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DOE OSTI2020

Windowed Fourier transform and cross-correlation algorithms for molecular tagging velocimetry

In this study, simulated and experimental molecular tagging velocimetry (MTV) images have been analyzed with a technique commonly used to process grid images on surfaces, the windowed Fourier transform with local spectrum analysis (WFT-LSA). A systematic synthetic image study of the modulation transfer function (MTF) and error tendencies of the WFT-LSA was performed and compared with a PIV-style cross-correlation algorithm to see if advanced strategies such as iterative image deformation can improve analysis of gridded images with high noise levels. Testing of single-pass algorithms showed that in typical MTV images, the WFT-LSA yields significantly lower bias errors than cross-correlation (CC) at displacements greater than 1 pixel but slightly higher random error at all displacements and image conditions. Analysis of the MTF shows that CC provided better resolution of spatial fluctuations than the WFT-LSA in many combinations of grid size and interrogation window. Tests of image deformation algorithms showed that the gap in performance between CC and WFT-LSA is maintained even as both methods improve. Additionally, WFT-LSA and CC methods are applied to real MTV experiments in high-speed gas jet flows. A preliminary analysis of phosphorescence lifetime provided by acetone vapor excited at 266 nm is used for assessing the required gas speeds for making MTV application feasible. The application of WFT-LSA to real MTV images demonstrates the ability of the algorithm to handle further real-world effects that could not be considered in the synthetic image analysis, like reduced signal-to-noise ratio and non-uniform intensity of the tagging grid across the image introduced by the actual laser beam energy distribution. With experimental images, CC is more accurate with shear flows but less robust to high noise levels than WFT-LSA, as predicted by the synthetic image analysis.

42 ENGINEERING↗

DOE OSTI2026

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗

DOE OSTI2022

Photometric redshift uncertainties in weak gravitational lensing shear analysis: models and marginalization

ABSTRACT Recovering credible cosmological parameter constraints in a weak lensing shear analysis requires an accurate model that can be used to marginalize over nuisance parameters describing potential sources of systematic uncertainty, such as the uncertainties on the sample redshift distribution n(z). Due to the challenge of running Markov chain Monte Carlo (MCMC) in the high-dimensional parameter spaces in which the n(z) uncertainties may be parametrized, it is common practice to simplify the n(z) parametrization or combine MCMC chains that each have a fixed n(z) resampled from the n(z) uncertainties. In this work, we propose a statistically principled Bayesian resampling approach for marginalizing over the n(z) uncertainty using multiple MCMC chains. We self-consistently compare the new method to existing ones from the literature in the context of a forecasted cosmic shear analysis for the HSC three-year shape catalogue, and find that these methods recover statistically consistent error bars for the cosmological parameter constraints for predicted HSC three-year analysis, implying that using the most computationally efficient of the approaches is appropriate. However, we find that for data sets with the constraining power of the full HSC survey data set (and, by implication, those upcoming surveys with even tighter constraints), the choice of method for marginalizing over n(z) uncertainty among the several methods from the literature may modify the 1σ uncertainties on Ωm–S8 constraints by ∼4 per cent, and a careful model selection is needed to ensure credible parameter intervals.

Zhang, Tianqing (ORCID:000000025596198X)↗

DOE OSTI2022

Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data

Today's scientific simulations and instruments are producing a large amount of data, leading to difficulties in storing, transmitting, and analyzing these data. While error-controlled lossy compressors are effective in significantly reducing data volumes and efficiently developing databases for multiple scientific applications, they mainly support error controls on raw data, which leaves a significant gap between the data and user's downstream analysis. This may cause unqualified uncertainties in the outcomes of the analysis, a.k.a quantities of interest (QoIs), which are the major concerns of users in adopting lossy compression in practice. In this paper, we propose rigorous mathematical theories to preserve four families of QoIs that are widely used in scientific analysis during lossy compression along with practical implementations. Specifically, we first develop the error control theory for univariate QoIs which are essential for computing physical properties such as kinetic energy, followed by multivariate QoIs that are more commonly used in real-world applications. The proposed method is integrated into a state-of-the-art compression framework in a modular fashion, which could easily adapt to new QoIs and new compression algorithms. Experiments on real-world datasets demonstrate that the proposed method provides faithful error control on important QoIs including kinetic energy, regional average, and isosurface without trials and errors, while offering compression ratios that are up to 4x of the compression ratios provided by state-of-the-art compressors.

