Wolf Creek Cold Regions Model Set-up, Parameterisation and Modelling Summary

Non-Peer ReviewedWolf Creek Research Basin is in the Upper Yukon River Basin near Whitehorse, Yukon and is representative of headwaters in the northern Coast Mountains. It was established in 1993 to better develop northern hydrological models, and related hydrological process, ecosystem and climate science. Yukon Environment maintains Wolf Creek hydrometeorological and hydrometric stations and conducts regular snow surveys in the basin. A number of hydrological models have been tested on Wolf Creek and all have had great difficulty in simulating the cold regions hydrological processes that dominate its streamflow response to snowmelt and rainfall events. Developments in understanding hydrological processes and their interaction with terrestrial ecosystems and climate at Wolf Creek have lead to the development of the Cold Regions Hydrological Model (CRHM) by a consortium of scientists led by the University of Saskatchewan and Environment Canada. CRHM comprehensively incorporates the blowing snow, intercepted snow, sublimation, melt energetics, infiltration to frozen soils, organic terrain runoff and other cold regions hydrological phenomenon and discretizes the catchment on a hydrological response unit basis for applying water and energy balance calculations. The model is intended for prediction of ungauged basins with parameter selection from physically measurable properties of the river basin or regional transference of calibrated values. In Russia, a long tradition of cold regions hydrological research has led to the development of the Hydrograph model by the State Hydrological Institute, St. Petersburg. The Hydrograph model contains several promising innovations regarding the formation and routing of runoff, discretizes the basin using hydrological response units and addresses some (but not all) cold regions hydrological processes. Hydrograph parameter selection is made from both physically measured properties and those that are calibrated, but the calibrations can be easily regionalized. Test simulations of runoff processes using CRHM and Hydrograph for Wolf Creek Research Basin was undertaken using data archives that had been assembled and cleaned up in a related project by the University of Saskatchewan. The test simulations are a demonstration of model capabilities and a way to gain familiarity with the basin, its characteristics and data and to better compare model features. Data available included a GIS database of basin characteristics (topography and vegetation distribution) and the hydrometeorological and hydrometric observational dataset from Yukon Environment. The sub-surface hydrology presented a formidable unknown in parameterising the model. Hydrograph performed well in initial simulations of the basin hydrograph for multi-year runs. Several issues with observational data quality created substantial uncertainty in evaluating the model runs

Numerical modeling of soil flow and pressure distribution on a simple tillage tool using computational fluid dynamics

Soils, in general, undergo both elastic and plastic deformations upon loading. Strain dependant anisotropic elasto-plastic models are required for realistic modeling for soil-tool mechanics that will address issues like stress history and soil anisotropy. Although several such models have been proposed, the science of coupled poro-mechanical analysis of an unsaturated soil has not been fully addressed.Tillage tool modeling is primarily concerned with the analysis of soil deformation patterns and development of force prediction models for design optimization. Most of the models are based on quasi-static soil failure patterns that cause difficulty in accurately predicting soil-tool behaviour and soil forces for high speed operation. In recent years efforts have been made to improve the conventional analytical and experimental models by numerical approaches. Numerical simulations of soil-tool interactions using finite element modeling (FEM) and discrete element method (DEM) were mostly based on a solid mechanics approach. Due to limitations of constitutive relations, predictions of these numerical models have not been able to address tillage dynamics with high shear rates. The contribution of this research was to study the dynamics of soil-tool interaction using computational fluid dynamics (CFD) from the perspective of soil visco-plastic behavior.A motorised soil rheometer was developed for evaluating soil visco-plastic parameters for CFD simulations. The apparatus was used to determine soil yield stress and viscosity at different soil moisture and compaction levels.Three-dimensional CFD analyses were carried out using a commercial software CFX 4.4 to observe soil failure patterns around a tool and the pressure distribution on and around the tool. Duct flow as well as free-surface flow simulations of visco-plastic soil as a non-Newtonian Bingham material indicated soil deformation comprising of ‘plastic flow’ and ‘plug flow’ patterns. The soil failure front advancement demonstrated a critical speed range of 4 to 6.5 m s-1 where advancement of the failure front did not increase with speed. Soil pressure on the tool surface increased with the tool operating speed. Pressure distribution on the tool surface and draft requirement agreed well with the published literature based on experimental results and FEM analysis. The CFD approach, in its first attempt to tillage process, demonstrated its greater potential for dynamic modeling of soil-tool interaction

