serving as surrogates for humic-like substances (HULIS) has been investigated. Organic aerosol containing HULIS are ubiquitous in the atmosphere; however, their potential for ice cloud formation is uncertain. Immersion freezing has been studied for temperatures as low as 215K and solution water activity, a w , from 0.85 to 1.0. The freezing temperatures of water and aqueous solution droplets containing LEO and PP are 5–15 K warmer than homogeneous ice nucleation temperatures. Heterogeneous freezing temperatures can be represented by a horizontal shift of the ice melting curve as a function of solution aw by Δ a w = 0.2703 and 0.2466, respectively. Corresponding heterogeneous ice nucleation rate coefficients, Jhet, are (9.6 ± 2.5) × 10 4 and (5.4 ± 1.4) × 10 4 cm -2 s -1 for LEO and PP containing droplets, respectively, and remain constant along freezing curves characterized by Δ a w . Consequently predictions of freezing temperatures and kinetics can be made without knowledge of the solute type when relative humidity and ice nuclei (IN) surface areas are known. The acquired ice nucleation data are applied to evaluate different approaches to fit and reproduce experimentally derived frozen fractions. In addition, we apply a basic formulation of classical nucleation theory (α( T )-model) to calculate contact angles and frozen fractions. Contact angles calculated for each ice nucleus as a function of temperature, α( T )-model, reproduce exactly experimentally derived frozen fractions without involving free-fit parameters. However, assigning the IN a single contact angle for the entire population (single-α model) is not suited to represent the frozen fractions. Application of α-PDF, active sites, and deterministic model approaches to measured frozen fractions yield similar good representations. Furthermore, when using a single parameterization of α-PDF or active sites distribution to fit all individual a w immersion freezing data simultaneously, frozen fraction curves are not reproduced. This implies that these fitting formulations cannot be applied to immersion freezing of aqueous solutions, and suggests that derived fit parameters do not represent independent particle properties. Thus, from fitting frozen fractions only, the underlying ice nucleation mechanism and nature of the ice nucleating sites cannot be inferred. In contrast to using fitted functions obtained to represent experimental conditions only, we suggest to use experimentally derived J het as a function of temperature and a w that can be applied to conditions outside of those probed in laboratory. Finally, this is because J het (T) is independent of time and IN surface areas in contrast to the fit parameters obtained by representation of experimentally derived frozen fractions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

The point spread function of the soft X-ray telescope aboard Yohkoh

The point spread function of the SXT telescope aboard Yohkoh has been measured in flight configuration in three different X-ray lines at White Sands Missile Range. We have fitted these data with an elliptical generalization of the Moffat function. Our fitting method consists of chi squared minimization in Fourier space, especially designed for matching of sharply peaked functions. We find excellent fits with a reduced chi squared of order unity or less for single exposure point spread functions over most of the CCD. Near the edges of the CCD the fits are less accurate due to vignetting. From fitting results with summation of multiple exposures we find a systematic error in the fitting function of the order of 3% near the peak of the point spread function, which is close to the photon noise for typical SXT images in orbit. We find that the full width to half maximum and fitting parameters vary significantly with CCD location. However, we also find that point spread functions measured at the same location are consistent to one another within the limit determined by photon noise. A 'best' analytical fit to the PSF as function of position on the CCD is derived for use in SXT image enhancemnent routines. As an aside result we have found that SXT can determine the location of point sources to about a quarter of a 2.54 arc sec pixel.

Martens, Petrus C.↗
NASA NTRS1995

Dust in the small Magellanic Cloud. 2: Dust models from interstellar polarization and extinction data