Jiao, Pu↗

DOE OSTI2016

SU-G-BRA-02: Development of a Learning Based Block Matching Algorithm for Ultrasound Tracking in Radiotherapy

Purpose: To develop an ultrasound learning-based tracking algorithm with the potential to provide real-time motion traces of anatomy-based fiducials that may aid in the effective delivery of external beam radiation. Methods: The algorithm was developed in Matlab R2015a and consists of two main stages: reference frame selection, and localized block matching. Immediately following frame acquisition, a normalized cross-correlation (NCC) similarity metric is used to determine a reference frame most similar to the current frame from a series of training set images that were acquired during a pretreatment scan. Segmented features in the reference frame provide the basis for the localized block matching to determine the feature locations in the current frame. The boundary points of the reference frame segmentation are used as the initial locations for the block matching and NCC is used to find the most similar block in the current frame. The best matched block locations in the current frame comprise the updated feature boundary. The algorithm was tested using five features from two sets of ultrasound patient data obtained from MICCAI 2014 CLUST. Due to the lack of a training set associated with the image sequences, the first 200 frames of the image sets were considered a valid training set for preliminary testing, and tracking was performed over the remaining frames. Results: Tracking of the five vessel features resulted in an average tracking error of 1.21 mm relative to predefined annotations. The average analysis rate was 15.7 FPS with analysis for one of the two patients reaching real-time speeds. Computations were performed on an i5-3230M at 2.60 GHz. Conclusion: Preliminary tests show tracking errors comparable with similar algorithms at close to real-time speeds. Extension of the work onto a GPU platform has the potential to achieve real-time performance, making tracking for therapy applications a feasible option. This work is partially funded by NIH grant R01CA190298.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Extended forward sensitivity analysis of one-dimensional isothermal flow

Sensitivity analysis and uncertainty quantification is an important part of nuclear safety analysis. In this work, forward sensitivity analysis is used to compute solution sensitivities on 1-D fluid flow equations typical of those found in system level codes. Time step sensitivity analysis is included as a method for determining the accumulated error from time discretization. The ability to quantify numerical error arising from the time discretization is a unique and important feature of this method. By knowing the relative sensitivity of time step with other physical parameters, the simulation is allowed to run at optimized time steps without affecting the confidence of the physical parameter sensitivity results. The time step forward sensitivity analysis method can also replace the traditional time step convergence studies that are a key part of code verification with much less computational cost. One well-defined benchmark problem with manufactured solutions is utilized to verify the method; another test isothermal flow problem is used to demonstrate the extended forward sensitivity analysis process. Through these sample problems, the paper shows the feasibility and potential of using the forward sensitivity analysis method to quantify uncertainty in input parameters and time step size for a 1-D system-level thermal-hydraulic safety code. (authors)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Evaluating IMRT and VMAT dose accuracy: Practical examples of failure to detect systematic errors when applying a commonly used metric and action levels

