Browsing by Author "Huang, Gordon"

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Open Access
Algal control and prevention technologies for Lake Diefenbaker irrigation canals
(Faculty of Graduate Studies and Research, University of Regina, 2023-03) Gebreselassie, Samuel Teclemariam; Young, Stephanie; Huang, Gordon; Sharma, Satish; Idem, Raphael
The Lake Diefenbaker irrigation project makes up an extensive 500 km of canals that officially began in July 2020. These canals contain pumps for increased and enhanced irrigation throughout southern and central Saskatchewan. However, the efficiency of the canals is hindered by the growth of filamentous algae. The filamentous algae are a nuisance and block pumps, making it difficult for water to be distributed to all the desired locations within the province. Currently, a synthetic chemical, Magnacide H, is utilized to control the growth of the algae at the cost of approximately $1 million per year, which is high cost. This study, as such, seeks to review, evaluate, compare, and develop algal prevention and control technologies as well as propose a suitable canal design option that would minimize algae growth. Five field trips to Lake Diefenbaker Irrigation Canals were conducted in June, July, August, September, and October to ascertain the factors contributing to the canal's algal blooms. Tests were also conducted to determine the canal's suitability for irrigation to check whether the key parameters were within the optimal range. According to the test results, all the parameters were within the recommended Saskatchewan irrigation guideline. This study considers three algal prevention and treatment options: 1) Non-toxic dyes and colorants, 2) microbubbles and nanobubbles, and 3) Ultrasound technology. The use of microbubbles and nanobubbles technology was selected as the most suitable option. Although highly efficient, the other options failed because of their high costs and low location suitability. Furthermore, the study recommends that the modified canal design be deeper, narrower, sloped, or trapezoidal. Such a design is recommended because it can limit the amount of sunlight entering the water. In addition, deepening the canal's edges with an inclination ratio of 2:1 can help control the growth of algae by minimizing the number of shallow areas that receive sunlight penetration. As research and testing for algal control and prevention methods are still relatively new, further research is required to understand the effectiveness of algal control and prevention technologies fully.
Metadata only
Development of a community-based participatory network for integrated solid waste management
(University of Regina, Graduate Students' Association, 2008-04) Cai, Yanpeng; Huang, Gordon; Hui, Yu; Qian, Tan
Major theme of the research is to develop a participatory network for integrated solid waste management under uncertainty and complexity through a broad participation of stakeholders. The network can integrate relevant factors, processes, objectives and their interactions into a general modeling framework through comprehensive data collection, participatory modeling formulation and interactive policy analysis. Methods of questionnaire survey, systems analysis, stochastic process forecasting and inexact optimization will be jointly employed to allow systematic and comprehensive consideration of a number of social, economic, environmental and technical issues that are related to solid waste management at a community scale. It is anticipated that the proposed research can be directly useful for accomplishing integrated solid-waste management in many communities. The proposed network can be effective for easing the environmental burdens that exacerbate local people, strengthening the capacity of the stakeholders to access environmental services. The research outcomes include (a) results of the nature of environmental burdens and their impacts, (b) a participatory network for the collaboration of poor urban communities, NGOs, service providers and multiple-scale governments, (c) techniques for the promotion of community involvement and public participation in formulating policies related to integrated solid waste management, and (d) optimal decision alternatives for the collection, storage, transportation and disposal of solid waste. This research is to develop a community-scale participatory network for solid waste management, which is based on Methods of questionnaire survey, systems analysis, stochastic process forecasting and inexact optimization. The network could be useful for management municipal solid waste under multiple objectives.
Open Access
Development of Inference Methodology for Supporting Understanding of Composting Processes
(University of Regina Graduate Students' Association, 2011-04-01) Sun, Wei; Li, Gongchen; Huang, Gordon
Composting, one of the promising biotechnologies for solid waste management, is a process where organisms convert organic materials into a hygienic and bio-stable humus-like product. Food waste composting has gained increased attention in the past decade. Efficient operations of composting relies on insights of relationships between state variables (e.g. oxygen concentration, ash content, moisture content, and pH) and specific characteristics (e.g. microbial activities, maturity, and stability). Previously, many experimental approaches were developed in analyzing these relationships. However, experiment-based evaluations could hardly help quantify the interactions among multiple composting state variables. In comparison, a model-based analysis could help examine the inherent impacts of various factors on the biological and physiochemical processes and gain an in-depth insight into the related mechanisms. This study attempted to develop inference methodology based on multivariate analysis to describe the nonlinear relationships between the selected state variables and characteristics of interest in food waste composting. The experimental data from bench-scale composting reactors were used to demonstrate the applicability of proposed methods. These methods would help identify the most significant relationships, understand the interactive mechanisms, and infer the hard-to-obtain characteristics in an easier manner, during composting and many other environmental processes.
