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DOE OSTI2015

Critical points of metal vapors

A new method is proposed for calculating the parameters of critical points and binodals for the vapor–liquid (insulator–metal) phase transition in vapors of metals with multielectron valence shells. The method is based on a model developed earlier for the vapors of alkali metals, atomic hydrogen, and exciton gas, proceeding from the assumption that the cohesion determining the basic characteristics of metals under normal conditions is also responsible for their properties in the vicinity of the critical point. It is proposed to calculate the cohesion of multielectron atoms using well-known scaling relations for the binding energy, which are constructed for most metals in the periodic table by processing the results of many numerical calculations. The adopted model allows the parameters of critical points and binodals for the vapor–liquid phase transition in metal vapors to be calculated using published data on the properties of metals under normal conditions. The parameters of critical points have been calculated for a large number of metals and show satisfactory agreement with experimental data for alkali metals and with available estimates for all other metals. Binodals of metals have been calculated for the first time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

NREL Evaluates Performance of Hydraulic Hybrid Refuse Vehicles

This highlight describes NREL's evaluation of the in-service performance of 10 next-generation hydraulic hybrid refuse vehicles (HHVs), 8 previous-generation (model year 2013) HHVs, and 8 comparable conventional diesel vehicles operated by Miami-Dade County's Public Works and Waste Management Department in southern Florida. Launched in March 2015, the on-road portion of this 12-month evaluation focuses on collecting and analyzing vehicle performance data - fuel economy, maintenance costs, and drive cycles - from the HHVs and the conventional diesel vehicles. The fuel economy of heavy-duty vehicles, such as refuse trucks, is largely dependent on the load carried and the drive cycles on which they operate. In the right applications, HHVs offer a potential fuel-cost advantage over their conventional counterparts. This advantage is contingent, however, on driving behavior and drive cycles with high kinetic intensity that take advantage of regenerative braking. NREL's evaluation will assess the performance of this technology in commercial operation and help Miami-Dade County determine the ideal routes for maximizing the fuel-saving potential of its HHVs. Based on the field data, NREL will develop a validated vehicle model using the Future Automotive Systems Technology Simulator, also known as FASTSim, to study the impacts of route selection and other vehicle parameters. NREL is also analyzing fueling and maintenance data to support total-cost-of-ownership estimations and forecasts. The study aims to improve understanding of the overall usage and effectiveness of HHVs in refuse operation compared to similar conventional vehicles and to provide unbiased technical information to interested stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Optimisation of the Search for CP-symmetry Violation at the Deep Underground Neutrino Experiment

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long baseline experiment, which will be situated in South Dakota. Its detectors will utilise liquid-argon time projection chamber technology, which is able to capture neutrino interactions with an incredible spatial and calorimetric resolution. With what will become the world’s most intense neutrino beam, a highly capable near detector, and four (10kt fducial mass) far detector modules, DUNE will be able to achieve an ambitious physics programme. Most notably, DUNE will determine whether charge-parity symmetry is broken in neutrino oscillations - a finding that would have significant implications for the understanding of the matter-antimatter asymmetry in our Universe.This thesis presents the optimisation of a CP-violation analysis at DUNE using thePandora pattern-recognition software. The analysis assumes a 3.5 year exposure (1.36 × 1023 protons on target) to a neutrino and an antineutrino beam (7 year total). Only the predicted data of the far detector modules is used; near detector samples are not included. The initial sensitivity to CP-violation is found to be 3.8σ+0.9σ−1.1σ in an estimate that includes oscillation parameter uncertainties, systematic uncertainties and statistical fluctuations, and assumes a normal-ordering of the neutrino mass hierarchy. The performance of the Pandora event reconstruction is linked to that of the analysis, which is found to be limited by the reconstruction of the initial track-like region of electrons and photons. The ShowerRefinement algorithm is developed in response to this and its implementation into the analysis workflow results in an improved sensitivity to CP-violation of 4.6σ+0.9σ−1.0σ. With a perfected neutrino interaction vertex placement, this is further increased to 5.1σ+1.0σ−1.1σ.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Extrapolating Contaminant Effects from Individuals to Populations: A Case Study on Nanoparticle Toxicity to Daphnia Fed Environmentally Relevant Food Levels