Purpose: This study (1) examines a variety of real-world cases where systematic errors were not detected by widely accepted methods for IMRT/VMAT dosimetric accuracy evaluation, and (2) drills-down to identify failure modes and their corresponding means for detection, diagnosis, and mitigation. The primary goal of detailing these case studies is to explore different, more sensitive methods and metrics that could be used more effectively for evaluating accuracy of dose algorithms, delivery systems, and QA devices.Methods: The authors present seven real-world case studies representing a variety of combinations of the treatment planning system (TPS), linac, delivery modality, and systematic error type. These case studies are typical to what might be used as part of an IMRT or VMAT commissioning test suite, varying in complexity. Each case study is analyzed according to TG-119 instructions for gamma passing rates and action levels for per-beam and/or composite plan dosimetric QA. Then, each case study is analyzed in-depth with advanced diagnostic methods (dose profile examination, EPID-based measurements, dose difference pattern analysis, 3D measurement-guided dose reconstruction, and dose grid inspection) and more sensitive metrics (2% local normalization/2 mm DTA and estimated DVH comparisons).Results: For these case studies, the conventional 3%/3 mm gamma passing rates exceeded 99% for IMRT per-beam analyses and ranged from 93.9% to 100% for composite plan dose analysis, well above the TG-119 action levels of 90% and 88%, respectively. However, all cases had systematic errors that were detected only by using advanced diagnostic techniques and more sensitive metrics. The systematic errors caused variable but noteworthy impact, including estimated target dose coverage loss of up to 5.5% and local dose deviations up to 31.5%. Types of errors included TPS model settings, algorithm limitations, and modeling and alignment of QA phantoms in the TPS. Most of the errors were correctable after detection and diagnosis, and the uncorrectable errors provided useful information about system limitations, which is another key element of system commissioning.Conclusions: Many forms of relevant systematic errors can go undetected when the currently prevalent metrics for IMRT/VMAT commissioning are used. If alternative methods and metrics are used instead of (or in addition to) the conventional metrics, these errors are more likely to be detected, and only once they are detected can they be properly diagnosed and rooted out of the system. Removing systematic errors should be a goal not only of commissioning by the end users but also product validation by the manufacturers. For any systematic errors that cannot be removed, detecting and quantifying them is important as it will help the physicist understand the limits of the system and work with the manufacturer on improvements. In summary, IMRT and VMAT commissioning, along with product validation, would benefit from the retirement of the 3%/3 mm passing rates as a primary metric of performance, and the adoption instead of tighter tolerances, more diligent diagnostics, and more thorough analysis.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2015

On the uncertainty of temperature estimation in a rapid compression machine

Rapid compression machines (RCMs) have been widely used in the combustion literature to study the low-to-intermediate temperature ignition of many fuels. In a typical RCM, the pressure during and after the compression stroke is measured. Yet, measurement of the temperature history in the RCM reaction chamber is challenging. Thus, the temperature is generally calculated by the isentropic relations between pressure and temperature, assuming that the adiabatic core hypothesis holds. To estimate the uncertainty in the calculated temperature, an uncertainty propagation analysis must be carried out. Our previous analyses assumed that the uncertainties of the parameters in the equation to calculate the temperature were normally distributed and independent, but these assumptions do not hold for typical RCM operating procedures. Here, a Monte Carlo method is developed to estimate the uncertainty in the calculated temperature, while taking into account the correlation between parameters and the possibility of non-normal probability distributions. In addition, the Monte Carlo method is compared to an analysis that assumes normally distributed, independent parameters. Both analysis methods show that the magnitude of the initial pressure and the uncertainty of the initial temperature have strong influences on the magnitude of the uncertainty. Finally, the uncertainty estimation methods studied here provide a reference value for the uncertainty of the reference temperature in an RCM and can be generalized to other similar facilities.

42 ENGINEERING↗

DOE OSTI2022

Bayesian estimation of cross-section and errors of experiment and calculation for accurate prediction of neutronic characteristics

In some experiments, there might be a correlation of experimental errors such as an error caused by fabrication. The correlation of calculation errors also might exist among analyses of experiments. In the present study, considering these correlations, the cross-section and errors of experiment and calculation are adjusted for the accurate prediction of neutronic characteristics. The adjustment method is derived based on Bayesian theory. The 'a posteriori' distributions of cross-section and errors of experiment and calculation are obtained by the derivation. The case study is performed by using the benchmarks of light-water moderated experiments reported in ICSBEP. The error from fuel rod fabrication and measurement are included in the experiment error, and the error from the simplification of the benchmark model is included in the calculation error. Since these errors have a positive correlation among the benchmarks, the prediction accuracy is expected to be improved by considering these correlations. For the sensitivity analysis of the correlation among benchmarks, the correlation coefficient of experiment error and that of calculation error is assumed from 0.0 to 0.9. The results indicate that the prediction accuracy of the multiplication factor can be improved by increasing the correlation coefficient of experiment error and that of calculation error. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Modeling noise in global Mølmer-Sørensen interactions applied to quantum approximate optimization

