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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis

This paper intends to reveal the ability of the linear interpolation method to predict missing values in solar radiation time series. Reliable dataset is equally tends to complete time series observed dataset. The absence or presence of radiation data alters long-term variation of solar radiation measurement values. Based on that change, the opportunities to provide bias output result for modelling and the validation process is higher. The completeness of the observed variable dataset has significantly important for data analysis. Occurrence the lack of continual and unreliable time series solar radiation data widely spread and become the main problematic issue. However, the limited number of research quantity that has carried out to emphasize and gives full attention to estimate missing values in the solar radiation dataset.

42 ENGINEERING↗
DOE OSTI2016

SU-G-IeP2-08: Investigation On Signal Detectability in Volumetric Cone Beam CT Images with Anatomical Background

Purpose: To investigate the slice direction dependent detectability in cone beam CT images with anatomical background. Methods: We generated 3D anatomical background images using breast anatomy model. To generate 3D breast anatomy, we filtered 3D Gaussian noise with a square root of 1/f{sup 3}, and then assigned the attenuation coefficient of glandular (0.8cm{sup −1}) and adipose (0.46 cm{sup −1}) tissues based on voxel values. Projections were acquired by forward projection, and quantum noise was added to the projection data. The projection data were reconstructed by FDK algorithm. We compared the detectability of a 3 mm spherical signal in the image reconstructed from four different backprojection Methods: Hanning weighted ramp filter with linear interpolation (RECON1), Hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON3), and ramp filter with Fourier interpolation (RECON4), respectively. We computed task SNR of the spherical signal in transverse and longitudinal planes using channelized Hotelling observer with Laguerre-Gauss channels. Results: Transverse plane has similar task SNR values for different backprojection methods, while longitudinal plane has a maximum task SNR value in RECON1. For all backprojection methods, longitudinal plane has higher task SNR than transverse plane. Conclusion: In this work, we investigated detectability for different slice direction in cone beam CT images with anatomical background. Longitudinal plane has a higher task SNR than transverse plane, and backprojection with hanning weighted ramp filter with linear interpolation method (i.e., RECON1) produced the highest task SNR among four different backprojection methods. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Programs(IITP-2015-R0346-15-1008) supervised by the IITP (Institute for Information & Communications Technology Promotion), Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the MSIP (2015R1C1A1A01052268) and framework of international cooperation program managed by NRF (NRF-2015K2A1A2067635).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-140: Dynamic Wave Arc Trajectory Verification Using KV X-Ray Fluoroscopy

Purpose: Purpose: This study investigates the geometric accuracy of simultaneous Gantry/Ring rotation during Dynamic Wave Arc (DWA) delivery. Methods: The Vero SBRT system consists of a 6MV LINAC mounted on an O-ring gantry that can rotate around the vertical axis (±60°), similar to couch rotation on C-arm gantries. To provide CBCT and fluoroscopy imaging functionalities, two orthogonal kV imaging units are attached to the O-ring at −45°/+45° from the beam axis.Dynamic Wave Arc maximizes Vero's motion capabilities by employing synchronized gantry and ring motion on a complex non-coplanar trajectory in combination with aperture based optimized MLC segments.Four wave arc trajectories (T1-4) were delivered using a cubic phantom with a configuration of five lead beads. O-ring gantry position information was retrieved through continuous dual-source kV X-ray image acquisition during DWA. An in-house algorithm read in the image set, extracted the projected marker positions and determined the angulation through reconstruction of the beam source position. The geometric error was quantified as the distance between the independently detected positions from kV-images and reference trajectory derived from the treatment plan in the Ring-Gantry space. Results: The average displacement between the 3D gantry/ring positions reconstructed from the fluoroscopy images and the reference trajectory was 0.346 mm (SD 0,171) for T1. A mean offset of 0.348 mm (SD 0,182) and 0.357 mm (SD 0.194) was observed for trajectory T2(2segmens) and T3(4segments), respectively. The saw shape T4 presented a mean geometric error of 0.363 (SD 0.156). The overall systematic error of 0.350 was caused by the difference between planned reference trajectory created by linear interpolation between CP, and the machine delivery following a spline curve. Conclusion: An independent geometric QA approach has been developed for DWA delivery verification, successfully applied on diverse trajectories and disclosed that the Vero system is capable of accurately follow complex trajectories.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Kernel reconstruction methods for Doppler broadening — Temperature interpolation by linear combination of reference cross sections at optimally chosen temperatures

