Doctoral Dissertations (FEAS)

Permanent URI for this collectionhttps://hdl.handle.net/10155/401

Browse

Now showing 1 - 20 of 160

Context-aware pedestrian intent prediction for connected and automated vehicles
(2024-08-01) Abdelkader, Ghadeer; Elgazzar, Khalid; Khamis, Alaa
The safety of pedestrians crossing intersections continues to raise concerns since a continuous level of awareness should be maintained to achieve optimal safety. Advanced safety features in assisted and self-driving vehicles have the potential to augment situational awareness and improve the safety of road users. Detecting pedestrian intention is a key element in providing safer urban environments to automated vehicles. However, the complexity involved in anticipating pedestrian crossing intentions makes the task challenging, as these are internal states characterized by dynamic, non-verbal signals, and unpredictable or sudden movements. Such intricacies can lead to misunderstandings for autonomous vehicles, potentially leading to a higher incidence of pedestrian accidents. To achieve this target, there is a need for real-time crossing intentions for pedestrians. In recent years, there has been an increasing shift towards a new trend in extending deep neural networks into non-Euclidean spaces, commonly known as geometric deep learning. Research in deep learning on graphs is gaining momentum, showcasing the powerful descriptive capabilities of graph structures. These structures provide essential relationship data among various elements, proving invaluable across diverse learning applications. Our study introduces an innovative spatio-temporal graph-based model designed to extract and leverage spatial and temporal features from spatio-temporal graph data. The goal is to uncover hidden patterns within these graphs, which is crucial for accurately predicting pedestrian crossing intentions. By integrating both visual and contextual information, we present a unique approach to structuring traffic scenes as graph data. This involves a novel ego-centric vehicle approach with a wheel topology that effectively captures the dynamics and interactions among traffic participants, the surrounding environment, and pedestrians. Additionally, we explore the most impactful nodes that significantly influence the model’s predictive accuracy. The model was tested on three datasets, demonstrating promising results in predicting pedestrian crossing intentions across various urban traffic scenarios.
Development and evaluation of Nuclear-Renewable Hybrid Energy System simulator with load following
(2024-07-01) Lopes Alves Esteves, Otavio; Gaber, Hossam
This thesis addresses the integration and optimization of Nuclear-Renewable Hybrid Energy Systems (N-RHES) with a focus on Load Following (LF) capabilities. The primary aim is to enhance the operational flexibility of nuclear reactors to adapt to dynamic power demands. A dynamic simulation tool was developed for different nuclear reactor technologies, including Pressurized Water Reactors (PWR) and Molten Salt Reactors (MSR), enabling detailed analysis of reactor power behaviour under different Load Following scenarios. Additionally, a Nuclear Reactor in the Loop (NRiL) system was implemented for accurate real-time evaluation of control systems, providing precise assessments without the need for expensive and time-consuming physical tests. The final component, the Nuclear-Renewable Hybrid Energy System Simulator (N-RHESS), integrates an energy management system within the simulation environment, improving N-RHES designs and decision-making by allowing users to develop complex energy load profiles and assess the feasibility of integrating nuclear reactors. The research demonstrated significant improvements in the operational efficiency and economic viability of N-RHES, highlighting its potential to enhance grid reliability, reduce carbon emissions, and promote sustainable energy solutions. This work contributes to the field of energy systems engineering by providing innovative tools and methodologies for integrating and optimizing nuclear and renewable energy sources.
Yeast-based impedance biodosimetry for retrospective assessment of radiation exposures
(2024-07-01) Hassan, Amna; Atkinson, Kirk
In the event of a radiological accident, conventional dosimeters are not always present or available to provide dose estimates. As such, retrospective dosimetry techniques can be used to determine the radiation dose to populations and the environment. This work investigates the feasibility of Saccharomyces cerevisiae yeast cells as fortuitous dosimeters for retrospective assessments of exposures following radiological accidents using impedance biodosimetry. The radiation response of S. cerevisiae was examined by using cellular metabolic activity and impedance as a means to evaluate dose. A novel dosimeter design was developed to allow impedance measurements to be performed on yeast samples. Simulations with Geant4 Monte Carlo code were conducted to explain the significance of the local environment and its impact on impedance measurements. It was found that yeast irradiated in the presence of various adjacent materials yield different impedance responses and the local environment influences the radiative energy deposition in yeast cells. This is due to the primary and secondary photoelectrons and Compton electrons that are produced within these materials, which contribute to additional energy deposition and increase damage to cells. This effect was exploited by adding an intermediate material in yeast samples to amplify the impedance signals. In this current work, aluminum grains were utilized as the standard intermediate material in yeast dosimeters as a controlled proxy for real world situations and for the purposes of mechanistic analysis and sensitivity assessments. To evaluate the feasibility of impedance biodosimetry, a dose-response curve was produced by irradiating yeast cells from 0:5 Gy to 8 Gy using a ¹³⁷Cs gamma source. The dose-response curve exhibited a linear relationship of dose with changes in the impedance response. Additionally, the lowest detectable dose that could be measured using this methodology was determined to be 300mGy. Fading of the impedance signal was also investigated, where no noticeable fading over a 7-month period was observed. Finally, the impedance response of Fleischmann's ® yeast was examined, and it was found that commercially available yeast cells exhibit a similar response to laboratory-grade yeast, as well as a radiation response. Based on these experimental findings, yeast cells were determined to be suitable to use for retrospective dosimetry applications since these samples are widely available and require no additional processing. Yeast-based impedance biodosimetry was determined to be an inexpensive technique that could be used in the event of a radiological accident to evaluate initial dose estimates to exposed areas. However, since the local environment considerably influences the energy deposition in cells, knowledge of materials that may be adjacent to yeast samples during the exposure is necessary to provide accurate dose assessments.
