Spalling of high strength concrete in fire

Lalu, Octavian; Darmon, R; Lennon, Tom

doi:10.1088/1757-899x/1138/1/012027

Cited by 3 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With enhanced applications of HSC, there is rising concern about HSC's behavior in fire, which can damage structures (Figure 1). The phenomenon of spalling at higher temperatures is the primary reason for this concern (Khaliq and Kodur, 2018;Xiong and Liew, 2020;Kushnir et al, 2021;Lalu et al, 2021;Li et al, 2021). Usually, the structural elements of normal-strength concrete show considerable performance under exposure to fire.…”

Section: Introductionmentioning

confidence: 99%

Machine learning-based evaluation of parameters of high-strength concrete and raw material interaction at elevated temperatures

Chen¹,

Suhail

Bahrami

et al. 2023

Front. Mater.

View full text Add to dashboard Cite

High-strength concrete (HSC) is vulnerable to strength loss when exposed to high temperatures or fire, risking the structural integrity of buildings and critical infrastructures. Predicting the compressive strength of HSC under high-temperature conditions is crucial for safety. Machine learning (ML) techniques have emerged as a powerful tool for predicting concrete properties. Accurate prediction of the compressive strength of HSC is important as HSC can experience strength losses of up to 80% after exposure to temperatures of 800°C–1000°C. This study evaluates the efficacy of ML techniques such as Extreme Gradient Boosting, Random Forest (RF), and Adaptive Boosting for predicting the compressive strength of HSC. The results of this study demonstrate that the RF model is the most efficient for predicting the compressive strength of HSC, exhibiting the R2 value of 0.98 and lower mean absolute error and root mean square error values than the other applied models. Furthermore, Shapley Additive Explanations analysis highlights temperature as the most significant factor influencing the compressive strength of HSC. This article provides valuable insights into the timely and effective determination of the compressive strength of HSC under high-temperature conditions, benefiting both the construction industry and academia. By leveraging ML techniques and considering the critical factors that influence the compressive strength of HSC, it is possible to optimize the design and construction process of HSC and enhance its resilience to high-temperature exposure.

show abstract

Section: Introductionmentioning

confidence: 99%

Machine learning-based evaluation of parameters of high-strength concrete and raw material interaction at elevated temperatures

Chen¹,

Suhail

Bahrami

et al. 2023

Front. Mater.

View full text Add to dashboard Cite

show abstract

Flexural behavior of a box ferrocement beams consisting of self-compacted mortar reinforced by fiber glass mesh and GFRP bars after exposure to high temperatures

Abdullah

Abdulla

2023

Journal of Building Engineering

View full text Add to dashboard Cite

Review of Ultrasonic Pulse Methods for Evaluation of Mechanical Properties of Concrete with Different Percentages of Non-sintered Hwangto at High Temperature

Kim¹,

Kim²,

Jeong³

et al. 2023

Fire Sci. Eng.

View full text Add to dashboard Cite

In this study, the effect of non-sintered hwangto on the high-temperature residual mechanical properties of concrete is analyzed. The specimens are classified as NC and HT, which are mixed with 15% and 30% non-sintered hwangto, respectively, and the W/B is set 0.33. The unit weight, compressive strength, and ultrasonic pulse velocity of the specimens heated at room temperature and at 100 °C, 200 °C, 300 °C, 500 °C, and 700 °C are analyzed, and the correlation between ultrasonic pulse velocity and residual compressive strength is analyzed. The analysis result shows that the higher the mixing ratio of non-sintered hwangto, the lower is the mass loss rate at high temperature and the higher is the residual compressive strength of HT compared with those of NC. Meanwhile, the ultrasonic pulse velocity of HT is similar to or slightly higher than those of NC in areas with high temperatures of 300 °C or beyond. Results of correlation analysis shows a difference of approximately 10.0% between the NC and the HT specimens.

show abstract

Spalling of high strength concrete in fire

Cited by 3 publications

References 0 publications

Machine learning-based evaluation of parameters of high-strength concrete and raw material interaction at elevated temperatures

Machine learning-based evaluation of parameters of high-strength concrete and raw material interaction at elevated temperatures

Flexural behavior of a box ferrocement beams consisting of self-compacted mortar reinforced by fiber glass mesh and GFRP bars after exposure to high temperatures

Review of Ultrasonic Pulse Methods for Evaluation of Mechanical Properties of Concrete with Different Percentages of Non-sintered Hwangto at High Temperature

Contact Info

Product

Resources

About