This paper establishes a new family of methods to perform temperature interpolation of nuclear interactions cross sections, reaction rates, or cross sections times the energy. One of these quantities at temperature T is approximated as a linear combination of quantities at reference temperatures (T j ). The problem is formalized in a cross section independent fashion by considering the kernels of the different operators that convert cross section related quantities from a temperature T 0 to a higher temperature T — namely the Doppler broadening operation. Doppler broadening interpolation of nuclear cross sections is thus here performed by reconstructing the kernel of the operation at a given temperature T by means of linear combination of kernels at reference temperatures (T j ). The choice of the L 2 metric yields optimal linear interpolation coefficients in the form of the solutions of a linear algebraic system inversion. The optimization of the choice of reference temperatures (T j ) is then undertaken so as to best reconstruct, in the L∞ sense, the kernels over a given temperature range [T min ,T max ]. The performance of these kernel reconstruction methods is then assessed in light of previous temperature interpolation methods by testing them upon isotope 238 U. Temperature-optimized free Doppler kernel reconstruction significantly outperforms all previous interpolation-based methods, achieving 0.1% relative error on temperature interpolation of 238 U total cross section over the temperature range [300 K,3000 K] with only 9 reference temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

SU-E-I-10: Investigation On Detectability of a Small Target for Different Slice Direction of a Volumetric Cone Beam CT Image

Purpose: To investigate the detectability of a small target for different slice direction of a volumetric cone beam CT image and its impact on dose reduction. Methods: Analytic projection data of a sphere object (1 mm diameter, 0.2/cm attenuation coefficient) were generated and reconstructed by FDK algorithm. In this work, we compared the detectability of the small target from four different backprojection Methods: hanning weighted ramp filter with linear interpolation (RECON 1), hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON 3), and ramp filter with Fourier interpolation (RECON4), respectively. For noise simulation, 200 photons per measurement were used, and the noise only data were reconstructed using FDK algorithm. For each reconstructed volume, axial and coronal slice were extracted and detection-SNR was calculated using channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels. Results: Detection-SNR of coronal images varies for different backprojection methods, while axial images have a similar detection-SNR. Detection-SNR{sup 2} ratios of coronal and axial images in RECON1 and RECON2 are 1.33 and 1.15, implying that the coronal image has a better detectability than axial image. In other words, using coronal slices for the small target detection can reduce the patient dose about 33% and 15% compared to using axial slices in RECON 1 and RECON 2. Conclusion: In this work, we investigated slice direction dependent detectability of a volumetric cone beam CT image. RECON 1 and RECON 2 produced the highest detection-SNR, with better detectability in coronal slices. These results indicate that it is more beneficial to use coronal slice to improve detectability of a small target in a volumetric cone beam CT image. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (NIPA-2014-H0201-14-1002) supervised by the NIPA (National IT Industry Promotion Agency). Authors declares that s/he has no conflict of Interest in relation to the work in this abstract.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Evaluation of Accuracy and Performance of a Bilinear Interpolator with Dense EOS Tables in xRage

This study investigates the performance and accuracy of simulations using air and deuterium equation-of-state (EOS) tables that have been densified coupled with linear interpolation, as opposed to the default rational interpolation used in EOSPAC. EOS tables that are densified by adding in more temperature and density points that have been calculated by the rational function interpolator are able to improve the accuracy of the linear interpolator by over 50%. There was no change in runtime performance for a simulation using a dense EOS table with linear interpolation. In a memory limited case, dense EOS tables had no apparent effect on the simulation runtime or memory usage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Assimilating irregularly spaced sparsely observed turbulent signals with hierarchical Bayesian reduced stochastic filters

