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Skip to Search Results- 150Graduate and Postdoctoral Studies (GPS), Faculty of
- 150Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 8Physics, Department of
- 8Physics, Department of/Journal Articles (Physics)
- 7Computing Science, Department of
- 6Mathematical and Statistical Sciences, Department of
- 150Thesis
- 28Article (Published)
- 8Report
- 4Article (Draft / Submitted)
- 4Research Material
- 2Conference/Workshop Poster
- 55Department of Civil and Environmental Engineering
- 19Department of Chemical and Materials Engineering
- 18Department of Computing Science
- 17Department of Electrical and Computer Engineering
- 14Department of Mechanical Engineering
- 4Department of Physics
- 6Al-Hussein, Mohamed (Civil and Environmental Engineering)
- 5AbouRizk, Simaan (Civil and Environmental Engineering)
- 3Dinavahi, Venkata (Electrical and Computer Engineering)
- 3Huang, Biao (Chemical and Materials Engineering)
- 3Mohamed, Yasser (Civil and Environmental Engineering)
- 3Nikolaidis, Ioanis (Computing Science)
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Fall 2022
The objective of signal decomposition is to extract and separate distinct signal components from a composite signal. Signal decomposition has been studied in many applications, such as image, video, audio, and speech signals. This thesis focuses on the category of signal decomposition on...
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Re-Sampling the Ensemble Kalman Filter for Improved History Matching and Characterizations of Non-Gaussian and Non-Linear Reservoir Models
DownloadSpring 2015
Reservoir simulation models play an important role in the production forecasting and field development planning. To enhance their predictive capabilities and capture the uncertainties in model parameters, stochastic reservoir models should be calibrated to both geologic and flow observations. The...
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Fall 2009
In the refining industry, the cost of a power system interruption is dominated by an associated loss of production. Power distribution within a refinery includes a set of production units within a highly inter-dependent process, where the outage of a single unit affects the production of...
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Spring 2020
Reinforcement learning (RL) has received wide attention in various fields lately. Model-free RL brings data-driven solutions that learn the control strategy directly from interaction with process data without the need for a process model. This is especially beneficial in the case of nonlinear...
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Reservoir and geomechanical coupled simulation of CO2 sequestration and enhanced coalbed methane recovery
DownloadFall 2009
Coalbeds are an extremely complicated porous medium with characteristics of heterogeneity, dual porosity and stress sensitivity. In the past decades great achievements have been made to the simulation models of pressure depletion coalbed methane (CBM) recovery process and CO2 sequestration and...
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Residential construction manufacturing estimating framework: the case of lightweight timber framing
DownloadFall 2020
The term industrialized construction was adopted by the offsite construction industry where the building components are prefabricated in factories and then transported to the construction site for on-site assembly. With this shift towards industrialized construction, new challenges were...
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Results of optimization parameter experiments
2014-04-01
A set of experiments performed in QUB-Express to compare different optimizer configurations.
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Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization
DownloadFall 2015
Availability of large amounts of industrial process data is allowing researchers to explore new data-based modelling methods. In this thesis, Gaussian process (GP) regression, a relatively new Bayesian approach to non-parametric data based modelling is investigated in detail. One of the primary...
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