Many-qubit Mølmer-Sørensen (MS) interactions applied to trapped ions offer unique capabilities for quantum information processing, with applications including quantum simulation and the quantum approximate optimization algorithm (QAOA). Here, we develop a physical model to describe many-qubit MS interactions under four sources of experimental noise: vibrational mode frequency fluctuations, laser power fluctuations, thermal initial vibrational states, and state preparation and measurement errors. The model parametrizes these errors from simple experimental measurements, without free parameters. Herein, we validate the model in comparison with experiments that implement sequences of MS interactions on two 171 Yb + ions. The model shows reasonable agreement after several MS interactions as quantified by the reduced chi-squared statistic $χ^{2}_{red}$≈2. As an application we examine MaxCut QAOA experiments on three and six ions. The experimental performance is quantified by approximation ratios that are 91% and 83% of the optimal theoretical values. Our model predicts $0.93^{+0.03}_{-0.02}$ and $0.95^{+0.04}_{-0.03}$, respectively, with disagreement in the latter value attributable to secondary noise sources beyond those considered in our analysis. With realistic experimental improvements to reduce measurement error and radial trap frequency variations, the model achieves approximation ratios that are 99% of the optimal. Incorporating these improvements into future experiments is expected to reveal new aspects of noise for future modeling and experimental improvements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Mass Variance from Archival X-ray Properties of Dark Energy Survey Year-1 Galaxy Clusters

Using archival X-ray observations and a log-normal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behavior of X-ray temperatures, $T_X$, with optical richness, $\lambda_{RM}$, for clusters in the redshift range $0.2 50\%$ complete for clusters with $\lambda_{RM} > 130$. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, $\sigma_{\ln Tx | \lambda} = 0.275 \pm 0.019$. Joined with constraints for $T_X$ scaling with halo mass from the Weighing the Giants program and richness--temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, $\sigma_{\ln M | \lambda} = 0.30 \pm 0.04\, _{({\rm stat})} \pm 0.09\, _{({\rm sys})}$, at an optical richness of approximately 70. Uncertainties in external parameters, particularly the slope and variance of the $T_X$--mass relation and the covariance of $T_X$ and $\lambda_{RM}$ at fixed mass, dominate the systematic error. The $95\%$ confidence region from joint sample analysis is relatively broad, $\sigma_{\ln M | \lambda} \in [0.14, \, 0.55]$, or a factor ten in variance.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Criteria for stochastic pinning control of networks of chaotic maps

This paper investigates the controllability of discrete-time networks of coupled chaotic maps through stochastic pinning. In this control scheme, the network dynamics are steered towards a desired trajectory through a feedback control input that is applied stochastically to the network nodes. The network controllability is studied by analyzing the local mean square stability of the error dynamics with respect to the desired trajectory. Through the analysis of the spectral properties of salient matrices, a toolbox of conditions for controllability are obtained, in terms of the dynamics of the individual maps, algebraic properties of the network, and the probability distribution of the pinning control. We demonstrate the use of these conditions in the design of a stochastic pinning control strategy for networks of Chirikov standard maps. To elucidate the applicability of the approach, we consider different network topologies and compare five different stochastic pinning strategies through extensive numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Using Gaia DR2 to constrain local dark matter density and thin dark disk

We use stellar kinematics from the latest Gaia data release (DR2) to measure the local dark matter (DM) density ρ DM in a heliocentric cylinder of radius R= 150 pc and half-height z= 200 pc. We also explore the prospect of using our analysis to estimate the DM density in local substructure by setting constraints on the surface density and scale height of a thin dark disk aligned with the baryonic disk and formed due to dissipative dark matter self-interactions. Performing the statistical analysis within a Bayesian framework for three types of tracers, we obtain ρDM = 0.016 ± 0.010 M ⊙ /pc 3 for A stars; early G stars give a similar result, while F stars yield a significantly higher value. For a thin dark disk, A stars set the strongest constraint: excluding surface densities (5–12) M ⊙ /pc 2 for scale heights below 100 pc with 95% confidence. The upper bound of this constraint implies ≲ 1% of the Milky Way DM mass is present in a dissipative dark sector. Comparing our results with those derived using Tycho-Gaia Astrometric Solution (TGAS) data, we find that the uncertainty in our measurements of the local DM content is dominated by systematic errors that arise from assumptions of our dynamical analysis in the low z region. Furthermore, there will only be a marginal reduction in these uncertainties with more data in the Gaia era. We comment on the robustness of our method and discuss potential improvements for future work.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Planck constraints on holographic dark energy