Ecological risk assessment (ERA) is charged with assessing the likelihood a chemical will have adverse environmental or ecological effects. When assessing the risk of a potential contaminant to biological organisms, ecologists are most concerned with the sustainability of populations of organisms, rather than protecting every individual. However, ERA most commonly relies on data on the effect of a potential contaminant on individuals because these experiments are more feasible than costly population-level exposures. In this work, we address the challenge of extrapolating these individual-level results to predict population-level effects. Previous per-capita population growth rate estimates calculated from individual-level exposures of Daphnia pulicaria to silver nanoparticles (AgNPs) at different food rations predict a critical daily food requirement for daphnid populations exposed to 200 μg/L AgNPs to avoid extinction. To test this, we exposed daphnid populations to the same AgNP concentration at three different food inputs, with the lowest ration close to the extinction threshold predicted from data on individuals. The two populations with the higher food inputs persisted, and the population with the lowest food input went extinct after 50 days but did persist through two generations. Further, we demonstrate that we can extrapolate between these levels of biological organization by parameterizing an individual-level biomass model with data on individuals’ response to AgNPs and using these parameters to predict the outcome for control and AgNP-exposed populations. Key to successful extrapolation is careful modeling of temporal changes in resource density, driven by both the experimental protocols and feedback from the consumer. The implication for ecotoxicology is that estimates of extinction thresholds based on studies of individuals may be reliable predictors of population outcomes, but only with careful treatment of resource dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Measuring the thermal and ionization state of the low- z IGM using likelihood free inference

ABSTRACT We present a new approach to measure the power-law temperature density relationship $T=T_0 (\rho/ \bar{\rho })^{\gamma -1}$ and the UV background photoionization rate $\Gamma _{{{{\rm H\, {\small I}}}}{}}$ of the intergalactic medium (IGM) based on the Voigt profile decomposition of the Ly α forest into a set of discrete absorption lines with Doppler parameter b and the neutral hydrogen column density $N_{\rm H\, {\small I}}$. Previous work demonstrated that the shape of the $b-N_{{{{\rm H\, {\small I}}}}{}}$ distribution is sensitive to the IGM thermal parameters T0 and γ, whereas our new inference algorithm also takes into account the normalization of the distribution, i.e. the line-density dN/dz, and we demonstrate that precise constraints can also be obtained on $\Gamma _{{{{\rm H\, {\small I}}}}{}}$. We use density-estimation likelihood-free inference (DELFI) to emulate the dependence of the $b-N_{{{{\rm H\, {\small I}}}}{}}$ distribution on IGM parameters trained on an ensemble of 624 nyx hydrodynamical simulations at z = 0.1, which we combine with a Gaussian process emulator of the normalization. To demonstrate the efficacy of this approach, we generate hundreds of realizations of realistic mock HST/COS data sets, each comprising 34 quasar sightlines, and forward model the noise and resolution to match the real data. We use this large ensemble of mocks to extensively test our inference and empirically demonstrate that our posterior distributions are robust. Our analysis shows that by applying our new approach to existing Ly α forest spectra at z ≃ 0.1, one can measure the thermal and ionization state of the IGM with very high precision ($\sigma _{\log T_0} \sim 0.08$ dex, σγ ∼ 0.06, and $\sigma _{\log \Gamma _{{{{\rm H\, {\small I}}}}{}}} \sim 0.07$ dex).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Unveiling acoustic physics of the CMB using nonparametric estimation of the temperature angular power spectrum for Planck

