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Skip to Search Results- 4Artificial neural network
- 1Axial crack
- 1Bayesian inference
- 1Building performance evaluation
- 1Building thermal dynamics
- 1Condition based maintenance
- 1AbouRizk, Simaan (Civil and Environmental Engineering)
- 1Adeeb, Samer (Civil and Environmental Engineering)
- 1Chen, Yuxiang (Civil and Environmental Engineering)
- 1Hammad, Ahmed (Civil and Environmental Engineering)
- 1Leung, Juliana (Civil and Environmental Engineering)
- 1Tian, Zhigang (Mechanical Engineering)
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Fall 2020
This research involves the development of a forecasting model that will aid project managers in estimating the owner’s project management staff requirements for a construction project utilizing historical data. This will support project managers in the decisions of hiring new resources or working...
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Spring 2019
Data-driven modelling has been widely applied in building operation optimization, energy management, ongoing commissioning, and so on. This thesis presents a comprehensive study of data-driven modelling for analysis of building thermal dynamics. First, three types of data-driven models, namely,...
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Novel Artificial Neural Network Model for Predicting Failure Pressure of Thin-walled Pipes Containing Axially-oriented Surface Cracking Subjected to Internal Pressure
DownloadSpring 2024
Axial cracking is a major integrity threat for oil and natural gas transmission pipelines in Canada since its presence can lead to detrimental oil leaks or ruptures, resulting in pipeline incidents, and eventually causing severe damage to the property and the environment. Therefore, periodically...
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Fall 2018
Maintenance management in wind energy industry has great impact on overall wind power cost. Optimizing maintenance strategies can substantially reduces the cost and makes wind energy more competitive among the energy resources. Due to the extreme conditions of remote or offshore sites where the...