New survey technologies are able to provide detailed data on the form and topography of riverbeds. With this increased data resolution, the required computational time rather than data availability has become the limiting factor for river models. Detailed bathymetric data can be used to provide better empirical representation of drag and roughness at fine scales, allowing a priori selection of roughness using known physics rather than a posteriori calibration. However, we do not have sufficient guidance or understanding from the literature to represent known heterogeneities smaller than our practical grid scale. The problem is what to do with known subgrid-scale bathymetric features and roughness when our models must use a coarser computational grid. In this project, we simplify this complex problem to analyzing flow in a simple open channel with a single patch of relatively high roughness against an otherwise uniform background of low roughness. We model this open channel with a two-dimensional, depth-averaged river model. By running multiple simulations using different grid sizes we gain insight into how the relationship between the grid cell size and the patch size affects the appropriate physical selection of roughness parameter. As the primary focus, the present work proposes and investigates several methods for upscaling known fine-scale drag coefficient data to a coarser grid resolution for a model. For the tested conditions, it appears that a simple area-weighted linear average is simple to apply and creates a flow field very similar to the best results achieved by calibration. As a secondary issue, the present work examines grid-dependent behaviors when using model calibration. Although recalibration of models for different grid scales is a common practice among modelers, we could find relatively little documentation or analysis. In our work, we examine both single-cell calibration (i.e. changing roughness in only the cell containing the rough patch) and multiple-grid cell calibration involving neighbor cells. With either method, improving calibration required multiple model simulations and comparative analysis for each tested grid size and was inefficient compared to the upscaling approach. As expected, the calibration at a given grid size was always inappropriate for a different grid size. / text

A well-represented description of convection in weather and climate models is essential since convective clouds strongly influence the climate system. Convective processes interact with radiation, redistribute sensible and latent heat and momentum, and impact hydrological processes through precipitation. Depending on the models’ horizontal resolution, the representation of convection may look very different. However, the convective scales not resolved by the model are traditionally parameterized by an ensemble of non-interacting convective plumes within some area of uniform forcing, representing the “large scale”. A bulk representation of the mass-flux associated with the individual plumes in the defined area provide the statistical effect of moist convection on the atmosphere. Studying the characteristics of the ECMWF ensemble prediction system it is found that the control forecast of the ensemble system is not variable enough in order to yield a sufficient spread using an initial perturbation technique alone. Such insufficient variability may be addressed in the parameterizations of, for instance, cumulus convection where the sub-grid variability in space and time is traditionally neglected. Furthermore, horizontal transport due to gravity waves can act to organize deep convection into larger scale structures which can contribute to an upscale energy cascade. However, horizontal advection and numerical diffusion are the only ways through which adjacent model grid-boxes interact in the models. The impact of flow dependent horizontal diffusion on resolved deep convection is studied, and the organization of convective clusters is found very sensitive to the method of imposing horizontal diffusion. However, using numerical diffusion in order to represent lateral effects is undesirable. To address the above issues, a scheme using cellular automata in order to introduce lateral communication, memory and a stochastic representation of the statistical effects of cumulus convection is implemented in two numerical weather models. The behaviour of the scheme is studied in cases of organized convective squall-lines, and initial model runs show promising improvements. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Submitted. </p>

In this work I describe various approaches to electrochemical energy storage at the grid-scale. Chapter 1 provides an introduction to energy storage and an overview of the history and development of flow batteries. Chapter 2 describes work on the hydrogen-chlorine regenerative fuel cell, detailing its development and the record-breaking performance of the device. Chapter 3 dives into catalyst materials for such a fuel cell, focusing on ruthenium oxide based alloys to be used as chlorine redox catalysts. Chapter 4 introduces and details the development of a performance model for a hydrogen-bromine cell. Chapter 5 delves into the more recent work I have done, switching to applications of quinone chemistries in flow batteries. It focuses on the pairing of one particular quinone (2,7-anthraquinone disulfonic acid) with bromine, and highlights the promising performance characteristics of a device based on this type of chemistry. / Engineering and Applied Sciences

