Intumescent fireproof coatintgs based on zeolite-like cement matrices

Ескіз

Дата

2023-09

Автори

Krivenko Pavel
Guzii Sergii
Rudenko Igor
Konstantynovskyi Oleksandr

Заголовок журналу

Журнал ISSN

Назва тому

Видавець

Wiley

Анотація

Concrete and reinforced concrete building structures (for example, such as tunnels) lose carrying ability in case of high‐temperature fire action. The aim of the research is to study the prevention of reinforced concrete structures (for example, such as tunnels) under fire action in case of using the proposed coating based on the alkaline aluminosilicate binder, which would not consist of organic components dangerous to health. The ratios between constituent oxides in the binder which ensure the ability to bloat the coating under fire action were determined. The performance properties of developed fire protective coating were defined after artificial aging (cycles of alternate drying and cooling) and fire action: bloating factor ‐ 2.0…5.1, adhesion strength ‐ 6.6…8.0 MPa, compressive strength ‐ 2.3…4.5 MPa, cohesive strength of 1.2…1.5 MPa, thermal conductivity coefficient ‐ 0.042…0.066 W/m‐°C, total porosity ‐ 92…97 %. The temperature at which the coating starts to bloat = 200…250 °C has been developed. The results of the test held in the open air suggested drawing a conclusion that with a coating thickness of 6 mm protection of the reinforced concrete from fragile fracture and from plastic deformations in the metal of the reinforcement they provided under fire exposure for a period of 3 hours.

Опис

Ключові слова

adhesion, aluminosilicate pellets, cohesion, intumescent coating, tunnel, zeolite-like cement matrices, кафедра технології будівельних конструкцій і виробів

Бібліографічний опис

Intumescent fireproof coatintgs based on zeolite-like cement matrices / P. Krivenko, S. Guzii, I. Rudenko, O. Konstantynovskyi // Proceedings in civil engineering. - 2023. - Vol. 5. - P. 923 - 929. - Bibliogr. : 40 titl.

item.page.endorsement

item.page.review

item.page.dataset

item.page.dataset