FABRICATION, CHARACTERIZATION, AND IRRADIATION OF AN AUSTENITIC OXIDE DISPERSION STRENGTHENED STEEL SUITED FOR NEXT GENERATION NUCLEAR APPLICATIONS

As nuclear energy systems become more advanced, the materials encompassing them need to perform at higher temperatures for longer periods of time. In this Master’s thesis we experiment with an oxide dispersion strengthened (ODS) austenitic steel that has been recently developed. ODS materials have a small concentration of nano oxide particles dispersed in their matrix, and typically have higher strength and better extreme temperature creep resistance characteristics than ordinary steels. However, no ODS materials have ever been installed in a commercial power reactor to date. Being a newer research material, there are many unanswered phenomena that need to be addressed regarding the performance under irradiation. Furthermore, due to the ODS material traditionally needing to follow a powder metallurgy fabrication route, there are many processing parameters that need to be optimized before achieving a nuclear grade material specification. In this Master’s thesis we explore the development of a novel ODS processing technology conducted in Beijing, China, to produce solutionized bulk ODS samples with ~97% theoretical density. This is done using relatively low temperatures and ultra high pressure (UHP) equipment, to compact the mechanically alloyed (MA) steel powder into bulk samples without any thermal phase change influence or oxide precipitation. By having solutionized bulk ODS samples, transmission electron microscopy (TEM) observation of nano oxide precipitation within the steel material can be studied by applying post heat treatments. These types of samples will be very useful to the science and engineering community, to answer questions regarding material powder compacting, oxide synthesis, and performance. Subsequent analysis performed at Queen’s University included X-ray diffraction (XRD) and inductively coupled plasma optical emission spectrometry (ICP-OES). Additional TEM in-situ 1MeV Kr2+ irradiation experiments coupled with energy dispersive X-ray (EDX) techniques, were also performed on large (200nm+) non-stoichiometric oxides embedded within the austenite steel grains, in an attempt to quantify the elemental compositional changes during high temperature (520oC) heavy ion irradiation.

EFFECTS OF BUBBLE-FACILITATED VOC TRANSPORT FROM LNAPL SMEAR ZONES ON VAPOR INTRUSION

Light non-aqueous phase liquid (LNAPL) sources can pose a significant threat to indoor air through vapour intrusion (VI). Most conceptual and numerical models of VI assume that the transport of volatile organic compounds (VOCs) is a diffusion-limited process. Recently, alternate conditions have been identified that could lead to faster transport, including the presence of preferential pathways and methanogenic gas production. In this study, an additional mechanism that could lead to faster transport was investigated: bubble-facilitated VOC transport from LNAPL smear zones. A laboratory investigation was preformed using pentane in one-dimensional laboratory columns and two-dimensional visualization experiments. Results of the column experiments showed that average VOC mass fluxes in the bubble-facilitated columns were over two orders of magnitude greater than in the diffusion-limited columns. In addition, the flux signal was intermittent, consistent with expectations of bubble-facilitated transport as bubbles expand, mobilize and are released to the vadose zone at various times during the test. The results from the visualization experiments showed gas fingers growing and mobilizing over time, which supports the findings of the column experiments. In conclusion, these results demonstrate the potential for bubble-facilitated VOC transport to affect mass transfer in LNAPL smear zones, and lead to increased indoor air concentrations by VI.

Detection and Grading of Prostate Cancer in Temporal Enhanced Ultrasound using Convolutional Neural Networks

Prostate cancer is the most common non-dermatological cancer amongst men in the developed world. The current definitive diagnosis is core needle biopsy guided by transrectal ultrasound. However, this method suffers from low sensitivity and specificity in detecting cancer. Recently, a new ultrasound based tissue typing approach has been proposed, known as temporal enhanced ultrasound (TeUS). In this approach, a set of temporal ultrasound frames is collected from a stationary tissue location without any intentional mechanical excitation. The main aim of this thesis is to implement a deep learning-based solution for prostate cancer detection and grading using TeUS data. In the proposed solution, convolutional neural networks are trained to extract high-level features from time domain TeUS data in temporally and spatially adjacent frames in nine in vivo prostatectomy cases. This approach avoids information loss due to feature extraction and also improves cancer detection rate. The output likelihoods of two TeUS arrangements are then combined to form our novel decision support system. This deep learning-based approach results in the area under the receiver operating characteristic curve (AUC) of 0.80 and 0.73 for prostate cancer detection and grading, respectively, in leave-one-patient-out cross-validation. Recently, multi-parametric magnetic resonance imaging (mp-MRI) has been utilized to improve detection rate of aggressive prostate cancer. In this thesis, for the first time, we present the fusion of mp-MRI and TeUS for characterization of prostate cancer to compensates the deficiencies of each image modalities and improve cancer detection rate. The results obtained using TeUS are fused with those attained using consolidated mp-MRI maps from multiple MR modalities and cancer delineations on those by multiple clinicians. The proposed fusion approach yields the AUC of 0.86 in prostate cancer detection. The outcomes of this thesis emphasize the viable potential of TeUS as a tissue typing method. Employing this ultrasound-based intervention, which is non-invasive and inexpensive, can be a valuable and practical addition to enhance the current prostate cancer detection.