Estimation of the angular power spectrum is one of the important steps in Cosmic Microwave Background (CMB) data analysis. Here, we present a nonparametric estimate of the temperature angular power spectrum for the Planck 2013 CMB data. The method implemented in this work is model-independent, and allows the data, rather than the model, to dictate the fit. Since one of the main targets of our analysis is to test the consistency of the ΛCDM model with Planck 2013 data, we use the nuisance parameters associated with the best-fit ΛCDM angular power spectrum to remove foreground contributions from the data at multipoles ℓ ≥50. We thus obtain a combined angular power spectrum data set together with the full covariance matrix, appropriately weighted over frequency channels. Our subsequent nonparametric analysis resolves six peaks (and five dips) up to ℓ ∼1850 in the temperature angular power spectrum. We present uncertainties in the peak/dip locations and heights at the 95% confidence level. We further show how these reflect the harmonicity of acoustic peaks, and can be used for acoustic scale estimation. Based on this nonparametric formalism, we found the best-fit ΛCDM model to be at 36% confidence distance from the center of the nonparametric confidence set—this is considerably larger than the confidence distance (9%) derived earlier from a similar analysis of the WMAP 7-year data. Another interesting result of our analysis is that at low multipoles, the Planck data do not suggest any upturn, contrary to the expectation based on the integrated Sachs-Wolfe contribution in the best-fit ΛCDM cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Assessing Uncertainty and Repeatability in Time-Lapse VSP Monitoring of CO2 Injection in a Brine Aquifer, Frio Formation, Texas (A Case Study)

This study was done to assess the repeatability and uncertainty of time-lapse VSP response to CO 2 injection in the Frio formation near Houston Texas. A work flow was built to assess the effect of time-lapse injected CO 2 into two Frio brine reservoir intervals, the ‘C’ sand (Frio1) and the ‘Blue sand’ (Frio2). The time-lapse seismic amplitude variations with sensor depth for both reservoirs Frio1 and Frio2 were computed by subtracting the seismic response of the base survey from each of the two monitor seismic surveys. Source site 1 has been considered as one of the best sites for evaluating the time-lapse response after injection. For site 1, the computed timelapse NRMS levels after processing had been compared to the estimated time-lapse NRMS level before processing for different control reflectors, and for brine aquifers Frio1, and Frio2 to quantify detectability of amplitude difference. As the main interest is to analyze the time-lapse amplitude variations, different scenarios have been considered. Three different survey scenarios were considered: the base survey which was performed before injection, monitor1 performed after the first injection operation, and monitor2 which was after the second injection. The first scenario was base-monitor1, the second was basemonitor2, and the third was monitor1-monitor2. We considered three ‘control’ reflections above the Frio to assist removal of overburden changes, and concluded that third control reflector (CR3) is the most favorable for the first scenario in terms of NRMS response, and first control reflector (CR1) is the most favorable for the second and third scenarios in terms of NRMS response. The NRMS parameter is shown to be a useful measure to assess the effect of processing on time-lapse data. The overall NRMS for the Frio VSP data set was found to be in the range of 30% to 80% following basic processing. This could be considered as an estimated baseline in assessing the utility of VSP for CO 2 monitoring. This study shows that the CO 2 injection in brine reservoir Frio1 (the ‘C’ sand unit) does induce a relative change in amplitude response, and for Frio2 (the ‘Blue’ sand unit) an amplitude change has been also detected, but in both cases the uncertainty, as measured by NRMS indicates the reservoir changes are, at best, only slightly above the noise level, and often below the noise level of the overall data set.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Analysis Approach and Data Package for Mayak Public Doses: Data Supporting the Calculation of Representative Doses to Members of the Public from Airborne Releases of 131 I at the Mayak Production Association from 1948 through 1972