We study the dust in the Small Magellanic Cloud using our polarization and extinction data (Paper 1) and existing dust models. The data suggest that the monotonic SMC extinction curve is related to values of lambda(sub max), the wavelength of maximum polarization, which are on the average smaller than the mean for the Galaxy. On the other hand, AZV 456, a star with an extinction similar to that for the Galaxy, shows a value of lambda(sub max) similar to the mean for the Galaxy. We discuss simultaneous dust model fits to extinction and polarization. Fits to the wavelength dependent polarization data are possible for stars with small lambda(sub max). In general, they imply dust size distributions which are narrower and have smaller mean sizes compared to typical size distributions for the Galaxy. However, stars with lambda(sub max) close to the Galactic norm, which also have a narrower polarization curve, cannot be fit adequately. This holds true for all of the dust models considered. The best fits to the extinction curves are obtained with a power law size distribution by assuming that the cylindrical and spherical silicate grains have a volume distribution which is continuous from the smaller spheres to the larger cylinders. The size distribution for the cylinders is taken from the fit to the polarization. The 'typical', monotonic SMC extinction curve can be fit well with graphite and silicate grains if a small fraction of the SMC carbon is locked up in the grain. However, amorphous carbon and silicate grains also fit the data well. AZV456, which has an extinction curve similar to that for the Galaxy, has a UV bump which is too blue to be fit by spherical graphite grains.

Rodrigues, C. V.↗
NASA NTRS2009

Complexity of Sizing for Space Suit Applications

The `fit? of a garment is often considered to be a subjective measure of garment quality. However, some experts attest that a complaint of poor garment fit is a symptom of inadequate or excessive ease, the space between the garment and the wearer. Fit has traditionally been hard to quantify, and space suits are an extreme example, where fit is difficult to measure but crucial for safety and operability. A proper space suit fit is particularly challenging because of NASA?s need to fit an incredibly diverse population (males and females from the 1st to 99th percentile) while developing a minimum number of space suit sizes. Because so few sizes are available, the available space suits must be optimized so that each fits a large segment of the population without compromising the fit of any one wearer.

Rajulu, Sudhakar↗
DOE OSTI2012

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including the most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions: Comparable prediction models were obtained with LKB, RS, and logistic NTCP models. Including clinical factors improved the predictive power of all models significantly.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Evolving efforts to maintain and improve XPS analysis quality in an era of increasingly diverse uses and users

Based on literature analysis, X-ray photoelectron spectroscopy (XPS) use continues to increase exponentially. This increased use is accompanied by anecdotal reports and systematic analyses indicating a growing presence of significantly flawed data analyses. Recognition of this problem within the surface analysis community has increased with an understanding that both inexperienced users and increased use of XPS outside the surface analysis community contribute to the problem. The XPS community has initiated several efforts to help address the problem, which is not unique to XPS. This paper describes some of the specific problems identified and some of the community efforts intended to address them. Here, we describe activities focused on three specific issues: (i) requests for detailed guides and protocols and bite-sized versions of information for non-experts, (ii) incomplete data and analysis reporting, and (iii) the high rate of peak fitting problems. A 2019 survey identified the need for guides, protocols, and standards to assist XPS users. One set of such guides has been published, and another is being assembled. Providing incremental bites of useful information is the goal of a series of papers on specific challenges to surface analysis with example solutions has been initiated as Notes and Insights papers in Surface and Interface Analysis. Examination of XPS-containing papers finds that information to establish the credibility and reproducibility of XPS results is often very incomplete. Unfortunately, ISO and ASTM standards require an amount of parameter reporting that seems excessive and unrealistic for many research publications. Initial approaches to develop and distribute a graded approach to parameter reporting are briefly described. Multiple efforts are underway to address the high rate of problems associated with photoelectron peak fitting. These include guides to peak fitting, guides to peak identification and fitting for specific elements, and the development of a peak fitting social network. The fitting social network is designed to facilitate interactions between new and experienced XPS users; analysts trying to fit XPS data (for publication or other reasons) can ask questions and establish dynamic conversations. Encouraging and enabling high-quality XPS analysis and reporting requires several different types of effort from all members of the surface and interface analysis community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Artificial intelligence based analysis of nanoindentation load–displacement data using a genetic algorithm

In this work, we developed an automated tool, Nanoindentation Neo package for the analysis of nanoindentation load–displacement curves using a Genetic Algorithm (GA) applied to the Oliver-Pharr method (Oliver et al.,1992). For some materials, such as polycrystalline isotropic graphites, Least Squares Fitting (LSF) of the unload curve can produce unrealistic fit parameters. These graphites exhibit sharply peaked unloading curves not easily fit using the LSF, which tends to overestimate the indenter tip geometry parameter. To tackle this problem, we extended our general materials characterization tool Neo for EXAFS analysis (Terry et al., 2021) to fit nanoindentation data. Nanoindentation Neo automatically processes and analyzes nanoindentation data with minimal user input while producing meaningful fit parameters. GA, a robust metaheuristic method, begins with a population of temporary solutions using model parameters called chromosomes; from these we evaluate a fitness value for each solution, and select the best solutions to mix with random solutions producing the next generation. A mutation operator then modifies existing solutions by random perturbations, and the optimal solution is selected. We tested the GA method using Silica and Al reference standards. We fit samples of graphite and a high entropy alloy (HEA) consisting of BCC and FCC phases.