Interest in developing a detailed understanding of jet plume aerodynamics has increased significantly in recent years, for both civil (noise reduction) and military (Infra-Red signature modelling) aerospace applications. Such flows are critically dependent on turbulence modelling of the jet plume shear layer mixing. Reynolds averaged Navier Stokes (RANS) CFD tends to overpredict while Large Eddy Simulation (LES) CFD underpredicts potential core length. Difficulties in LES begin with the challenge of providing accurate resolution of thin turbulent boundary layers at nozzle exit. Providing physically meaningful 3D unsteady LES inlet conditions is a challenge in nozzle flows since turbulence at nozzle inlet experiences relaminarisation, which determines the boundary layer state at nozzle exit. The present thesis addresses these challenges by developing and validating against benchmark measurements an LES approach for nozzle/plume flows based on an advanced inlet condition treatment and an improved level of Sub-Grid-Scale (SGS) modelling. A technique for synthetic inlet condition generation based on a rescaling/recycling method (R2M) for LES predictions of nozzle flows has been applied and validated in the present work. Results reveal the benefits of this method such that self-consistent, correlated turbulent structures were sustained throughout the high acceleration region associated with nozzle convergence, with the turbulence anisotropy developing in the expected manner. The LES results for velocity profile shape at nozzle exit are better than low Re RANS predictions. Use of the Smagorinsky SGS closure produced level of turbulence energy at nozzle exit significantly lesser than measured. A recently proposed SGS model by Piomelli and Guerts (PGSGS) that defines the SGS length scale based on local turbulence quantities using a mesh independent formulation was also applied to the nozzle flow test case with significant improvement in the turbulence energy development through the nozzle. The LES method is applied to a supersonic jet discharging from a rectangular convergentdivergent nozzle. Results show that the R2M technique was able to generate realistic turbulence conditions at nozzle inlet that were consistent with available measured data. Using a carefully designed mesh and the advanced PGSGS model, turbulent structures were sustained through the nozzle, enabling good prediction of the nozzle exit boundary layer state and near field development. The improved capture of shear layer turbulence enabled better predictions of shear layer growth, leading to improved capture of shock cell behaviour and potential core length.

Motivated by the role of decarbonizing the electric power sector to mitigate climate change, I assess the economic and environmental merits of three key technologies for decarbonizing the electric power sector across four chapters in this thesis. These chapters explore how adding flexibility to power plants equipped with carbon capture and sequestration (CCS) affects system costs and carbon dioxide (CO2) emissions, how grid-scale electricity storage affects system CO2 emissions as a power system decarbonizes, and how distributed solar photovoltaic (distributed PV) electricity generation suppresses wholesale electricity prices. In each chapter, I address these questions through a combination of power system optimization, statistics, and techno-economic analysis, and tie my findings to policy implications. In Chapter 2, I compare the cost-effectiveness of “flexible” CCS retrofits to other compliance strategies with the U.S. Clean Power Plan (CPP) and a hypothetical stronger CPP. Relative to “normal” CCS, “flexible” CCS retrofits include solvent storage that allows the generator to temporarily eliminate the CCS parasitic load and increase the generator’s net efficiency, capacity, and ramp rate. Using a unit commitment and economic dispatch (UCED) model, I find that flexible CCS achieves more cost-effective emissions reductions than normal CCS under the CPP and stronger CPP, but that flexible CCS is less cost-effective than other compliance strategies under both reduction targets. In Chapter 3, I conduct a detailed comparison of how flexible versus normal CCS retrofits affect total system costs and CO2 emissions under a moderate and strong CO2 emission limit. Given that a key benefit of flexible CCS relative to normal CCS is increased reserve provision, I break total system costs into generation, reserve, and CCS capital costs. Using a UCED model, I find that flexible CCS retrofits reduce total system costs relative to normal CCS retrofits under both emission limits. Furthermore, 40-80% of these cost reductions come from reserve cost reductions. Accounting for costs and CO2 emissions, though, flexible CCS poses a trade-off to policymakers under the moderate emission limit, as flexible CCS increases system CO2 emissions relative to normal CCS. No such trade-off exists under the stronger emission limit, as flexible CCS reduces system CO2 emissions and costs relative to normal CCS. In Chapter 4, I quantify how storage affects operational CO2 emissions as a power system decarbonizes under a moderate and strong CO2 emission limit through 2045. In so doing, I aim to better understand how storage transitions from increasing CO2 emissions in historic U.S. systems to enabling deeply decarbonized systems. Additionally, under each target I compare how storage affects CO2 emissions when participating in only energy, only reserve, and energy and reserve markets. Using a capacity expansion (CE) model to forecast fleet changes through 2045 and a UCED model to quantify how storage affects system CO2 emissions, I find that storage quickly transitions from increasing to decreasing CO2 emissions under the moderate and strong emission limits. Whether storage provides only energy, only reserves, or energy and reserves drives large differences in the magnitude, but not the direction, of the effect of storage on CO2 emissions. In Chapter 5, I quantify a benefit of distributed photovoltaic (PV) generation often overlooked by value of solar studies, namely the market price response. By displacing high-cost marginal generators, distributed PV generation reduces wholesale electricity prices, which in turn reduces utilities’ energy procurement costs. Using 2013 through 2015 data from California including a database of all distributed PV systems in the three California investor owned utilities, we estimate historic hourly distributed PV generation in California, then link that generation to reduced wholesale electricity prices via linear regression. From 2013 through 2015, we find that distributed PV suppressed historic median hourly LMPs by up to $2.7-3.1/MWh, yielding avoided costs of up to $650-730 million. These avoided costs are smaller than but on the order of other avoided costs commonly included in value of solar studies, so merit inclusion in future studies to properly value distributed PV.