Historical activities at facilities producing nuclear materials for weapons released radioactivity into the air and water. Past studies in the United States have evaluated the release, atmospheric transport and environmental accumulation of 131 I from the nuclear facilities at Hanford in Washington State and the resulting dose to members of the public (Farris et al. 1994). A multi-year dose reconstruction effort (Mokrov et al. 2004) is also being conducted to produce representative dose estimates for members of the public living near Mayak, Russia, from atmospheric releases of 131 I at the facilities of the Mayak Production Association. The approach to calculating individual doses to members of the public from historical releases of airborne 131 I has the following general steps: • Construct estimates of releases 131 I to the air from production facilities. • Model the transport of 131 I in the air and subsequent deposition on the ground and vegetation. • Model the accumulation of 131 I in soil, water and food products (environmental media). • Calculate the dose for an individual by matching the appropriate lifestyle and consumption data for the individual to the concentrations of 131 I in environmental media at their residence location. A number of computer codes were developed to facilitate the study of airborne 131 I emissions at Hanford. Of particular interest is DESCARTES code that modeled accumulation of 131 I in environmental media (Miley et al. 1994). In addition, the CIDER computer code estimated annual doses to individuals (Eslinger et al. 1994) using the equations and parameters specific to Hanford (Snyder et al. 1994). Several of the computer codes developed to model 131 I releases from Hanford are general enough to be used for other facilities. Additional codes have been developed, including the new individual dose code CiderF (Eslinger and Napier 2013), and applied to historical releases of 131 I from Mayak. This document provides a data package that identifies computer code runs and associated input and output files prepared for the purpose of calculating doses to members of the public from atmospheric releases of 131 I at the Mayak Production Association for the time period 1948 through 1972.

Mayak↗

DOE OSTI2022

A Reanalysis of Public Galactic Bulge Gravitational Microlensing Events from OGLE-III and -IV

Abstract Modern surveys of gravitational microlensing events have progressed to detecting thousands per year, and surveys are capable of probing Galactic structure, stellar evolution, lens populations, black hole physics, and the nature of dark matter. One of the key avenues for doing this is the microlensing Einstein radius crossing time (t E) distribution. However, systematics in individual light curves as well as oversimplistic modeling can lead to biased results. To address this, we developed a model to simultaneously handle the microlensing parallax due to Earth's motion, systematic instrumental effects, and unlensed stellar variability with a Gaussian process model. We used light curves for nearly 10,000 OGLE-III and -IV Milky Way bulge microlensing events and fit each with our model. We also developed a forward model approach to infer the t E distribution by forward modeling from the data rather than using point estimates from individual events. We find that modeling the variability in the baseline removes a source of significant bias in individual events, and the previous analyses overestimated the number of t E > 100 day events due to their oversimplistic model ignoring parallax effects. We use our fits to identify the hundreds filling a regime in the microlensing parameter space that are 50% pure of black holes. Finally, we have released the largest-ever catalog of Markov Chain Monte Carlo parameter estimates for microlensing events.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Statistical tests of galactic dynamo theory

Mean-field galactic dynamo theory is the leading theory to explain the prevalence of regular magnetic fields in spiral galaxies, but its systematic comparison with observations is still incomplete and fragmentary. Here we compare predictions of mean-field dynamo models to observational data on magnetic pitch angle and the strength of the mean magnetic field. We demonstrate that a standard α{sup 2}Ω dynamo model produces pitch angles of the regular magnetic fields of nearby galaxies that are reasonably consistent with available data. The dynamo estimates of the magnetic field strength are generally within a factor of a few of the observational values. Reasonable agreement between theoretical and observed pitch angles generally requires the turbulent correlation time τ to be in the range of 10–20 Myr, in agreement with standard estimates. Moreover, good agreement also requires that the ratio of the ionized gas scale height to root-mean-square turbulent velocity increases with radius. Our results thus widen the possibilities to constrain interstellar medium parameters using observations of magnetic fields. This work is a step toward systematic statistical tests of galactic dynamo theory. Such studies are becoming more and more feasible as larger data sets are acquired using current and up-and-coming instruments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Inverse Modeling of Hydrologic Parameters Using Surface Flux and Runoff Observations in the Community Land Model

