Doctoral Theses and Dissertations

Permanent URI for this collection


Recent Submissions

Now showing 1 - 20 of 453
  • ItemOpen Access
    Predictive visual servoing; uncertainty analysis and probabilistic robust frameworks
    (Faculty of Graduate Studies and Research, University of Regina, 2023-06) Sajjadi, Sina; Mehrandezh, Mehran; Janabi-Sharifi, Farrokh; Dai, Liming; Stilling, Denise; Paranjape, Raman; Mouhoub, Malek; Xie, Wen-Fang
    Motion control of robots in unstructured environments is a challenging task. The utilization of cameras as an information-rich sensor shows promise. In this context, image-based visual predictive controllers have gained attention due to their optimal-ity and constraint-handling capabilities. However, their performance deteriorates in presence of uncertainties in the robotic platforms, system models, and measurements. This work proposes a set of robust image-based visual predictive control methods that overcome the shortcomings of the previous visual servoing methods in the presence of uncertainties. In this dissertation, we have proposed a set of adaptive, stochastic, risk-averse, and learning-based visual servoing schemes that improve the performance and constraint compliance of visual servoing systems compared to their classical coun-terparts. The validity of the proposed control frameworks has been evaluated on a 6-DOF serial industrial manipulator and a model unmanned aerial vehicles via various experiments and simulations.
  • ItemOpen Access
    Systems Biology of Host-Pathogen Protein-Protein Interactions
    (Faculty of Graduate Studies and Research, University of Regina, 2023-06) Rahmatbakhsh, Matineh; Babu, Mohan; Dahms, Tanya; Hansmeier, Nicole; Hu, Pingzhao
    Despite undeniable therapeutic developments in infectiology, emerging infectious diseases continue to be a growing threat to public health, as seen by the current COVID- 19 pandemic caused by the novel virus severe acute respiratory syndrome coronavirus (SARS-CoV-2). This virus is classified as an obligate intracellular parasite that co-opts host cellular proteins, often through protein-protein interactions (PPIs), to ensure its replication. Therefore, this thesis aims to integrate high-throughput proteomic approaches with computational modelling to systematically characterize SARS-CoV-2-human networks for a detailed understanding of SARS-CoV-2 pathogenesis. The angiotensin-converting enzyme (ACE2) receptor of SARS-CoV-2 is displayed on many human cells, including the lungs and other organs. However, despite considerable knowledge explaining the SARS-CoV-2 infection mechanism, organ-specific SARS-CoV- 2-host protein interactions remain understudied. In Chapter 2, we carried out an organ/tissue-unbiased proteomic profiling approach of mapping SARS-CoV-2-human protein interactions using high-throughput mass spectrometry (MS)-based proteomic approaches. First, automated machine learning (ML)-based computational workflows with different algorithmic strategies were devised to generate high-quality tissue-specific and tissue-common SARS-CoV-2-human PPIs. Subsequent clustering of highly conserved networks using an optimized complex-based analysis framework uncovered several virally targeted protein complexes (VTCs), reflecting conserved mechanisms of replication. Finally, organ/tissue-specific interaction revealed that NSP3 protein evades host antiviral innate immune signaling by targeting IFIT5 for de-isgylation. Although host interactome is indirectly affected during viral infection, earlier studies have only focused on characterizing the properties of the viral proteins within the host-viral interactions. However, systematically exploring the host-viral interactions from the perspective of the host interactome is essential and should be included in PPI network for a better understanding of viral pathogenesis. In Chapter 3, we combined cofractionation mass spectrometry (CF-MS) with a novel deep learning-based framework, DeepiCE, to map physiologically relevant viral-host and host interactome. First, through comprehensive statistical validations, we demonstrated the remarkable performance of DeepiCE over the state-of-the-art method for network construction. DeepiCE was then applied to co-elution data from salivary samples of individuals infected with SARS-CoV- 2, which led to the generation of high-quality viral-host and host interactome maps highly relevant to SARS-CoV-2 infection. Subsequent clustering of resulting networks using a sophisticated two-stage clustering framework generated high-quality SARS-CoV-2 affected protein complexes, many of which were enriched for diverse cellular processes related to viral pathogenesis and provided new insights into SARS-CoV-2 infection from both the host and pathogen perspective. Despite arduous and time-consuming experimental efforts, PPIs for many pathogenic microbes with their human host are still unknown, limiting our understanding of the intricate interactions during infection and the identification of therapeutic targets. Since computational tools offer a promising alternative, in Chapter 4, we developed a R/Bioconductor package, HPiP software with a series of amino acid sequence property descriptors and an ensemble machine learning classifiers to predict the yet unmapped interactions between pathogen and host proteins. Using SARS-CoV-1 or the novel SARSCoV- 2 coronavirus-human PPI training sets as a case study, we show that HPiP achieves good performance with PPI predictions between SARS-CoV-2 and human proteins, which we confirmed experimentally using several quality control metrics. HPiP also exhibited strong performance in accurately predicting the previously reported PPIs when tested against the sequences of pathogenic bacteria, Mycobacterium tuberculosis and human proteins. Collectively, our fully documented HPiP software will hasten the exploration of PPIs for a systems-level understanding of many understudied pathogens and uncover molecular targets for repurposing existing drugs.