An investigation of ultraviolet and ionizing radiation on the eye-lens of rainbow trout
(2024-06-01) Kocemba, Marta; Waller, Edward; Waker, Anthony
The lens of the eye is one of the most radiosensitive tissues in the body, and the effects of radiation on the eye-lens are not fully understood. Dose limit and tissue effect threshold recommendations have been lowered due to cataracts occurring at unexpected doses, and there is therefore a need for biological experiments on the early stages of cataractogenesis. There is also a need for radiobiological evidence in the context of environmental radioprotection, since the current recommendations for dose limits to non-human biota are based on assumptions rather than evidence of radiation response. In this work, the effects of ionizing and ultraviolet radiation on the eye-lens of rainbow trout have been investigated in vitro. Eye-lenses were excised and maintained in culture, then irradiated with either X-rays or ultraviolet (UV) radiation and assessed for several types of damage response. Optical quality was quantified using laser focal analysis; the structural integrity of cell membranes was assessed by measuring protein leakage from eye-lenses; and the response of lens cells to the radiation was characterized using proteomics analysis. A dose of 0.2 J/cm² of UVB radiation was shown to produce no changes in the optical quality of intact rainbow trout eye-lenses over 30 days post-irradiation. However, there is evidence of a damage-response process that triggers cellular 'housekeeping' and results in irradiated lenses maintaining transparency longer than control lenses. Comparative studies with groups of lenses being exposed to either 1 J/cm² of UVB radiation or 2 Gy of X-rays has shown that this dose of ionizing radiation produces significant changes in the expression of proteins related to cell membranes, DNA repair, and removal of damaged proteins. The UVB dose led to elevated expression of the same types of proteins, but not in significant amounts. Combining results across damage assays and experiments has revealed trends which support the concepts of individual variation in radiosensitivity, membrane damage and bystander effect as factors in early cataractogenesis, and the relationship between stress response and lens transparency. Overall, this characterization of specific aspects of damage response in the eye-lens to ionizing and ultraviolet radiation has contributed to the understanding of cataractogenesis as well as environmental radioprotection.
Novel thermoluminescent dosemeter for the measurement of the eye lens operational dose equivalent in mixed neutron-gamma radiation fields
(2024-07-01) Beregic, Virgiliu Doru; Nichita, Eleodor
Based on ICRP 118 (2012) recommendations, the Canadian Nuclear Safety Commission amended the Radiation Protection Regulations in their recent document “REGDOC-2.7.2, Dosimetry, Volume I: Ascertaining Occupational Dose”, reducing the equivalent dose limit for the eye lens of a nuclear energy worker from 150 mSv to 50 mSv in a one-year dosimetry period and to 100 mSv in a five-year dosimetry period, and adding the personal dose equivalent at 3mm soft-tissue depth, Hp(3), to the list of Radiation Protection quantities, as the representative operational quantity for the dose to the lens of the eye. The Hp(3) operational quantity is measured using a dosemeter covered by 3mm of tissue-equivalent material. To date, despite there being some attempts to calculate eye-lens conversion coefficients for neutrons and to evaluate the dose due to occupational exposure by Monte Carlo simulations, no operational eye-lens dosemeters for mixed neutron-gamma fields have been developed anywhere in the world. The objective of this research was to design and manufacture a novel thermoluminescent dosemeter to measure directly the Hp(3) in mixed neutron-gamma fields. A prototype was developed and its applicability to the concurrent measuring of the neutron and gamma operational eye lens dose equivalents in a mixed neutron-gamma field was demonstrated both experimentally and by Monte Carlo simulation with the GEANT4 toolkit.
