State-of-the-art review of capabilities and limitations of polymer and glass fibers used for fiber-reinforced concrete
The concrete industry has long been adding discrete fibers to cementitious materials to
compensate for their (relatively) low tensile strengths and control possible cracks. Extensive …
compensate for their (relatively) low tensile strengths and control possible cracks. Extensive …
Advances in Gaussian random field generation: a review
Gaussian (normal) distribution is a basic continuous probability distribution in statistics, it
plays a substantial role in scientific and engineering problems that related to stochastic …
plays a substantial role in scientific and engineering problems that related to stochastic …
A novel eigenvalue-based iterative simulation method for multi-dimensional homogeneous non-Gaussian stochastic vector fields
Y Jiang, Y Hui, Y Wang, L Peng, G Huang, S Liu - Structural Safety, 2023 - Elsevier
The generation of sample functions of stochastic fields or processes is a prerequisite to use
the Monte Carlo method in stochastic mechanics and structural reliability analysis. When it …
the Monte Carlo method in stochastic mechanics and structural reliability analysis. When it …
Seismic resilience of transportation networks with deteriorating components
Performance assessment of a transportation network is naturally a complicated problem.
This is mainly due to the fact that such a spatially distributed network is subjected to a variety …
This is mainly due to the fact that such a spatially distributed network is subjected to a variety …
Consideration of time-evolving capacity distributions and improved degradation models for seismic fragility assessment of aging highway bridges
This paper presents a methodology to develop seismic fragility curves for deteriorating
highway bridges by uniquely accounting for realistic pitting corrosion deterioration and time …
highway bridges by uniquely accounting for realistic pitting corrosion deterioration and time …
Effect of the interaction of corrosion pits among multiple tensile rebars on the reliability of RC structures: Experimental and numerical investigation
The deterioration of reinforced concrete (RC) structures due to chloride-induced corrosion is
not spatially uniform because of the spatial variability related to material properties and …
not spatially uniform because of the spatial variability related to material properties and …
Concrete cover cracking and service life prediction of reinforced concrete structures in corrosive environments
Z Cui, A Alipour - Construction and Building Materials, 2018 - Elsevier
Crack initiation of concrete cover due to corrosion defines the end of functional service life
where repair or replacement is required for corroded reinforced concrete (RC) structures …
where repair or replacement is required for corroded reinforced concrete (RC) structures …
Seismic life-cycle cost analysis of ageing highway bridges under chloride exposure conditions: Modelling and recommendations
Chloride-induced corrosion of highway bridges constitutes a critical form of environmental
deterioration and may result in significant escalation of seismic life-cycle costs due to …
deterioration and may result in significant escalation of seismic life-cycle costs due to …
Random field-based reliability updating framework for existing RC structures incorporating the effect of spatial steel corrosion distribution
S Srivaranun, M Akiyama, K Masuda… - Structure and …, 2022 - Taylor & Francis
In recent years, interest in the effect of the spatial variability associated with steel corrosion
on the safety and reliability of reinforced concrete (RC) structures in harsh environments has …
on the safety and reliability of reinforced concrete (RC) structures in harsh environments has …
Structural deterioration knowledge ontology towards physics-informed machine learning for enhanced bridge deterioration prediction
The structural deterioration knowledge in existing mathematical physics models offers a
unique opportunity to develop data-driven, physics-informed machine learning (ML) for …
unique opportunity to develop data-driven, physics-informed machine learning (ML) for …