Energy Engineering - Doctoral Theses
Permanent URI for this collection
Browse
Recent Submissions
Item Enhanced modelling of transport decarbonisation and policy pathways for Ireland(University College Cork, 2023) O'Riordan, Vera; Rogan, Fionn; Daly, Hannah E.; O'Gallachoir, Brian; Climate and Energy Modelling ServicesThe release of increasing human-induced greenhouse gas emissions and the corresponding global temperature rise has prompted a growing political consensus on a decarbonised future to prevent any sustained economic or environmental harm. Many countries are using energy system modelling tools to develop strategies and policy measures to deliver timely and effective reductions of harmful greenhouse gas emissions across all energy-related sectors. Ireland, with ambitious legally binding carbon budgets, and decarbonisation targets for transport, is a country in the process of assessing and addressing key transport decarbonisation challenges faced by high-emitting countries. This thesis - with its scientific contributions on transport emissions, methodological advancements for transport and multi-sector energy systems simulation modelling, and policy recommendations on how effective measures have been in the past or could be in the future - serves as a small, but novel, piece of this process. The thesis updates the Irish Car Stock Model to investigate the importance of taxation policy using a novel bottom-up stock simulation approach. The simulation model evaluates the 2008 car tax policy in Ireland and finds that while the policy was effective at reducing CO2 emissions, it had a high cost of carbon abatement, between €1,500 – 2,200 per tCO2. The thesis develops the Irish Passenger Transport Emissions and Mobility (IPTEM) model, which for the first time, calculates the overall passenger transport demand in Ireland by trip purpose, trip distance, and mode type. The methodological advancement is in the combination of passenger transport demand from all modes of transport and information from the National Travel Survey, national transport providers, and the Irish Car Stock Model. The study finds that 82% of passenger transport demand is met by cars in Ireland, and the main reason for travel is for work (30%), shopping (19%), and companion journeys (16%). The study also finds that 40% of emissions come from journeys less than 8 kilometres. In Chapter 4, this thesis develops a new model, the LEAP Ireland ASI (Avoid-Shift-Improve) model which projects emissions and demand for passenger and freight transport up to 2030. It is novel in its application of the Avoid-Shift-Improve framework for scenarios focused on reducing the need to travel in the first instance (“Avoid”), then on modal shifting towards increased public transport use and active travel (“Shift”), and then on scenarios focused on improving the fuels used to ones with a lower carbon intensity (“Improve). These scenarios are modelling in combination with one another and the interaction between the policies is also determined. In Chapter 5, the thesis develops a new methodology for simulation modelling to project carbon dioxide emissions, how different scenarios could reduce carbon dioxide emissions, and how these fit in with sectoral emissions ceilings within carbon budgets. The thesis tracks past sectoral emissions and simulates the mitigation potential of a suite of scenarios for transport, residential, electricity, services, and industry sectors. The LEAP Ireland model developed in Chapter 5 can simulate the impact of additional policies, track policy performance, and simulate mitigation potential. The data sources, methodology, and carbon budget analysis are outlined in this novel simulation modelling framework designed to support countries with their carbon budgeting commitments. This thesis also examines the interaction effect between these policy scenarios and discusses their combinations' synergistic and antagonistic effects. The contribution of this thesis is the improvements made to the modelling methods and more robust evidence base for developing sound decarbonisation transport policy measures by shifting the focus beyond car efficiency and electrification.Item Multi–scale simulation of hybrid inorganic–organic films(University College Cork, 2023) Muriqi, Arbresha; Nolan, Michael; Horizon 2020The discovery of novel materials and associated process chemistries is crucial for the realization of higher performance electronic devices and the progress of nanotechnology in general. Hybrid materials are a special class of materials with unusual features which are attracting great interest for a wide range of applications. The unique properties of hybrid materials arise from the combination of advantages of both building blocks, i.e., inorganic and organic, which allow material functionalities that are not present in the individual components to be engineered. The properties of these materials can be also tuned depending on the requirements of the application by the choice of the components. Hybrid films are fabricated using molecular layer deposition (MLD) technique, a variant of the widely used atomic layer deposition (ALD) technique, which enables precision and control at the atomistic scale. In recent years, many MLD processes for hybrid films have been developed. However, much less is known about the growth mechanism of hybrid MLD films. In my thesis I used first principles density functional theory (DFT) simulations to investigate the key steps in the mechanism of hybrid film deposition through MLD, to address open questions around earlier MLD experiments and to predict the most suitable precursors for deposition processes. We build up an atomistic level understanding of the growth chemistry of different types of hybrid films by modelling the relevant MLD deposition processes. In particular, deep investigations on how precursor atomic structure determines film growth, stability and flexibility is carried out. We focus on the key MLD process chemistries, namely alucone and titanicone films, both of high interest for passivation layers in