A NOVEL MODELING AND STATE OF CHARGE ESTIMATION SCHEME FOR LITHIUM-ION BATTERIES

Lithium Ion (Li-Ion) batteries have got attention in recent decades because of their undisputable advantages over other types of batteries. They are used in so many our devices which we need in our daily life such as cell phones, lap top computers, cameras, and so many electronic devices. They also are being used in smart grids technology, stand-alone wind and solar systems, Hybrid Electric Vehicles (HEV), and Plug in Hybrid Electric Vehicles (PHEV). Despite the rapid increase in the use of Lit-ion batteries, the existence of limited battery models also inadequate and very complex models developed by chemists is the lack of useful models a significant matter. A battery management system (BMS) aims to optimize the use of the battery, making the whole system more reliable, durable and cost effective. Perhaps the most important function of the BMS is to provide an estimate of the State of Charge (SOC). SOC is the ratio of available ampere-hour (Ah) in the battery to the total Ah of a fully charged battery. The Open Circuit Voltage (OCV) of a fully relaxed battery has an approximate one-to-one relationship with the SOC. Therefore, if this voltage is known, the SOC can be found. However, the relaxed OCV can only be measured when the battery is relaxed and the internal battery chemistry has reached equilibrium. This thesis focuses on Li-ion battery cell modelling and SOC estimation. In particular, the thesis, introduces a simple but comprehensive model for the battery and a novel on-line, accurate and fast SOC estimation algorithm for the primary purpose of use in electric and hybrid-electric vehicles, and microgrid systems. The thesis aims to (i) form a baseline characterization for dynamic modeling; (ii) provide a tool for use in state-of-charge estimation. The proposed modelling and SOC estimation schemes are validated through comprehensive simulation and experimental results.

A Study of the Microwave Carbothermic Reduction of Chromite Ore

Microwave reduction testing using activated charcoal as a reducing agent was performed on a sample of Black Thor chromite ore from the Ring of Fire deposit in Northern Ontario. First, a thermodynamic model was constructed for the system. Activity coefficients for several species were found in the literature. The model predicted chromium grades of 61.60% and recoveries of 93.43% for a 15% carbon addition. Next, reduction testing on the chromite ore was performed. Tests were performed at increasing power levels and reduction times. Testing atmospheres used were air, argon, and vacuum. The reduced product had maximum grades of 72.89% and recoveries of 80.37%. These maximum values were obtained in the same test where an argon atmosphere was used, with a carbon addition of 15%, optimal power level of 1200 W (actual 1171 W), and a time of 400 seconds. During this test, 17.53% of the initial mass was lost as gas, a carbon grade of 1.95% was found for the sintered core product. Additional work is recommended to try and purify the sintered core product as well as reduce more of the initial sample. Changing reagent schemes or a two step reduction / separation process could be implemented.

HEAT MANAGEMENT IN THE PUMPING INFRASTRUCTURE AREA OF AN ESTERHAZY MINE

Heat management in mines is a growing issue as mines expand physically in size and depth and as the infrastructure grows that is required to maintain them. Heat management is a concern as it relates to the health and safety of the workers as set by the regulations of governing bodies as well as the heat sensitive equipment that may be found throughout the mine workings. In order to reduce the exposure of working in hot environments there are engineering and management systems that can monitor and control the environmental conditions within the mine. The successful implementation of these methods can manage the downtime caused by heat stress environments, which can increase overall production. This thesis introduces an approach to monitoring and data based heat management. A case study is presented with an in depth approach to data collection. Data was collected for a period of up to and over one year. Continuous monitoring was conducted by equipment that was developed both commercially and within the mine site. The monitoring instrumentation was used to assess the environmental conditions found within the study area. Analysis of the data allowed for an engineering assessment of viable options in order to control and manage the environment heat stress. An option is developed and presented which allows for the greatest impact on the heat stress conditions within the case study area and is economically viable for the mine site.