42 ENGINEERING↗
DOE OSTI2012

Applying a Hypoxia-Incorporating TCP Model to Experimental Data on Rat Sarcoma

Purpose: To verify whether a tumor control probability (TCP) model which mechanistically incorporates acute and chronic hypoxia is able to describe animal in vivo dose-response data, exhibiting tumor reoxygenation. Methods and Materials: The investigated TCP model accounts for tumor repopulation, reoxygenation of chronic hypoxia, and fluctuating oxygenation of acute hypoxia. Using the maximum likelihood method, the model is fitted to Fischer-Moulder data on Wag/Rij rats, inoculated with rat rhabdomyosarcoma BA1112, and irradiated in vivo using different fractionation schemes. This data set is chosen because two of the experimental dose-response curves exhibit an inverse dose behavior, which is interpreted as due to reoxygenation. The tested TCP model is complex, and therefore, in vivo cell survival data on the same BA1112 cell line from Reinhold were added to Fischer-Moulder data and fitted simultaneously with a corresponding cell survival function. Results: The obtained fit to the combined Fischer-Moulder-Reinhold data was statistically acceptable. The best-fit values of the model parameters for which information exists were in the range of published values. The cell survival curves of well-oxygenated and hypoxic cells, computed using the best-fit values of the radiosensitivities and the initial number of clonogens, were in good agreement with the corresponding in vitro and in situ experiments of Reinhold. The best-fit values of most of the hypoxia-related parameters were used to recompute the TCP for non-small cell lung cancer patients as a function of the number of fractions, TCP(n). Conclusions: The investigated TCP model adequately describes animal in vivo data exhibiting tumor reoxygenation. The TCP(n) curve computed for non-small cell lung cancer patients with the best-fit values of most of the hypoxia-related parameters confirms previously obtained abrupt reduction in TCP for n < 10, thus warning against the adoption of severely hypofractionated schedules.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

SANS quantification of bound water in water-soluble polymers across multiple concentration regimes

Contrast-variation small-angle neutron scattering (CV-SANS) is a widely used technique for quantifying hydration water in soft matter systems, but it is predominantly applied in the dilute regime or for systems with a well-defined structure factor. Here, CV-SANS was used to quantify the number of hydration water molecules associating with three water-soluble polymers with different critical solution temperatures and types of water–solute interactions in dilute, semidilute, and concentrated solution through the exploration of novel methods of data fitting and analysis. Multiple SANS fitting workflows with varying levels of model assumptions were evaluated and compared to give insight into SANS model selection. These fitting pathways ranged from general, model-free algorithms to more standard form and structure factor fitting. In addition, Monte Carlo bootstrapping was evaluated as a method to estimate parameter uncertainty through simulation of technical replicates. The most robust fitting workflow for dilute solutions was found to be form factor fitting without CV-SANS ( i.e. polymer in 100% D 2 O). For semidilute and concentrated solutions, while the model-free approach can be mathematically defined for CV-SANS data, the addition of a structure factor imposes physical constraints on the optimization problem, suggesting that the optimal fitting pathway should include appropriate form and structure factor models. The measured hydration numbers were consistent with the number of tightly bound water molecules associated with each monomer unit, and the concentration dependence of the hydration number was largely governed by the chemistry-specific interactions between water and polymer. Polymers with weaker water–polymer interactions ( i.e. those with fewer hydration water molecules) were found to have more bound water at higher concentrations than those with stronger water–polymer interactions due to the increase in the number of forced water–polymer contacts in the concentrated system. This SANS-based method to count hydration water molecules can be applied to polymers in any concentration regime, which will lead to improved understanding of water–polymer interactions and their impact on materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2013

