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Classification of Hardened Cement and Lime Mortar Using Short-Wave Infrared Spectrometry Data

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Structural Analysis of Historical Constructions

Part of the book series: RILEM Bookseries ((RILEM,volume 18))

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Abstract

This paper evaluated the feasibility of using spectrometry data in the short-wave infrared range (1,300–2,200 nm) to distinguish lime mortar and Type S cement mortar using 42 lab samples (21 lime-based, 21 cement-based) each 40×40×40 mm were created. A Partial Least Squares Discriminant Analysis model was developed using the mean spectra of 28 specimens as the calibration set. The results were tested on the mean spectra of the remaining 14 specimens as a validation set. The results showed that, spectrometry data were able to fully distinguish modern mortars (made with cement) from historic lime mortars with a 100% classification accuracy, which can be very useful in archaeological and architectural conservation applications. Specifically, being able to distinguish mortar composition in situ can provide critical information about the construction history of a structure, as well as to inform an appropriate intervention scheme when historic material needs to be repaired or replaced.

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Acknowledgements

The authors wish to thank Dr. Hugh Byrne and Luke O’Neill from Dublin Institute of Technology as well as Mr. Derek Holmes and Mr. John Ryan from University College Dublin for their support and assistance in conducting the experimental parts of the study. Funding for this work was provided by New York University’s Center for Urban Science and Progress. Dr. Gowen acknowledges funding from the European Research Council (ERC) under the starting grant programme ERC-2013-StG call—Proposal No. 335508—BioWater.

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Correspondence to Zohreh Zahiri .

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Zahiri, Z., Laefer, D.F., Gowen, A. (2019). Classification of Hardened Cement and Lime Mortar Using Short-Wave Infrared Spectrometry Data. In: Aguilar, R., Torrealva, D., Moreira, S., Pando, M.A., Ramos, L.F. (eds) Structural Analysis of Historical Constructions. RILEM Bookseries, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-99441-3_47

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  • DOI: https://doi.org/10.1007/978-3-319-99441-3_47

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99440-6

  • Online ISBN: 978-3-319-99441-3

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