In this paper, we consider a practical filtering approach for assimilating irregularly spaced, sparsely observed turbulent signals through a hierarchical Bayesian reduced stochastic filtering framework. The proposed hierarchical Bayesian approach consists of two steps, blending a data-driven interpolation scheme and the Mean Stochastic Model (MSM) filter. We examine the potential of using the deterministic piecewise linear interpolation scheme and the ordinary kriging scheme in interpolating irregularly spaced raw data to regularly spaced processed data and the importance of dynamical constraint (through MSM) in filtering the processed data on a numerically stiff state estimation problem. In particular, we test this approach on a two-layer quasi-geostrophic model in a two-dimensional domain with a small radius of deformation to mimic ocean turbulence. Our numerical results suggest that the dynamical constraint becomes important when the observation noise variance is large. Second, we find that the filtered estimates with ordinary kriging are superior to those with linear interpolation when observation networks are not too sparse; such robust results are found from numerical simulations with many randomly simulated irregularly spaced observation networks, various observation time intervals, and observation error variances. Third, when the observation network is very sparse, we find that both the kriging and linear interpolations are comparable.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Overset meshes for incompressible flows: On preserving accuracy of underlying discretizations

This study on overset meshes for incompressible-flow simulations is motivated by accurate prediction of wind farm aerodynamics involving large motions and deformations of components with complex geometry. Specifically, using first-order hyperbolic and elliptic equation proxies for the incompressible Navier-Stokes (NS) equations, we investigate the influence of information exchange between overset meshes on numerical performance where the underlying discretization is second-order accurate. The first aspect of information exchange surrounds interpolation of solution where we examine Lagrange and point-cloud-based interpolation for creating constraint equations between overset meshes. To maintain overall second-order accuracy, higher-order interpolation is required for elliptic problems, but linear interpolation is sufficient for hyperbolic problems in first-order form. Higher-order point-cloud-based interpolation provides a pathway to maintaining accuracy in unstructured meshes, but at higher complexity. The second aspect of information exchange focuses on comparing the approaches of overset single system (OSS) and overset Additive Schwarz (OAS) for coupling the linear systems of the overlapping meshes. While the former involves a single linear system, in the latter the discrete linear systems are solved separately, and solving the global system is accomplished through outer iterations and sequential information exchange in a Jacobi fashion. For the test cases studied, accuracy for hyperbolic problems is maintained by performing two outer iterations, whereas many outer iterations are required for elliptic systems. The order-of-accuracy studies explored here are critical for verifying the overset-mesh coupling algorithms used in engineering simulations. Accuracy of these simulations themselves is, however, quantified using engineering quantities of interest such as drag, power, etc. Consequently, we conclude with numerical experiments using NS equations for incompressible flows where we show that linear interpolation and few outer iterations are sufficient for achieving asymptotic convergence of engineering quantities of interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Filling the Gaps: A Bayesian Mixture Model for Imputing Missing Soil Water Content Data

ABSTRACT Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water‐limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well ( R 2 = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap‐fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries.

Ogle, Kiona [School of Informatics, Computing, and↗
DOE OSTI2025

Geospatial modeling of near subsurface temperatures of the contiguous United States for assessment of materials degradation

Abstract Understanding subsurface temperature variations is crucial for assessing material degradation in underground structures. This study maps subsurface temperatures across the contiguous United States for depths from 50 to 3500 m, comparing linear interpolation, gradient boosting (LightGBM), neural networks, and a novel hybrid approach combining linear interpolation with LightGBM. Results reveal heterogeneous temperature patterns both horizontally and vertically. The hybrid model performed best achieving a root mean square error of 2.61 °C at shallow depths (50–350 m). Model performance generally decreased with depth, highlighting challenges in deep temperature prediction. State-level analyses emphasized the importance of considering local geological factors. This study provides valuable insights for designing efficient underground facilities and infrastructure, underscoring the need for depth-specific and region-specific modeling approaches in subsurface temperature assessment.