  • ItemOpen Access
    Examining Motivational Interviewing and Booster Sessions in Internet-Delivered Cognitive Behaviour Therapy for Post- Secondary Students: An Implementation Trial
    (Faculty of Graduate Studies and Research, University of Regina, 2022-01) Peyenburg, Vanessa Angelica; Hadjistavropoulos, Heather; Beshai, Shadi; Wright, Kristi; Hebert, Cristyne; Alavi, Nazanin
    Approximately one in three post-secondary students experience clinical levels of anxiety or depression during their academic career, with many students not receiving treatment. Internet-delivered cognitive behaviour therapy (ICBT) is an alternative to face-to-face services that is effective in general adult populations, but has been associated with high attrition rates and smaller effect sizes in student populations. In this implementation trial, the efficacy and uptake of an ICBT course for anxiety and depression (i.e. the UniWellbeing Course) was examined in Saskatchewan. Given the evidence from the face-to-face literature, the role of motivational interviewing (MI) and booster lessons was also examined. Using a two-factor design (factor 1: online MI); factor 2: booster lesson), a total of 308 clients were randomized to one of four groups: standard care (n = 78), MI (n = 76), booster (n = 77), and MI + booster (n = 77). Overall, 89.9% (n = 277) of clients started treatment. The aims of the study were to assess (1) the efficacy of the UniWellbeing Course in reducing symptoms of anxiety and depression and increasing perceived academic functioning; (2) the impact of a pre-treatment MI component on attrition and engagement; (3) the impact of a booster lesson on depression, anxiety, and perceived academic functioning at 3-month follow-up; and (4) the combined effect of MI and booster. Overall, students reported significant, large decreases in symptoms of depression (Cohen’s d: 1.25 – 1.67) and anxiety (Cohen’s d: 1.42 – 2.01) from pretreatment to post-treatment, with 47.5% and 56.6% of clients experiencing reliable recovery on measures of depression and anxiety, respectively. Small, but significant, effects were seen for improvements in perceived academic functioning across the four conditions (Cohen’s d: 0.20 – 0.48). Changes were maintained at 1-month and 3-month ii follow-up on all primary measures across conditions. Overall, 54.0% (n = 150) of clients accessed all four lessons of the UniWellbeing Course. The addition of pre-treatment MI did not confer improvements to treatment completion rates or engagement (e.g., mean logins or messages sent to therapists). Small between-group effects were seen in favour of MI for depression (Cohen’s d: 0.23), anxiety (Cohen’s d: 0.25), and mental healthrelated disability (between-group Cohen’s d: 0.35) at post-treatment. In terms of the booster lesson, only 30.9% (n = 43) of clients accessed the booster lesson, although clients who accessed it were satisfied with the content and timing of the booster overall. Between-group effects were not significant for the booster at 3-month follow-up. Subanalyses comparing clients who utilized the booster to those who did not were underpowered, but revealed a larger decrease in depressive symptoms (between-group Cohen’s d: 0.31) at 3-month follow-up. No advantage was found for the combination of MI and booster on treatment completion, engagement, or outcomes. Overall, there is some evidence to suggest that including MI at pre-treatment results in greater symptom reduction although these benefits do not persist to 1-month and 3-month follow-up. The inclusion of a self-guided booster lesson may also help with continued symptom management up to 3-month follow-up, but low uptake is a barrier to clients experiencing these benefits. Uptake of the course was highest among White female participants and at large universities, suggesting a need for alternative recruitment strategies to increase uptake among other student populations. Findings from this trial contribute to the literature on improving ICBT outcomes for post-secondary students.
  • ItemOpen Access
    Examining native Saskatchewan bumble bees health using species occurrence data, pathogen incidence and gut microbial associations
    (Faculty of Graduate Studies and Research, University of Regina, 2023-07) Palmier, Kirsten Michelle; Cameron, Andrew; Sheffield, Cory; Davis, Maria; Somers, Chris; Siemer, Julia; Currie, Rob
    Bees are important pollinators, though, recent evidence suggests some species of bumble bees (Hymenoptera, Apidae, Bombini, Bombus Latreille) are declining in parts of their ranges due to a combination of drivers such as climate change, pesticide use, habitat loss, competition for resources and pathogens acting upon the bees at once. A relatively new and important area of gut microbial research, the fungal and bacterial gut community members, could offer insight on why some species of bumble bees are declining while others remain stable. In this thesis, I use a combination of field and molecular methods to investigate aspects of bumble bee health in Saskatchewan, Canada, including species occurrence and pathogen incidence and explore microbial associations with known and potential pathogens. The second chapter explores the need for a bumble bee monitoring program in Saskatchewan and how standardization compares to non-standardized survey methods. I compared bumble bee occurrence data from four datasets in terms of sampling effort over time and how properties of each dataset influenced species conservation assessments. The Palmier dataset was a single collection event in 2018 using a standardized survey methods. The Royal Saskatchewan Museum (RSM) and Global Biodiversity Information Facility (GBIF) datasets represented specimens collected with unstandardized collection events over decades. The iNaturalist dataset contained citizen science observations. The Palmier dataset was the largest of the four datasets and despite the single collection event, species richness in the Palmier dataset was comparable to the RSM and GBIF datasets. The iNaturalist dataset was biased to locations with higher population density and overrepresented species at-risk compared to the Palmier, RSM and GBIF datasets. The third chapter (previously published) documents the first occurrences of the Common Eastern Bumble Bee (B. impatiens), a managed species that is not native to the Canadian prairies, recorded from southeastern Alberta. The fourth chapter (also previously published) documents the first Canadian occurrence of a recently characterized trypanosomatid bumble bee pathogen, Crithidia expoeki, in native Saskatchewan bumble bees. The fifth chapter explores the fungal and bacterial gut communities of bumble bees and their associations with common bee pathogens. The results indicate that pathogens cause dysbiosis, or imbalance of microbial communities in bumble bees. A differential abundance analysis revealed significantly enriched and depleted taxa in bees testing positive for specific pathogens. The results from this study can be used to compare microbial strain level differences across geographic landscapes over time. The sixth chapter investigates a novel yeast association and swollen proventriculus in the digestive tract of at-risk bumble bee species across Canada. It was discovered that the swollen proventriculus morphology occurred only in males in the subgenus Bombus, a taxon in which the majority of North American species are at-risk. Classic culturing methods and Sanger sequencing revealed that bumble bees with a swollen proventriculus harboured distinct yeast communities in high numbers. Using 16S rRNA sequencing, I also found higher abundances of lactic acid bacteria and Gillimella bacteria in male bumble bees with a swollen proventriculus compared to bumble bees of both sexes without.
  • ItemOpen Access
    Heavy oil recovery by combined solvent and hot water (CS-HW) injection: Experimental, numerical and data mining-based analysis
    (Faculty of Graduate Studies and Research, University of Regina, 2023-06) Masoomi, Reza; Torabi, Farshid; Muthu, Jacob; Tontiwach, Paitoon; Zeng, Fanhua; Mobed, Nader; Hassanzadeh, Hassan
    In this study, a hybrid EOR process is developed and optimized in a two-well configuration for heavy-oil recovery which combines solvent injection using different solvents such as carbon dioxide (CO2), methane (CH4) and propane (C3H8) with a moderate reservoir heating by hot-water flooding (HWF) as a solution to enhanced heavy oil recovery (EHOR), reduce energy consumption, and improved solvent retrieval efficiency. The combined injection of solvent and hot water offers several advantages including reduction of energy consumption compared to steam-based thermal EOR methods, and reduction of solvent volume required to reduce the viscosity of heavy oil. The proposed hybrid EOR method of combined solvent and hot water (CS-HW) injection outperformed the sole injection of solvent, conventional water flooding (WF) and hot-water flooding (HWF) by sustaining the foamy oil flow and effectively delaying water and gas breakthrough times. A total of 21 laboratory tests including water flooding (WF), hot-water flooding (HWF), solvent injection, combined solvent and hot water (CS-HW) injection in a two-well configuration were designed and conducted. More specifically, the design parameters such as injection rate (qinj) and temperature (Tinj), solvent composition and slug size were optimized with the objective of maximizing heavy oil recovery. In order to study the numerical simulation of CS-HW injection and other laboratory tests presented in this research, CMG-STARS module was used. Sensitivity analysis was performed on the effective parameters of CS-HW injection process to obtain the best history-match between the experimental data and the simulation model. Furthermore, a new computational approach for predicting the performance of hot-water flooding (HWF) in unconsolidated heavy oil reservoirs was presented. The proposed model predicts the changes in the oil–water viscosity ratio (μo/μw) by estimating the reservoir temperature distribution through porous media. Then, the dimensionless and normalized variables were redefined to forecast water fractional flow as a function of temperature and water saturation. Moreover, the proposed approach predicts the cumulative heavy oil production and recovery factor more accurately and with less required input data and runtime compared to CMG-STARS (computer modeling group), etc. Estimated results were validated using laboratory experimental data and numerical simulation outputs. The relative errors between oil recovery factors obtained from computational approach and experimental data were measured to be about 5.3%, 1.7% and 1.2% and 2.5% for injection temperatures of 40, 60, 80 and 100 °C, respectively. Finally, this thesis provides a novel data mining-based analysis by using artificial neural network (ANN) methodology to develop a high-performance neural simulation tool for predicting the efficiency of CS-HW injection process. In order to train, test and validate the model the experimental and simulation data obtained in this study together with available data in the literature were fed to the machine learning technique to develop a CSHW recovery performance predictive model. The proposed intelligent predictive model is expected to help petroleum engineers as an alternative model to predict the efficiency of CS-HW injection process, where other models have limitations and their input parameters are often not easily accessible.
