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Quantitative Analysis of Historic Mortars by Digital Image Analysis of Thin Sections

Author(s):


Medium: journal article
Language(s): English
Published in: Restoration of Buildings and Monuments, , n. 2, v. 23
Page(s): 83-92
DOI: 10.1515/rbm-2016-0011
Abstract:

In restoration work, the compatibility between old and new building material is the key point for sustainable repair of buildings or monuments. Consequently, conservation scientists are looking for an alternative method to the traditional procedures to determine the aggregate grading curve and the binder/aggregate-ratio of the historic material. The problem of using the traditional methods is the frequent major intervention in an existing building. These destructive methods are not allowed. Whereas, to get information about the historic mortar, a new technique, the digital image analysis (DIA), is applied in this paper. Moreover, small amounts of the historic material have already been prepared as thin sections and analysed with a microscope. Modern microscopy techniques allow investigations of quantitative and qualitative composition of historic material. Incentive of this work was to get all the required information to recreate the historic mortar by using the DIA with an open source program only at one thin section. In addition, to examine the accuracy and the significance of the DIA, all results were compared with a known mixture, and in a second test series, the results of the DIA were compared with the traditional methods. The results show that the DIA of thin sections of a historic mortar is highly effective for analysing decisive factors like the binder/aggregate-ratio and the grading curve of the aggregates. Furthermore, it is possible to analyse the mortar only by having one thin section using an open source program ImageJ. Especially in the case of carbonate rock as aggregate, DIA is the only method to analyse these characteristics of a mortar.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1515/rbm-2016-0011.
  • About this
    data sheet
  • Reference-ID
    10531243
  • Published on:
    17/12/2020
  • Last updated on:
    19/02/2021
 
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