The structural performance of concrete structures subjected to fire is greatly influenced by the heating temperature. Therefore, an accurate estimation of the heating temperature is of vital importance for deriving a reasonable diagnosis and assessment of fire-damaged concrete structures. In current practice, various heating temperature estimation methods are used, however, each of these estimation methods has limitations in accuracy and faces disadvantages that depend on evaluators’ empirical judgments in the process of deriving diagnostic results from measured data. Therefore, in this study, a concrete heating test and a non-destructive test were carried out to estimate the heating temperatures of fire-damaged concrete, and a heating temperature estimation method using an adaptive neuro-fuzzy inference system (ANFIS) algorithm was proposed based on the results. A total of 73 datasets were randomly extracted from a total of 87 concrete heating test results and we used them in the data training process of the ANFIS algorithm; the remaining 14 datasets were used for verification. The proposed ANFIS algorithm model provided an accurate estimation of heating temperature.

A fire that occurs in a reinforced concrete (RC) structure accompanies a heating temperature, and this negatively affects the concrete material properties, such as the compressive strength, the bond between cement paste and aggregate, and the cracking and spalling of concrete. To appropriately measure the reduced structural performance and durability of fire-damaged RC structures, it is important to accurately estimate the heating temperature of the structure. However, studies in the literature on RC structures damaged by fire have focused mostly on structural member tests at elevated temperatures to ensure the fire resistance or fire protection material development; studies on estimating the heating temperature are very limited except for the very few existing models. Therefore, in this study, a heating temperature estimation model for a reinforced concrete (RC) structure damaged by fire was developed using a statistical Bayesian parameter estimation approach. For the model development, a total of 77 concrete test specimens were utilized; based on them, a statistically highly accurate model has been developed. The usage of the proposed method in the framework of the 500 °C isotherm method in Eurocode 2 has been illustrated through an RC column resistance estimation application.

Spray-on fireproofing materials (SFRMs) and intumescent paints are commonly used to enhance the fire resistance of steel structures. Despite extensive studies on the performance of SFRMs and intumescent paints, there remains a significant lack of research on the material properties of certified products used in real-world applications, especially according to exposed temperatures. In this study, heating experiments were conducted to investigate the material properties of two widely used certified materials in Korea, focusing on their application thickness and exposure temperature. The experiments set target temperatures ranging from room temperature to 900 °C in increments of 100 °C. Additionally, various material properties, such as changes in shape and the insulation performance of the SFRM and intumescent paint, were observed at each temperature. Notably, the moisture content and discoloration depth of the SFRM displayed a consistent trend under different exposure temperatures, a material property that has not been previously reported. Furthermore, the insulation performance of the two materials differed by approximately 17% to 25% compared to an uncoated specimen exposed to the same temperature. The findings on the properties of SFRMs and intumescent paint relative to the exposure temperature presented in this study can serve as valuable data for selecting materials to improve fire resistance performance across various construction sites in the future. Additionally, they can act as key reference data in the diagnostic evaluation process for assessing the impact of fire on steel structures.

1. 서 론 건축물에서 화재확산을 억제하기 위한 방법으로는 2차 점화원의 제거나 내부

During an accidental fire in buildings, the corridor becomes the path for flame and smoke to spread, exposing the occupants to danger. Therefore, this study conducted real-scale fire experiments using corridors of size 2.4(L) × 10(W) × 2.4(H) m an “L-type” corridor for one-way evacuation and a “T-type” corridor for two-way evacuation to analyze the characteristics of fire according to the shape of corridors. The real-scale fire experiments were conducted in a fire room (2.4(L) × 3.6(W) × 2.4(H) m) with a single opening (2.0(W) × 1.8(H) m). The combustibles used inside the fire room were wood cribs, with a heat release rate of 651.4 kW, in the L-type corridor and chairs, with a heat release rate of 95.7 kW, in the T-type corridor. The temperature inside the corridor was measured during the real-scale fire experiments, and the average maximum measured temperature was 432.1 °C in the L-type corridor and 103.5 °C in the T-type corridor. The experimental results and the ventilation characteristics according to the corridor types were applied to BFD curves to show the process of designing fire growth models according to corridor types.