  • ItemOpen Access
    A narrative exploration of the right to health in the lives of Indigenous women
    (Faculty of Graduate Studies and Research, University of Regina, 2023-06) Latta, Lori Patricia; Hoeber, Larena; Cooper , Elizabeth; Green , Brenda; Abonyi, Sylvia; McIntosh, Thomas; Forman, Lisa
    This study explores, through critical narrative analysis, the understanding of Indigenous women about conditions that they need to be healthy, and how their stories and reflections provide a critique that can inform thinking around the right to health. Literature from varied disciplinary perspectives describes the right to health, and a body of health human rights, as conceptual tools that identify the conditions all people require to be healthy, encompassing not just health care and access to material goods, but equality, culture, power and participation. Literature also provides some critique of human rights, and indicates that their alignment with dominant discourses and powers may be a barrier to their effectiveness for Indigenous people. With reference to Habermas’ theories of communicative action, including the colonization thesis, the lifeworlds of 14 Indigenous women were explored in relation to the institutional discourse of health human rights. The study finds that in the stories that women shared there was some validation of human rights instruments relating to health, which identify as rights violations health harms such as violence, disruption of families, experiences of racism, and lack of support for mental health. However, women’s interpretation of these events often differed from institutional discourse in that they located responsibility for violations less in the people or organizations that harmed them, and more in processes of colonization carried out by successive Canadian governments, that effectively undermined their rights and their health. As they reflected on their stories, women identified a right to knowledge about history and the impact of colonization on Indigenous people as being important to their physical and mental health. Other findings are that a rights-based assessment of women’s health that focuses on experiences of violations and harms may be perceived as deficit-based. To be more meaningful to Indigenous women, a discourse of human rights in health could speak to their strengths and resources, and support broadly defined goals in physical, spiritual and mental health by removing barriers to agency. This study joins a body of other research in finding that explicit rights-based participation in service delivery and health policy development and evaluation may help to avoid abuses in the future, but may require more autonomous forms of governance and service delivery to address longstanding power imbalance and distrust. The study concludes that a discourse of health human rights can better meet the needs of Indigenous women when colonialism is named as a human rights abuse and the primary cause of health inequity that affects their families and communities, reinforcing their life world knowledge with rights-based accountability, and creating common understanding in the public sphere.
  • ItemOpen Access
    Policy issue networks: Social network analysis case studies
    (Faculty of Graduate Studies and Research, University of Regina, 2023-07) Katchuck, Michelle Lisa; McNutt, Kathleen; Longo, Justin; Rayner, Jeremy; Childs, Jason; Stoddart, Mark CJ
    This research demonstrates that Social Network Analysis (SNA) can be a powerful, proactive tool for policy makers to understand the online policy networks in which they operate. It does so by undertaking SNA at two points in time to quantify the actor nodes of three Canadian public policy networks, comparing the network evolution over time, and visualizing their structure and relationships with related policy issues. The three Canadian policy case study subjects are cannabis legalization, nuclear energy development, and the Trans Mountain Pipeline expansion project (TMX). The cases were selected for their current social importance and national concern, and complexity as socio-technical systems. Cannabis legalization represents a social policy shift, while the other two policy issues involve highly technical infrastructure projects to provide the energy that drives modern society at a time when energy solutions and needs are shifting. The research was undertaken to answer three main questions: Does a network structure consist of multiple clusters of subnetworks primarily concerned with tangential issues but bridged together to form a network for this policy issue? Is there any evidence of network effects that affect the network’s evolution over time? Finally, is there evidence that regional or international networks are present? The study’s findings provide significant evidence that addresses these questions. For example, for question one, the cannabis legalization network shows an isolated online community primarily interested in the research and use of cannabis as a medical treatment, an issue tangential to the primary policy focus but connected to the policy issues. For question two, Canada’s stated nuclear policy shift toward small modular reactors reveals an online issue network dominated by industry rather than government actors. Finally, regarding question three, the study found that regional clusters were especially apparent in the cannabis legalization and TMX networks. This research provides insight into the policy networks of the specific cases, which contributes to the literature on these policy topics and network analysis in terms of network structure and evolution. It also validates the use of SNA in a policy analysis toolkit. Where existing literature has examined Internet-age government, it has found that governments often replicate routine procedures and processes in new, virtual forms rather than innovate or reimagine their capabilities. Government actors have improved their responsiveness, but they also need to fundamentally change their behaviour, particularly in engaging stakeholders in meaningful public policy analysis. SNA is a novel use afforded by technology that has gone unexplored to innovate government performance. This dissertation adds to the lengthy body of research in SNA by experimenting with a practical application of its theories and methods. The critical conceptual approach underpinning this thesis is complexity theory, which provides the framework to situate the dynamic environment of policy making and stakeholder engagement. It is hoped that this research will help policy makers by providing a toolkit that enables visualizing how issue patterns emerge in real-time, patterns that can represent the “unknown unknowns” — the voices not yet heard, the unanticipated concerns, and the opportunities not yet discovered to reach out to broader or underrepresented communities in the policy arena.
  • ItemOpen Access
    Exploring the work-related experiences of retail workers in Saskatchewan: A critical narrative study
    (Faculty of Graduate Studies and Research, University of Regina, 2023-08) Gyimah, Issah; Abu, Bockarie; Xia, Ji; Twyla, Salm; Gabriela, Novotna; Ken, Montgomery
    The retail industry is predominant in providing goods and services to customers worldwide. For example, studies have found that more than 10% of employees work in the retail sector in Canada. However, frontline retail employees experience considerable challenges, such as mistreatment and hostility from managers. Yet, research has generally failed to explore the nature of those challenges or offer strategies to address them. Using a narrative inquiry/approach methodology, the study explored the work-related experiences and conditions of four frontline retail workers at a Regina, Saskatchewan, Canada store. The study drew on critical theory and social justice theory as theoretical lenses to challenge the prevalence of neoliberal ideology at the studied workplace and its influence on the work-related experiences of frontline workers at that workplace. The narrative inquiry building blocks of temporality, sociality, spatiality, and other narrative approaches, as well as the theoretical framework, guided the presentation and discussion of the study findings. The participants’ narratives revealed they experienced neoliberal policies and practices that they thought constituted voicelessness, sexism, individualism, racism, nepotism, underemployment, and cronyism at their retail store. The integration of the participants’ data created informative narratives of their work-related experiences and offered a way to improve their fragmented, scattered, and sometimes contradictory narratives into coherent narratives. The narratives also revealed that some participants perceived their workplace conditions as overwhelming, harsh, and alien. The implications of the findings of the study for policy, practice, and theory development, as well as suggestions for further research and recommendations arising from the study, are discussed.