To combat climate change, governments have pledged to become more dependent on renewable electricity production. However, the intermittency of renewable power generation requires modern grid-scale energy storage systems, which are currently being explored with lithium-ion batteries (LIBs). However, this technology faces significant safety, social, and financial concerns. As an alternative chemistry, aqueous zinc-ion batteries (ZIBs) show much promise for grid-scale energy storage with their safe, inexpensive design. Major bottlenecks of ZIB performance include their limited practical specific capacity, and low capacity retention. Organic cathodes, specifically the use of redox-active quinone molecules, are an upcoming contender for customizable and simple ZIB cathode design that can be optimized for good performance. However, these cathodes are often plagued by capacity fade caused by quinone dissolution and inactivation. Grafting these quinone molecules to the supporting conductive carbon substrate via covalent bonding had been previously explored in LIB and supercapacitor electrode design as an effective way to mitigate capacity fade. In this work, the development of aqueous ZIB cathodes with 9,10-phenanthrenequinone (PQ) molecules grafted to carbon black substrates was done via a facile in-situ generated diazonium salt reaction synthesis technique. Electrochemical and material analysis confirmed the presence of covalent grafting. This grafting modification was compared to the standard cathode design of adsorbing the quinones on carbon substrates like Ketjenblack (KB) and Vulcan Black (VB). Battery cycling tests were performed and the grafted PQ-KB cells achieved a discharge capacity of 99 mAh g-1 after 1000 charge-discharge cycles with accelerated testing at a charge/discharge rate of 200 mA g-1 and 10 mA g-1. These cells maintained 67% of their initial capacity compared to the 55% for the adsorbed PQ on KB cells. This approach highlights the promise of grafting organic material as a technique to support organic cathodes for next-generation ZIB design. / Thesis / Master of Applied Science (MASc) / Renewable electricity production is necessary to mitigate climate change but the production of electricity through many renewables like wind and solar can vary significantly on any given day. Lithium-ion batteries are being explored for storing electricity for use on the grid, but they have many downsides including being flammable and expensive. Zinc-ion batteries are non-flammable and cost-effective alternatives to lithium-ion batteries. They are currently not as widely used as lithium-ion batteries because of their poorer performance. However, for storing electricity for power grids, with the correct selection of materials to make the battery, zinc-ion batteries can perform well enough to compete with lithium-ion batteries. This work investigates a modification of a material used in zinc-ion batteries, that allows the battery to maintain a higher capacity after many charge and discharge cycles.

