Daria Jóźwiak-Niedźwiedzka

Influence of Blended Cements with Calcareous Fly Ash on Chloride Ion Migration and Carbonation Resistance of Concrete for Durable Structures

The objective of this paper is to examine the possible use of new blended cements containing calcareous fly ash in structural concrete, potentially adequate for structural elements of nuclear power plants. The investigation included five new cements made with different contents of non-clinker constituents: calcareous fly ash, siliceous fly ash, ground granulated blastfurnace slag, and a reference cement—ordinary Portland cement. The influence of innovative cements on the resistance of concrete to chloride and carbonation exposure was studied. Additionally, an evaluation of the microstructure was performed using optical microscopy on concrete thin sections. Test results revealed a substantial improvement of the resistance to chloride ion penetration into concrete containing blended cements. The resistance was higher for increased clinker replacement levels and increased with curing time. However, concrete made with blended cements exhibited higher depth of carbonation than the Portland cement concrete, except the Portland-fly ash cement with 14.3% of calcareous fly ash. The thin sections analysis confirmed the values of the carbonation depth obtained from the phenolphthalein test. Test results indicate the possible range of application for new cements containing calcareous fly ash.

Assessment of Scaling Durability of Concrete with CFBC Ash by Automatic Classification Rules

AbstractThe objective of this investigation was to develop rules for automatic assessment of concrete quality by using selected artificial intelligence methods based on machine learning. The range of tested materials included concrete containing nonstandard waste material—the solid residue from coal combustion in circulating fluidized bed combustion boilers (CFBC ash) used as an additive. Performed experimental tests on the surface scaling resistance provided data for learning and verification of rules discovered by machine learning techniques. It has been found that machine learning is a tool that can be applied to classify concrete durability. The rules generated by computer programs AQ21 and WEKA by using the J48 algorithm provided a means for adequate categorization of plain concrete and concrete modified with CFBC fly ash as materials resistant or not resistant to the surface scaling.

Diagnosis of Concrete Quality by Structural Analysis

In this paper, the structure of concrete is reviewed, and the analysis of concrete components is presented from the viewpoint of diagnosing that structure. The diagnosis of a complex concrete structure entails the identification of concrete components—such as aggregate, paste, pores, etc.—and the estimation of concrete quality, existing damage, and possible causes of failures. The most effective methods for concrete diagnosis, such as microscopic image analysis, are briefly described. The importance of quantitative results of material analysis and image processing is highlighted.

Microscopic observations of self‐healing products in calcareous fly ash mortars

The results of microstructural characterization of mortars containing fly ash class C (High Calcium Fly Ash) from combustion of lignite are presented. The evaluation of the microstructure was performed using scanning electron microscope, optical, and confocal microscope. The tested beams were bent till the crack and microcracks opening, which were healed during the different curing time. The results showed that the replacement of cement with fly ash class C influenced the process of crack healing. The addition of HCFA, at both 30% and 60%, speeds up the self‐healing process in cracks and particularly in micro‐cracks. In the research, the completely filling up of the cracks by new phases has not been observed, only the beginning of such process has been noticed. Microsc. Res. Tech., 78:22–29, 2015.

APPLICATION OF MACHINE LEARNING FOR PREDICTION OF CONCRETE RESISTANCE TO MIGRATION OF CHLORIDES

The objective of this research was to develop rules for automatic categorization of concrete quality using selected artificial intelligence methods based on machine learning. The range of tested materials included concrete containing non-conventional additive of solid residue from coal combustion in fluidized bed boilers (CFBC fly ash). Performed experimental tests on chloride migration provided data for learning and testing of rules discovered by machine learning techniques. The rules generated by computer programs AQ21 and WEKA using J48 algorithm provided means for adequate categorization of plain concrete and concrete modified with CFBC fly ash as materials of good and acceptable resistance to chloride penetration.

Influence of blended cements on the concrete resistance to carbonation

The influence of high calcium fly ash as clinker replacement in blended cements on the resistance of concrete structures to the carbonation is presented. The paper concerns of five blended cements made with different contents of supplementary cementitious materials: high and low calcium fly ash and ground granulated blastfurnance slag and one reference cement – Portland cement. The aim was to study the carbonation depth on several concretes designed with a constant water to binder ratio and with various blended cements. Additionally, the prediction of the maximum carbonation depth was proposed. The evaluation of the microstructure was performed using optical microscopy on thin sections in transmitted light. The best results according to the resistance to carbonation achieved the concretes made with Portland-fly ash cement where 14.3 % of high calcium fly ash was used. CEM II/A-W can be used to prove the fc28 and resistance to carbonation for XC3 class.

Application of Image Analysis to Identify Quartz Grains in Heavy Aggregates Susceptible to ASR in Radiation Shielding Concrete

Alkali-silica reaction (ASR) is considered as a potential aging-related degradation phenomenon that might impair the durability of concrete in nuclear containments. The objective of this paper is the application of digital analysis of microscopic images to identify the content and size of quartz grains in heavy mineral aggregates. The range of investigation covered magnetite and hematite aggregates, known as good absorbers of gamma radiation. Image acquisition was performed using thin sections observed in transmitted cross-polarized light with λ plate. Image processing, consisting of identification of ferrum oxide and epoxy resin, and the subsequent application of a set of filtering operations resulted in an adequate image reduction allowing the grain size analysis. Quartz grains were classified according to their mean diameter so as to identify the reactive range. Accelerated mortar bar tests were performed to evaluate the ASR potential of the aggregates. The SiO2 content in the heavyweight aggregates determined using the image analysis of thin sections was similar to XRF test result. The content of reactive quartz hematite was 2.7%, suggesting that it would be prone to ASR. The expansion test, according to ASTM C1260, confirmed the prediction obtained using the digital image analysis.

Potential for Alkali–Silica Reaction in Radiation Shielding Concrete Containing Special Aggregates

In the present study, the potential for the alkali–silica reaction (ASR) in radiation shielding concrete containing special aggregates is presented. The tests were performed on two kinds of aggregate: (1) high-density aggregate to absorb the gamma radiation (barite, magnetite, and hematite) and (2) mineral with high bound water content to attenuate the neutron flux (serpentinite). The optical microscopy in transparent light on thin sections, XRD and XRF method, was used to assess the mineral composition of aggregates. ASTM C1260 test method for potential alkali reactivity of aggregates was applied also to investigate the effect of different content and crystal size of silica on the expansion due to ASR. The tests revealed that all tested aggregates, such as barite, magnetite, hematite, and serpentinite, were characterized by low solubility at high pH. The XRD and XRF results have shown presence of silica in all tested aggregates, but the microscopic observations enhanced size and composition of SiO2 crystals. The aggregates were not deleterious themselves, but the different content and size of SiO2 crystals in the aggregate influenced their potential for alkali–silica reaction. The quartz in heavy kinds of rocks and in the serpentinite used for radiation shielding was just as much potentially susceptible to deleterious ASR as quartz in common rocks used in concrete technology. In the hematite, silica crystals were classified as microcrystalline, so it should be considered as potentially reactive. The expansion tests confirmed that hematite was highly reactive. Other aggregates after 14 days of testing did not exceed 0.1% elongation limit. The microstructural analysis of thin sections prepared from mortars after ASTM C1260 test confirmed expansion of aggregate grains due to ASR.