Predicting Changes of the State of a Bridge Reinforced with Concrete Superstructures in View of Operational Changes
| Author(s): |
Pavlo Ovchynnykov
(Dep. “Bridges and Tunnels” , Dnipro National University of Railway Transport named after Academician V. Lazaryan)
Olha Dubinchyk (Dep. “Bridges and Tunnels” , Dnipro National University of Railway Transport named after Academician V. Lazaryan) Oleksii Tiutkin (Dep. “Bridges and Tunnels” , Dnipro National University of Railway Transport named after Academician V. Lazaryan) Vitalii Kildieiev (Dep. “Bridges and Tunnels” , Dnipro National University of Railway Transport named after Academician V. Lazaryan) Volodymyr Sedin (Dep. “Basement and Foundations” , Prydniprovska State Academy of Civil Engineering and Architecture) Kateryna Bikus (Dep. “Basement and Foundations” , Prydniprovska State Academy of Civil Engineering and Architecture) |
|---|---|
| Medium: | journal article |
| Language(s): | English |
| Published in: | Civil and Environmental Engineering Reports, September 2019, n. 3, v. 29 |
| Page(s): | 134-152 |
| DOI: | 10.2478/ceer-2019-0030 |
| Abstract: |
To solve the problem of predicting the service life of superstructures, this work proposes the basis and methodological developments of creep theory with increasing loads as well as regression analysis of the results of laboratory experiments. The main limitation in terms of reinforcement is corrosion in the concrete cracks, which was determined during laboratory experiments. Based on the results, the approximate analytical dependences concerning reinforcement corrosion depth change over time at a constant value of crack width were selected. The paper substantiates the validity of the analytical dependences as a result of regression analysis; it proposes formulae for determining the corrosion rate of rebars in reinforced concrete superstructures. The obtained analytical dependences allowed for the developing of a process for predicting changes to the state of the superstructure in light of operational changes. |
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data sheet - Reference-ID
10705176 - Published on:
19/02/2023 - Last updated on:
19/02/2023