  • ItemOpen Access
    Treating comorbid insomnia in patients receiving transdiagnostic Internet-delivered Cognitive Behaviour Therapy for anxiety and depression: A randomized controlled trial
    (Faculty of Graduate Studies and Research, University of Regina, 2023-06) Edmonds, Micheal Robert; Hadjistavropoulos, Heather; Carleton, R. Nicholas; Gordon, Jennifer; Katapally, Tarun; Berger, Thomas
    Studies have demonstrated that transdiagnostic Internet-delivered Cognitive Behavioural Therapy (ICBT) programs for patients experiencing anxiety and depression can produce large improvements in symptoms. Comorbid insomnia is common among individuals seeking treatment for anxiety and depression, yet transdiagnostic ICBT programs rarely target insomnia and many ICBT patients report that symptoms of insomnia remain after treatment. The current trial was designed to explore the value of including a brief intervention for insomnia alongside an existing transdiagnostic program (Wellbeing Course). A new insomnia intervention was developed using a patient-oriented approach to maximize ease-of-understanding and overall acceptability to patients. Patients were randomly assigned to receive either the standard Wellbeing Course (n = 75) or the newly developed Sleep-Enhanced program (n = 142). The Standard Wellbeing program included basic sleep hygiene advice. The Sleep-Enhanced program included psychoeducation about insomnia and a brief introduction to sleep restriction and stimulus control, which are two key behavioural components of cognitive behavioural therapy for insomnia. Patients assigned to the Sleep-Enhanced program reported larger reductions in insomnia than patients in the Standard Wellbeing control condition (Cohen’s d = 0.67; p = 0.001). There were no statistically significant differences between the Standard Wellbeing Course and the Sleep-Enhanced program in terms of course completion rate (χ 2(1) = 0.653; p = 0.419) or mean reduction in symptoms of generalized anxiety (F(1, 135) = 1.10; p = 0.296) or major depression (F(1, 139) = 3.62; p = 0.059) symptoms. Patients who received the sleep-enhanced program who more frequently adhered to sleep restriction guidelines reported greater reductions in insomnia symptoms during the program (p = 0.031). Patient-reported adherence to stimulus control instructions was not associated with symptom change (p = 0.836). Patients reported several factors impacted their sleep during the program, the most commonly reported being anxiety (n = 98/128; 77%), care responsibilities (n = 75/128; 59%), and interruptions such as being woken by noises/external factors (n = 71/128; 55%). The trial results demonstrate that including a brief intervention targeting insomnia can be beneficial for many patients seeking treatment primarily for symptoms related to anxiety and depression, while maintaining the effectiveness of the program for reducing symptoms of anxiety and depression.
  • ItemOpen Access
    Optimizing Internet-Delivered Cognitive Behavioural Therapy for public safety personnel: Qualitative insights from clients and stakeholders to guide program improvements
    (Faculty of Graduate Studies and Research, University of Regina, 2023-06) Beahm, Janine Danielle; Hadjistavropoulos, Heather; Carlton, R. Nicholas; Gallant, Natasha; Jones, Nick; Lai, Shalini
    Public Safety Personnel (PSP) (e.g., EMS/paramedics, police officers) experience high rates of clinically significant symptoms of mental health disorders. The high rates have been explained by the extraordinary occupational stressors that PSP experience. There is a need for accessible treatment options to overcome common barriers to care in PSP populations. Internet-delivered cognitive behavioural therapy (ICBT) has the potential to provide effective treatment while overcoming barriers to care. PSPNET is a clinical research unit that has adapted an ICBT program to meet the needs of PSP. The current dissertation is designed to explore the extent to which PSPNET has been optimized and can be further enhanced to meet the needs of PSP. The dissertation consists of three studies assessing stakeholder perceptions of PSPNET from both the client-level and the organizational level (i.e., PSP leaders). The studies are guided by a micro-learning health system framework that emphasizes integrating research and clinical practice to make continuous improvements to interventions. Qualitative data are used because of the substantial potential to develop specific recommendations for iterative improvements to PSPNET. The studies were conducted sequentially. In Study 1, Beahm et al. (2021) examined client communication data (i.e., client emails and feedback surveys) from 82 clients enrolled in the PSP Wellbeing Course, a core transdiagnostic ICBT course offered by PSPNET. The study shows that most clients reported benefits from the program. Results also evidenced that clients identified more aspects of the program as helpful, than they identified areas for improvement. The study results were used to make several of the proposed changes to the course (e.g., inclusion of audio and video content, inclusion of new additional resources). In study 2, Beahm et al. (2022) examined client communication data (i.e., client emails, feedback surveys, and intake screening notes) from 126 Saskatchewan-based clients to explore if PSP were seeking and using ICBT to manage occupational stressors. Results evidenced that almost all (96.8%) clients reported seeking ICBT for one or more occupational stressors. Clients noted that skills from the course helped them manage stress related to a variety of occupational stressors. The data were used to make changes to PSP specific examples and case stories in the course, as well as for identifying new additional resources that were needed for the course (e.g., health anxiety, information for families, mental health supports in the workplace). In Study 3, semi-structured interviews were conducted with 10 PSP leaders based in Saskatchewan. The study explored PSP leaders’ perceptions of PSPNET using the RE-AIM evaluation framework and assessed perceptions of the strengths and weaknesses of PSPNET along five dimensions (i.e., reach, effectiveness, adoption, implementation, maintenance). The results showed PSPNET was reaching PSP, that PSP leaders believed PSPNET was beneficial, and that they were willing to continue to support PSPNET. Leaders also offered feedback for improving reach and implementation of PSPNET (e.g., emphasizing the preventative aspects of PSPNET), some of which are under consideration by the PSPNET team. Other feedback had already been implemented by the team which signalled a need for improved communication with PSP leaders related to implementation of PSPNET (e.g., adding audio content). The collective results from the studies evidenced the value of using qualitative feedback from multiple stakeholders for program improvement. The studies evidenced that PSP value ICBT and highlighted factors that strengthen ICBT for PSP.