COMPARING THE LIGHT CURVES OF SIMULATED TYPE Ia SUPERNOVAE WITH OBSERVATIONS USING DATA-DRIVEN MODELS

We propose a robust, quantitative method to compare the synthetic light curves of a Type Ia supernova (SN Ia) explosion model with a large set of observed SNe Ia, and derive a figure of merit for the explosion model's agreement with observations. The synthetic light curves are fit with the data-driven model SALT2 which returns values for stretch, color, and magnitude at peak brightness, as well as a goodness-of-fit parameter. Each fit is performed multiple times with different choices of filter bands and epoch range in order to quantify the systematic uncertainty on the fitted parameters. We use a parametric population model for the distribution of observed SN Ia parameters from large surveys, and extend it to represent red, dim, and bright outliers found in a low-redshift SN Ia data set. We discuss the potential uncertainties of this population model and find it to be reliable given the current uncertainties on cosmological parameters. Using our population model, we assign each set of fitted parameters a likelihood of being observed in nature, and a figure of merit based on this likelihood. We define a second figure of merit based on the quality of the light curve fit, and combine the two measures into an overall figure of merit for each explosion model. We compute figures of merit for a variety of one-, two-, and three-dimensional explosion models and show that our evaluation method allows meaningful inferences across a wide range of light curve quality and fitted parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Cold neutron-deuteron capture and Wigner-SU(4) symmetry

We calculate the cold neutron-deuteron (nd) capture cross section,σ nd to next-to-next-to leading order (NNLO) using the model-independent approach of pionless effective-field theory [EFT(π)]. At leading order we find σ nd = 0.314 ± 0.217 mb, while the experimental result is 0.508(15) mb for a laboratory neutron velocity of 2200 m/s. At next-to-leading-order (NLO), we show that σnd is sensitive to the low-energy constant (LEC) $L$$^{(0)}_{1}$ of the two-nucleon isovector current appearing at NLO. A fit of $L$$^{(0)}_{1}$ at NLO to the triton magnetic moment yields a NLO prediction of σ nd = 0.393 ± 0.164 mb, where the error comes from propagating the error from the $L$$^{(0)}_{1}$ fit. At NNLO, we find that a new three-nucleon magnetic moment counterterm is required for renormalization-group invariance of both σnd and the triton magnetic moment. Fitting the NNLO correction to $L$$^{(0)}_{1}$ (denoted $L$$^{(1)}_{1}$) to cold neutron-proton capture (σnp) yields a NNLO prediction of σ nd = 0.447 ± 0.130 mb, where the error comes from propagating the error from the $L$$^{(1)}_{1}$ fit. We also study different fittings of $L$$^{(0)}_{1}$ and $L$$^{(1)}_{1}$ to σ np , σ nd , and/or the triton magnetic moment. For example, fitting $L$$^{(0)}_{1}$ simultaneously to σ np , σ nd , and the triton magnetic moment at NLO, and fitting $L$$^{(1)}_{1}$ simultaneously to σ np and σnd at NNLO, yields σ nd = 0.480 ± 0.114 mb and 0.511 ± 0.042 mb, respectively, where errors are naively estimated from EFT(π) power counting. Additionally, we discuss how Wigner SU(4) symmetry may alter the naive EFT(π) expansion of σ nd .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Uncertainty quantification for optical model parameters

Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of our work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fit and create corresponding 95% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. Here, we study a number of reactions involving neutron and deuteron projectiles with energies in the range of 5–25 MeV/u, on targets with mass A=12–208. We investigate the correlations between the parameters in the fit. The case of deuterons on 12 C is discussed in detail: the elastic-scattering fit and the prediction of 12 C(d,p) 13 C transfer angular distributions, using both uncorrelated and correlated χ 2 minimization functions. The general features for all cases are compiled in a systematic manner to identify trends. This work shows that, in many cases, the correlated χ 2 functions (in comparison to the uncorrelated χ 2 functions) provide a more natural parameterization of the process. These correlated functions do, however, produce broader confidence bands. Further optimization may require improvement in the models themselves and/or more information included in the fit.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Molecular radiotherapy: The NUKFIT software for calculating the time-integrated activity coefficient

