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Application of CFD zooming for preliminary design of a low emissions combustor.
No full textThe design of low emissions combustors is particularly challenging as there is a requirement to deliver designs that meet a large number of performance, emissions and operability (often conflicting) objectives. There is an increasing need for combustor preliminary design and performance tools which can be used in the early phases of the design process for rapid design space exploration thereby reducing the risk and cost in the long term.
Although both reduced order models and higher fidelity tools have been widely used for preliminary design independently, significant benefit can be derived from using a multi-fidelity modelling approach to address the limitation of reduced order model (accuracy) and high fidelity CFD (time and cost). To the author’s best knowledge there is no information in the public domain related to the coupling of reduced order models with higher fidelity 3D CFD multi-fidelity modelling tools for low emissions gas turbine combustion systems. Such a tool has a potential to offer a good compromise between modelling accuracy and computational expense.
In this PhD research, a novel multi-fidelity zooming combustor preliminary design method is proposed. The method uses design outcomes of an existing reduced order model based design tool to construct CFD models for a series of RANS simulations.
A case study for the design of a Lean Direct Injection Partially Premixed combustor was conducted to identify the limitations of an existing reduced order modelling approach. Dedicated CFD simulations were performed to demonstrate that improved methods/models/correlations can be derived from these higher fidelity simulations to refine the existing reduced order model. The main research contributions are summarised below:
External aerodynamics
– Performance is sensitive to inlet velocity profiles, the effect of which cannot be reflected in ROMs, realistic compressor outlet profiles is needed instead of generic turbulent pipe flow profiles.
– Performance maps were generated from CFD which include more degrees of freedom and suggest a different ‘optimum locus’ than 1D correlations.
Fuel injector initial conditions
– The Sauter Mean Diameter calculated from correlations in the ROM is not suitable to be used as injection initial condition. Detailed correlations on jet breakup were used to generate representative droplet size and velocity for different nozzle designs and conditions.
– Swirler flow split correlations does not account for flow turning in the venturi and the pre-mixer, coarse mesh CFD was sufficient to generate more accurate flow splits among different stages.
Reacting flow
– The initial 10 fuel nozzle ports design from the ROM was not sufficient for good mixing quality at the main stage, which resulted in higher flame temperature. The number was increased to 16, which provides more uniform flame distribution at the circumferential direction.
– Three of the four methods used to generate the time delay provides consistent results. The time delay was used as an input of the ROM thermoacoustic analysis model.
– The reactor layout can be better customised for emissions prediction with extra zones within the pilot injector and the dilution zone to account for reaction and recirculation.
– Combustor cooling design was refined without modifying the variables of ROM, in which circumferential distribution was not captured. Simplified re-fining method was developed at less computational expense compared to complete Conjugate Heat Transfer simulations with the radiation model.
Based on these findings, the reduced order design tool could be refined once the data from all parametric study cases are extracted and incorporated in the model, which is recommended as the future development of the work. The CFD model constructed could also be used to initiate higher fidelity Large Eddy Simulation.PhD in Aerospac
How institutional entrepreneurs theorize change and change theorization.
No full textThis thesis explores how over time institutional entrepreneurs (IEs) theorize change in
mature fields. Based on the case of a social enterprise that seeks to secure support for its
innovative solution and introduce change across multiple actors in a mature field of
global health, this study highlights how IEs theorize change and change their
theorization throughout the institutional change project. Furthermore, drawing on the
process ontology, I elaborate on the process of theorization by showing how field actors
contest change and solution, prompting organization members to become more deeply
embedded in the institutional environment and change their theorization. This
counterintuitive observation adds a new perspective to the paradox of embedded agency
and contributes to understanding how theorization and institutionalization processes
unfold recursively. Finally, the insights from this study challenge the assumptions of
IEs as heroic figures by illustrating how the cognitive frames and solutions of
organization members change as they make sense of the institutional arrangements,
interests, and issues of different field actors.PhD in Leadership and Managemen
Battery temperature prediction using a hybrid machine learning and system identification technique
No full textAuger, Daniel J. - Associate SupervisorBattery thermal management is crucial for electric vehicle technology.