  • ItemOpen Access
    Integration of electric vehicles into power systems
    (Faculty of Graduate Studies and Research, University of Regina, 2023-05) Ahmed, Mohamed Ahmed Elhendawi; Wang, Zhanle; Bais; Laforge, Paul; Deng, Dianliang; Liang, Xiaodong
    The power system is continuously evolving and facing various challenges, such as increasing demand, and large-scale electric vehicle (EV) penetration. These challenges have a negative impact on the reliability and sustainability of the power system. For instance, EV charging represents an intensive electric load. Their penetration into the power system poses significant challenges to the operation and control of the power distribution system. Therefore, grid operators need to prepare for high-level EV penetration into the power system. On the other hand, EVs can be used as mobile energy storage systems for frequency regulation, which refers to vehicle-to-grid (V2G) applications. Since power generation must be controlled to continuously meet demand, and any imbalance between supply and demand will cause voltage and frequency deviation, short-term load forecasting becomes increasingly important. In this study, we developed a full wavelet neural network approach for short-term load forecasting, which is an ensemble method of full wavelet packet transform and neural networks. The proposed approach decreases MAPE by 20% compared to the traditional neural network methods. To tackle the frequency deviation issue, this study proposes centralized and distributed optimization models for V2G applications to provide frequency regulation to power systems. The centralized model has limitations which are addressed by developing a distributed model. The distributed model is solved iteratively with the alternating direction method of multipliers (ADMM). Simulation results show that the proposed models can aggregate EVs for frequency regulation; meanwhile, the EV owners can obtain monetary rewards. A data-driven and parameterized EV charging model is proposed to evaluate the impact of EV penetration on urban residential power distribution. Characteristics of EV charging are analyzed using actual profiles in Saskatchewan, Canada and a location-based algorithm identifies residential EV charging data. Model parameters are modeled by using statistical methods and aggregated using the Monte Carlo method. The results show that the proposed models are valid, accurate, and robust. The impact of EV penetration on power distribution systems is evaluated by integrating EV charging profiles and base demand into a load flow model based on transformer loading and voltage drop at customers' houses. Simulation results show that the 15-house distribution system can incorporate up to 22 EVs during on-peak demand days, while the 22-house system cannot handle more than 11 EVs. The observed trend can be attributed to the rise in on-peak demand as the number of houses in the distribution system increases, thereby necessitating a reduction in the critical number of EVs. The study proposes an optimal EV charging model that is considered as an elastic demand under the concept of demand response. The model schedules and controls EV charging to minimize peak demand and shift load off from the peak demand period. Results demonstrate the effectiveness of the model in reducing peak demand and deferring infrastructure investment.
  • ItemOpen Access
    Impact of race on police officer's use of force decision-making
    (Faculty of Graduate Studies and Research, University of Regina, 2023-06) Ahlgrim, Billea Jo Marie; Arbuthnott, Katherine; Kratzig, Gregory; Oriet, Chris; Pennycook, Gordon; James, Lois
    The current study investigated the potential impact of a subject of complaint’s (SOC’s) race on officer decision-making, in addition to the potential impact of several other factors (i.e., dispatch priming, policing experience, fatigue, and chronic stress). This is a serious gap in research of officer decision-making within a Canadian context, with little existing investigation. The study sample was comprised of 298 Royal Canadian Mounted Police (RCMP) employees; 149 recruits from Depot Division, and 149 active duty officers from Divisions across Canada. An intimate partner violence (IPV) vignette was presented in an online format in five stages (i.e., dispatch, arrival, three escalating scenes with the SOC: sitting, standing, and with a knife). At each point of the vignette participants responded to a risk assessment questionnaire that asked them to rate their perceptions of the scenario and what intervention option they would choose at that assessment point. The factorial study design was a 2 (Experience: recruits vs member) x 2 (Race of SOC: White or Indigenous) x 2 (Dispatch Priming: + prior knowledge of SOC race) x 5 (Vignette Risk Assessment Points) with all but the last factor tested betweenparticipants. The race of the SOC was observed to impact risk assessment rating only at the most ambiguous assessment point. Specifically, when SOC behaviour was ambiguous, risk assessment ratings increased more for Indigenous SOCs than for White SOCs. This result could indicate that there was an increased reliance on racial biases and stereotypes when rating perceived level of risk during an ambiguous situation. However, despite this increased perception of risk, race did not influence intervention option choice, even in the most ambiguous situation. This suggests that either biases did not impact behaviour choices, or individuals were able to manage initial biases before choosing an intervention option. Dispatch priming of SOC race was also found to impact situational awareness ratings when the vignette was most ambiguous, indicating that the information that is provided by dispatch has the potential to impact officer decision-making, especially if the scene is ambiguous. The current study indicates the possible but limited impact of race on officers’ perceptions of risk but not on their behaviour regarding intervention options. Experience was found to impact risk assessment ratings such that active duty officers were likely to have more stable and realistic risk assessments throughout the vignette. Officers were also likely to indicate they would use less force in their intervention option choices. This highlights the importance of real work experience in developing an individual’s decision-making skills.
  • ItemOpen Access
    A theory of spatial granular computing
    (Faculty of Graduate Studies and Research, University of Regina, 2023-04) Zhao, Liquan; Yao, Yiyu; Hepting, Daryl; Yao, JingTao; Jia, Na; Kinsner, Witold
    This thesis proposes a theory of spatial granular computing. A granule is composed of one or more atomic granules, and the rationality of this definition is expounded from four aspects: simplicity, applicability, measurability, and visualization. A projection is introduced, which is a one-to-one mapping from granules to points in an nD unit hypercube. Based on this, some basic questions of spatial granular computing are discussed. When discussing the rough set models from the perspective of micro knowledge space, all the models can be easily applied to incomplete information systems and continuous information systems as well. For any equivalence granule in the macro knowledge space, its spatial rough granule model is introduced and the induced three regions are obtained from each of the three planes. Expansions of the spatial rough granule model are examined in three aspects of binary relation, domain and approximation space. Not only are (fuzzy) tolerance relation, (fuzzy) equivalence relation, and coarse-fine relation but also all operations and models defined by relation matrices, and the properties can be easily proved. By focusing on relation matrices and coarse-fine relation, the reduction of knowledge is strictly related to the general concept of independence, so we can use the bases of micro and macro knowledge spaces for granular analysis, which can successfully solve the bottleneck of computing reducts. The measures are divided into granularity and fineness. All measure functions that satisfy nonnegativity, monotonicity and norm invarant can be generalized to measure granules. Subsethood holds twelve axioms, and it can be generalized and extended to conditional granularity (entropies) and conditional fineness (entropies) which are used to measure the coarse-fine relation between two granules and satisfy twelve corresponding axioms. Different definitions of similarity and difference may have different axioms which can be divided into three aspects: symmetry, boundary conditions and monotonicity. Nonnegativity can be replaced by boundary conditions, and any one of the kinds of triangle inequalities can be used as monotonic condition. Structural problems have always been a major challenge in computational science. This thesis explores the multidimensional structures from the perspective of granular computing. Any nD object can be viewed from different dimensions, and it corresponds to an adjacency relation matrix in each view. By discussing the relation between geometry and topology, granular topology algorithm is proposed and it is the general process of granular analysis that all algorithms should follow. By projecting a hypergraph to a hyperedge project graph, all adjacency relations between vertices of the hypergraph are naturally revealed by the meet of the relation vectors corresponding the vertices of the project graph. In this way, it can not only largely reduce the dimension of tensor but also be used to represent any (directed) hypergraph. Two kinds of graph/digraph information systems are defined, each graph/digraph information system can produce one micro and one macro knowledge spaces in which micro and macro rough graph/digraph models are built on its vertices and its edges respectively. This thesis introduces how to obtain the vertex and edge adjacency relation matrices of a quotient graph/digraph, performs structural analysis for fuzzy granules based on their corresponding fuzzy relation matrices respectively as well as for fuzzy graphs/digraphs based on their corresponding vertex and edge adjacency relation matrices respectively, and generalize all measure methods and operations for (equivalence) granules to (equivalence) graphs/digraphs.