Development of multi-physics capabilities in coupling computational fluid dynamics and thermodynamics for molten salt reactor applications
(2024-03-01) Scuro, Nikolas Lymberis; Mohany, Atef; Piro, Markus H.A.
Existing knowledge gaps in Molten Salt Reactors (MSR), such as understanding fuel salt chemistry and fission product retention, require rigorous investigations to support reactor safety. The objective of this work was to develop a novel computational toolset tailored for multi-physics simulations of MSR studies that could fill the aforementioned knowledge gaps. This toolset studied the intricate dependence between thermal-hydraulics and salt chemistry by coupling the computational fluid dynamics code OpenFOAM with the computational thermodynamics code Thermochimica . This coupling facilitates the simulation of scenarios relevant to MSR reactor safety, which is especially important given that MSRs have a low technical readiness level relative to other reactor technologies. Two demonstration problems exemplify the applications and outcomes of this project, which was in support of the SAMOSAFER Co-ordinated Research Project of the European Commission. The initial problem revolves around the first step of the molten salt clean-up fluorination process, which vaporizes molten fuel components (i.e., UF4) into its volatile form (i.e., UF6). Simulations revealed that the fluorination time is strongly dependent on the molten salt system, salt viscosity, and temperature. Compared with experimental results, the simulations displayed a strong correlation in vaporization rates under steady-state conditions, giving credence to the validity of the local equilibrium hypothesis. The second demonstration problem centred on the molten salt fast reactor. Here, normal operating conditions were examined, focusing on fission product retention and release, such as Cs, La, Xe in promising molten fluoride systems (e.g., LiF – ThF4 – UF4 77.5-20-2.5 mol%). Simulations demonstrated that most fission products are retained by the salt and the evaporation rates of several compounds, such as, LiF, ThF4, UF4, CsF, Cs2, Cs2F2, LaF3, F, F2 posed to be almost insignificant when compared to other known volatile/gaseous fission products, such as xenon. This investigation provided an understanding of how fast the UF4/UF3 molar ratio reaches optimal design limits, which plays a pivotal role in controlling corrosion. In conclusion, the outcomes underscore advancements in computational capabilities, promising to elucidate further the intricacies of designing and testing multifaceted scenarios in the realm of MSRs.
Robust nonlinear controller for single ended primary inductor converter supplying shared load from multiple sources with asymmetrical dynamics
(2024-04-01) El Haj, Youssef; Sood, Vijay; Milman, Ruth
This work proposes a systematic approach to design a novel Integral Sliding Mode Controller (ISMC) for a Single-Ended Primary-Inductor converter (SEPIC) with dynamic load sharing. The designed sliding surface is used to connect and control two different input-energy sources via two SEPICs to drive a parallel-connected load with a fixed or dynamic autotuned sharing ratio. This structure enables to maintain battery health and extend its life. This proposal provides a solution that is scalable to the power system industry where there is a need to integrate other energy sources to the main power network; the proposed controller can function with sources having different dynamics and varying voltage levels with respect to the main network. Furthermore, the work also contributes to the field of control theory by deriving and designing a SMC for a SEPIC converter with only one parameter to tune where the upper and lower bounds are derived. The designed surface results in a minimal chattering behaviour at the output voltage as well as at the duty cycle level and allows for operating the SEPIC at a fixed switching frequency. The proposed controller can withstand up to a 75% variation in the input voltage, 100% variation on the load side in addition to providing a superior cold start performance. The proposed controller is nonlinear and has a variable structure; these features suit the SEPIC converter which is based on switching behaviour. The controller’s ability to reject input voltage disturbances which vary over a wide range is a key to integrating alternative energy sources (such as an ultracapacitor) to the main power network. Finally, the work demonstrates how the proposed sliding surface can be modified to drive two parallel converters to dynamically share load current where the current shared ratio is autotuned during the transient period while at steady-state it follows a pre-set shared ratio.