Purpose: Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error.Methods: The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB.Results: To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit parameters and their standard error estimated by using SAAM numerical and NUKFIT showed differences of <1%. The differences for the time-integrated activity coefficients were also <1% (standard error between 0.4% and 3%). In general, the application of the software is user-friendly and the results are mathematically correct and reproducible. An application of NUKFIT is presented for three different clinical examples.Conclusions: The software tool with its underlying methodology can be employed to objectively and reproducibly estimate the time integrated activity coefficient and its standard error for most time activity data in molecular radiotherapy.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

{sup 18}F-FLT uptake kinetics in head and neck squamous cell carcinoma: A PET imaging study

Purpose: To analyze the kinetics of 3{sup ′}-deoxy-3{sup ′}-[F-18]-fluorothymidine (18F-FLT) uptake by head and neck squamous cell carcinomas and involved nodes imaged using positron emission tomography (PET). Methods: Two- and three-tissue compartment models were fitted to 12 tumor time-activity-curves (TACs) obtained for 6 structures (tumors or involved nodes) imaged in ten dynamic PET studies of 1 h duration, carried out for five patients. The ability of the models to describe the data was assessed using a runs test, the Akaike information criterion (AIC) and leave-one-out cross-validation. To generate parametric maps the models were also fitted to TACs of individual voxels. Correlations between maps of different parameters were characterized using Pearson'sr coefficient; in particular the phosphorylation rate-constants k{sub 3-2tiss} and k{sub 5} of the two- and three-tissue models were studied alongside the flux parameters K{sub FLT-2tiss} and K{sub FLT} of these models, and standardized uptake values (SUV). A methodology based on expectation-maximization clustering and the Bayesian information criterion (“EM-BIC clustering”) was used to distil the information from noisy parametric images. Results: Fits of two-tissue models 2C3K and 2C4K and three-tissue models 3C5K and 3C6K comprising three, four, five, and six rate-constants, respectively, pass the runs test for 4, 8, 10, and 11 of 12 tumor TACs. The three-tissue models have lower AIC and cross-validation scores for nine of the 12 tumors. Overall the 3C6K model has the lowest AIC and cross-validation scores and its fitted parameter values are of the same orders of magnitude as literature estimates. Maps ofK{sub FLT} and K{sub FLT-2tiss} are strongly correlated (r = 0.85) and also correlate closely with SUV maps (r = 0.72 for K{sub FLT-2tiss}, 0.64 for K{sub FLT}). Phosphorylation rate-constant maps are moderately correlated with flux maps (r = 0.48 for k{sub 3-2tiss} vs K{sub FLT-2tiss} and r = 0.68 for k{sub 5} vs K{sub FLT}); however, neither phosphorylation rate-constant correlates significantly with SUV. EM-BIC clustering reduces the parametric maps to a small number of levels—on average 5.8, 3.5, 3.4, and 1.4 for K{sub FLT-2tiss}, K{sub FLT}, k{sub 3-2tiss}, and k{sub 5.} This large simplification is potentially useful for radiotherapy dose-painting, but demonstrates the high noise in some maps. Statistical simulations show that voxel level noise degrades TACs generated from the 3C6K model sufficiently that the average AIC score, parameter bias, and total uncertainty of 2C4K model fits are similar to those of 3C6K fits, whereas at the whole tumor level the scores are lower for 3C6K fits. Conclusions: For the patients studied here, whole tumor FLT uptake time-courses are represented better overall by a three-tissue than by a two-tissue model. EM-BIC clustering simplifies noisy parametric maps, providing the best description of the underlying information they contain and is potentially useful for radiotherapy dose-painting. However, the clustering highlights the large degree of noise present in maps of the phosphorylation rate-constantsk{sub 5} and k{sub 3-2tiss}, which are conceptually tightly linked to cellular proliferation. Methods must be found to make these maps more robust—either by constraining other model parameters or modifying dynamic imaging protocols.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-I-07: Response Characteristics and Signal Conversion Modeling of KV Flat-Panel Detector in Cone Beam CT System