  • ItemOpen Access
    Ensemble-based framework and its applications to characterizing growth and propagation dynamics of wormhole networks and steam chambers in a heavy oil reservoir
    (Faculty of Graduate Studies and Research, University of Regina, 2023-01) Yang, Shikai; Yang, Daoyong; Torabi, Farshid; Jin, Yee-chung; Qing, Hairuo; Yang, Chaodong
    As for the enormous heavy oil resources all over the world, cold heavy oil production with sand (CHOPS) technique has been successfully utilized to exploit them as the primary recovery due to the induced high-permeability channels (i.e., wormholes) together with foamy oil flow, while the steam-assisted gravity drainage (SAGD) process has been widely used as an efficient enhanced oil recovery (EOR) method because of the steam chamber propagation together with viscosity reduction and gravity drainage. Numerous efforts have been made to characterize the growth and propagation dynamics of wormhole networks and steam chambers; however, it is still a challenging task to reproduce the experimental measurements and field observations due to the physical constraints and strong nonlinearity. Therefore, it is of fundamental and practical significance to develop robust and versatile techniques for characterizing the growth and propagation dynamics of wormhole networks in a CHOPS process and a steam chamber in a SAGD process, respectively. A modified pressure-gradient-based (PGB) sand failure criterion has been developed for quantifying the dynamical and preferential wormhole propagation during a CHOPS process. By upscaling it from pore-scale to grid-scale, such a sand failure criterion is successfully validated with a laboratory experiment and then extended to a field case. Subsequently, a damped iterative-ensemble-Kalman-filter (IEnKF) technique has been developed for dynamically and implicitly determining the model uncertainties during a CHOPS simulation, while an improved upscaling process has been proposed to improve the versatility and accuracy of the PGB sand failure criterion. Not only does such an ensemble-based data assimilating algorithm demonstrate a satisfactory convergence, but also the simulated wormhole network shows its great similarity to the experimental observation. Moreover, the impacts of foamy oil flow, sand failure, and slurry flow are comprehensively evaluated by employing various sets of multiphase relative permeability for the simulation. By integrating the modified PGB sand failure criterion, foamy oil model, multiphase relative permeability model, and damped-IEnKF algorithm into a reservoir simulator (i.e., CMG STARS), a unified, efficient, and consistent ensemble-based framework has been established to characterize the field-scale wormhole growth and propagation dynamics with good accuracy and efficiency, demonstrating its practicality and robustness in simulating the CHOPS processes in heavy oil reservoirs. A heat-penetration criterion has then been newly developed and integrated into a reservoir simulator (i.e., CMG STARS) for characterizing the steam chamber growth and propagation dynamics during a SAGD process, while thermally sensitive co/countercurrent relative permeabilities are incorporated in the simulation. Temperature distribution ahead of a steam chamber interface (SCI) is dynamically calibrated by such a heatpenetration criterion, providing a simple and convenient way to pragmatically, dynamically, and accurately quantify heat transfer during a SAGD simulation.
  • ItemOpen Access
    Improvement of weakly compressible moving particle semi-implicit method and its application
    (Faculty of Graduate Studies and Research, University of Regina, 2023-01) Xiao, Huiwen; Jin, Yee-chung; Wu, Peng; Zhao, Gang; Yao, Yiyu; Li, Samuel
    Moving Particle semi-implicit method (MPS) is one of the well-known Lagrange particle methods that is advantageous in addressing complex hydraulic engineering problems. Although the accuracy and reliability can be addressed in particle methods, instability arises due to pressure fluctuations from particle clustering and improvements are beneficial for method development. Particle distribution is an area that requires improvement. In this study, a particle smoothing algorithm was developed and incorporated to the weakly compressible MPS, namely sWCMPS. From the definition and derivation of basic MPS operators, uniform particle distribution is critically important to numerical accuracy. Within the framework of sWCMPS, numerical operators were modified by implementing coordinate transfer and smoothing algorithm. Modification of the numerical operators showed significant improvements resulting in the reduction of particle clustering, smoother pressure distributions and pressure oscillations. To validate the numerical feasibility, several numerical cases were simulated to compare sWCMPS to the weakly compressible MPS (WCMPS), including a pre-defined two-dimensional (2-D) analytical function, Poiseuille’s flow, Taylor Green vortex and a dam break. Simulation results showed a reduction of the error caused by irregular particle distribution with lower particle clustering and smaller pressure oscillation. In addition, the newly developed sWCMPS algorithm can achieve numerical accuracy even by applying a larger courant number, indicating a better computational efficiency. To improve computational efficiency with a simple algorithm, explicit algorithms have been proposed such as the WCMPS method. Although accuracy can be fulfilled in WCMPS, instability arises due to pressure fluctuations of the moving particles. In this study, an explicit Poisson Pressure Equation (PPE) was introduced to address particle instability by improving the pressure calculation, referred to as the Weakly Compressible Moving Particle Explicit (WCMPE) method. By predicting pressure through the equation of state for WCMPS, divergence-free condition is conserved without the implementation of small time-steps. Several numerical cases were investigated by the WCMPE method, including 2D jet impinging on a solid plate, oscillating drop, lid driven cavity, rolling tank experiment, sloshing tank simulation and jet impinging from the bottom of a tank. In general, simulation results showed smooth pressure distribution and improved particle stability were obtained with the incorporation of WCMPE. WCMPE method improved the pressure calculation and stability of WCMPS while preserving its coding system with high computational efficiency. The WCMPE method is then extended to multiphase flow simulation. In this study, the multiphase WCMPE method was developed with a simple density smooth technique and interface detection procedure. Several numerical cases were investigated by the multiphase WCMPE method, including Rayleigh-Taylor (R-T) instability cases with various density and viscosity ratio conditions, oil spill and oil-water sloshing experiments. Numerical simulation results showed good agreements with analytical solutions. Experimental data obtained in multiphase WCMPE results also exhibited negligible unphysical pressure oscillation and pressure noise points.