Design and investigation of renewable natural gas and methane production systems
(2024-04-01) Bolt, Andre; Dincer, Ibrahim; Agelin-Chaab, Martin
This thesis presents the design and investigation of renewable natural gas and methane production systems. The thesis comprises a theoretical and an experimental portions. The experimental portion of the thesis includes the design, construction, and experimental testing of a new helical fixed-bed reactor, as well as a production system to support and monitor the reactor. Additionally, the experimental system integrates gas bending and the recycling of the coolant working fluid to pre-heat the reactant molecules prior to entering the reactor. The experimental tests include studying the effects of pressure variability at the inlet of the reactor, variations in the reactor starting temperature, and variations in the mole ratio between reactants. Most notably, the system is able to achieve a maximum CH4 production rate of 10.61 L/h. This equates to overall energy and exergy efficiencies of 13.36% and 12.46%, respectively. However, during the simulation aspect of the thesis, computational fluid dynamics (CFD) analyses are conducted. These analyses consider the design of four unique fixed-bed natural gas reactor concepts. Additionally, each of the reactor concepts is presented as having three unique configurations. The analyses show that Concept 4’s helical reactor design presents the greatest potential to mitigate elevations in the reactors’ temperature due to more of its surface area being exposed compared to the other reactor concepts. Additionally, Configuration 1 of Concept 4 is able to achieve a yield of 86.7%. The theoretical portion also investigates four novel multigeneration systems capable of synthesizing natural gas while simultaneously producing several useful outputs. System 1 considers a target location of Alberta, Canada, and uses biomass and solar energy as its source. The system achieves energy and exergy efficiencies of 61.0% and 28.6%, respectively, during heating mode. The other three multigeneration systems reduce CO2 emissions from industries that produce substantial amounts of greenhouse gas emissions (cement, steel, and glass industries), through the integration of chemical absorption techniques, the CO2 that is extracted can be used to synthesize CH4 renewably. These systems also harness solar, wind, hydro, and tidal as the energy sources.
Investigation of new renewable energy-based multigeneration systems for Saudi Arabia
(2024-04-01) Altayib, Khalid; Dincer, Ibrahim
This thesis explores three hybridized, large-scale solar thermal energy multigeneration systems: System 1 combines solar thermal energy with biomass, System 2 with geothermal, and System 3 with a petroleum coke and biomass blend. Each system provides power, heating, desalination, and other commodities. The thesis aims to develop energy system flowsheets integrating multiple technologies and assess their exergetic and economic benefits through case studies in KSA. Although the systems are of different kinds and scales, their economic parameters are found to be similar in terms of payback periods. System 1 achieves energy and exergy efficiencies of 50.4% and 45%, respectively. It generates annually 1040 GWh of electric power, 860 GWh of cogenerated heat, 80 GWh of refrigeration, 1100 tons of hydrogen, 26000 tons of chlorine gas, 11,600 tons of concentrated aqueous sodium hydroxide, 11,300 tons of ammonia, 1740 tons of aqueous urea, 905,000 m3 of fresh water. System 2 generates 700 GWh/year of power, 1200 GWh/year of heating, 27,100 tons/year of methanol, 130 million m3/year of fresh water, 42,500 tons/year of oxygen with efficiencies of 22% energy and 30% exergy. System 3 generates 1200 GWh/year of power, 690 GWh/year of heating, 12,700 tons/year of hydrogen, 19,300 tons/year of dried dates, 290,000 m3/year of fresh water and 80 GWh/year of cooling. The energy and exergy efficiencies of System 3 are 83.2% and 64%, respectively. For all systems, the chemical reactors are modelled using the Aspen Plus, which helps determine the best oxygen-to-biomass fraction in the gasifier as 15% at the turbine inlet temperature of 1500°C for System 1, the optimum methanol synthesis temperature in the range of 250°C-300°C for System 2, and results in 1.5 H2/C as the best molar ratio in hydro-gasifier to enhance the synthetic methane production rate for System 3. The thesis study underscores the potential of multigeneration and hybridization in improving the economics and ecology of renewable energy systems and offering insights applicable beyond the case studies explored.
Analysis of net zero energy buildings and communities that strategically integrate transportation energy
(2024-05-01) Garmsiri, Shahryar; Rosen, Marc A.
The limited oil supplies, rising fuel prices and greenhouse gas (GHG) emissions, have heightened the demand for alternative energy sources, especially in transportation and residential sectors. The rise of electric vehicles (EVs), plug-in hybrid vehicles (PHEVs), and fuel cell vehicles (FCVs) have reduced dependence on oil and emissions. Governments and researchers are exploring net zero energy building/community (NZEB/C) options to meet GHG emission mandates for new and existing dwellings. This study evaluates the benefits of integrating transportation energy with a NZEB via the electric grid, focusing on EVs, PHEVs, and FCVs. The study analyzes energy performance in a NZEB/C and transportation sector, aiming to achieve net zero energy status in both new and existing communities. The motivation of this study is to address the limited research on EV, PHEV integration with NZEBs, particularly on larger NZEB/Cs and FCV side. A methodology was developed to analyze communities with various vehicles simultaneously, addressing issues with software programs lacking databases for alternative fuels. MATLAB was used for simultaneous energy analysis and transportation integration, reducing computational time and eliminating the need for multiple programs. This analysis, unrestricted to specific software programs, fills the gap in analyzing integration of transportation energy within a NZEB/C for potential benefits. A 1-D thermal resistance network was developed, enabling faster energy usage calculations and better understanding of energy flow within a house/building. The study revealed, discharge of energy from EV battery, PHEV and FCV energy contributions via their hydrogen and biogas fuel tanks accounted for 10%, 16%, and 25%, respectively, of the community's energy consumption. As the communities considered are expanded to larger sizes, energy discharge and contribution decreases due to vehicle storage limitations and the increased presence of smaller vehicles in the analysis. The PHEV converted to operate on biogas is an attractive type of vehicle for transportation energy integration due to its lower cost compared to gasoline and diesel fuels. However, it is less environmentally friendly compared to EVs and FCVs due to the emission produced using biogas. The FCV's economic benefits determined to be achieved when the cost of hydrogen fuel was less than 4.95 CAD/kg.