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC) - Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent - as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to the different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

inverse, modeling, hydrologic, parameters, flux, r↗

DOE OSTI2016

TH-CD-207A-05: Lung Surface Deformation Vector Fields Prediction by Monitoring Respiratory Surrogate Signals

Purpose: In this study, we developed and evaluated a method for predicting lung surface deformation vector fields (SDVFs) based on surrogate signals such as chest and abdomen motion at selected locations and spirometry measurements. Methods: A Patient-specific 3D triangular surface mesh of the lung region at end-expiration (EE) phase was obtained by threshold-based segmentation method. For each patient, a spirometer recorded the flow volume changes of the lungs; and 192 selected points at a regular spacing of 2cm X 2cm matrix points over a total area of 34cm X 24cm on the surface of chest and abdomen was used to detect chest wall motions. Preprocessing techniques such as QR factorization with column pivoting (QRCP) were employed to remove redundant observations of the chest and abdominal area. To create a statistical model between the lung surface and the corresponding surrogate signals, we developed a predictive model based on canonical ridge regression (CRR). Two unique weighting vectors were selected for each vertex on the surface of the lung, and they were optimized during the training process using the all other phases of 4D-CT except the end-inspiration (EI) phase. These parameters were employed to predict the vertices locations of a testing data set, which was the EI phase of 4D-CT. Results: For ten lung cancer patients, the deformation vector field of each vertex of lung surface mesh was estimated from the external motion at selected positions on the chest wall surface plus spirometry measurements. The average estimation of 98th percentile of error was less than 1 mm (AP= 0.85, RL= 0.61, and SI= 0.82). Conclusion: The developed predictive model provides a non-invasive approach to derive lung boundary condition. Together with personalized biomechanical respiration modelling, the proposed model can be used to derive the lung tumor motion during radiation therapy accurately from non-invasive measurements.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Bayesian Physics Informed Spatio-Temporal Network for Streamflow Data Imputation

Reliable reconstruction of incomplete streamflow records is critical for improving hydrological forecasting, flood preparedness, and water resource management. However, large observational gaps and uncertainties in governing physical parameters limit the accuracy of traditional statistical and machinelearning imputation frameworks. To address these challenges, we develop a Bayesian Physics-Informed Spatio-Temporal Network (BPI-STNet) that jointly captures spatial and temporal dependencies while enforcing hydrologic consistency through embedded physical constraints. The framework integrates a GraphSAGE-LSTM architecture to model spatial connectivity across gauges and temporal flow dynamics, coupled with a Bayesian update mechanism to estimate uncertain parameters in a simplified water-balance framework. Unlike conventional physics-informed networks that rely on sampling-based posterior estimation, BPI-STNet derives an analytic solution to the inverse problem, allowing closed-form Bayesian updates of uncertain parameters Λ={α,β,k} using Gaussian priors and likelihoods. Applied to daily observations from the Susquehanna River Basin (1980-2022), BPI-STNet achieves substantial improvements over a purely data-driven RGNN baseline, which reduced RMSE by 23 % and MAE by 9 %, and achieving an average NSE values up to 0.96. The results demonstrate that coupling Bayesian inference with physics-informed learning yields physically consistent, uncertainty-aware reconstructions that preserve the temporal persistence and statistical distribution of observed flows. The proposed framework establishes a generalizable paradigm for data-sparse hydrologic systems where both data fidelity and physical interpretability are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗

DOE OSTI2021

Magnetic structure, excitations and short-range order in honeycomb Na 2 Ni 2 TeO 6