We perform a detailed investigation on the cosmological constraints on the holographic dark energy (HDE) model by using the Plank data. We find that HDE can provide a good fit to the Plank high-l (l ∼> 40) temperature power spectrum, while the discrepancy at l ≅ 20-40 found in the ΛCDM model remains unsolved in the HDE model. The Plank data alone can lead to strong and reliable constraint on the HDE parameter c. At the 68% confidence level (CL), we obtain c = 0.508 ± 0.207 with Plank+WP+lensing, favoring the present phantom behavior of HDE at the more than 2σ CL. By combining Plank+WP with the external astrophysical data sets, i.e. the BAO measurements from 6dFGS+SDSS DR7(R)+BOSS DR9, the direct Hubble constant measurement result (H{sub 0} = 73.8 ± 2.4 kms{sup −1}Mpc{sup −1}) from the HST, the SNLS3 supernovae data set, and Union2.1 supernovae data set, we get the 68% CL constraint results c = 0.484 ± 0.070, 0.474 ± 0.049, 0.594 ± 0.051, and 0.642 ± 0.066, respectively. The constraints can be improved by 2%-15% if we further add the Plank lensing data into the analysis. Compared with the WMAP-9 results, the Plank results reduce the error by 30%-60%, and prefer a phantom-like HDE at higher significant level. We also investigate the tension between different data sets. We find no evident tension when we combine Plank data with BAO and HST. Especially, we find that the strong correlation between Ω{sub m}h{sup 3} and dark energy parameters is helpful in relieving the tension between the Plank and HST measurements. The residual value of χ{sup 2}{sub Plank+WP+HST}−χ{sup 2}{sub Plank+WP} is 7.8 in the ΛCDM model, and is reduced to 1.0 or 0.3 if we switch the dark energy to w model or the holographic model. When we introduce supernovae data sets into the analysis, some tension appears. We find that the SNLS3 data set is in tension with all other data sets; for example, for the Plank+WP, WMAP-9 and BAO+HST, the corresponding Δχ{sup 2} is equal to 6.4, 3.5 and 4.1, respectively. As a comparison, the Union2.1 data set is consistent with these three data sets, but the combination Union2.1+BAO+HST is in tension with Plank+WP+lensing, corresponding to a large Δχ{sup 2} that is equal to 8.6 (1.4% probability). Thus, combining internal inconsistent data sets (SNIa+BAO+HST with Plank+WP+lensing) can lead to ambiguous results, and it is necessary to perform the HDE data analysis for each independent data sets. Our tightest self-consistent constraint is c = 0.495 ± 0.039 obtained from Plank+WP+BAO+HST+lensing.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Preliminary Sensitivity Analysis for Sensors Impacts on Building Control Performance

This report describes the preliminary sensitivity analysis for sensor impacts on building control performance through the US Department of Energy’s Oak Ridge National Laboratory’s Flexible Research Platform (FRP-2) building. The rooftop unit system provides cooling and heating to the building. The main heating coil is a gas heating coil. Each zone is served by a variable air volume box with an electricity reheat coil. The rooftop unit and variable air volume box controls adopted the practical control sequences from ASHRAE Guideline 36-2018: High-Performance Sequences of Operation. For sensors, the incipient (time-changing) sensor errors, including bias sensor error and precision sensor error, are the inputs of interest. The outputs are energy consumption and thermal comfort (e.g., the predicted percentage of dissatisfied occupants). The large-scale simulation (3,600 cases) was conducted on a cloud platform by integrating sensor errors and ASHRAE Guideline 36 control sequences into an emulator based on the EnergyPlus simulation program with Python energy management system feature. The surrogate models were developed based on cloud simulation results. The uncertainty analysis showed that the sensor errors substantially affect building energy consumption and thermal comfort. The sensitivity analysis shows a ranking of sensor error impacts for each interested output item (e.g., cooling energy, reheat coil heating energy, predicted percentage of dissatisfied occupants). In FY 2022, sensor locations, types, and costs will be evaluated. The field test in Oak Ridge National Laboratory’s Flexible Research Platform building regarding sensor impacts will also be performed. Finally, a comparative analysis will be conducted based on the field test results and emulator results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Single-Isocenter Multiple-Target Stereotactic Radiosurgery: Risk of Compromised Coverage