Multiphysics modeling, study, and analysis of atmospheric pressure plasma-based mass separation system for high-level radioactive waste treatment
(2024-02-01) Darda, Sharif Abu; Gaber, Hossam
Disposing and storing increasing High-Level Radioactive Waste (HLRW) volume is challenging and costly. Frequently, a large mass of this storage volume is low or non-radioactive elements. For high-level liquid waste, the total waste mass, if grouped into amu mass, 98.9% is for bulk elements with 1–65 amu, 0.7% is for fission products with 80–160 amu, and 0.4% is for actinides with 225–250 amu. Of this waste, 99.7% of the radioactivity comes from the fission products, while substantial bulk elements contribute only 0.1% of the radioactivity. Therefore, clean separation as a group of elements may significantly reduce the HLRW storage volume and maintenance cost. In the case of Spent Fuel (SF), over 95% of the mass is transuranium elements, and only 4–5% is fission products. Here, a clean mass group separation to recover uranium and other transuranium elements from the waste may optimize the nuclear fuel cycle. Traditional chemical separation of actinides from SF for recycling frequently creates a higher volume of waste to manage. Plasma mass separation divides ions according to their atomic or molecular mass in a plasma device. According to T. Ohkawa and colleagues, the principle of the band gap ion mass filter (BGIMF) states that using a combination of an axial magnetic field and a radial or azimuthal electric field, the ions in a plasma can be radially separated according to mass. Mass separation frequently takes place in a high vacuum environment. An atmospheric pressure plasma mass separator may have further advantages over high vacuum plasma separation. Rather than separating individual atoms of an element, an atmospheric pressure plasma mass separator can be utilized to process HLRW and separate waste elements into mass groups for proper management. This research concentrates on separating High-Level Radioactive Waste (HLRW) using a Plasma Mass Separation System (PMSS) and explores the physics and technology requirements using the COMSOL multiphysics tool. While PMSS can handle various Radioactive Waste (RW) types, the focus here is on HLRW. The study designs a universal plasma mass separation device operating in noble gas atmospheric pressure Inductively Coupled Plasma (ICP).
Categories in control systems software: toward a unified theory of programming & control
(2023-12-01) Teatro, Timothy A.V.; Eklund, J. Mikael; Milman, Ruth
Category theory is applied to the design and modeling of control systems application software with emphasis on feedback control. The language of application is iso standard C++17, though the design is abstract and can be gainfully applied in any language expressive enough to embed domain specific languages for event stream processing with sufficient structure. The design is derived in a category, Cpp, of a subset of C++ programs where types are modelled as sets and programs/routines are modelled as functions. This gives a forgetful functor from Cpp to 𝕊𝗲𝘁, the category of sets which, in theory, facilitates broader compatibility with theories of dynamical systems in concrete categories. A library of abstract datatypes (struct templates) and natural transformations (parametrically polymorphic function templates) is developed to demonstrate that (1) Cpp carries a bicartesian closed structure and (2) this structure has representation as standard compliant code. The axioms of this structure are encoded as unit-tests. And from this structure we specialize “machines” in the sense of Goguen (or more generally, Arbib & Manes), which actualise in Cpp as Moore machines. These Moore machines are then used as a basic model for the I/S/O structure of a control program. Categorical Moore machines can be cast in terms of algebra and coalgebra which give natural mechanism to the input-driven evolution of internal state of the control programs, and infinite records of behaviour. The internal language of that model is consonant with sufficiently structured domain specific event-stream processing languages. The core examples and a case study use Rx, but FRP is a stated ideal and avenue for future work for modeling of interconnected and hybrid systems with computer controlled components. The architecture is applied in two examples: (1) a simulated spring-mass- damper system with PID-force control, where comparison is made to analytical results, and (2) NMPC path tracking of a mobile robot with obstacle avoidance through soft constraint.