Maintaining the battery within a specific temperature range ensures safety and
efficiency. Excessive heat can damage the battery and reduce its lifespan, while
too low temperatures can also impair performance. Battery thermal
management systems are responsible for maintaining the optimal temperature
range for batteries. BTMSs work in conjunction with battery management
systems to ensure that the battery's temperature is carefully monitored and
controlled. BTMSs use a combination of active and passive methods to regulate
the battery temperature, including cooling and heating systems, thermal
insulation, and thermal energy recovery.
Currently, the main function of Battery Thermal Management Systems is to
monitor the battery temperature in real-time. What they lack is the ability to
predict future temperatures. Introducing a temperature predictive system, which
utilises input parameters like current battery temperature, ambient temperature,
state of charge, and internal resistance and capacity, can enhance
performance. The accuracy of the prediction model determines how well the
system maintains the battery within the optimal temperature range.
Machine learning is valuable for prediction applications due to its ability to
analyse vast data sets, uncover intricate patterns, and establish correlations.
However, it necessitates extensive data for training, encompassing diverse
environmental conditions and usage scenarios. To address the challenges of
accurately predicting battery temperature, this study proposes a new hybrid
system, including an ML-based battery temperature prediction model along with
an online battery parameter identification unit. The online battery parameter
identification unit updates the battery's electrical parameters, which are used to
calculate the battery's heat generation rate in real-time. That unit provides
continuous updates to the prediction model, allowing it to dynamically adjust the
battery's electrical and thermal parameters in response to any changes in the
battery (i.e. changes in SoC, temperature and battery age). The system's ability
to provide up-to-date information on the battery's state enhances the accuracy
of the prediction model. The prediction model consists of an Adaptive Neuro-
Fuzzy Inference System to analyse the battery's thermal behaviour based on
various input parameters. The input parameters include the battery's current
temperature, the ambient temperature, the battery's internal parameters and a
short history of charge/discharge. The prediction model then uses that input
data to predict the battery's future temperature in real-time. By incorporating the
data from the battery online identification system, the prediction model can
accurately adjust the thermal and electrical parameters of the battery, ensuring
the accuracy of the temperature prediction.
Experimental tests were conducted on mass-produced Samsung cylindrical
cells for results validation, simulating real-world usage across a wide range of
ambient temperatures (-10 °C to 40°C) and long-term ageing tests using the
WLTP driving cycles. This generated a valuable dataset for thermal analysis.
The proposed system accurately predicts cell temperature under various
conditions, demonstrating robust performance against changes in state of
charge, state of health, and ambient temperature. The model is designed for
real-time industrial applications with minimised complexity.PhD in Transport System
Optimization of surface area loading rate in moving bed biofilm reactor systems for wastewater treatment
No full textStephenson, Tom - Associate Supervisor
Lyu, Tao - Associate SupervisorThis thesis reviews Moving Bed Biofilm Reactor (MBBR) systems for wastewater
treatment, focusing on Chemical Oxygen Demand (COD) and ammonia nitrogen
(NH4-N) surface area removal rates. The study uses Partial Least Squares (PLS)
Regression, and Fitted Regression, to identify key operational parameters and their
impacts on system performance. It was found that Surface Area Loading Rate
(SALR), and Organic Loading Rate (OLR) are significant predictors for COD and
NH4-N removal rates. Specifically, optimizing NH4-N SALR, alongside, OLR, specific
surface area (SSA) and hydraulic retention time (HRT), was shown to significantly
enhances biofilm nitrification activity. Findings from this study highlighted media
selection as a critical factor, with effective surface area proving essential for
promoting removal activity and preventing pore clogging. Evaluations of different
media characteristics demonstrated how media choice can impact overall system
performance. Maintaining an optimal OLR proved crucial for maximizing COD and
NH4-N removal rates in MBBRs. This study determined optimal conditions for
achieving high COD and NH4-N surface area removal rates: for COD removal, an
effective SALR of 19.96 g COD/m2.d, a COD concentration of 1.60 kg COD/m3, an
SSA of 500 m2/m3, a media fill ratio (MFR) of 30%, and a 10-hour HRT were ideal.