  • ItemOpen Access
    Experimental and numerical investigations on wind characteristics and wind induced vibrations of bridge structures
    (Faculty of Graduate Studies and Research, University of Regina, 2022-12) Xia, Dandan; Dai, Liming; Henni, Amr; Mehrandezh, Menrand; Morgan; Mobed, Nader; Li, Xianguo
    As more and more flexible structures such as long span bridges and suspension bridges are built in the world, their increased flexibility can cause serious concerns for researchers and engineers. For such structures, wind load has become one of the most important dominant loads under consideration in the analysis and design of structures. Thus, accurate and reliable evaluations of the wind characteristics are critical, as the evaluations may provide a solid foundation for which the design of wind-resistant structures can be relied upon. Therefore, according to the importance and sensitivity of this subject in some special applications, the current research has been presented both analytically and experimentally, which may be utilized as guidance for researchers and engineers around the world in this field. The wind field measurement system used for this research acquires the high frequency wind speed data for the process of tropical cyclone and monsoon wind. Wind characteristics are studied systematically with wind data collected. Furthermore, the comparative study of stationary and non-stationary models, which is established with a self-adaptive procedure, is conducted. The established non-stationary model presents advantages for measuring the time related wind speed variations. Analytical results obtained in the research expose the difference between the traditional stationary and non-stationary models cannot be ignored, especially over a large time horizon. Moreover, in order to predict the wind speed with higher accuracy, a more accurate prediction method based on wavelet decomposition and chaotic diagnosis is also proposed. The wind speed prediction method considers the frequency domain characteristics of wind speed series for improving prediction accuracy. Wind speed data collected from the long term experiments and downloaded historical data are applied to verify the accuracy and reliability of the proposed prediction method. Wind induced vibration is another aspect which will affect the safety of the structures. As a typical and commonly seen type of wind induced vibration, vortex induced vibration (VIV) of bridges and the aerodynamic influences of the bridge attachments on the VIV are studied experimentally with a wind tunnel test. The effect of the attachments installed on the bridge deck such as crash barriers, wind barriers and traffic flows on VIV behaviors including lock-in wind speeds and vibration characteristics are systematically investigated. A new method by combing the unscented Kalman Filter with unknown input and simplification of Tylor series expression for studying the loads generated by vortex and VIV is proposed in the research. The governing equation developed is simplified by Taylor expression which can be applied for general bridge decks, unscented Kalman Filter with unknown input (UKF-UI) method is utilized to identify the self-excited and aerodynamic forces in VIV lock in regions. Instead of using fitted mathematical model, such a method can be directly applied on wind tunnel test data of general bridge deck types. The research findings are valuable for better analyzing and comprehending wind characteristics as well as interactions between wind and structures, and are expected to provide a practically sound guidance for designing wind-resistant structures especially flexible structures subject to wind exertion.
  • ItemOpen Access
    Development of high-resolution climate projections over Canada in the 21st century
    (Faculty of Graduate Studies and Research, University of Regina, 2023-03) Wu, Yinghui; Huang, Gordon; Young, Stephanie; Zhu, Hua; Deng, Dianliang; Nasiri, Fuzhan
    In this research, high-resolution climate projections over Canada have been developed through the WRF model. The spatial and temporal variations of Canada’s temperature, precipitation, and precipitation extremes in the 21st century have been comprehensively analyzed. Potential mechanisms in terms of temperature, precipitation, and precipitation extremes over Canada have been investigated, and effects of anthropogenic warming on these variables have been revealed. In addition, permafrost degradation under climate change is extended to a global scale, and a dynamic longterm classification scheme for discontinuous permafrost is proposed. The annual mean temperature over Canada is projected to increase by [1.53, 1.98], [2.51, 3.86], and [2.94, 6.19]°C in the 2030s, the 2050s, and the 2080s under RCP4.5 and RCP8.5 respectively, with largest increase in winter. The annual total precipitation is projected to increase by [16.33, 68.96], [64.80, 121.62], and [123.62, 184.33] mm in three future periods. It is found that the westerlies have significant impacts on Canada’s precipitation variations, and extreme precipitation frequency are related to ENSO phases. A dynamic SOM-based permafrost classification scheme (DSOMPCS) is developed to provide robust, objective, and detailed classifications for discontinuous permafrost. Linear relationship is found between global temperature increase and permafrost loss. When global temperature increases by 1°C, there will be a 2.5 million km2 of permafrost loss. This research will help provide insights into effects of anthropogenic warming on multiple aspects of climatology. The results can provide valuable information for mitigation and adaptation of climatic changes in a Canadian and global context.
  • ItemOpen Access
    Walking and thinking: Critical reflections on “Walking the Bypass: A Meditation on Place”
    (Faculty of Graduate Studies and Research, University of Regina, 2022-09) Wilson, Kenneth Clayton; Farrell-Racette, Sherry; Dashchuk, James; Bracht, Kathryn; Irwin, Kathleen; Archibald-Barber, Jesse; Donald, Dwayne
    ôma kihci-kiskinwahamasinahikan âpacihtâmakan êsa kwayask itahkamikisiwina taitwêstamâkêmakahk ôma pimohtêwin-êkwa-masinahikêwin kiskinwahamawi-osîhcikâsowin kihci-kiskinwahamasinahikan “ê-pimohtêhk âsokanihk: ê-mâmitonêyihcikêhk ôma itâpatakêyimisowin,” ê-itwêmakahk kwayask âcimowin ôma pêyakwan wîhowin ohci. Nîkân masinahikanêkinohk atamiskawikow ôma atoskêwin, tânisi ê-pimakotêk, êkwa mîna kakwêcihkêmowina: “pimohtêwin cî ka-kî-mêskwacipayin pakwâcaskiy isi ôma kihci-askiy?” êkwa, misawâc ê-kihcêyihtakwâhk, “môniyâwak cî ka-kî-nisitohtamwak ôma ôta askîhk ê isipimohtêcik?”