Development and analysis of thermal management strategies to improve Lithium-ion battery performance
(2024-01-01) Shahid, Seham; Agelin-Chaab, Martin
The transportation industry contributes more than a quarter of the global greenhouse gas emissions and transportation electrification was introduced as a means to decarbonize the industry. One of the major challenges related to the electrification of technologies are the thermal challenges associated with Lithium-ion batteries which are the leading candidate for electric batteries. In this research, these thermal challenges have been investigated with the objective of effective cooling and increased thermal uniformity within cylindrical Lithium-ion batteries. To achieve this, novel hybrid thermal management strategies have been proposed that combine air, liquid, and phase change material cooling systems. Several configurations of the proposed strategies are designed and analyzed through both experimental and numerical studies. The proposed hybrid strategies were able to limit the maximum temperature of the battery module to below ~29 °C. The developed battery module also achieved the desired temperature uniformity to less than 5 °C. Furthermore, the proposed hybrid strategies eliminate the requirement of a pump and reservoir system since there is no flow of liquid coolant within the battery module. This reduces the energy required for the operation of the thermal management system, thereby increasing the available energy for propulsion. Therefore, the proposed hybrid strategies and battery modules are capable of maintaining the thermal environment required by the Lithium-ion batteries for effective performance and can also be scaled to an entire battery pack for a range of applications.
Spectrum sharing for multi-user massive MIMO networks
(2023-12-01) Saif, Rosa; ShahbazPanahi, Shahram
In this dissertation, we propose a creative approach to advance 5G network technologies by investigating the impact of employing an underlay spectrum sharing (USS) scheme on the performance of two massive multi-input-multi-output (MIMO) networks. We explore an USS approach where a multi-user massive MIMO network (primary network (PN)), i.e., the owner of the frequency spectrum, allows another multi-user massive MIMO network, the secondary network (SN), to utilize its allocated spectrum to serve secondary users (SUs). Within this context, we devise joint power allocation and beamforming techniques at the SN for both conventional time-division duplexing (C-TDD) and reverse time-division duplexing (R-TDD) protocols. In the C-TDD approach, both the PN and SN operate concurrently in either the uplink (UL) or downlink (DL) modes. In the R-TDD protocol, the PN and SN do not simultaneously operate in the UL or DL modes. It is worth noting that, during the training phase of the PN (learning phase of the SN), all the SN’s nodes remain silent and listen to the PN to acquire as much information as possible about the PN. The optimization problems aim to maximize the SN’s achievable sum-rate in both UL and DL, while guaranteeing the minimum acceptable individual rate for each primary user (PU) and satisfying the SN’s power constraints. Effective solutions are proposed for both the C-TDD and R-TDD protocols, including novel methods to mitigate interference caused by the SN’s nodes to the PN’s nodes during UL and DL phases. We assume that the PN parameters are set by the PN independently, without considering the presence of the SN, to minimize the SN’s potential impact on the PN’s frame structure and system design. Our simulation results demonstrate that for a moderate-scale SN coverage area, both C-TDD and R-TDD approaches reveal almost comparable performance. Additionally, changes in the SN’s settings have a small effect on the total sum-rate of the PN when our proposed method is employed. Finally, for all tested values of the number of antennas at the secondary base stations (SBS), the R-TDD approach outperforms the C-TDD approach when the SN coverage area is large, and vice versa.
Design and development of a context-aware collaborative autonomous real-time vehicle systems framework
(2023-11-01) Pereira Peixoto, Maria Joelma; Azim, Akramul
The increasing autonomy of intelligent systems, with applications extending from self-driving vehicles to home-based robots, has emerged as a critical area of focus in modern research. Yet, to acknowledge the full potential of these systems, numerous challenges must be addressed. This thesis encapsulates rigorous research resulting in eight scientific papers investigating autonomous systems’ efficacy and efficiency. Our study proposes the Context-Aware Collaborative Autonomous Real-Time Vehicle Systems (CARVS) Framework and focuses on improving context awareness, simplifying remote task processing, and quantifying prediction uncertainty in Machine Learning (ML) algorithms. Our intention is to move forward the state-of-the-art in autonomous systems based on our findings as we investigate the employment of noise as a stimulus to boost agent exploration. We also address the development of mapping and task management systems for connected autonomous vehicles (CAVs) using edge, fog, and cloud computing. Furthermore, we study the quantification of uncertainty in ML algorithm predictions to describe their behaviours and decision-making mechanisms. This research provides valuable insights for the continuous improvement of autonomous learning and the ability to deal with uncertainties in dynamic and unpredictable environments, which could lead to greater acceptance of such systems.