Optimal NH4-N removal was achieved with a SALR of 1.38 gNH4-N/m2.d, NH4-N
concentration of 0.10 kgNH4-N/m3, an SSA of 500 m2/m3, an MFR of 45%, and a 10-
hour HRT. For simultaneous COD and NH4-N removal, optimal conditions included
an NH4-N SALR 1.60 gNH4-N/m2.d, an OLR of 3.2 kg COD/m3.d, NH4-N
concentration of 0.1 kg NH4-N/m3, MFR of 50%, SSA of 500 m2/m3, and HRT of
10 hours. The work demonstrates that balancing operational parameters to prevent
issues like clogging and substrate overloading is essential for maximizing organic
removal and NH4-N transformation. The findings provide a framework for optimizing
MBBR systems, making them more adaptable and efficient for diverse wastewater
treatment applications. Future research should focus on developing innovative
materials, technologies, and strategies to further optimize MBBR performance,
thereby advancing sustainable wastewater management practices.MSc by Research in Wate
Shaft failure and overspeed modelling: systems integration and overall engine response
No full textThe consequences of a shaft failure can be severe if not controlled or contained, potentially
leading to an uncontained engine failure. Engine certification requirements dictate
that an engine must be capable of handling a shaft failure event, with no hazardous
release of debris. Demonstrating that an engine will have no hazardous consequences requires
either a full-scale engine test or a comprehensive set of simulations. Engine tests
of this scale are prohibitively expensive; therefore manufacturers rely upon validated
engine models to provide predictions.
Following a shaft failure, the turbine is free to accelerate since it is free from load.
The specific bearing arrangement dictates whether the turbine is constrained axially.
Should the turbine be free to move axially, i.e. unlocated, then additional complexity is
introduced through interactions between rotating and static components. The objective
of this research is to develop a tool that is capable of modelling a shaft failure event, in
particular a high pressure shaft failure, with the ability to capture the inter-connected
relationship between engine systems. Such a tool can be applied early on in a design
program, which is also applicable to intact engine post-stall predictions.
The developed Whole Engine Simulation Tool, WEST, features a one-dimensional poststall
model of the compression system, a quasi-steady turbine solver, a transient onedimensional
secondary air system model, a friction model and a comprehensive combustion
model suite. The compression system features a fully-upwind Roe solver (TRSS),
modified to incorporate variable composition gas, source terms and an entropy fix.
WEST was validated against steady-state flight envelope data, an intact low power
fuel spike and compressor rig surge data. WEST was applied to a high pressure shaft
failure case study, which demonstrated its ability to capture the multidisciplinary nature
of shaft failure scenarios. A part of this study was the complete derivation of a set of
turbine overspeed characteristics; since the conditions experienced by a turbine during
a shaft failure modify its ability to extract power from the incoming flow.PhD in Aerospac
Navigating non-family CEO succession in family businesses.
No full textReinmoeller, Patrick - Associate SupervisorSuccession in family businesses poses unique challenges due to the overlap of
ownership and leadership roles. The complexity of such challenges is heightened
when considering a non-family member as a successor for leading the business.
This thesis explores why family businesses hire non-family CEOs. The
investigation unfolds across three papers, a systematic literature review and two
empirical papers, each contributing to a comprehensive understanding of non-
family leadership succession. The literature review paper presents that existing
research primarily examines the outcomes of leadership successions and largely
ignores the decisions behind these. The paper lays the foundation with a
conceptual framework derived from a systematic review of 53 articles, which
reveals a knowledge gap on non-family CEO succession decisions through a
non-family CEO succession framework. This framework guides the subsequent
empirical inquiry. The two empirical papers address this gap by adopting an
interpretivist approach. The second and third papers draw on qualitative data
from 29 interviews with UK-based family business owners. The second paper
provides an in-depth examination of the factors influencing the non-family CEO
succession decision and presents that it is not one but two decisions: (1) a
decision to consider non-family candidates and (2) a decision to select a non-
family CEO amongst the candidate pool. The third paper identifies and focuses
on the influences of four distinct roles family owners play in making the decision
to consider non-family CEO candidates for the CEO position. The conceptual and
empirically grounded models developed in this thesis open the black box of non-
family CEO succession and allow family businesses to explore non-family CEO
succession opportunities.PhD in Leadership and Managemen
Navigating multiple paradoxes - insights from family business leaders
No full textReinmoeller, Patrick - Associate SupervisorManaging conflicting objectives, for example, balancing short-term success with long-term survival, is challenging. Paradox literature suggests that conflicts regarding learning, performing, belonging, organising and control (Smith & Lewis, 2011) are persistent, containing coexisting, contradictory, and interdependent elements.
