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

2019 ◽  
Vol 23 (2) ◽  
pp. 83-92 ◽  
Author(s):  
Bernhard Middendorf ◽  
Tim Schade ◽  
Karin Kraus

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.

2016 ◽  
Author(s):  
C. Lance Stewart ◽  
◽  
Gary E. Stinchcomb ◽  
Elizabeth A. Hasenmueller ◽  
Steven L. Forman

2021 ◽  
Author(s):  
Joao Barata ◽  
Jorge Gomes ◽  
Ana C. Azerêdo ◽  
Luís V. Duarte

<p>The Barremian Upper Kharaib Formation reservoir unit was deposited in a carbonate ramp setting and shows moderate vertical facies variability, transitioning from a wackestone-dominated transgressive phase into a grainstone-dominated regressive phase. A dual-porosity system containing micro and macro-pores characterizes this reservoir, with microporosity as the dominant fraction of total porosity and holding large amounts of hydrocarbons in place. Porosity variations in the reservoir section shows no clear vertical trends, while permeability shows significantly higher values in the regressive phase sediments.</p><p>Digital image analysis (DIA) was done on this study using the different methods of visual estimation, colour selection based on histogram analysis and trained machine learning, with the measured area seen as a proxy for the total pore volume. A total of 285 images captured from 142 thin sections from 4 different wells were analysed. Colour selection through automated batch processing was done to quantify total macroporosity in all thin sections, using the petrographic images captured under XPL. Different RGB color codes and tolerance parameters were used in different runs on the same image, in an attempt to address the uncertainty in macroporosity measurements. Machine learning was applied using selected training images and manually classified pixel sets defining 2 classes (porous and non-porous space).</p><p>Total macroporosity is separated into interparticle and intraparticle/mouldic porosity (intrafossil porosity and probable dissolution of bioclasts/peloids/intraclasts) based on visual estimations, given that an unambiguous automated classification of these pore types is practically impossible to obtain. Microporosity is estimated to represent more than 60% of the total porosity. Considerable differences exist between the pore networks of the transgressive and regressive phase deposits, with the latter showing stronger heterogeneity and higher average interparticle macroporosity values in grainstone intervals containing coarser carbonate particles and small or no amount of interparticle micrite. These carbonate particles are, however, micritized and contain considerable volumes of microporosity within.</p><p>Pore type quantification through DIA can provide an objective, relatively quick and inexpensive methodology to provide useful insights into petrophysical relationships and to complement petrographic observations and core analysis results. Detailed depositional and stratigraphic models coupled with this quantitative data would help to better understand the depositional and diagenetic controls on rock properties variability.</p>


2003 ◽  
Vol 26 (1) ◽  
pp. 31-35 ◽  
Author(s):  
Julio R. Piva ◽  
Ana M. Canal ◽  
Carlos E Piva ◽  
Verónica Reus ◽  
Natalia R. Salvetti ◽  
...  

2015 ◽  
Author(s):  
Alcides Chaux ◽  
George J Netto ◽  
Authur L Burnett

The addition of molecular biomarkers is needed to increase the accuracy of pathologic factors as prognosticators of outcome in penile squamous cell carcinomas (SCC). Evaluation of these biomarkers is usually carried out by immunohistochemistry. Herein we assess p53 immunohistochemical expression on tissue samples of penile SCC using freely-available, open-source software packages for digital image analysis. We also compared the results of digital analysis with standard visual estimation. Percentages of p53 positive cells were higher by visual estimation than by digital analysis. However, correlation was high between both methods. Our study shows that evaluation of p53 immunohistochemical expression is feasible using open-source software packages for digital image analysis. Although our analysis was limited to penile SCC, the rationale should also hold for other tumor types in which evaluation of p53 immunohistochemical expression is required. This approach would reduce interobserver variability, and would provide a standardized method for reporting the results of immunohistochemical stains. As these diagnostic tools are freely-available online, researchers and practicing pathologists could incorporate them in their daily practice without increasing diagnostic costs.


Crop Science ◽  
2016 ◽  
Vol 57 (2) ◽  
pp. 550-558 ◽  
Author(s):  
Chenxi Zhang ◽  
Garland D. Pinnix ◽  
Zheng Zhang ◽  
Grady L. Miller ◽  
Thomas W. Rufty

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