Na 2 Ni 2 TeO 6 has a layered hexagonal structure with a honeycomb lattice constituted by Ni 2+ and a chiral charge distribution of Na + that resides between the Ni layers. In the present work, the antiferromagnetic transition temperature of Na 2 Ni 2 TeO 6 is confirmed at TN˜ 27 K, and further, it is found to be robust up to 8 T magnetic field and 1.2 GPa external pressure; and, without any frequency-dependence. Slight deviations from nominal Na-content (up to 5%) does not seem to influence the magnetic transition temperature, TN. Isothermal magnetization curves remain almost linear up to 13 T. Our analysis of neutron diffraction data shows that the magnetic structure of Na 2 Ni 2 TeO 6 is faithfully described by a model consisting of two phases described by the commensurate wave vectors vec kc, (0.5 0 0) and (0.5 0 0.5), with an additional short-range order component incorporated in to the latter phase. Consequently, a zig-zag long-range ordered magnetic phase of Ni 2+ results in the compound, mixed with a short-range ordered phase, which is supported by our specific heat data. Theoretical computations based on density functional theory (DFT) predict predominantly in-plane magnetic exchange interactions that conform to a J1-J2-J3 model with a strong J3 term. The computationally predicted parameters lead to a reliable estimate for TN and the experimentally observed zig-zag magnetic structure. A spin wave excitation in Na 2 Ni 2 TeO 6 at E ˜ 5 meV at T = 5 K is mapped out through inelastic neutron scattering experiments, which is reproduced by linear spin wave theory calculations using the J values from our computations. Our specific heat data and inelastic neutron scattering data strongly indicate the presence of short-range spin correlations, at T > TN, stemming from incipient antiferromagnetic clusters.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Performance-based earthquake early warning for tall buildings

The ShakeAlert Earthquake Early Warning (EEW) system aims to issue an advance warning to residents on the West Coast of the United States seconds before the ground shaking arrives, if the expected ground shaking exceeds a certain threshold. However, residents in tall buildings may experience much greater motion due to the dynamic response of the buildings. Therefore, there is an ongoing effort to extend ShakeAlert to include the contribution of building response to provide a more accurate estimation of the expected shaking intensity for tall buildings. Currently, the supposedly ideal solution of analyzing detailed finite element models of buildings under predicted ground-motion time histories is not theoretically or practically feasible. The authors have recently investigated existing simple methods to estimate peak floor acceleration (PFA) and determined these simple formulas are not practically suitable. Instead, this article explores another approach by extending the Pacific Earthquake Engineering Research Center (PEER) performance-based earthquake engineering (PBEE) to EEW, considering that every component involved in building response prediction is uncertain in the EEW scenario. Additionally, while this idea is not new and has been proposed by other researchers, it has two shortcomings: (1) the simple beam model used for response prediction is prone to modeling uncertainty, which has not been quantified, and (2) the ground motions used for probabilistic demand models are not suitable for EEW applications. In this article, we address these two issues by incorporating modeling errors into the parameters of the beam model and using a new set of ground motions, respectively. We demonstrate how this approach could practically work using data from a 52-story building in downtown Los Angeles. Using the criteria and thresholds employed by previous researchers, we show that if peak ground acceleration (PGA) is accurately estimated, this approach can predict the expected level of human comfort in tall buildings.