Design and development of reusable feature-based next-generation embedded software
(2023-12-01) Maruf, Md Al; Azim, Akramul
The emergence of next-generation embedded systems, emphasized by their shortened life cycles, necessitates an urgent shift towards agile software design and development. The objective is to achieve timely product delivery while maintaining safety and quality standards. Anticipating that next-generation software will interconnect numerous devices, an efficient architecture supporting advanced functionalities or features becomes essential. Fog and edge computing emerge as promising computing paradigms for next-generation embedded applications. These platforms are particularly pertinent for safety-critical and time-sensitive systems, such as autonomous vehicles. However, integrating these platforms into embedded systems presents challenges in designing and developing software supporting future demands like mobility and machine learning (ML) model training. This research focuses on identifying the reusable features through static analysis from legacy embedded software to improve code reuse for faster development and create a feature model for understanding features and their requirements. The feature model displays embedded software’s integrated variants and constraints details to reduce the feature verification and validation effort. It supports reusability, significantly easing key development phases such as requirement analysis, which is often a major bottleneck in the timely release of embedded software, even with agile methodologies. Further, the study emphasizes designing fog computing architecture that benefits embedded applications like over-the-air (OTA) software updates and improves the performance of large ML model training by efficient model partitioning across edge devices. Our research presents a feature-based embedded software development approach that incorporates the advanced features in the feature model and streamlines the entire development cycle from design to deployment. A Python tool is developed to automatically extract reusable features from publicly available GitHub embedded software projects, showcasing the practical applicability of our research in real-world scenarios.
Modelling of radioactive particle resuspension after a dirty bomb event
(2023-12-01) Perera, Sharman; Waller, Edward J.
The primary hazard of a Dirty Bomb emanates not from the initial detonation but from the subsequent re-suspension of deposited radioactive particles. Although radiological contamination is substantial on surfaces initially, the biological risk intensifies through ingestion or inhalation due to re-suspension. Experimental simulations in a 10 m wind chamber unveiled average bin-by-bin resuspension factors for particle sizes between 0.9 and 6.5 μm downstream from the initial fallout. Calculated values were 4.12E-05 × (1 ± 46.8%) m-1 and 4.56E-05 × (1 ± 79.5%) m-1, indicating the magnitude of the resuspension process. In a prototypical study using data from a full-scale dirty bomb experiment by DRDC Canada, maximum committed effective inhalation radiation doses were calculated as 1.89E+02 μSv for the public and 1.89E-2 μSv for first responders, considering a 35.2 × (1 ± 10%) GBq dirty bomb. Subsequently, Computational Fluid Dynamics (CFD) was applied via FLUENT software, incorporating Regional and Global models to simulate particle resuspension. The unsteady Large Eddy Simulation viscous model with Smagorinsky-Lilly Subgrid-Scale models effectively captured turbulent flow dynamics. CFD resuspension factors at specific locations were computed as 4.14E-04 × (1 ± 13.3%) m-1 and 4.01E-4 × (1 ± 16.3%) m-1 for particle sizes between 0.9 and 6.75 μm. Notably, an order of magnitude difference between CFD and experimental results highlights the intricacies in modelling particle resuspension. Future refinements may include incorporating surface roughness elements in both downstream and transverse directions in the Regional CFD model to capture particle saltation, enhancing resuspension predictions' accuracy, and introducing a multilayer resuspension model. This study underscores the complex nature of Dirty Bomb scenarios, emphasizing the need for a holistic understanding that combines experimental insights with advanced computational modelling for effective risk assessment and response planning.
PoT: bridging IoT with phone technology
(2023-09-01) Khalil, Haytham; Elgazzar, Khalid
The ”Phone of Things” (PoT) introduces an innovative integration of IoT systems with the widely available telephone network infrastructure. It repurposes underused home landlines and existing communication servers, weaving them into the IoT fabric. By transforming IoT devices into SIP endpoints within the VoIP ecosystem, users can monitor and interact with these devices through regular phone calls, voice commands, or text messages. PoT presents a seamless user experience by capitalizing on ubiquitous phone network infrastructure while promoting context-aware telephony solutions. Using open-source technologies, PoT ensures affordability, interoperability, scalability, and security. A tangible PoT prototype is developed using a Raspberry Pi equipped with Asterisk, a renowned open-source IP-PBX software. The Raspberry Pi acts as a gateway, facilitating communication between IoT devices and VoIP servers. Performance evaluation testing reveals that the Raspberry Pi 4 B can manage up to 182 concurrent calls, while the less performant Raspberry Pi Zero W can handle 12 simultaneous calls. These results highlight the potential of these compact, affordable boards as ideal PoT gateways for homes and small-to-medium businesses, making deployment of the framework more economical. In addition, the thesis introduces ”tSIP”, a streamlined SIP version designed for PoT. It offers a concise message format, achieving up to 22% and 46% size reduction compared to traditional SIP and CoSIP messages. This compact format ensures quicker transmission, energy efficiency, and optimized network usage. The study also presents a decentralized registration and authentication mechanism for PoT, based on blockchain technology. A prototype is crafted on a private blockchain, emphasizing privacy, speed, and cost-effectiveness. This mechanism aligns with SIP’s security standards and caters to embedded smart devices’ constraints. Lastly, to illustrate PoT’s real-world application, the ”Location Transparency Call” (LTC) system is introduced. LTC provides a context-aware telephony solution for businesses. It tracks employees via their RFID access tags, ensuring that incoming calls are redirected to the nearest phone to their current location, reducing missed business call occurrences.