Science & Technology - Other Topics↗
DOE OSTI2011

An empirical model of diagnostic x-ray attenuation under narrow-beam geometry

Purpose: The purpose of this study was to develop and validate a mathematical model to describe narrow-beam attenuation of kilovoltage x-ray beams for the intended applications of half-value layer (HVL) and quarter-value layer (QVL) estimations, patient organ shielding, and computer modeling. Methods: An empirical model, which uses the Lambert W function and represents a generalized Lambert-Beer law, was developed. To validate this model, transmission of diagnostic energy x-ray beams was measured over a wide range of attenuator thicknesses [0.49-33.03 mm Al on a computed tomography (CT) scanner, 0.09-1.93 mm Al on two mammography systems, and 0.1-0.45 mm Cu and 0.49-14.87 mm Al using general radiography]. Exposure measurements were acquired under narrow-beam geometry using standard methods, including the appropriate ionization chamber, for each radiographic system. Nonlinear regression was used to find the best-fit curve of the proposed Lambert W model to each measured transmission versus attenuator thickness data set. In addition to validating the Lambert W model, we also assessed the performance of two-point Lambert W interpolation compared to traditional methods for estimating the HVL and QVL [i.e., semilogarithmic (exponential) and linear interpolation]. Results: The Lambert W model was validated for modeling attenuation versus attenuator thickness with respect to the data collected in this study (R{sup 2} > 0.99). Furthermore, Lambert W interpolation was more accurate and less sensitive to the choice of interpolation points used to estimate the HVL and/or QVL than the traditional methods of semilogarithmic and linear interpolation. Conclusions: The proposed Lambert W model accurately describes attenuation of both monoenergetic radiation and (kilovoltage) polyenergetic beams (under narrow-beam geometry).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Consistent Fluid Property Evaluation in RELAP5-3D

Previous investigations have developed and tested a methodology to improve the consistency between used to determine the fluid property derivatives used in the numerical solution scheme and the solution scheme itself. Within a bounding rectangle of the fluid property table for a fluid state point, linear interpolants for both fluid property values and their derivatives are calculated. A weighted average between these interpolants the analytical approximations of the fluid properties and derivatives is formed with a weighting factor between 0.0 and 1.0. This average has shown potential to reduce mass error relating to the fluid properties in RELAP5-3D. This linear interpolation and weighted averaging methodology has been implemented in RELAP5-3D with two additional options that adjust the weighting factor in the average according to the location within the bounding rectangle. The first calculates the weighting factor based only on the position between the left and right internal energy endpoints. The second also factors the position between the upper and lower pressure grid points into the calculation of the weighting factor. The new coding passes verification testing and expanded testing of the various options. Graphs are presented from three kinds of test cases, a two volume basic model, Edward’s O’Brien blowdown, and typical PWR. Some trends of the effect of crossing fluid property table pressure and internal energy grid line are identified and discussed for the simple and Edwards test cases. Preliminary results show that it the consistent fluid methodology can reduce mass error in simple cases, but in more complex input models, there is no clear best.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Conical intersection seams in polyenes derived from their chemical composition