Owners of family firms often pursue multiple goals, such as continuing a legacy, maintaining control and ensuring continued economic success. As a result, family firms are prone to paradoxes and provide an ideal context for paradox research.
An examination of 3,370 articles revealed a research focus on isolated paradoxes, for example balancing management control and employee empowerment (Lewis et al., 2019), while only few studies explore a relationship between specific paradoxes (Jarzabkowski et al., 2013). However, while the work which acknowledges the interrelated nature of paradoxes argues that paradoxes influence each other, the paradoxes are still discussed as separate entities.
This study investigates, therefore, if present paradoxes are influencing each other or if the paradoxes are interconnected intimately. This is done through a thematic analysis of interviews with 40 family business CEOs and owner-CEOs from a variety of industries.
This research makes three key contributions. Firstly, it demonstrates the existence of a network of network of interconnected paradoxes, expanding paradox theory by showing that paradoxes are not isolated phenomena but instead form networks, which pose challenges to management.
Secondly, the study introduces the Holistic Paradox Management (HPM) framework, which comprises four strategic focuses: Evolution, Alignment, Integration, and Stewardship. This framework provides a structured approach to navigating and understanding the networks of paradoxes within organisations.
Thirdly, by focusing on the experiences of individual managers and employees, this study explains how personal values, identities, and cognitive biases influence both the formation of networks of paradoxes and their management.PhD in Leadership and Managemen
Dry batch and semi-continuous digestion: optimising the science behind it
No full textWagland, Stuart T. - Associate SupervisorDry anaerobic digestion (AD) is usually linked to inhibitors accumulation, however
existing knowledge from wet AD cannot be directly translated to palliate this issue
due to the high total solids content (TS) and the reduced mixing limiting diffusion
and free water where reactions take place. This thesis investigated the main
inhibitory pathways in dry AD and the effect of operational parameters on them.
In batch processes the adjustment of the inoculum to substrate ratio (I:S)
demonstrated an effect on reducing acidification at the beginning of the process.
Furthermore, percolate recirculation showed the best impact to improve contact
between microorganisms and substrate and buffer the digester, avoiding pH
reduction and producing an 8-fold increase in total methane production compared
to water addition at similar conditions. Optimisation of percolate recirculation was
also key in maximising production of methane in the full-scale batch dry AD plant
studied, with drops of production if recirculation was over the optimum range due
to collapse of the biomass pile and inhibitors accumulation. Semi-continuous dry
AD of organic fraction of municipal solid waste (OFMSW) resulted in high
ammonia accumulation, followed by accumulation of propionic acid producing
reactor failure. Different dosing strategies were tested when digesting OFMSW.
Dose of trace elements (TE) was done to improve synthesis of enzymes needed
in hydrogenotrophic methanogenesis, activated carbon (AC) was added to
increase electron transfer between hydrogenotrophic archaea and syntrophic
bacteria, while MgCl2 aimed to maintain intracellular osmotic pressure and
reduce free ammonia (FA) inhibition. TE dosing increased methane production
but did not avoid the accumulation of propionic acid. These results were contrary
to available literature in AD at TS lower than 20 %, probably due to the reduced
diffusion observed at 40 % TS. Addition of AC and an osmoprotectant like MgCl2
were also unable to reduce propionic accumulation, but methane production
improved by 28 % compared to the TE additions. Additionally, short retention
times where insufficient for syntrophic acetate oxidation bacteria (SAOB) due to
inhibition, producing its wash followed by the reduction of strict hydrogenotrophic
archaea. This allowed versatile Methanosarcina to become dominant and change
methane production to acetoclastic even at high FA over 1 g/l.STREAM Eng
Unveiling the mechanisms of the UV/chlorine process for water treatment
No full textJarvis, Peter - Associate SupervisorPesticides in drinking water pose public health risks and challenges for water utilities. Advanced oxidation processes (AOPs), such as UV/H2O2, are increasingly used for pesticide degradation. UV/chlorine has emerged as an
alternative because of its lower chemical requirements and compatibility with UV-LEDs. However, the complex photochemistry of UV/chlorine and its impact on radical generation and downstream water quality need to be elucidated.
