Digital twin for civil engineering systems: An exploratory review for distributed sensing updating
We live in an environment of ever-growing demand for transport networks, which also have
ageing infrastructure. However, it is not feasible to replace all the infrastructural assets that …
ageing infrastructure. However, it is not feasible to replace all the infrastructural assets that …
Developing prediction equations for soil resilient modulus using evolutionary machine learning
L Sadik - Transportation Infrastructure Geotechnology, 2024 - Springer
The soil resilient modulus (MR) is essential to pavement design. This parameter is
determined through a costly and time-consuming repeated load triaxial test. Accordingly …
determined through a costly and time-consuming repeated load triaxial test. Accordingly …
Structural health monitoring of civil structures: A diagnostic framework powered by deep metric learning
Recent advances in learning systems and sensor technology have enabled powerful
strategies for autonomous data-driven damage detection in structural systems. This work …
strategies for autonomous data-driven damage detection in structural systems. This work …
[HTML][HTML] A multi-fidelity surrogate model for structural health monitoring exploiting model order reduction and artificial neural networks
Stochastic approaches to structural health monitoring (SHM) are often inevitably limited by
computational constraints. For instance, for Markov chain Monte Carlo algorithms relying …
computational constraints. For instance, for Markov chain Monte Carlo algorithms relying …
Metamodel-based seismic fragility analysis of concrete gravity dams
Probabilistic methods, such as fragility analysis, have been developed as a promising
alternative for the seismic assessment of dam-type structures. However, given the costly …
alternative for the seismic assessment of dam-type structures. However, given the costly …
Artificial intelligence for structural glass engineering applications—overview, case studies and future potentials
Abstract'Big data'and the use of'Artificial Intelligence'(AI) is currently advancing due to the
increasing and even cheaper data collection and processing capabilities. Social and …
increasing and even cheaper data collection and processing capabilities. Social and …
An integrated texture analysis and machine learning approach for durability assessment of lightweight cement composites with hydrophobic coatings modified by …
The aim of the study was to determine a set of image texture features of the lightweight
cementitious composites (LLC) with hydrophobic coatings modified with nanocellulose and …
cementitious composites (LLC) with hydrophobic coatings modified with nanocellulose and …
Switching Bayesian dynamic linear model for condition assessment of bridge expansion joints using structural health monitoring data
Age-related deterioration and premature failure have been primary concerns for bridge
expansion joints. It is essential to improve the understanding of their operational …
expansion joints. It is essential to improve the understanding of their operational …
[HTML][HTML] Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review
Civil infrastructure assets' contribution to countries' economic growth is significantly
increasing due to the rapid population growth and demands for public services. These civil …
increasing due to the rapid population growth and demands for public services. These civil …
Design-oriented machine-learning models for predicting the shear strength of prestressed concrete beams
LA Bedriñana, J Sucasaca, J Tovar… - Journal of Bridge …, 2023 - ascelibrary.org
The shear behavior of prestressed concrete (PC) beams is a complex problem because
there are many influential parameters involved. Currently, the code-based shear strength of …
there are many influential parameters involved. Currently, the code-based shear strength of …