Review of artificial intelligence-based bridge damage detection
Bridges are often located in harsh environments and are thus extremely susceptible to
damage. If the initial damage is not detected in time, it can develop further causing safety …
damage. If the initial damage is not detected in time, it can develop further causing safety …
Optimizing machine learning algorithms for improving prediction of bridge deck deterioration: A case study of Ohio bridges
A Rashidi Nasab, H Elzarka - Buildings, 2023 - mdpi.com
The deterioration of a bridge's deck endangers its safety and serviceability. Ohio has
approximately 45,000 bridges that need to be monitored to ensure their structural integrity …
approximately 45,000 bridges that need to be monitored to ensure their structural integrity …
Bridge infrastructure asset management system: Comparative computational machine learning approach for evaluating and predicting deck deterioration conditions
R Assaad, IH El-Adaway - Journal of Infrastructure Systems, 2020 - ascelibrary.org
Bridge infrastructure asset management system is a prevailing approach toward having an
effective and efficient procedure for monitoring bridges through their different development …
effective and efficient procedure for monitoring bridges through their different development …
A state-of-the-art review of bridge inspection planning: Current situation and future needs
AM Abdallah, RA Atadero, ME Ozbek - Journal of Bridge …, 2022 - ascelibrary.org
Inspections are important to ensuring adequate safety and performance of a bridge
throughout its service life. Bridge inspections are highly connected with maintenance …
throughout its service life. Bridge inspections are highly connected with maintenance …
Evaluating deterioration of tunnels using computational machine learning algorithms
Tunnels are an integrated part of the transportation infrastructure. Structural evaluation and
inspection of tunnels are vital tasks to assess the deterioration of tunnels and maintain their …
inspection of tunnels are vital tasks to assess the deterioration of tunnels and maintain their …
Compressive Strength Evaluation of Fiber‐Reinforced High‐Strength Self‐Compacting Concrete with Artificial Intelligence
TT Nguyen, H Pham Duy… - Advances in Civil …, 2020 - Wiley Online Library
This paper describes the application of two artificial intelligence‐(AI‐) based methods to
predict the 28‐day compressive strength of fiber‐reinforced high‐strength self‐compacting …
predict the 28‐day compressive strength of fiber‐reinforced high‐strength self‐compacting …
Structural damage detection using hybrid deep learning algorithm
Timely monitoring the large-scale civil structure is a tedious task demanding expert
experience and significant economic resources. Towards a smart monitoring system, this …
experience and significant economic resources. Towards a smart monitoring system, this …
Bridge deck deterioration: Reasons and patterns
The deck condition of bridges is one of the most important factors impacting the connectivity
and efficiency of transportation networks. Bridges with quickly deteriorating deck conditions …
and efficiency of transportation networks. Bridges with quickly deteriorating deck conditions …
Modeling the quantitative assessment of the condition of bridge components made of reinforced concrete using ANN
R Trach, V Moshynskyi, D Chernyshev, O Borysyuk… - Sustainability, 2022 - mdpi.com
Bridges in Ukraine are one of the most important components of the infrastructure, requiring
attention from government agencies and constant funding. The object of the study was the …
attention from government agencies and constant funding. The object of the study was the …
[PDF][PDF] A neural network approach for predicting hardened property of geopolymer concrete
This paper presents the application of an Artificial Neural Network (ANN) approach to predict
the 28-day compression strength of Geopolymer concrete (GPC) from the input ingredients …
the 28-day compression strength of Geopolymer concrete (GPC) from the input ingredients …