58 GEOSCIENCES↗

DOE OSTI2013

Spatial frequency spectrum of the x-ray scatter distribution in CBCT projections

Purpose: X-ray scatter is a source of significant image quality loss in cone-beam computed tomography (CBCT). The use of Monte Carlo (MC) simulations separating primary and scattered photons has allowed the structure and nature of the scatter distribution in CBCT to become better elucidated. This work seeks to quantify the structure and determine a suitable basis function for the scatter distribution by examining its spectral components using Fourier analysis.Methods: The scatter distribution projection data were simulated using a CBCT MC model based on the EGSnrc code. CBCT projection data, with separated primary and scatter signal, were generated for a 30.6 cm diameter water cylinder [single angle projection with varying axis-to-detector distance (ADD) and bowtie filters] and two anthropomorphic phantoms (head and pelvis, 360 projections sampled every 1°, with and without a compensator). The Fourier transform of the resulting scatter distributions was computed and analyzed both qualitatively and quantitatively. A novel metric called the scatter frequency width (SFW) is introduced to determine the scatter distribution's frequency content. The frequency content results are used to determine a set basis functions, consisting of low-frequency sine and cosine functions, to fit and denoise the scatter distribution generated from MC simulations using a reduced number of photons and projections. The signal recovery is implemented using Fourier filtering (low-pass Butterworth filter) and interpolation. Estimates of the scatter distribution are used to correct and reconstruct simulated projections.Results: The spatial and angular frequencies are contained within a maximum frequency of 0.1 cm{sup −1} and 7/(2π) rad{sup −1} for the imaging scenarios examined, with these values varying depending on the object and imaging setup (e.g., ADD and compensator). These data indicate spatial and angular sampling every 5 cm and π/7 rad (∼25°) can be used to properly capture the scatter distribution, with reduced sampling possible depending on the imaging scenario. Using a low-pass Butterworth filter, tuned with the SFW values, to denoise the scatter projection data generated from MC simulations using 10{sup 6} photons resulted in an error reduction of greater than 85% for the estimating scatter in single and multiple projections. Analysis showed that the use of a compensator helped reduce the error in estimating the scatter distribution from limited photon simulations by more than 37% when compared to the case without a compensator for the head and pelvis phantoms. Reconstructions of simulated head phantom projections corrected by the filtered and interpolated scatter estimates showed improvements in overall image quality.Conclusions: The spatial frequency content of the scatter distribution in CBCT is found to be contained within the low frequency domain. The frequency content is modulated both by object and imaging parameters (ADD and compensator). The low-frequency nature of the scatter distribution allows for a limited set of sine and cosine basis functions to be used to accurately represent the scatter signal in the presence of noise and reduced data sampling decreasing MC based scatter estimation time. Compensator induced modulation of the scatter distribution reduces the frequency content and improves the fitting results.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Dark Energy Survey Year 3 results: calibration of lens sample redshift distributions using clustering redshifts with BOSS/eBOSS

ABSTRACT We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies used in weak gravitational lensing and galaxy clustering studies. To perform these measurements, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrate systematic errors that result from the galaxy clustering bias, and we find that our method is generally unbiased in calibrating the mean redshift. We apply our method to the data, and estimate the redshift distribution for 11 different photometrically selected bins. We find general agreement between clustering redshift and photometric redshift estimates, with differences on the inferred mean redshift found to be below |Δz| = 0.01 in most of the bins. We also test a method to calibrate a width parameter for redshift distributions, which we found necessary to use for some of our samples. Our typical uncertainties on the mean redshift ranged from 0.003 to 0.008, while our uncertainties on the width ranged from 4 to 9 per cent. We discuss how these results calibrate the photometric redshift distributions used in companion papers for DES Year 3 results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Petroleum Refinery Jobs and Economic Development Impact (JEDI) Model User Reference Guide

The Jobs and Economic Development Impact (JEDI) models, developed through the National Renewable Energy Laboratory (NREL), are user-friendly tools utilized to estimate the economic impacts at the local level of constructing and operating fuel and power generation projects for a range of conventional and renewable energy technologies. The JEDI Petroleum Refinery Model User Reference Guide was developed to assist users in employing and understanding the model. This guide provides information on the model's underlying methodology, as well as the parameters and references used to develop the cost data utilized in the model. This guide also provides basic instruction on model add-in features, operation of the model, and a discussion of how the results should be interpreted. Based on project-specific inputs from the user, the model estimates job creation, earning and output (total economic activity) for a given petroleum refinery. This includes the direct, indirect and induced economic impacts to the local economy associated with the refinery's construction and operation phases. Project cost and job data used in the model are derived from the most current cost estimations available. Local direct and indirect economic impacts are estimated using economic multipliers derived from IMPLAN software. By determining the regional economic impacts and job creation for a proposed refinery, the JEDI Petroleum Refinery model can be used to field questions about the added value refineries may bring to the local community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