Purpose: To determine the dosimetric effects of rotational errors on target coverage using volumetric modulated arc therapy (VMAT) for multitarget stereotactic radiosurgery (SRS). Methods and Materials: This retrospective study included 50 SRS cases, each with 2 intracranial planning target volumes (PTVs). Both PTVs were planned for simultaneous treatment to 21 Gy using a single-isocenter, noncoplanar VMAT SRS technique. Rotational errors of 0.5°, 1.0°, and 2.0° were simulated about all axes. The dose to 95% of the PTV (D95) and the volume covered by 95% of the prescribed dose (V95) were evaluated using multivariate analysis to determine how PTV coverage was related to PTV volume, PTV separation, and rotational error. Results: At 0.5° rotational error, D95 values and V95 coverage rates were ≥95% in all cases. For rotational errors of 1.0°, 7% of targets had D95 and V95 values <95%. Coverage worsened substantially when the rotational error increased to 2.0°: D95 and V95 values were >95% for only 63% of the targets. Multivariate analysis showed that PTV volume and distance to isocenter were strong predictors of target coverage. Conclusions: The effects of rotational errors on target coverage were studied across a broad range of SRS cases. In general, the risk of compromised coverage increased with decreasing target volume, increasing rotational error and increasing distance between targets. Multivariate regression models from this study may be used to quantify the dosimetric effects of rotational errors on target coverage given patient-specific input parameters of PTV volume and distance to isocenter.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

A Method for Assessing Ground-Truth Accuracy of the 5DCT Technique

Purpose: To develop a technique that assesses the accuracy of the breathing phase-specific volume image generation process by patient-specific breathing motion model using the original free-breathing computed tomographic (CT) scans as ground truths. Methods: Sixteen lung cancer patients underwent a previously published protocol in which 25 free-breathing fast helical CT scans were acquired with a simultaneous breathing surrogate. A patient-specific motion model was constructed based on the tissue displacements determined by a state-of-the-art deformable image registration. The first image was arbitrarily selected as the reference image. The motion model was used, along with the free-breathing phase information of the original 25 image datasets, to generate a set of deformation vector fields that mapped the reference image to the 24 nonreference images. The high-pitch helically acquired original scans served as ground truths because they captured the instantaneous tissue positions during free breathing. Image similarity between the simulated and the original scans was assessed using deformable registration that evaluated the pointwise discordance throughout the lungs. Results: Qualitative comparisons using image overlays showed excellent agreement between the simulated images and the original images. Even large 2-cm diaphragm displacements were very well modeled, as was sliding motion across the lung–chest wall boundary. The mean error across the patient cohort was 1.15 ± 0.37 mm, and the mean 95th percentile error was 2.47 ± 0.78 mm. Conclusion: The proposed ground truth–based technique provided voxel-by-voxel accuracy analysis that could identify organ-specific or tumor-specific motion modeling errors for treatment planning. Despite a large variety of breathing patterns and lung deformations during the free-breathing scanning session, the 5-dimensionl CT technique was able to accurately reproduce the original helical CT scans, suggesting its applicability to a wide range of patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

A systematic decision-making methodology to formalize the selection of degree of realism in screening analysis of probabilistic risk assessment

In the nuclear power domain, Probabilistic Risk Assessment (PRA) is used to inform decision-making for Nuclear Power Plants (NPPs). Recently, there has been an increase in the utilization of modeling and simulation (M&S) to support the estimation of PRA inputs. Risk analysts should carefully select the PRA items that require M&S and their degree of realism (DoR) with consideration of the required resources. To support this selection, this article formulates a systematic decision-making approach for the DoR selection. The DoR selection is made based on two predictive decision-making attributes: the predicted differences in safety risk estimate (ΔSaRi) and the cost of analysis (ΔCAN). This research also develops and quantifies causal models to estimate ΔSaRi and ΔCAN. The causal model-based prediction of ΔSaRi and ΔCAN helps reduce the trial-and-error nature of the DoR selection in the PRA screening analysis and provides insights for DoR selection and the gradual refinements of PRA realism. This approach is demonstrated for a case study on fire PRA of NPPs, where an adequate DoR is selected from two fire models: an engineering correlation and a zone model.

Alkhatib, Sari [Department of Nuclear, Plasma, and↗