Design of an Experimental Rig to Characterize the Gust Response of Small Wind Turbines and Autorotating Seeds

This thesis investigates the rotational behavior of abstracted small-wind-turbine rotors exposed to a sudden increase in oncoming flow velocity, i.e. a gust. These rotors consisted of blades with aspect ratios characteristic of samara seeds, which are known for their ability to maintain autorotation in unsteady wind. The models were tested in a towing tank using a custom-built experimental rig. The setup was designed and constructed to allow for the measurement of instantaneous angular velocity of a rotor model towed at a prescribed kinematic profile along the tank. The conclusions presented in this thesis are based on the observed trends in effective angle-of-attack distribution, tip speed ratio, angular velocity, and time delay in the rotational response for each of rotors over prescribed gust cases. It was found that the blades with the higher aspect ratio had higher tip speed ratios and responded faster than the blades with a lower aspect ratio. The decrease in instantaneous tip speed ratio during the onset of a prescribed gust correlated with the time delay in each rotor model's rotational response. The time delays were found to increase nonlinearly with decreasing durations over which the simulated gusts occurred.

Investigating the mesh dependency and upscaling of 3D grain-based models for the simulation of brittle fracture processes in low-porosity crystalline rock

The application of 3D grain-based modelling techniques is investigated in both small and large scale 3DEC models, in order to simulate brittle fracture processes in low-porosity crystalline rock. Mesh dependency in 3D grain-based models (GBMs) is examined through a number of cases to compare Voronoi and tetrahedral grain assemblages. Various methods are used in the generation of tessellations, each with a number of issues and advantages. A number of comparative UCS test simulations capture the distinct failure mechanisms, strength profiles, and progressive damage development using various Voronoi and tetrahedral GBMs. Relative calibration requirements are outlined to generate similar macro-strength and damage profiles for all the models. The results confirmed a number of inherent model behaviors that arise due to mesh dependency. In Voronoi models, inherent tensile failure mechanisms are produced by internal wedging and rotation of Voronoi grains. This results in a combined dependence on frictional and cohesive strength. In tetrahedral models, increased kinematic freedom of grains and an abundance of straight, connected failure pathways causes a preference for shear failure. This results in an inability to develop significant normal stresses causing cohesional strength dependence. In general, Voronoi models require high relative contact tensile strength values, with lower contact stiffness and contact cohesional strength compared to tetrahedral tessellations. Upscaling of 3D GBMs is investigated for both Voronoi and tetrahedral tessellations using a case study from the AECL’s Mine-by-Experiment at the Underground Research Laboratory. An upscaled tetrahedral model was able to reasonably simulate damage development in the roof forming a notch geometry by adjusting the cohesive strength. An upscaled Voronoi model underestimated the damage development in the roof and floor, and overestimated the damage in the side-walls. This was attributed to the discretization resolution limitations.

Examination of the Effect of Time Delay on Fragmentation

The main objective of blasting is to produce optimum fragmentation for downstream processing. Fragmentation is usually considered optimum when the average fragment size is minimum and the fragmentation distribution as uniform as possible. One of the parameters affecting blasting fragmentation is believed to be time delay between holes of the same row. Although one can find a significant number of studies in the literature, which examine the relationship between time delay and fragmentation, their results have been often controversial. The purpose of this work is to increase the level of understanding of how time delay between holes of the same row affects fragmentation. Two series of experiments were conducted for this purpose. The first series involved tests on small scale grout and granite blocks to determine the moment of burden detachment. The instrumentation used for these experiments consisted mainly of strain gauges and piezoelectric sensors. Some experiments were also recorded with a high speed camera. It was concluded that the time of detachment for this specific setup is between 300 and 600 μs. The second series of experiments involved blasting of a 2 meter high granite bench and its purpose was the determination of the hole-to-hole delay that provides optimum fragmentation. The fragmentation results were assessed with image analysis software. Moreover, vibration was measured close to the blast and the experiments were recorded with high speed cameras. The results suggest that fragmentation was optimum when delays between 4 and 6 ms were used for this specific setup. Also, it was found that the moment at which gases first appear to be venting from the face was consistently around 6 ms after detonation.