This research compared UV/H2O2 and UV/chlorine for the removal of five pesticides commonly detected in the East of England drinking water sources (metazachlor, propyzamide, quinmerac, flufenacet and clopyralid), evaluated their impact on disinfection by-product (DBP) formation, and determined the effectiveness of activated carbon (AC) post-treatment. For pesticide degradation, the UV/chlorine process was evaluated at three irradiation wavelengths (254, 275 and 295 nm) and two pH conditions (6 and 9), reflecting various chlorine absorbance and speciation conditions. Four methods were assessed to measure UV irradiance in the 275 and 295 nm UV-LED reactors, which differed from the conventional 254 nm collimated beam in geometry and emission wavelength. Ferrioxalate actinometry was identified as the most accurate method.
UV/H2O2 achieved higher pesticide degradation rates than UV/chlorine using optimised doses of 20 mg/L H2O2 and 4 mg/L chlorine. UV/chlorine was impacted by both pH and wavelength of irradiation, with optimal degradation rates at pH 6 and 254 nm due to higher radical generation. At pH 6, 254 nm was more effective than 275 and 295 nm, while at pH 9 the wavelengths were comparable except for metazachlor and flufenacet, which underwent photolysis at 254 nm. Second-order rate constants for the reactions of hydroxyl radicals (HO•) and radical chlorine species (RCS) with the pesticides are presented, with some reported for the first time.
DBP formation potential tests, using tannic acid (TA) as a model natural organic matter compound, showed similar increases in chloroform (CF) yield (25%) following both AOPs. Haloacetic acid (HAA) yield increased following UV/chlorine at 200 mJ/cm2, then remained constant at higher UV doses, while following UV/H2O2 it decreased then increased at higher UV doses. Non-target analysis of transformation products (TPs) identified smaller, more chlorinated compounds formed during UV/chlorine than UV/H2O2. Correlations between TPs and regulated DBPs identified TA, digallic acid and gallic acid as precursors for HAA and CF. Pathways leading to formation of regulated and unregulated DBPs were proposed. The TPs formed had increased oxidation states relative to TA and were more hydrophilic. These were still removed by AC when applied as a post-treatment, leading to comparable dissolved organic carbon reductions between the AOPs and subsequent decreases in CF and HAA yields by 79-96% and 89-99%, respectively.
These findings improve the mechanistic understanding of AOPs and inform strategies to optimise pollutant removal while managing DBP risks in drinking water.PhD in Wate
Dataset: Effect of deposit chemistry on the stress corrosion cracking susceptibility of CMSX-10 at 550°C and 700°C
No full textSEM images, optical images and an excel file containing crack depth measurements.Turbine blades of aero gas turbines can be at risk of stress corrosion cracking (SCC) below 700°C due to the effects of stress, sulphur-containing gases and deposits that are ingested into the turbine.
Therefore, understanding the effect of different deposits on the SCC susceptibility of single crystal nickel-based superalloys at different temperatures is crucial. This study has investigated the effect of
NaCl, sea salt and 80/20 mole% Na2SO4/K2SO4 on the SCC susceptibility of CMSX-10 at 550°C and 700°C. The results suggest that chlorine containing salts play an important role in accelerating stress
corrosion cracking at 550°C, where the formation of HCl leads to the breaking down of the oxide and exposing the base alloy to a sulphidation environment. At 700°C stress corrosion cracking is
accelerated by the mix of sulphates that lead to reduced melting points, where the 80/20 mol% Na2SO4/K2SO4 has shown the highest susceptibility to SCC.Rolls Royc