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Geopolymer fly ash composites modified with cotton fibre

Kozub Barbara, Pławecka K., Figiela B., Korniejenko K.

Archives of Materials Science and Engineering

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2023

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Vol. 121, nr 2

60--70

EN

Purpose: The work’s primary goal is to assess the influence of the cotton fibres addition and their proportion on the strength properties and thermal conductivity of foamed geopolymer composites based on fly ash. Design/methodology/approach: Fly ash from a thermal power plant was used as the foundation material to create the geopolymer composites in this study. Volcanic silica was used as an additional source of silicon. As an additive, the recycled cotton flock was used in amounts of 0.5%, 1% and 2% by weight of dry ingredients. The density, compressive, and three-point bending strength of the created geopolymers were measured. Moreover, the thermal conductivity measurements for three temperature ranges: 0–20°C, 20–40°C, and 30–50°C for all investigated geopolymers were conducted. The structure of tested materials was observed using a scanning electron microscope (SEM). Findings: It was demonstrated within the context of the study that the addition of cotton fibres to foamed fly ash-based geopolymers aids in slightly reducing their density. Cotton fibres can be used to boost the strength of the examined geopolymers; for samples with 1% cotton fibres added, compressive strength rose by around 22% and flexural strength by about 67%. Additionally, it is feasible to lower their thermal conductivity coefficient by incorporating cotton fibres into foamed fly ash-based geopolymers. Practical implications: The results obtained highlight the potential of fly ash-based geopolymer composites with the addition of cotton flocks for application as insulating materials in the building industry. Originality/value: The novelty of this work is the demonstration of the possibility of producing foamed geopolymers based on fly ash with the addition of recycled cotton fibres, with properties that make them suitable for use as building insulation materials.

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Application of classification neural networks for identification of damage stages of degraded low alloy steel based on acoustic emission data analysis

Krajewska-Śpiewak Joanna, Lasota Igor, Kozub Barbara

Archives of Civil and Mechanical Engineering

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2020

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Vol. 20, no. 4

156--165

EN

The paper presents the influence of low alloy steel degradation on the acoustic emission (AE) generated during static tension of notched specimen. The material was cut from a technological pipeline long-term operated in the oil refinery industry. Comparative analysis of AE activity generated by damage process of degraded and new material has been carried out. The different AE parameters were used to detect different stages of fracture process of low alloy steel under quasi-static tensile test. Neural networks with three layers were created with Broyden–Fletcher–Goldfarb–Shanno learning algorithm for a database analysis. The different AE parameters were included in the input layer. Classification neural networks were created in order to determine the stages of material degradation. The results obtained from the carried out studies will be used as the basis for new methodology development of the assessment of the structural condition of in-service equipment.

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Identification of the tensile damage of degraded carbon steel and ferritic alloy-steel by acoustic emission with in situ microscopic investigations

Lyasota Igor, Kozub Barbara, Gawlik Józef

Archives of Civil and Mechanical Engineering

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2019

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Vol. 19, no. 1

274--285

EN

The paper presents results obtained from the destructive laboratory investigation conducted on materials from pressure vessels after long-term operation in the refinery industry. Tested materials contained structural defects, which arose from improper heat treatment during steel plate manufacturing. Detailed metallographic and chemical composition tests and static tensile tests were conducted. Next, complex tensile tests were conducted with simultaneous acoustic emission (AE) monitoring while observing microstructural changes by light microscopy. From the laboratory tests, the correlations between the AE signal parameters and material microstructural damage during the tensile tests were developed. The results will be used as a basis of new algorithms for the structural condition assessment of in-service pressure equipment.