Open Access
Dewatering Behaviour of Clay Slurries
(Faculty of Graduate Studies and Research, University of Regina, 2017-01) Khan, Faseel Suleman; Azam, Shahid; deMontigny, David; Velez, Maria; Huang, Gordon
The main objective of this research was to develop a fundamental understanding of the dewatering behaviour of clay slurries. A comprehensive research methodology was developed to understand the natural dewatering processes of consolidation, desiccation and consolidation-desiccation. Laboratory investigation methods were improved, data analysis techniques were enhanced, and numerical methods were customized. An active clay slurry was prepared at different initial conditions (3 LL to 1 LL) to mimic field conditions ranging from a thin slurry to a paste-like consistency. Thin samples were used in a conventional oedometer test and in the evaporation test. A correlation was developed between the oedometer test and the bench-top centrifuge test to describe slurry consolidation. Likewise, the instantaneous profile method was applied to thin samples resulting in avoiding the need of instrumentation in evaporation tests. The small-strain consolidation theory was customized to predict large-strain consolidation deformations and diffusion equation was used to simulate desiccation. The use of effective stress and soil suction as state variables was found suitable for clay slurries. A consolidation-desiccation framework was developed to identify the governing dewatering processes operative within a slurry deposit. This research produced useful laboratory test methods, which can be implemented at on-site laboratories for determining the consolidation and desiccation properties of clay slurries. Similarly, the improved understanding of the significance of initial conditions (suspension to a paste-like consistency) on slurry dewatering is important to develop material-specific tailings deposition schemes. Finally, an understanding of the governing dewatering processes is useful to develop site-specific tailings management strategies.
Open Access
Multi-level energy-environmental-economic modeling for supporting low-carbon transition of power systems under uncertainty
(Faculty of Graduate Studies and Research, University of Regina, 2022-11) Zhang, Xiaoyue; Huang, Gordon; Young, Stephanie; Zhu, Hua; Yao, Yiyu; Qin, Xiaosheng
To combat climate change, the low-carbon transition of electricity systems is of critical significance. Such transition is a complex and long-term process, involving many social, economic, environmental, technical and political factors, and requires a complete analysis for every aspect of the transition pathways. In this dissertation, low-carbon transition strategies of electricity systems were studied from three levels. A set of identification, optimization, and simulation models were developed to facilitate the analysis. For the efforts made at the technical level, the necessity and feasibility of introducing an emerging low-carbon power generating technology (i.e., SMRs) have been studied, with a focus on suitable site selection and environmental impact analysis. For the power systems level, optimized low-carbon transition pathways have been identified, taking into account the effects of multiple uncertainties and the associated risks. In addition, given the tight ties that exist between socio-economic systems and power systems, corresponding impacts of the transition strategy made in the second level on socioeconomic systems have been explored, such that the performance of the entire economy can be assessed. The major contribution of this research is the development of a set of innovative models to aid in the management of power system transition under uncertainty. Overall, the proposed models outperformed the previous modeling approaches due to their advantages in complexity characterization, uncertainty representation, impact analysis, and policy formulation. In detail, the proposed models and related contributions are: (1) climate-oriented SMR site recognition model (CSSR), which is capable of taking long term variation of climate conditions into consideration while conducting siting studies; (2) SMR-induced environmental input-output model (SEIOM), which can quantify contributions of having an emerging power-generating technology as an alternative energy supplier to emission mitigation and related impacts on other sectors; (3) stochastic multistage lifecycle programming model (SMLP), through which detailed environmental and economic profiles of each power generation technology were systematically investigated within lifecycle frameworks and were considered in power system optimization modeling, such that the robustness of the resulting decision support can be enhanced; (4) coupled non-deterministic optimization and mixed-level factorial analysis model (NOMFA), which is an attempt to integrate the system optimization methods with mixed-level factorial design under various uncertainties, such that effects of various external interferences and their interactions on the systems can be investigated; (5) nondeterministic optimization-driven factorial CGE model (NFCGE), which is an integration of “economy-wide” equilibrium models and “technology-rich” energy system optimization approaches, and can help investigate the responses of various economic sectors to alternative transition strategies as identified through the optimization efforts. The developed models were applied to a number of Canadian and Chinese cases to demonstrate the applicability and superiority. The results can assist decision-makers in identifying the most efficient and feasible low-carbon transition pathways for power systems and in achieving a more balanced energy-environment-economic structure.
Open Access
Piecewise Linearization-based Inexact Nonlinear Programming for Waste Management
(University of Regina Graduate Students' Association, 2011-04-02) Sun, Wei; Li, Gongchen; Huang, Gordon
Effects of economies-of-scale can often bring about nonlinearities in objective functions in a municipal solid waste management planning under uncertainties. Previously, two types of approaches were employed to deal with the scale effects within an inexact optimization framework. One approach was to find efficient algorithms to directly solve the resulting nonlinear objective functions with inexact information. The other type of approach was to approximate nonlinear expressions so that existing algorithms could be applied. In fact, nonlinear systems usually can be approximated more accurately by piecewise linear functions through splitting the state space into piecewise regions and assuming sub-system is linear within each region. Thus, this study aims to develop piecewise linearization-based inexact nonlinear programming and apply it to hypothesis cases of waste allocation planning. Interactive algorithms were designed for solving the proposed methods. The results showed that a more accurate approximation for nonlinearities reflecting effects of economies-of-scale between unit transportation costs and waste flows as well as between unit operation costs and waste treatment amounts were obtained. Most of unit transportation costs or unit operation costs were less than those in conventional programming, which finally contributed to a lower net system costs. This implied that the often ignored effects of economies-of-scale should be considered accurately in the real-world waste management system.