Statistical analysis on ancient mortars: A case study of the Balivi Tower in Aosta (Italy)
Graphical abstract
Introduction
Mathematical and statistical methods are widely used in studies on cultural heritage. Chemometric analyses support dating and provenancing of the raw materials of archeological and historical objects such as glasses [1], [2], [3], [4], [5], [6], ceramics [7], [8], [9], [10], organic binders [11] and stones [12]. A chemometric approach allows the user to extract relevant information from a large number of data set that has to be managed after a research study [13].
Despite the widespread application of chemometrics to the conservation of cultural heritage, only few a statistical studies aimed at mortar characterization have been made. All of these studies were only concerned about the grouping and the classification of samples, and nothing has been published that directly compares the various analytical techniques that can be used for characterizing mortars.
Rampazzi et al. [13] used PCA to investigate specimens and samples of historical mortars. A PLS (Partial Least Squares regression for one y-variable) was needed to create a statistical method for estimating the binder/aggregate ratio (B/A). Using a SIMCA method (Soft Independent Models of Class Analogy), Musumarra et al. [14] distinguished Gothic and Flemish mortars used for mural paintings in Chiaravalle Abbey. The test results from thermal analysis, mercury porosimetry and mechanical strength analysis were used by Moropoulou et al. [15], [16] for the classification of historical mortars in Byzantine and Ottoman monuments using PCA. Principal component analysis (PCA) was also used by Giuffrida et al. [17] to distinguish between painted plasters and wall covering plasters. Alvarez et al. [18] proposed a method based on hot hydrochloric acid attack of mortars to carry out a separation of the binder and the aggregate, while Sanjurjo-Sánchez et al. [19] used a multivariate statistical analysis of the chemical data obtained by X-ray diffraction and neutron activation analysis for the differentiation of mortars groups from the Santa Eulalia de Bóveda temple (Spain).
This study is thus one of the firsts chemometrical studies on mortars and is, in particular, the first chemometric study comparing analytical techniques that are currently used for their examination.
This research aims to classify and date mortar samples collected from the quadrangular tower of the Balivi Complex in Aosta. The information acquired was compared with archive data of previous studies [20], [21], [22] to distinguish the different mortar mixtures and to determine the various rebuilding periods and restorations.
This study also aims to evaluate the validity and the actual need for the most common analytical techniques used for mortar characterization such as Calcimetry, Thermogravimetric Analysis (TGA), Differential Thermal Analysis (DTA), Ionic Chromatography (IC) and Fourier Transform Infrared Spectroscopy (FT-IR) [23], [24], [25], that in some cases provide comparable information.
A statistical investigation of the results of such analytical techniques should result in a reduction in the number of analyses needed to characterize mortars.
Section snippets
Mortar samples
Sixteen samples in total were taken using a scalpel from all four facades at different heights of the Balivi tower (Fig. 1). The sampling locations are shown in Fig. 2. The samples were finely ground using an agate mortar, to obtain a particles size of about 230 mesh. The powdered samples were analyzed by Calcimetry, TG/DTA, IC and FTIR.
The calcimetry was performed using the UNI 11140:2004 procedure [26].
For TG/DTA analysis, a Pyris Diamond TG/DTA Differential Thermal Analyzer was used, with
Variables
All the variables for the study of mortars composition were used for both Q-mode Cluster Analysis and PCA using a matrix of 16 objects by 8 variables. In this study case only the first two principal components were considered, as their cumulative explained variance reached 79% (52% and 27% for the first and second principal component respectively). This value is considered suitable for an adequate description of the whole data set and, therefore, for correct interpretation of the results.
The
Conclusions
This study offers a new approach to the statistical study of ancient mortars. Based on their composition, Cluster Analysis and the PCA showed a diversification between the mortar samples. This division is probably due to different manufacturing periods for the mortars, coinciding with documented rebuilding works that affected the Balivi Tower Complex in Aosta after the Barbarian Invasions.
For the first time this investigation evaluates the role and agreement between variables acquired after
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