Les simulations en mécanique du solide présentent des difficultés comme le traitement de l'incompressibilité ou les non-linéarités dues aux grandes déformations, aux lois de comportement et de contact. L'objectif principal de ce travail est de proposer des méthodes éléments finis capables de gérer l'incompressibilité en grandes déformations en utilisant des éléments de faible ordre. Parmi les approches de la littérature, les formulations mixtes offrent un cadre théorique intéressant. Dans ce travail, une formulation mixte à trois champs (déplacements, pression, gonflement) est introduite. Dans certains cas, cette formulation peut être condensée en formulation à deux champs. Cependant, il est connu que le problème discret obtenu par une approche éléments finis de type Galerkin n'hérite pas automatiquement de la condition de stabilité “inf-sup” du problème continu : les éléments finis utilisés, et notamment les ordres d'interpolation doivent être choisis de sorte à vérifier cette condition de stabilité. Cependant, il est possible de s'affranchir de cette contrainte en ajoutant des termes de stabilisation à la formulation EF Galerkin. Cette approche permet entre autres d'utiliser des ordres d'interpolation égaux. Dans ce travail, des éléments finis stables de type P2/P1 sont utilisés comme référence, et comparés à une formulation P1/P1, stabilisée soit avec une fonction bulle, soit avec une méthode VMS (Variational Multi-Scale) basée sur un espace sous-grille orthogonal à l'espace EF. Combinées à un modèle grandes déformations basé sur des déformations logarithmiques, ces approches sont d'abord validées sur des cas académiques puis sur des cas industriels. / Simulations in solid mechanics exhibit difficulties as dealing with incompressibility or nonlinearities due to finite strains, constitutive laws and contact. The basic motivation of our work is to propose efficient finite element methods capable of dealing with incompressibility in finite strain context, and using low order elements. Among the approaches in the literature, mixed formulations offer an interesting theoretical framework. In this work, a three-field mixed formulation (displacement, pressure, volumetric strain) is investigated. In some cases, this formulation can be condensed in a two-field formulation. However, it is well-known that the discrete problem given by the Galerkin finite element technique, does not inherit the “inf-sup” stability condition from the continuous problem: the finite elements used, and in particular the interpolation orders must be chosen so as to satisfy this stability condition. However, it is possible to circumvent it, by adding terms stabilizing the FE Galerkin formulation. The latter approach allows the use of equal order interpolation. In this work, stable finite elements of type P2/P1 are used as reference, and compared to a P1/P1 formulation, stabilized with a bubble function, or with a VMS method (Variational Multi-Scale) based on a sub-grid-space orthogonal to the FE space. Combined to a finite strain model based on logarithmic strain, these approaches are first validated on academic cases and then on industrial cases.

This thesis addresses a series of questions related to the problem of achieving reliable and physically consistent representations of aerosol-cloud interaction in global circulation models (GCM). In-situ data and modeling tools are used to develop and evaluate novel parameterization schemes for the process of aerosol activation for applications in GCM simulations. Atmospheric models of different complexity were utilized, ranging from detailed Lagrangian parcel model simulations of the condensational growth of droplets, to one-dimensional single column model with aerosol and cloud microphysics, and finally GCM simulations performed with the Community Atmosphere Model (CAM). A scheme for mapping the sub-grid scale variability of cloud droplet number concentrations (CDNC) to a number of microphysical process rates in a GCM was tested, finding that neglecting this impact can have substantial influences in the integrated cloud properties. A comprehensive comparison and evaluation of two widely used, physically-based activation parameterizations was performed in the framework of CAM5.1. This was achieved by utilizing a numerical adjoint sensitivity approach to comprehensively investigate their response under the wide range of aerosol and dynamical conditions encountered in GCM simulations. As a result of this, the specific variables responsible for the observed differences in the physical response across parameterizations are encountered, leading to further parameterization improvement.

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In dieser Arbeit stelle ich ein neu entwickeltes, dynamisches Modell für das turbulente sternbildende interstellare Medium auf Skalen von einigen zehn Parsecs vor, welches den Namen MIST (Multi-phase Interstellar medium model with Star formation and Turbulence) trägt. Das Verhalten von MIST wurde mittels seiner Ein-Zonen-Gleichgewichtslösungen aber auch im Rahmen von Large Eddy Simulationen untersucht, wobei verschiedenste Beobachtungsresultate gleichzeitig reproduziert werden konnten.