batteries. We assist the interpretation of experimental findings by showing for the first time why the ethylene glycol precursor performs poorly in making stable alucone films and why glycerol is better. For titaiocone films we highlight the role of the substrate and the titanium containing precursors on the initial MLD steps and in film production. We have also predicted that aromatic molecules are a good choice for stable hybrid films and their chemistry can be manipulated without impacting on the stability and this has been borne out by experimental work.Furthermore, we predict suitable MLD chemistries for production of hybrid antibacterial materials. We also study the diffusion phenomena of MLD precursors into polymeric substrates with the vapour phase infiltration (VPI) technique to understand the chemical interactions and corroborate the experimental data on Ru nanostructures and self-healing materials. Finally, we provide atomic level understanding around novel organometallic precursors and predict their applicability for deposition of oxide and hybrid thin films. The work in my thesis illustrates the key role of atomistic simulations in materials and process development.Item Applications of big data and machine learning in global energy system modelling(University College Cork, 2022) Joshi, Siddharth; O'Gallachoir, Brian; Holloway, Paul; Glynn, James; Science Foundation IrelandGlobal efforts to limit atmospheric warming well below 2 degree celcius above pre-industrial levels form the backbone of our response to mitigate the detrimental effects of climate change. The energy sector contributes circa 75% of global GHG emissions, amongst which the Electricity and Heat sectors each contribute ~40%, and the Transport sector contributes ~20% to the total global energy-related GHG emissions. The recent IPCC AR6 report finds that in nearly all possible emission scenarios considered, the world is heading towards a 1.5 degree celcius global temperature rise by the early 2030s. Pursuant to this, Energy Systems Models (ESMs) and Integrated Assessment Models (IAMs) are essential tools that provide energy system pathways to limit global warming below the temperature threshold. Thus, improving the accuracies of ESMs and IAMs will lead to measurable improvement in energy policy formulation and evaluation,thereby increasing the likelihood of meeting the commitments under the Paris Climate Agreement. This thesis develops and applies novel frameworks and methods that use a big data and machine learning driven strategy to improve the technology potential assessment of global decentralised solar PV technology and projection of transport energy service demand. The frameworks and methods developed in this thesis are presented in a format of methodological design principles followed by a case study using them. Specifically, on the supply side, the thesis investigates the global high-resolution spatiotemporal technical potential of rooftop solar PV for 2015 and further growth in the technical potentials from 2020-2050. For this assessment case study, the developed framework utilises a suite of GIS derived geospatial metrics in conjunction with a custom machine learning framework to calculate the global rooftop area at a high spatial resolution. Further using an IAM, the role of decentralised solar PV in global future energy transitions is explored. On the demand side, the thesis introduces a new machine learning model called ‘TrebuNet’ that is capable of high accuracy in estimating future energy service demand in the transport sector. The thesis thus provides the first development of machine learning and GIS based methods to improve the accuracy of global ESMs and IAMs. Particular attention is also paid towards the reproduction and transparency of the methods and the frameworks developed in this thesis for cross- disciplinary research. The thesis contributes to the important task of climate change mitigation by providing a bridge between mature IAM and ESM modelling and emerging machine learning-big data-driven tools. In doing so, this thesis demonstrates how the emerging methods in conjunction with large geospatial open source data, can aid in improving the technology representation of variable renewable energy technology in energy systems. The thesis also lays the foundation for providing solutions to energy system related tasks that are currently limited by high computational costs and data. The datasets and analysis generated by this thesis are presently assisting in unlocking the global role of decentralised renewable energy technologies in future energy systems and are also encouraging shifts in national decarbonisation pathways.Item Design, modeling, analysis, and characterization of 3-D inductors for PwrSoC/PwrSiP DC-DC converters(University College Cork, 2023) Shetty, Chandra; O Mathuna, Cian; Ye, Liang; Duffy, Maeve; Science Foundation IrelandInductors are essential components in power supplies. Increasingly, point-of-load (POL) power delivery is now the primary issue across all market sections, such as battery-powered portable electronic systems, including laptops, smartphones, tablets, etc. With increasing performance and decreasing footprint, there is a rising demand for on-chip three-dimensional (3-D) inductors. Micro inductors are used in on-chip voltage regulators, radio-frequency (RF) circuits, microsensors, microactuators, power MEMS devices, etc. The benefits of 3-D inductors such as high inductance density can be extended to such applications. This work deals with the design, modeling, and characterization of 3-D inductors for power supply applications: Power Supply in Package (PwrSiP) and Power Supply on Chip (PwrSoC) applications. Even though much work has been carried out to fabricate high inductance density 3D inductors on silicon for power applications, little or no attention has been given to (1) develop a closed-form expression for the inductance, (2) introduce novel structures for the improved figures-of-merit, and (3) dc ratio of inductance to resistance Ldc/Rdc (also known as dc quality factor