Modified wavelet-based pulse width modulation technique for cascaded H-bridge multilevel converter
(2023-08-01) Patel, Jigneshkumar R; Sood, Vijay K.
Power electronics (PE) converters are crucial for providing a cost-effective, reliable, and efficient solutions for integrating renewable energy sources (RES) into the electrical grid. Over the years, many converter topologies have been developed for low, medium, and high voltage applications. However, they work more efficiently when appropriate modulation techniques are used. Many pulse width modulation (PWM) methods have been presented to decrease output harmonics, such as carrier-based (PWM methods, selective harmonic elimination (SHE), and nearest-level modulation (NLM). Regardless, these methods raise the complexity and expense of the converter, reduce the fundamental component, and increase high-frequency harmonics in the output signal. In the present work, a novel wavelet-based PWM (WPWM) method is developed for a multilevel converter. This mathematical modulation technique reduces the harmonic content at both low and high frequencies, improves the fundamental component in the output, and reduces switching losses. However, in multilevel converters, the gate pulses generated by WPWM are designed to only shape the output voltage without considering the load balancing between the DC sources or split capacitors. Hence, an additional load-balancing algorithm is necessary. This work proposes a new phase-shifting WPWM method that naturally balances load sharing between all the DC sources or split capacitors in the multi-level converter. This method operates at a low switching frequency, thereby keeping switching losses low, and reducing total harmonic distortion (THD). Moreover, since the proposed method is a mathematical closed-form PWM method, it can be evaluated within a finite number of iterations as compared to the open-ended SHE method. The proposed method is simple and runs efficiently in real-time, which enables fast system dynamics during transient conditions. Also, it does not depend on a minor computational time-step. Hence, it can be implemented on a low-cost digital controller. The validity of the proposed method is validated both by MATLAB/Simulink model, LTSpice model, and experimental tests. The results are discussed and compared against other PS-PWM methods to demonstrate the advantages of the proposed method.
A contactless and non-intrusive current measurement technique for low and medium voltage AC power systems
(2023-08-01) Shrawane, Prasad; Sidhu, Tarlochan S.
The real-time state of current is essential to precisely monitor and control the AC power systems. It is also crucial for detecting various types of faults that may lead to long duration and wide area outages and affect the reliability and dependability. Traditional core wound window type current transformers (CTs) are widely used for current measurement at present. Increasing number of distribution energy resources integrated to the power systems network require a greater number of such instrument transformers for efficient monitoring and control of the grid. However, these CTs require complex and time-consuming operational procedure for installation and maintenance. In addition, they have a major drawback of saturation. To overcome this drawback, they need a higher accuracy leading to bigger size and higher costs and, therefore, beget the need for alternative current measurement techniques. They also pose a serious hazard of explosion if their secondary windings are left open circuited. In this thesis a technique of non-invasive contactless current measurement using Tunneling magnetoresistive (TMR) sensors is proposed and implemented for AC power systems. The proposed sensors overcome the aforementioned drawbacks of the CTs and provide more accurate outputs for asymmetrical currents during fault conditions. A thorough investigation is carried out to study the effect of distance, conductor insulation, and frequency of source current on their performance while applied for single-phase and three-phase current measurements. The sensors were calibrated to overcome the inequality in the sensed magnetic field due to the various aspects such as the distance from the source, minute structural variations, the magnitude of the source current, and harmonics. This thesis introduces a new technique to determine the phase angle error in absence of time-synchronized data. The weighted fusion technique is applied to six pair combinations from an array of four sensors in a three-phase triangular and horizontal structure for accuracy improvement. The measurement accuracy based on the sets of weighting factors corresponding to a minimum TVE showed promising and successful validation of the magnetic sensors for a possible replacement of CTs in the ac current measurement.

Browse

Recent Submissions