Probabilistic Analysis and Time Variation Model of Concrete Compressive Strength in Existing Buildings
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9, Issue 3
Abstract
Probabilistic analysis and time variation model of concrete compressive strength in existing buildings were conducted based on relevant site testing data. The data were collected from rebound hammer (RH) method and core test method. There were 73,840 of RH test data and 4,149 of core test data. First, the data were normalized through dividing by the cube strength, to eliminate the concrete grade effect. The probability distribution analysis showed that the normal distribution is more suitable than the log-normal distribution. Moreover, it was found that the mean value of the core test data was higher than that of the RH data. Further, regression analysis on the data was carried out, and two quadratic functions were adopted to capture the time variation models of the compressive strength based on the RH data, and the core test data, respectively. Furthermore, some more data were obtained by the Genetic algorithm-back propagation (GA-BP) neural network method, and the time variation models were accordingly updated including the new data. Finally, the relationship between the RH model and core test model was discussed, and two approximately linear curves existed from 0 to 30 years and 31 to 60 years. Hopefully, this probabilistic analysis and the time variation model can be helpful in the assessment of the bearing capacity and evaluation of structure reliability in concrete structures.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research has been generously supported by the National Natural Science Foundation of China (Grant Nos. 52038006 and 51878395), Introduction and Education Plan for Young and Innovative Talents in Colleges and Universities of Shandong Province, and Shandong Jianzhu University Engineering Appraisal and Reinforcement Research Institute Ltd. for providing the data, which are gratefully acknowledged by the authors.
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Information & Authors
Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9 • Issue 3 • September 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Feb 12, 2023
Accepted: May 24, 2023
Published online: Jul 12, 2023
Published in print: Sep 1, 2023
Discussion open until: Dec 12, 2023
ASCE Technical Topics:
- Buildings
- Compressive strength
- Data analysis
- Distribution functions
- Engineering fundamentals
- Existing buildings
- Field tests
- Material mechanics
- Material properties
- Materials engineering
- Mathematical functions
- Mathematics
- Methodology (by type)
- Probability
- Probability distribution
- Research methods (by type)
- Strength of materials
- Structural engineering
- Structures (by type)
- Tests (by type)
Authors
Metrics & Citations
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