THERMAL ENVIRONMENT MODELING AND OPTIMIZATION OF GREENHOUSE IN COLD REGIONS

Thermal simulation models for the time-dependent heating requirement of greenhouses are very important for the evaluation of various energy-saving technologies, and energy-efficient design of greenhouses based on local climates. A quasi-steady state thermal model “GREENHEAT” was developed using the programing language MATLAB for simulation heating requirement in conventional greenhouses. The model could predict the hourly heating requirement based on the input of hourly weather data, indoor environmental parameters, and physical and thermal properties of greenhouse building materials. The model was validated with measured data from a commercial greenhouse located in Saskatoon, Canada, and the monthly average error in prediction was found to be less than 5.0%. This study also reviewed various energy-saving technologies used in greenhouses in cold climate, and the GREENHEAT model allowed selections of commonly used ones in the simulation. The GREENHEAT model was used for evaluating the impact of various geometrical parameters on the heating requirement of the single span and multiple-span conventional greenhouses located in Saskatoon. Results showed that the east-west oriented gable roof greenhouse could be more energy-efficient for the multi-span gutter connected greenhouse whereas quonset shape as a free-standing single span greenhouse. The large span width could be beneficial for the single-span greenhouses, but the impact of increased span width could be negligible on the heating demand of multi-span greenhouses. The model was also used for an economic feasibility analysis of year-round vegetable production (tomato, cucumber, and pepper) in northern Saskatchewan, and tomato was found to be the most economical vegetable as compared to the cucumber and pepper. Another heating simulation model CSGHEAT was developed to estimate of the supplemental heating requirement of mono-slope Chinese-style solar greenhouses (CSGs). This model is also a quasi-steady state thermal model using the programming language MATLAB, and it can simulates the hourly heating requirement of CSGs. The model was validated with experimental data from a CSG located in Winnipeg, Manitoba. The average error for prediction of the hourly heating requirement was found to be less than 8.7%. The model sensitivities to various geometrical and thermal parameters were studied. The results indicated that the thermal properties of cover, thermal blanket, and parameter insulation were the most important design parameters in CSGs. Finally, the heating requirement in CSGs was modeled using TRNSYS simulation tool, and the predictions were compared with that of CSGHEAT. The result indicated that TRNSYS had serious limitations for modeling of greenhouse thermal environment, thereby high uncertainties could occur, thus was not suitable for greenhouse simulation

Water quality modeling of Lake Diefenbaker

Lake Diefenbaker is one of the most important sources of water in the prairie province of Saskatchewan, Canada. It is a long (181.6 km) and narrow (maximum width 6 km) reservoir formed along the South Saskatchewan River by the construction of the Gardiner and Qu'Appelle River dams in the 1960s. The reservoir has a surface elevation of 556.87 meters above sea level (full supply level) with a maximum depth of 60 m, a surface area of approximately 393 km2 and a volume of 9.03 km3. The reservoir and dams are part of a multipurpose hydraulic project, which provides water for irrigation, drinking water, eco-services, hydropower generation, aquaculture and recreation as well as for flood mitigation. Surface water quality modeling is a useful tool to simulate and predict nutrient dynamics in lakes, reservoirs, and rivers, as well as the fate and transport of sediment and toxic contaminants in freshwater environments. In this study, water quality modeling of Lake Diefenbaker was carried out in order to help understand the mixing regimes and biological processes in the aquatic environment of this strategic reservoir. Based on the study's objectives, the physical and chemical characteristics of the lake and available data, the laterally-averaged two-dimensional model CE-QUAL-W2 hydrodynamic and water quality model was deemed the best model for Lake Diefenbaker. CE-QUAL-W2 was developed by the US Army Corp of Engineers to simulate the hydrodynamics, water quality, aquatic biology and aquatic chemistry in surface waters. On the one hand, this study provided information on temperature and hydrodynamic behaviors of Lake Diefenbaker as well as sediment and nutrient transport, nutrient uptake and algal activities. On the other hand, it addressed some key and limitations in the application of water quality models. Limitations addressed include studying snow cover effects on the ice surface in winter, applying variable algal stoichiometry, using combined local/global optimization for model calibration, and running the model on High-Performance Cluster (HPC) systems