Qdc). The contributions of this thesis are as follows: (1) analytical models for the inductances of 3-D inductors (toroid, solenoid, and spiral) with air-core are developed and validated by fabricating 3-D inductors on PCB, (2) a detailed study of the impact of design parameters on dc ratio of inductance to resistance (Ldc/Rdc) of 3-D micro air-core inductors is carried out and demonstrated by fabricating inductors on PCB, and (3) design, modeling, and analysis for two novel inductor topologies with magnetic thin films are presented. Followed by the introductory and literature review chapters, in the third chapter, analytical expressions for the DC inductance of four types of 3-D inductors with circular cross-section pillars (CCSP) and rectangular cross-section pillars (RCSP) are derived: (1) a toroid with CCSP; (2) a toroid with RCSP; (3) a solenoid with CCSP; and (4) a solenoid with RCSP. The inductance models are validated against numerical solutions (ANSYS Maxwell and ANSYS Q3D) and measurement results of this work as well as previously published works. The fourth chapter of the thesis focuses on the impact of design parameters such as the number of turns, pitch, height, conductor dimensions, etc. on the Qdc of different 3-D micro air-core inductor configurations. Two well-known traditional inductors are considered for the illustration: the toroid and the solenoid. Solenoid and toroid inductors are fabricated on PCB in 5 mm X 5 mm area to validate the results from Finite Element Analysis (FEA) solutions. Subsequent two chapters explore the design, inductance modeling, and analysis of two novel magnetic core inductor topologies: the fifth chapter presents a novel 3-D spiral inductor structure with magnetic thin films and the sixth chapter introduces a novel inductor structure with a coaxial cross-section of copper conductor and a single layer magnetic thin film core surrounding it. Small-signal performance of the proposed inductors compared with the previously published works to demonstrate their potential for power supply applications; the proposed inductors have the potential to achieve higher figures-of-merit (FOM). A closed-form analytical expression for the inductance, including both air-core (winding) and magnetic core (thin-films) contributions, of the novel inductor structures is derived. Finally, the seventh chapter summarises the research findings. The experimental work in this thesis focused on PCB and silicon inductors. In general, the design, analysis, and characterization methods adapted in the thesis are valid for PCB, in-silicon, and on-silicon inductors.Item Combined wave, wind, and current simulation in laboratory basins with floating offshore wind turbines(University College Cork, 2022-09-16) Otter, Aldert; Murphy, Jimmy; Desmond, Cian; Pakrashi, Vikram; Science Foundation IrelandTesting scale models of Floating Offshore Wind Turbines (FOWT) under realistic offshore conditions at scale in wave basins is challenging. There exists a strong coupling between the turbine aerodynamics and platform hydrodynamics, and working in the two different fluid domains of air and water causes a scaling mismatch between Reynolds- and Froude scaling. Furthermore, not every test facility with wave basins has the equipment to generate wind and current to simulate combined environmental loadings. To overcome these challenges a hybrid test method to simulate wind and current was developed for this thesis. Hybrid testing is a combination of real-time numerical modelling and scale model testing. The aerodynamic loads of wind and hydrodynamic loads of currents are calculated in real-time and applied to the FOWT scale model via mechanical actuators. To emulate aerodynamic loads a Multi-Propeller Actuator (MPA) was developed using off-the shelve parts from recreational aerial drones on a custom-made frame. By using several propellers with different thrust directions, multiple aerodynamic loads can be emulated simultaneously, and emulating forces rather than viscous loads solves the scaling mismatch. Aerodynamic loads have been emulated by other researchers with propeller actuators, however, only very few examples of using multiple propellers were found in the literature. The study with the MPA adds to this knowledge gap. A winch actuator was developed to simulate sea currents. By emulating the drag force of a current on the platform of the FOWT, and approximating wave-current interactions by adjusting wave spectra, currents can reliably be simulated. No other examples of this method to simulate current were found, representing a clear knowledge gap. The study with the winch actuator fills this gap in the literature. Both actuators are controlled with a Software-in-the-Loop (SIL) application. This control method uses real-time feedback from a load cell and motion tracking system to update the loads calculation with the real-time numerical simulation for each time-step, improving the accuracy of the simulation. Simulating current with the winch actuator is referred to as SIL current. Experimental results throughout this body of work have been validated with offline numerical simulations using FAST and AQWA. Two validation metrics, developed for this study, have been applied to the results. Experiments with SIL current have also been validated by repeating the experiments with physical current, referred to as the full physical method, and comparing the results of both methods. Both actuators were applied to a 1/50 scale model of the INNWIND semisubmersible platform with the NREL 5 MW as the simulated wind turbine. The results have shown the winch actuator can reliably and accurately emulate the drag force of a current on the FOWT platform and the method to approximate wave-current interactions was found adequate. The results also showed that the MPA can reliably and accurately emulate thrust- and torque loads of the NREL 5 MW turbine. The SIL current and aerodynamics emulation with the MPA, in combination with physical waves, were found suitable to replicate realistic offshore conditions at scale in the wave basin.