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- Carbonation depth (1)
- City Growth (1)
- Cladding Connection (1)
- Compressive strength (1)
- Computational wind engineering (1)
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- Durability (1)
- Fatigue (1)
- Flow visualization (1)
- Machine Learning; Deep Learning; Convolutional Neural Network; Damage Detection; Damage Localization; Structural Health Monitoring; Image Processing; Signal Processing; Vibration; Concrete structures. (1)
- Machine learning (1)
- Mixture proportioning (1)
- Rain-flow Counting Algorithm (1)
- Recycled aggregate concrete (1)
Articles 1 - 3 of 3
Full-Text Articles in Computational Engineering
Effects Of City Growth On Tall Building Cladding Fatigue, Hang You
Effects Of City Growth On Tall Building Cladding Fatigue, Hang You
Electronic Thesis and Dissertation Repository
As city develops there will be changes in the aerodynamic characteristics due to varying building surrounding and topology. For example, the city growth around a tall building can cause an increase in wind load due to venturi or wake effects or decrease due to sheltering effects depending on the type of surrounding. The densification of cities will also increase the turbulence level due to wake effects. In the present study, the implication of these changes on the aerodynamic forces on cladding connections is investigated. With increased fluctuations in the wind loads, the cladding connections will also experience stress fluctuations, which …
Machine Learning Prediction Of Mechanical And Durability Properties Of Recycled Aggregates Concrete, Itzel Rosalia Nunez Vargas
Machine Learning Prediction Of Mechanical And Durability Properties Of Recycled Aggregates Concrete, Itzel Rosalia Nunez Vargas
Electronic Thesis and Dissertation Repository
Whilst recycled aggregate (RA) can alleviate the environmental footprint of concrete production and the landfilling of colossal amounts of demolition waste, there need for robust predictive tools for its effects on mechanical and durability properties. In this thesis, state-of-the-art machine learning (ML) models were deployed to predict properties of recycled aggregate concrete (RAC). A systematic review was performed to analyze pertinent ML techniques previously applied in the concrete technology field. Accordingly, three different ML methods were selected to determine the compressive strength of RAC and perform mixture proportioning optimization. Furthermore, a gradient boosting regression tree was used to study the …
Classification, Localization, And Quantification Of Structural Damage In Concrete Structures Using Convolutional Neural Networks, Majdi Flah
Electronic Thesis and Dissertation Repository
Applications of Machine Learning (ML) algorithms in Structural Health Monitoring (SHM) have recently become of great interest owing to their superior ability to detect damage in engineering structures. ML algorithms used in this domain are classified into two major subfields: vibration-based and image-based SHM. Traditional condition survey techniques based on visual inspection have been the most widely used for monitoring concrete structures in service. Inspectors visually evaluate defects based on experience and engineering judgment. However, this process is subjective, time-consuming, and hampered by difficult access to numerous parts of complex structures. Accordingly, the present study proposes a nearly automated inspection …