Purpose: The flat-panel detector response characteristics are investigated to optimize the scanning parameter considering the image quality and less radiation dose. The signal conversion model is also established to predict the tumor shape and physical thickness changes. Methods: With the ELEKTA XVI system, the planar images of 10cm water phantom were obtained under different image acquisition conditions, including tube voltage, electric current, exposure time and frames. The averaged responses of square area in center were analyzed using Origin8.0. The response characteristics for each scanning parameter were depicted by different fitting types. The transmission measured for 10cm water was compared to Monte Carlo simulation. Using the quadratic calibration method, a series of variable-thickness water phantoms images were acquired to derive the signal conversion model. A 20cm wedge water phantom with 2cm step thickness was used to verify the model. At last, the stability and reproducibility of the model were explored during a four week period. Results: The gray values of image center all decreased with the increase of different image acquisition parameter presets. The fitting types adopted were linear fitting, quadratic polynomial fitting, Gauss fitting and logarithmic fitting with the fitting R-Square 0.992, 0.995, 0.997 and 0.996 respectively. For 10cm water phantom, the transmission measured showed better uniformity than Monte Carlo simulation. The wedge phantom experiment show that the radiological thickness changes prediction error was in the range of (-4mm, 5mm). The signal conversion model remained consistent over a period of four weeks. Conclusion: The flat-panel response decrease with the increase of different scanning parameters. The preferred scanning parameter combination was 100kV, 10mA, 10ms, 15frames. It is suggested that the signal conversion model could effectively be used for tumor shape change and radiological thickness prediction. Supported by National Natural Science Foundation of China (81101132, 11305203) and Natural Science Foundation of Anhui Province (11040606Q55, 1308085QH138)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-477: Investigation of DEFGEL Dosimetry Using MRI

Purpose: The DEFGEL dosimeter/phantom allows for the measurement of 3D dose distributions while maintaining tissue equivalence and deformability. Although DEFGEL is traditionally read out with optical CT, the use of MRI would permit the measurement of 3D dose distributions in optically interfering configurations, like while embedded in a phantom. To the knowledge of the authors, this work is the first investigation that uses MRI to measure dose distributions in DEFGEL dosimeters. Methods: The DEFGEL (6%T) formula was used to create 1 cm thick, 4.5 cm diameter cylindrical dosimeters. The dosimeters were irradiated using a Varian Clinac 21EX linac. The MRI based transverse relaxation rate (R2) of the gel was measured in a central slice of the dosimeter with a Spin-Echo (SE) pulse sequence on a 3T GE SIGNA PET/MR scanner. The R2 values were fit to a monoexponential dose response equation using in-house software (MATLAB). Results: The data was well fit using a monoexponential fit for R2 as a function of absorbed dose (R{sup 2} = 0.9997). The fitting parameters of the monoexponential fit resulted in a 0.1229 Gy{sub −1}s{sub −1} slope. The data also resulted in an average standard deviation of 1.8% for the R2 values within the evaluated ROI. Conclusion: The close fit for the dose response curve shows that a DEFGEL based dosimeter can be paired with a SE MRI acquisition. The Type A uncertainty of the MRI method shows adequate precision, while the slope of the fit curve is large enough that R2 differences between different gel doses are distinguishable. These results suggest that the gel could potentially be used in configurations where an optical readout is not viable, such as measurements with the gel dosimeter positioned inside larger or optically opaque phantoms. This work is partially funded by NIH grant R01CA190298.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Development of Digital Twin Predictive Model for PWR Components: Updates on Multi Times Series Temperature Prediction Using Recurrent Neural Network, DMW Fatigue Tests, System Level Thermal-Mechanical-Stress Analysis