. nîso masinahikanêkinohk pîkiskwêmakan tânisi kâ-pimohtêhk naspasinahikân ôma ê-isi-âniskôstêk isi ôma atoskêwinihk; nôkohcikêmakan nanâtohk âcimowina kâmiyonâkwahk êkwa kâ-isîhcikêhk isi-pimohtêwin êsa ê-kikinikâtêk ôma atoskêwin. Nisto masinahikanêkinohk pîkiskwêmakan tânisi kâ-itahkamikisihk kwayask, tâpiskôc kwayask itahkamikisiwina êwako askiy êkwa kâ-nisitohtamâhk; iyiniwi-kiskêyihtamowin ôma ê-miyoitôtâmiyit askiy êkwa atâhko-kiskinwahamâtowin; êkwa tânisi kâ-nisitohtâsoyahk êsa askiy ohci, ê-mêskwacipayihk itahkamikisiwina, êkwa tânisi kâ-itâpisihkik iyiniwak êwako anima kiskêyihtamowina. nêwo masinahikanêkinohk pîkiskwêmakan kâ-âpacihtâhk êsa atoskêwinihk: masinahikêwina ê-masinahikêhk Willam Least Heat-Moon, Nick Papadimitriou, êkwa Iain Sinclair ohci; tânisi kâ-wîkiyâhk ê-ispayihikoyâhk; pêyako-pimohtêwin; kwayask âcimowina êmiywâsik; êkwa masinâpiskahikêwin. piyisk, iskwêyânihk pîkiskwêmakan tânisi kâ-isiitôtamâhk ê-atoskêyâhk ôma kihci-kiskinwahamasinahikanihk—êkwa nika-kî-itôtênân, kîspin êsa kihci-âhkosiwin êkâ ê-kî-âyimahk ta-atoskêmitoyâhk ôma nîso askîwin aspin ohci. kiskêyihtâkwan kahkiyaw ê-nêstosiyâhk êwako kihci-âhkosiwin, kistêyihtâkwan ta- nisitohtamâhk ôma misawâc ê-miywâsik êtikwê êwako atoskêwinihk, kâ-kî-mêskwacipayihk ayisk kihci-âhkosiwin COVID-19 ê-astêk ôma ôta. This thesis presents a critical, theoretical, and methodological exegesis of the walking-and-writing research-creation doctoral project “Walking the Bypass: A Meditation on Place,” as represented by the creative-nonfiction manuscript of the same title. The first chapter introduces the project, its aims and scope, and its research questions: “can walking turn non-places into places?” and, more importantly, “can settlers come into a relationship with the land through walking?” The second chapter discusses the context of walking art as it applies to this project; it presents accounts of a range of aesthetic and political walking practices that influenced this project. The third chapter presents the project’s theoretical context, including theories of place and space; Indigenous theories of land and cosmology; and object-oriented ontology, affect theory, and Indigenous critiques of those ways of thinking. The fourth chapter explores the project’s methodological touchstones: writing by William Least Heat-Moon, Nick Papadimitriou, and Iain Sinclair; psychogeography; solo walking practices; creative nonfiction; and photography. Finally, the conclusion suggests future directions which this research could take—and would have taken, had the pandemic not made working with others so difficult during the past two years. As much as everyone is tired of the pandemic, it’s important to acknowledge that it may have been the greatest influence on this project, which changed significantly in response to the challenges presented by Covid-19.
  • ItemOpen Access
    Determination of evaporative flux from water and soil surfaces
    (Faculty of Graduate Studies and Research, University of Regina, 2023-02) Suchan, Jared Joseph; Azam, Shahid; Xue, Jinkai; Azadbakht, Saman; Chi, Guoxiang; Gurrapu, Sunil
    The Canadian Prairies has the highest water demand-to-availability ratio in Canada. The region is characterized by a scarcity of water resources because evaporation generally exceed precipitation. Evaporation is a complex phenomenon based on interactions between meteorological and physiological factors. The purpose of this research was to accurately determine evaporative flux from water and soil surfaces. The main research contributions of this research are summarized as follows: (i) a Bench-scale Atmospheric Simulator (BAS/BAS2) was developed to control artificially generated parameters for short time periods; (ii) a Controlled Photogrammetry System (CPS) using Structure-from-Motion (SfM) technology was developed for accurate and non-destructive measurement of dimensional changes during evaporation; (iii) high-quality evaporation datasets were developed for calibration of devices, validation of prediction equations and evaluation of theoretical frameworks; (iv) predictive models for evaporation from water were evaluated to select appropriate empirical equations for predicting potential evaporative flux from water; and (v) a theoretical framework for evaporation from soils was developed to correlate with soil behavior (water retention and soil shrinkage) for both fresh water and saline water. The findings of this research are useful for developing methods to minimize evaporation and for helping with devising water use policy.
  • ItemOpen Access
    MPS modeling of cross-sectional averaged shallow-water equations: Development and application
    (Faculty of Graduate Studies and Research, University of Regina, 2022-12) Sarkhosh, Payam; Jin, Yee-chung; Xue, Jinkai; Yang, Daoyong; Fan, Lisa; Zhang, Wenming
    In the last two decades, mesh-free or particle methods have been widely applied to solve shallow water equations. This research presents a moving particle simulation (MPS) scheme to spatially integrate the cross-sectional average shallow water equations, called 1D MPS-SWE solver. First, a first-order accurate numerical scheme in space and time is developed, applicable to prismatic open channels with closed boundaries. A density-ratio formula is derived for computing the cross-sectional area using the Newton-Raphson iteration and based on the particle number density concept. The newly derived formula does not miscompute the cross-sectional area if an incorrect searching radius parameter is selected, unlike the typical volume-summation equation in mesh-free shallow water flows. Dynamic Stabilization is utilized to capture shockwave problems, a case-independent procedure based on the inelastic collision with unequal masses. The solver is then improved to a second-order accuracy in space and time applicable for non-prismatic open channels with open boundaries. For this purpose, the well-known MacCormack predictor-corrector scheme in the mesh-based schemes is extended to the Lagrangian framework. Furthermore, upwind and downwind MPS gradient operators are introduced. Second-order schemes usually suffer from unphysical oscillations. To solve this numerical issue, the total variation diminishing (TVD) flux-limiter scheme is developed for the MPS formulation to preserve monotonicity, which does not require characteristic speeds of the system. In mesh-based methods, the non-conservative form of the momentum equation is problematic in scenarios with discontinuities, particularly in higher-order schemes. However, the non-conservative convective flux term does not exist under the Lagrangian framework in preserving momentum conservation. Since the algebraic density-ratio formula computes the cross-sectional area in the present work, the open boundary treatment requires less computational effort than mesh-based methods because the partial differential continuity equation is omitted as a boundary value problem. The 1D MPS-SWE solver satisfies positivity-preserving and well-balancing properties without the need for any threshold value for treating the dry bed and friction term. Additionally, it can model free-surface flows in prismatic and non-prismatic open channels with various open and/or closed boundary conditions. Later, a Picard iteration-based framework to solve the density-ratio formula is presented. Compared to the conventional Newton-Raphson iteration, the new strategy is advantageous as the iterative convergence is strongly accomplished with accuracy up to double-machine precision. Notably, the results of the MPS-SWE solver are inconsistent with the experimental data at the early dam-break stages subject to the non-hydrostatic pressure effect. To enhance the accuracy of the solver to mimic frictional dam-break flows, a hybrid solver of 1D MPS-SWE and a 2D MPS large-eddy simulation accompanied by a sub-particle scale is introduced. The configuration of sub-domains is established so that the 1D solves the regions with dominantly hydrostatic pressure, while the 2D solver is accounted for the non-hydrostaticity. A moving coupling system is proposed based on two-layer shallow water equations with identical densities that construct two sub-domains. Then, the region with highly vertical acceleration is substituted by the 2D model. Also, two different section and layer coupling systems are developed in which the overlapping zone and boundary interface move with time. As regards the second, a new method is presented to deal with irregular boundary interface while satisfying the momentum transfer. The model validation and application show that the present hybrid solver performs well and considerably decreases the computational time from 2D models.