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1341 - 1350 / 2000
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Identification of the damage types for reinforced concrete using CNN models
Yue Shi, RunYu Wang, Xue Bai, 2025, original scientific article

Keywords: convolutional neural network, reinforced concrete, damage detection, image recognition, structural health monitoring, deep learning
Published in DiRROS: 01.09.2025; Views: 434; Downloads: 200
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1345.
Polyethylene terephthalate glycolysis : kinetic modeling and validation
Maja Gabrič, Žan Lavrič, Martin Schwiderski, Laureline Marc, Erik Temmel, Miha Grilc, Blaž Likozar, 2025, original scientific article

Published in DiRROS: 01.09.2025; Views: 446; Downloads: 194
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Municipal solid waste incineration (MSWI) bottom ash-blended cementitious materials : performance, challenges, and potential solutions
Boyu Chen, Priyadharshini Perumal, Chen Liu, Yun Chen, Cheng Chang, Majda Pavlin, Davor Kvočka, Vilma Ducman, Tero Luukkonen, Mirja Illikainen, Guang Ye, 2025, review article

Abstract: The recycling of municipal solid waste incineration (MSWI) bottom ash as a supplementary cementitious material (SCM) has attracted global attention, driven by the increasing availability of this by-product and the demand for sustainable SCMs to lower CO2 emissions from cement production. Currently, the widespread use of MSWI bottom ash in the cement industry is hindered by the lack of guidelines to regulate material composition, optimize pretreatment processes, and specify mix design requirements. This review compiles and analyzes literature data on mix design, microstructural evolution, fresh properties, mechanical properties, durability, leaching risks, and environmental impacts of MSWI bottom ash-blended cement pastes, mortars, and concretes. The analysis aims to assess the influence of the pretreatment and physicochemical properties of bottom ash on the microstructure and performance of blended cementitious materials. The Ash Impact Strength Index (AISI) is introduced to quantify the effects of various factors on compressive strength, enabling direct comparison across different studies. Based on the statistical analysis of the 28-day AISI, the key quality requirements for MSWI bottom ash as an SCM are proposed, along with the optimal mix design. This work provides valuable insights and practical guidance to support the integration of bottom ash into the cement industry.
Keywords: ash, ash-blended cementitious materials, performance
Published in DiRROS: 29.08.2025; Views: 431; Downloads: 279
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