The long-term operation (LTO) of nuclear power plant (NPP) beyond their original design life of 40 years, can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Frequent NDE requirement may lead to frequent shutdown of the NPP. This in turn can lead to power outage and additional NDE-inspection-cost related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing more digital approach such as by using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. Towards this goal Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program is working on the development of a DT framework that can be used for real time environmental fatigue prediction of reactor components. The DT framework is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics such as finite element (FE) based modeling tools. Towards this overall goal, following are some of the major contributions made during the FY21: 1) Multiple 82/182 dissimilar metal weld (DMW) specimens (both solid-weld and joint-weld representing the actual reactor multi-metal nozzles) were fatigue tested. The resulting fatigue lives were compared to the NUREG-6909 based best-fit and design fatigue curves. Additionally, the results of 52/152 DMW fatigue specimens (which were recently tested at Republic of Korea under the sponsorship of International Nuclear Energy Research Initiative - INERI program) were compared to the NUREG-6909 based best-fit and design fatigue curves. From the comparison of 82/182 and 52/152 DMW test data with NUREG-6909 best-fit curve, most of the reported test data fall way away from the NUREG-6909 suggested best-fit or mean curve. The NUREG-6909 suggested best-fit curve is the best-fit curve of austenitic stainless steel and due to lack of enough data on Nickel-based welds, this is currently being used for predicting the life of Nickel-alloy-based welded components. However, the above observation may require higher scaling factor (e.g., ASME suggested factor of 20 on cycles rather than the current NUREG-6909 suggested factor of 12 on cycles) for scaling the austenitic-stainless-steel best-fit-curve for estimating the design or safe-life of a welded component. Accordingly, for example, if a DMW component experience a strain amplitude of 0.6% the PWR-water life of the component would be 52 cycles instead of 85 cycles. However, more DMW tests are required to further ascertain the above-mentioned observations. 2) A system level CAD and finite element model were developed which consists of reactor pressure vessel (RPV), part of steam generator (SG), part of pressurizer (PRZ), hot leg (HL), and surge line (SL). This is with detailed nozzle geometry and thermal-mechanical material properties of different metals to simulate realistic thermal-mechanical stress under connected system global thermal-mechanical boundary conditions. 3) Different system level heat transfer analyses were performed with estimation of relevant heat transfer coefficients. The resulting data were used in subsequent system level thermal-mechanical stress analysis and for generating spatial-temporal training and validation data for a system level digital-twin based temperature predictor. Transient heat transfer analyses were performed considering thermal boundary condition under design-basis (DB) loading and EDF (Électricité de France) data-based grid-load-following (EDF-GLF) loading cycles. 4) System level thermal-mechanical stress analysis was performed for identifying damage-prone hotspots and for future extension of the model for cyclic state prediction. From the system-level model simulation under DB loading cycle it is found that HL and the SL nozzle that connect to the HL can experience significant stress and strain and could be one of the weakest links in the overall reactor coolant system (RCS). 5) An AI/ML based DT model was developed for multi-time-series temperature prediction at any inside/outside thickness locations of PWR pressure boundary components. This is by using Recurrent-neural-network (RNN) and keras machine learning libraries. The RNN model was validated against two laboratory test-based data sets with one obtained through ANL’s in-air fatigue test system and other through PWR-water test loop. The experimentally validated DT model further validated against FE model results to predict thermal scarification related spatialtemporal temperatures at random locations of a component. The well validated DT model was then used for demonstrating spatial-temporal temperature prediction under 100+ years of reactor operation subjected to combined DB, EDF-GLF and randomized grid-load-following (RANDOMGLF) loading Cycles. The expert-elicitation DT model framework was developed assuming field/input/process measurements can be available from a few existing plant sensors and can readily be used by the NPP operators. The above temperature prediction model will feed to the next-step stress analysis model based on which the life of a component can be predicted in realtime, which is one of our future works.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Modeling of Radiolytic Hydrogen Generation of Irradiated Surrogate Aluminum Plates

The hydrogen generation from oxyhydroxide layers under irradiation is an important effect to understand for the long-term storage of aluminum-clad spent nuclear fuel. The original chemical model shows steady production of hydrogen from aluminum oxyhydroxide layers, with no roll-over effect in the curves of the hydrogen concentration until significant pressure has built up within the canister. This study uses a variety of kinetic fits to adjust the old chemical model to have roll-over effects that are consistent with new high-dose experiments. The data from aluminum 6061 coupon tests at high doses were used to fit several kinetic models. The 6061 aluminum samples are representative of the aluminum-clad fuel from the ATR. The fitted kinetic models were then used in a model of a mini-canister with much higher packing density to determine which kinetic rates would fit both sets of experimental tests. The rate constants for the kinetic mechanisms that were close were then tweaked such that the chemical models fit both the experimental data from the capsule tests and the data from the mini-canister tests. The kinetic models which fit the best are either inhibition by hydrogen, or a back reaction wherein H radical is reabsorbed onto the oxyhydroxide layer. The H back reaction rolls over quicker and may fit future collected data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