A modeling framework to anticipate, mitigate, and adapt to the impact of climate change on the durability of civil infrastructure

Research output: Book/ReportPh.D. thesis

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Abstract

For human settlements all over the world, concrete is commonly used as a construction material for civil infrastructure. The long service life, ranging from 30 to 100 years or even more, of concrete infrastructure necessitates considering future climatic conditions in design, maintenance, and replacement planning. For proactive adaptation and decision-making regarding the maintenance of the infrastructure that society and the economy depend on, it is essential to understand and analyse the impact of climate change on concrete infrastructure.

Over the last few decades, while many studies have focused on concrete infrastructure deterioration in the literature, limited research has been conducted on the impact of climate change on the deterioration of concrete structures. However, while these few studies present the first step to enable designers and decision-makers to anticipate the impacts of climate change on concrete infrastructure, the studies and frameworks are limited in their capability to mitigate and facilitate proactive adaption, such as optimized material design, increased robustness, and more adapted maintenance strategies, etc. This limitation arises from their reliance on simplified predictive models with empirical formulas, as well as assumptions about the processes involved in the analysis of the impact of climate change on concrete infrastructure, for example, mass transport mechanisms into concrete, mass flux through boundary surfaces, and the integration effect of climate change on concrete deterioration. Also, predictive competencies are inadequate due to insufficient critical physical couplings between mass transport, chemical equilibrium, and material properties. To progress beyond the state-of-the-art, science-based models for concrete deterioration must be developed considering fundamentals and integrated with climate projection models to analyze the impact of climate change on concrete deterioration. Therefore, this study aimed to establish a modeling framework that enables designers and decision-makers to provide scientific, relevant, and usable knowledge to guide decisions related to climate change impacts.

A conceptual framework for predicting, mitigating, and adapting to the impacts of climate change on the durability of concrete infrastructure was developed, thereby enabling the establishment of more robust design approaches as well as more resilient and adapted maintenance strategies for existing concrete infrastructures. Initially, a multi-species reactive transport model (RTM) was established, including of cement-based material through pore solution and solid phase changes under different environmental conditions. The prediction of concrete deterioration under actual environmental conditions, where concrete infrastructure is located in the real field, is more complex and often hardly comparable to results observed in labscale experiments, which may be due to fluctuations of climate conditions with time and the complex effect of boundary conditions. Therefore, the developed modeling framework was calibrated and tested in two case studies: i) data from the Solsvik field station, Norway, including observations of submerged concrete deterioration for more than 16 years, and ii) data from the Danish Technological Institute field station data, Denmark, including observations of concrete carbonation under atmospheric conditions for nearly eight years.

To account for the impact of climate change on concrete deterioration, the approach was further integrated with the statistical results of state-of-the-art climate models. For this study, the multi-model ensembles of global circulation models
(GCMs) projections under the very high GHG emissions scenario (RCP8.5), which is produced by the Coupled Model Intercomparison Project phase 5 (CMIP5) initiative, were used to investigate the impact of climate change on concrete structure deterioration in the period between 2020 and 2100. To avoid the biases and spatial resolution of these global projections that hinder their use in regional applications, the multi-model climate projections at high spatial resolution were downscaled to local scales using the Delta statistical downscaling method. The downscaled multimodel climate projections were statistically analysed to determine the uncertainty of climate projections, i.e., atmospheric temperature, relative humidity, and temperature and salinity level of seawater. Using distribution parameters from the climate projection for the RCP8.5 scenario, random samples were generated using the Latin hypercube sampling (LHS) technique. Using an integrated modeling framework, Monte Carlo simulations were performed to account for uncertainty information in the climate projections involved, and subsequently, an analytical probabilistic design approach was developed to identify critical climate projection outputs driving concrete deterioration in future climate projections. Finally, the results from the probabilistic design approach were used to investigate and identify more robust design approaches and more resilient and adapted maintenance strategies for concrete infrastructure, anticipating, mitigating, and adapting to the impacts of climate change on material deterioration.
Original languageEnglish
Place of PublicationKgs. Lyngby
PublisherTechnical University of Denmark
Number of pages231
Publication statusPublished - 2023

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