Abstract
Microstructure models are used to investigate bulk properties of a material given images of its microstructure. Through their use the effect of microstructural features can be investigated independently. Processes can then be optimised to give the desired selection of microstructural features. Currently automatic methods of segmenting SEM images either miss cracks leading to large overestimates of properties or use unjustifiable methods to select a threshold point which class cracks as porosity leading to over estimates of porosity. In this work, a novel automatic image segmentation method is presented which produces maps for each phase in the microstructure and an additional phase of cracks. The selection of threshold points is based on the assumption that the brightness values for each phase should be normally distributed. The image segmentation method has been compared to other available methods and shown to be as or more repeatable with changes of brightness and contrast of the input image than relevant alternatives. The resulting modelling route is able to predict density and specific heat to within experimental error, while the expected under predictions for thermal conductivity are observed.
Highlights
IntroductionSprayed materials have been the subject of numerous works focusing on methods for modelling based on images of their microstructures [1,2,3,4,5]
Sprayed materials have been the subject of numerous works focusing on methods for modelling based on images of their microstructures [1,2,3,4,5]. In general these studies aim to predict the bulk properties of the material to validate the modelling route before using the model to investigate underlying mechanics and directions for future materials or processing parameters
As only a single reference provides an estimate for the conductivity of the contact zone phase the effect of varying its conductivity is investigated here
Summary
Sprayed materials have been the subject of numerous works focusing on methods for modelling based on images of their microstructures [1,2,3,4,5] In general these studies aim to predict the bulk properties of the material to validate the modelling route before using the model to investigate underlying mechanics and directions for future materials or processing parameters. The imaging method and settings, image segmentation and processing method, mesh generation, model formulation, boundary conditions and domain size must all be carefully considered for a representative model Some of these steps, notably the image segmentation and processing contain hidden parameters which can be tuned by the user to fit the desired result. The resulting modelling route is not necessarily generally applicable
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