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Allan Harte

Publications and source records attributed to Allan Harte.

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Development of a Methodology for the Automated Spatial Mapping of Heterogeneous Elastoplastic Properties of Welded Joints

Knowledge of the mechanical properties of materials is required for the design and analysis of engineering products, however, the characterisation of heterogeneous properties using traditional techniques is limited by spatial resolution or insufficient reliability. This paper presents a novel methodology for the characterisation of heterogeneous mechanical properties by extending the virtual fields method through the automated spatial parameterisation of constitutive parameters. Collaboration with the United Kingdom Atomic Energy Authority provided this project with an application focus on the characterisation of the spatially-varying, elastoplastic mechanical properties of welded joints. The developed methodology enables the novel characterisation of welds with assorted geometries, varied loading configurations and dissimilar materials. Numerical verification of the developed method was performed using synthetic data equivalent to that obtained experimentally using optical measurements, where the kinematic fields are known and controlled. The results confirm that the proposed approach converges towards the target parameter maps without any a priori information on the distribution of the properties, successfully demonstrating the established methodology as a proof of concept.

cs.CE

PYVALE: A Fast, Scalable, Open-Source 2D Digital Image Correlation (DIC) Engine Capable of Handling Gigapixel Images

Background: Digital Image Correlation (DIC) is a widely used full-field measurement technique, but both open-source and commercial packages often have limitations such as operating-system restrictions, lack of support for deployment on computing clusters, and poor scalability to gigapixel-scale images common in Scanning Electron Microscopy DIC (SEM-DIC). Objective: Pyvale is an open-source software package designed for sensor simulation, uncertainty quantification, placement optimization, and calibration/validation. A key component of this is the development of a dedicated 2D DIC module intended for standalone use and integration within broader workflows. Methods: Pyvale provides a user-friendly Python interface with performant compiled routines underneath. At its core is a multithreaded, reliability-guided DIC algorithm. Its open-source MIT license enables wide deployment, including on computing clusters and in automated pipelines. Results: Benchmarking with the publicly available 2D DIC challenge 2.0 dataset shows that Pyvale achieves metrological performance comparable to existing commercial and open-source DIC codes. It can correlate gigapixel-scale image pairs in under 5 minutes on high-specification desktop workstations, with memory peaking at approximately 50 GB. Conclusions: Pyvale's strong metrological foundation, coupled with its scalability for SEM-DIC, positions it as a platform for sustained, community-driven development. Its design and licensing provide a foundation for future improvements in open-source DIC and integration into experimental design and validation workflows.

eess.IV