The knowledge of conical intersection seams is important to predict and explain the outcome of ultrafast reactions in photochemistry and photobiology. They define the energetic low-lying reachable regions that allow for the ultrafast non-radiative transitions. In complex molecules it is not straightforward to locate them. We present a systematic approach to predict conical intersection seams in multifunctionalized polyenes and their sensitivity to substituent effects. Included are seams that facilitate the photoreaction of interest as well as seams that open competing loss channels. The method is based on the extended two-electron two-orbital method [A. Nenov and R. de Vivie-Riedle, J. Chem. Phys. 135, 034304 (2011)]. It allows to extract the low-lying regions for non-radiative transitions, which are then divided into small linear segments. Rules of thumb are introduced to find the support points for these segments, which are then used in a linear interpolation scheme for a first estimation of the intersection seams. Quantum chemical optimization of the linear interpolated structures yields the final energetic position. We demonstrate our method for the example of the electrocyclic isomerization of trifluoromethyl-pyrrolylfulgide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-E-J-78: Internal Target Volume Delineation for Lung Tumors in Patients Treated with Robotic Radiosurgery

Purpose: To compare different approaches for Internal Target Volume (ITV) delineation for patients treated with fiducial-free robotic radiosurgery for primary and metastatic lung tumors. Methods: Ten patients undergoing Lung-Optimized Treatment (LOT) for robotic radiosurgery were imaged with inhale and exhale breath-hold CT scans and 8-phase 4DCT scan. We evaluated the differences in internal target volume (ITV) delineated using three approaches: 1) maximum intensity projection (MIP) images reconstructed from 4DCT scan (ITV-MIP); 2) linear interpolation of Gross Tumor Volumes (GTV) segmented on inhale and exhale breath-hold scans (ITV-BH); 3) linear interpolation of GTV segmented on inhale and exhale phases of 4DCT scan (ITV-2Phase). All contours were independently generated by the same radiation oncologist using lung window settings. Patients had ITV-MIP volumes ranging from 1.5 to 146.9 cc (mean 36.8 cc) located in various parts of the lung. Volume overlap and matching index (MI) were calculated and compared. The MI between two volumes was defined as the ratio of their intersection to their union. MI of 1 indicates the volumes are identical; MI of 0 indicates that there is no overlap. Results: The three approaches generated very different results. The average (SD) MI for ITV-MIP and ITV-BH was 0.52 (0.24); for ITV-MIP and ITV-2Phase it was 0.69 (0.13); and for ITV-BH and ITV-2Phase was 0.57 (0.21), (ANOVA, p=0.16). Relative to the ITV-MIP, the percentage of volume overlap was 72% (26%) and 90% (7%) for ITV-BH and ITV-2Phase, respectively (t-test, p=0.05). Conclusion: Differences between ITV-BH and ITV-MIP are due to inconsistent lung filling at breath-hold and nonlinear tumor motion. Therefore, methods to check breath-hold scanning against regular patient breathing patterns should be developed. Whenever possible, ITV-BH generated by the LOT workflow should be verified by 4DCT data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Marine Corps Base Camp Lejeune NRE Carbon Flux

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.In situ CO2 sensors were deployed on the AVPs at Stones Bay and Morgans Bay between AEM-1 ongoing bi-monthly discrete sampling events. CO2 fluxes were calculated using measured pCO2, and pCO2 estimated based on a linear interpolation of measured pCO2 (between start and end of each deployment). The intention of this dataset is to asses whether such a linear interpolation of pCO2 introduces a significant error to CO2 flux calculations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Calculating the grain boundary inclination of voxelated grain structures using a smoothing algorithm

We have developed a flexible method for calculating the grain boundary (GB) inclinations of voxelated grain structure data using smoothing algorithms. We compared the performance of four algorithms: the linear interpolation, Allen–Cahn, level-set, and vertex algorithms. We assessed their accuracy using 2D and 3D cases with known inclinations. The vertex algorithm provided the best balance between accuracy and efficiency for 2D structures while the linear interpolation algorithm provided the best balance for 3D structures. We compared the GB inclinations calculated using our smoothing method on a 3D high energy X-ray diffraction microscopy (HEDM) dataset to those determined by meshing the GBs. The two approaches determined similar GB plane distributions, though they varied significantly at triple junctions. In conclusion, the smoothing method was demonstrated for two sources of 3D voxelated grain structures: HEDM data and results from Monte Carlo Potts grain growth simulations.

36 MATERIALS SCIENCE↗