REALIZATION OF A CANINE POSITIONING DEVICE FOR IN SITU PROSTATE PHASE CONTRAST – COMPUTED TOMOGRAPHY IMAGING

Background: Worldwide, prostate cancer (PCa) is the most commonly diagnosed non-skin cancer in men. The current diagnostic standard of PCa requires invasive procedures such as needle biopsies. Non-invasive medical imaging techniques, such as Computed Tomography (CT), are only used as an adjunct for staging PCa. The development of a novel non-invasive imaging technique for PCa could revolutionize diagnostic standards and improve patient prognosis. The similarity between canine and human prostates, as well as similar PCa pathophysiology, makes the dog an ideal model for human PCa research. Initial investigations with Phase Contrast – CT (PC-CT) has shown potential for detecting morphological abnormalities in ex vivo canine prostates and therefore warrants further testing as a potential PCa diagnostic imaging technique. This research addresses the design, development and implementation of a canine positioning device used for in situ prostate PC-CT imaging on the Biomedical Imaging and Therapy –Insertion Device Beamline at the Canadian Light Source. This device is currently being used to collect micron-level resolution PC-CT reconstructions of canine cadaver prostates. This thesis lays the ground work for canine imaging on the BMIT – ID beamline at the CLS. The design and implementation of the device are described, along with the issues discovered and addressed

Stochastic vulnerability assessment of masonry structures: Concepts, modeling and restoration aspects

A methodology aiming to predict the vulnerability of masonry structures under seismic action is presented herein. Masonry structures, among which many are cultural heritage assets, present high vulnerability under earthquake. Reliable simulations of their response to seismic stresses are exceedingly difficult because of the complexity of the structural system and the anisotropic and brittle behavior of the masonry materials. Furthermore, the majority of the parameters involved in the problem such as the masonry material mechanical characteristics and earthquake loading characteristics have a stochastic-probabilistic nature. Within this framework, a detailed analytical methodological approach for assessing the seismic vulnerability of masonry historical and monumental structures is presented, taking into account the probabilistic nature of the input parameters by means of analytically determining fragility curves. The emerged methodology is presented in detail through application on theoretical and built cultural heritage real masonry structures

Development of a Large-Dose, High-Resolution Dosimetry Technique for Microbeam Radiation Therapy using Samarium-Doped Glasses and Glass-Ceramics

Microbeam radiation therapy (MRT) is a potential cancer therapy technique that uses an intense X-ray beam produced by a synchrotron. In MRT, an array of microplanar beams, called a microbeam, is delivered to a tumour. The dose at each centre of planar beams is extremely large (several hundred grays) while dose level in the valley between the peaks is below several tens of gray. Moreover, the width of each planar beam is typically 20 - 50 µm, and the distance from a centre of planar-beam to that of adjacent beam is 200 - 400 µm. For the latter reasons, the fundamental requirements for the dosimetry technique in MRT are (1) a micrometer-scale spatial resolution and (2) detection sensitivity at large doses (5 - 1000 Gy). No existing detectors can satisfy those two requirements together. The objective of the Ph.D. research is to develop a prototype dosimetry technique which fulfils the requirements for measuring the dose profile in the microbeam. The currently used approach relies on the indirect detection of X-rays; in which the X-ray dose is recorded on a detector plate, and then the recorded signals are digitized using a reader. Our proposed approach utilizes Sm3+-doped polycrystallites, glasses, and/or suitable glass-ceramics (though our approach is not limited to the use of Sm ion) for the detector plate, in which a valence reduction of Sm3+, that is the conversion of Sm3+ to Sm2+, takes place upon irradiation of X-rays. The extent of reduction is further read out using confocal fluorescence microscopy via the photoluminescence (PL) signals of Sm3+ and Sm2+. The work carried out throughout the course of the research includes the construction of confocal fluorescence microscopy, synthesis and characterizations of dosimeter materials, as well as application tests of our approach for measuring the dose profile of a microbeam used at synchrotron facilities -- Canadian Light Source (CLS), Saskatoon, Canada, European Synchrotron Radiation Facility (ESRF), Grenoble, France, and SPring-8, Hyogo, Japan. Further, the research has shown that 1 % Sm-doped fluoroaluminate glass is one of the best candidates for the type of dosimetric application. It has the dynamic range of ~1 to over 1000 Gy which covers the dose range used in MRT, excellent signal-to-noise ratio (large extent of Sm3+ → Sm2+ change), and excellent stability of recorded signal over time. The recorded signal in the detector is erasable by heating or exposing to light such as UV. Furthermore, with a use of confocal microscope, it has ability to measure the distribution pattern of dose over the cross-section of microbeam. Therefore, we believe that our approach is one of the most promising techniques available

Power System Simulation, Control and Optimization

This Special Issue “Power System Simulation, Control and Optimization” offers valuable insights into the most recent research developments in these topics. The analysis, operation, and control of power systems are increasingly complex tasks that require advanced simulation models to analyze and control the effects of transformations concerning electricity grids today: Massive integration of renewable energies, progressive implementation of electric vehicles, development of intelligent networks, and progressive evolution of the applications of artificial intelligence