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Application of the polyhedral template matching method for characterization of 2D atomic resolution electron microscopy images

Materials Characterization

Britton, Darcey; Hinojos, Alejandro E.; Hummel, Michelle H.; Adams, David P.; Medlin, Douglas L.

High-throughput image segmentation of atomic resolution electron microscopy data poses an ongoing challenge for materials characterization. In this paper, we investigate the application of the polyhedral template matching (PTM) method, a technique widely employed for visualizing three-dimensional (3D) atomistic simulations, to the analysis of two-dimensional (2D) atomic resolution electron microscopy images. This technique is complementary with other atomic resolution data reduction techniques, such as the centrosymmetry parameter, that use the measured atomic peak positions as the starting input. Furthermore, since the template matching process also gives a measure of the local rotation, the method can be used to segment images based on local orientation. We begin by presenting a 2D implementation of the PTM method, suitable for atomic resolution images. We then demonstrate the technique's application to atomic resolution scanning transmission electron microscopy images from close-packed metals, providing examples of the analysis of twins and other grain boundaries in FCC gold and martensite phases in 304 L austenitic stainless steel. Finally, we discuss factors, such as positional errors in the image peak locations, that can affect the accuracy and sensitivity of the structural determinations.

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Measurement of Photovoltaic Module Deformation Dynamics during Hail Impact Using Digital Image Correlation

IEEE Journal of Photovoltaics

Hartley, James Y.; Shimizu, Michael A.; Braid, Jennifer L.; Flanagan, Ryan; Reu, P.L.

Stereo high-speed video of photovoltaic modules undergoing laboratory hail tests was processed using digital image correlation to determine module surface deformation during and immediately following impact. The purpose of this work was to demonstrate a methodology for characterizing module impact response differences as a function of construction and incident hail parameters. Video capture and digital image analysis were able to capture out-of-plane module deformation to a resolution of ±0.1 mm at 11 kHz on an in-plane grid of 10 × 10 mm over the area of a 1 × 2 m commercial photovoltaic module. With lighting and optical adjustments, the technique was adaptable to arbitrary module designs, including size, backsheet color, and cell interconnection. Impacts were observed to produce an initially localized dimple in the glass surface, with peak deflection proportional to the square root of incident energy. Subsequent deformation propagation and dissipation were also captured, along with behavior for instances when the module glass fractured. Natural frequencies of the module were identifiable by analyzing module oscillations postimpact. Limitations of the measurement technique were that the impacting ice ball obscured the data field immediately surrounding the point of contact, and both ice and glass fracture events occurred within 100 μs, which was not resolvable at the chosen frame rate. Increasing the frame rate and visualizing the back surface of the impact could be applied to avoid these issues. Applications for these data include validating computational models for hail impacts, identifying the natural frequencies of a module, and identifying damage initiation mechanisms.

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Assessing decision boundaries under uncertainty

Structural and Multidisciplinary Optimization

Desmond, Jacob R.; Walsh, Timothy; Mccormick, Cameron; Smith, Chandler B.; Kurzawski, Andrew J.; Sanders, Clay M.; Eldred, Michael S.; Aquino, Wilkins

In order to make design decisions, engineers may seek to identify regions of the design domain that are acceptable in a computationally efficient manner. A design is typically considered acceptable if its reliability with respect to parametric uncertainty exceeds the designer’s desired level of confidence. Despite major advancements in reliability estimation and in design classification via decision boundary estimation, the current literature still lacks a design classification strategy that incorporates parametric uncertainty and desired design confidence. To address this gap, this works offers a novel interpretation of the acceptance region by defining the decision boundary as the hypersurface which isolates the designs that exceed a user-defined level of confidence given parametric uncertainty. This work addresses the construction of this novel decision boundary using computationally efficient algorithms that were developed for reliability analysis and decision boundary estimation. The proposed approach is verified on two physical examples from structural and thermal analysis using Support Vector Machines and Efficient Global Optimization-based contour estimation.

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Results 1501–1550 of 101,000
Results 1501–1550 of 101,000
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