Abstract
Concrete is a widely used construction material; however, the understanding of fatigue failure in cementitious material is lacking when compared to ferrous materials. The design life of concrete structures is also evaluated using PM rule of linear damage accumulation where the fatigue strength is represented by a combination of Goodman Diagrams & Wöhler Curves. Concrete is a heterogeneous material, which is inherently full of flaws, and has a considerable scatter in fatigue test data for same test conditions. Therefore, it is desirable to introduce probabilistic concepts to ensure adequate fatigue resistance of concrete structures. This paper attempts to identify the important parameter uncertainties associated with concrete fatigue material models for uniaxial compression based on a large data set of concrete fatigue tests obtained from literature. Parameter estimation from a given dataset of experiments can be done in different ways, and in addition sensitivity and identifiability analyses can be used to search for a unique set of parameters along with their uncertainties.
Originalsprog | Engelsk |
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Titel | IRSEC 2018 International Reliability and Safety Engineering Conference |
Antal sider | 7 |
Forlag | International Reliability and Safety Engineering Conference |
Publikationsdato | 2018 |
Status | Udgivet - 2018 |
Begivenhed | 5th International Reliability and Safety Engineering Conference - Shiraz University, Shiraz, Iran Varighed: 9 maj 2018 → 10 maj 2018 Konferencens nummer: 5 |
Konference
Konference | 5th International Reliability and Safety Engineering Conference |
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Nummer | 5 |
Lokation | Shiraz University |
Land/Område | Iran |
By | Shiraz |
Periode | 09/05/2018 → 10/05/2018 |
Bibliografisk note
AcknowledgementsThe project INFRASTAR (infrastar.eu) has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 676139. The grant is gratefully acknowledged.
Emneord
- Identifiability
- Sensitivity
- Concrete
- Fatigue
- Uncertainty
- Reliability