Modelling Fracture

Identifying patterns and trends of fracture in paintings requires a systematic approach to classifying different types of fracture such as cracks, delamination and warp.

An Empirical Approach

Our scheme for classifying fracture derives from empirical observation of the range of damage found in the Brown Gallery portraits. Each portrait in the collection was examined, including assessment of the various materials used in its construction – paint layers and structures, gilding, and wooden panels.

Multiple techniques fed into this analysis. Microscopy and SEM/EDX generated empirical data on paint stratigraphy and pigment identification. Manual measurement from high-resolution photography generated empirical data on crack pattern and size. Applying qualitative and quantitative criteria to these data enabled us to catalogue and differentiate the types of fracture displayed by the Brown Gallery portrait set in a systematic manner. The resultant classification scheme may also subsequently support analysis of other collections.

View each of the categories and subcategories in our scheme.

Colour photograph showing the detail of an area of Knole House portrait 45 sampled for analytic purposes
Colour photograph showing microscopic analysis of detail of paint layers from a Knole House painting

Classification Criteria

Multiple criteria are used to differentiate between the categories and subcategories of fracture in our scheme.

In the case of cracks, we distinguish major structural cracks (such as disjoins between panels or splits through the wood) from minor cracks visible on the front surface. Connectivity is also important and we distinguish isolated cracks from those appearing in networks. We are also concerned with the location in which any crack appears as well as the size of the crack.

In the case of delamination, we are concerned with layer in terms of which is now exposed – a paint layer, preparatory layer or wooden board.

Check the description of each category and subcategory in our model to learn about the associated criteria.