Concrete Hydration Model Characterization Using Evolutionary Optimization
Date
2020Metadata
Show full item recordAbstract
Pile thermal integrity assessment by means of temperature measurement has received
increasing attention in recent years. The thermal integrity testing method measures
temperature changes during the concrete curing process; using an appropriate concrete
hydration model together with tracking temperature development during the curing
process, defects within piles could be detected. However, the implementation of
thermal integrity testing in practice faces, potentially, many uncertainties including
undocumented concrete mixes, lack of knowledge of ground thermal properties,
uncertain boundary conditions for pile, etc... These uncertainties increase the complexity
of determining appropriate parameters for the hydration model, which directly affects
the defect detection capacity of the method. This paper presents an inverse approach
using differential evolution (DE) algorithms to determine the concrete hydration model.
With this approach, the finite element (FE) analysis is integrated into the DE algorithm to
generate approximate solutions that match a controlled dataset instead of approximating
the concrete hydration parameters with limited prior knowledge as currently used in
practice. Firstly, a field test temperature dataset with a well-defined boundary condition
is selected. The temperature development corresponding to the selected dataset is then
numerically simulated using an uncalibrated general hydration model. Finally, the
hydration model parameters are determined using DE algorithms based on the measured
and simulated temperature development as inputs. A field case study is presented in
the end of this paper. The results indicate that the proposed inverse approach using DE
Pile thermal integrity assessment by means of temperature measurement has received
increasing attention in recent years. The thermal integrity testing method measures
temperature changes during the concrete curing process; using an appropriate concrete
hydration model together with tracking temperature development during the curing
process, defects within piles could be detected. However, the implementation of
thermal integrity testing in practice faces, potentially, many uncertainties including
undocumented concrete mixes, lack of knowledge of ground thermal properties,
uncertain boundary conditions for pile, etc... These uncertainties increase the complexity
of determining appropriate parameters for the hydration model, which directly affects
the defect detection capacity of the method. This paper presents an inverse approach
using differential evolution (DE) algorithms to determine the concrete hydration model.
With this approach, the finite element (FE) analysis is integrated into the DE algorithm to
generate approximate solutions that match a controlled dataset instead of approximating
the concrete hydration parameters with limited prior knowledge as currently used in
practice. Firstly, a field test temperature dataset with a well-defined boundary condition
is selected. The temperature development corresponding to the selected dataset is then
numerically simulated using an uncalibrated general hydration model. Finally, the
hydration model parameters are determined using DE algorithms based on the measured
and simulated temperature development as inputs. A field case study is presented in
the end of this paper. The results indicate that the proposed inverse approach using DE
algorithms can be used effectively in thermal integrity testing.
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- Civil & Architectural Engineering [778 items ]
- Theme 4: Sustainability, Renovation, and Monitoring of Civil Infrastructure [36 items ]