Polynomial chaos expansion for lifetime assessment and sensitivity analysis of reinforced concrete structures subjected to chloride ingress and climate change

Reinforced concrete (RC) became one of the most widely used modern building materials. In the last decades a great interest has been shown in studying reinforcement corrosion as it became one of the main factors of degradation and loss of structural integrity of RC structures. The degradation process is accelerated in the case of RC structures situated in aggressive environments like marine environments or subjected to de-icing salts. In this paper it is shown how steel corrosion of the embedded rebars occurs and how this affects the service life of reinforced concrete structures. Also, an experimental study regarding the combined effect of carbonation and chloride ingress was realized. Samples with and without rebars were drilled from a RC slab which was stored in the laboratory for two years. Non-steady state migration tests were realized in order to determine the chloride profile, while the carbonation depth was measured using the colorimetric method based on phenolphthalein spraying. It was concluded that carbonation has a significant effect on chloride ingress, increasing it.

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Sensitivity analysis of Life Cycle Assessment to select reinforced concrete structures with one-way slabs

Engineering Structures ◽

10.1016/j.engstruct.2016.11.059 ◽

2017 ◽

Vol 132 ◽

pp. 586-596 ◽

Cited By ~ 12

Author(s):

J. Ferreiro-Cabello ◽

E. Fraile-Garcia ◽

E. Martinez-Camara ◽

M. Perez-de-la-Parte

Keyword(s):

Sensitivity Analysis ◽

Life Cycle Assessment ◽

Life Cycle ◽

Reinforced Concrete ◽

Concrete Structures ◽

Reinforced Concrete Structures

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Polynomial chaos expansion for sensitivity analysis

Reliability Engineering & System Safety ◽

10.1016/j.ress.2008.10.008 ◽

2009 ◽

Vol 94 (7) ◽

pp. 1161-1172 ◽

Cited By ~ 366

Author(s):

Thierry Crestaux ◽

Olivier Le Maıˆtre ◽

Jean-Marc Martinez

Keyword(s):

Sensitivity Analysis ◽

Polynomial Chaos ◽

Polynomial Chaos Expansion ◽

Chaos Expansion

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A Global Sensitivity Analysis Framework for Hybrid Simulation

10.31224/osf.io/wnqgb ◽

2021 ◽

Author(s):

Giuseppe Abbiati ◽

Stefano Marelli ◽

Nikolaos Tsokanas ◽

Bruno Sudret ◽

Bozidar Stojadinovic

Keyword(s):

Sensitivity Analysis ◽

Hybrid Model ◽

Polynomial Chaos ◽

Global Sensitivity Analysis ◽

Hybrid Simulation ◽

Polynomial Chaos Expansion ◽

Chaos Expansion ◽

Analysis Framework ◽

Global Sensitivity ◽

Sensitivity Indices

Hybrid Simulation is a dynamic response simulation paradigm that merges physical experiments and computational models into a hybrid model. In earthquake engineering, it is used to investigate the response of structures to earthquake excitation. In the context of response to extreme loads, the structure, its boundary conditions, damping, and the ground motion excitation itself are all subjected to large parameter variability. However, in current seismic response testing practice, Hybrid Simulation campaigns rely on a few prototype structures with fixed parameters subjected to one or two ground motions of different intensity. While this approach effectively reveals structural weaknesses, it does not reveal the sensitivity of structure's response. This thus far missing information could support the planning of further experiments as well as drive modeling choices in subsequent analysis and evaluation phases of the structural design process.This paper describes a Global Sensitivity Analysis framework for Hybrid Simulation. This framework, based on Sobol' sensitivity indices, is used to quantify the sensitivity of the response of a structure tested using the Hybrid Simulation approach due to the variability of the prototype structure and the excitation parameters. Polynomial Chaos Expansion is used to surrogate the hybrid model response. Thereafter, Sobol' sensitivity indices are obtained as a by-product of polynomial coefficients, entailing a reduced number of Hybrid Simulations compared to a crude Monte Carlo approach. An experimental verification example highlights the excellent performance of Polynomial Chaos Expansion surrogates in terms of stable estimates of Sobol' sensitivity indices in the presence of noise caused by random experimental errors.

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