Biocontrol of ochratoxigenic fungi by endogenous lactic acid bacteria and yeasts from ivorian robusta coffee in the context of climate change

Verheecke-Vaessen, Carol - Associate Supervisor Fontana, Angelique - Associate Supervisor Strub, Caroline - Associate SupervisorThis doctoral research delves into the innovative domain of biocontrol strategies targeting mycotoxigenic fungi in the context of climate change. Focusing on Ivorian coffee, a vital economic and agricultural commodity, the study explores the potential of indigenous lactic acid bacteria (LAB) and yeasts as biocontrol agents. Mycotoxins, toxic secondary metabolites produced by fungi, pose significant health risks and economic losses. As climate change amplifies the proliferation of mycotoxigenic fungi, the demand for sustainable and eco-friendly interventions intensifies. The research encompasses comprehensive isolation, identification, and characterization of LAB and yeasts from Ivorian coffee, evaluating their antagonistic properties against mycotoxigenic fungi. Furthermore, the study elucidates the mechanisms underlying the biocontrol activity, shedding light on how these microorganisms mitigate mycotoxin contamination. This research is pivotal in the pursuit of climate-resilient strategies for mycotoxin management, contributing to both food safety and agricultural sustainability.PhD in Environment and Agrifoo

AI-driven 5G networks for autonomous positioning system platform

Unmanned Aerial Vehicles (UAVs) are becoming essential for various urban applications, such as surveillance, delivery, logistics, disaster management, and traffic monitoring. However, their positioning performance in urban environments can be limited due to challenges such as non-line-of-sight (NLOS) propagation, multipath interference, and signal blockage caused by tall buildings, trees, and other obstacles. These factors lead to reduced positioning accuracy and unreliable communication. To address these issues, this thesis introduces three key and novel contributions. First, it presents one of the first real-world evaluations of the 5G network performance for UAV operations at altitudes between 50 and 110 meters, using XCAL-based field trials. This provides new insights into the altitude-dependent Quality of Service (QoS) parameters such as latency, throughput, and handover (HO) efficiency and provides practical recommendations for UAV-specific connectivity protocols. Second, a novel hybrid positioning framework is proposed that integrates the observed time difference of arrival (OTDOA) of the new 5G radio (NR) with the fusion of sensor and barometric pressure sensor through an Extended Kalman Filter (EK). This combination significantly improves positioning accuracy (2.8–7 m) in GNSS GNSS-challenged urban environment, which has not been demonstrated in prior UAV studies. Third, the thesis introduces a lightweight feedforward neural network (FNN) for mitigating NLOS errors in 5G-based UAV positioning. Trained on simulated MATLAB data, the model corrects time-of-arrival (TOA) measurements in real time, reducing positioning error to 1.3 m in LOS and 1.7 m in NLOS, outperforming conventional methods. Unlike existing solutions, this model is designed for real-time deployment on UAV platforms with limited resources. Overall, this research strengthens UAV navigation and connectivity in urban airspace by combining 5G advancements, sensor fusion, and AI-powered error correction. The novelty lies in the integration of real-world 5G performance analysis, a hybrid OTDOA sensor fusion framework, and an AI-based NLOS correction model into a unified solution for reliable, accurate, and scalable Urban Air Mobility (UAM), opening the door to future improvements in AI-driven 5G networks for autonomous system platforms.PhD in Aerospac

Top management involvement in key account management: a contingency model

Prior, Daniel - Associate SupervisorKey Account Management (KAM) plays a strategic role in driving long-term customer value, yet its implementation remains challenging. While prior research recognises the importance of Top Management Involvement (TMI) in KAM, limited attention has been paid to what drives such involvement, how it manifests in practice, and how it is shaped by contextual contingencies. This study addresses these gaps through an abductive, multi-case research design involving seven organisations. It identifies 19 drivers of TMI, categorised along proactive–reactive and strategic–operational–individual dimensions. TMI is found to manifest across three behavioural domains: displayed commitment, decision- making approach, and interaction style. Importantly, the study demonstrates that structural, environmental, cognitive, and operational contingency factors moderate the relationship between TMI drivers and executive behaviours. These findings make theoretical contributions by refining and extending the conceptualisation of TMI, increasing our understanding of how personal traits influence TMI, illustrating its dynamic nature, and challenging the assumption that TMI is inherently beneficial to KAM performance. The study also offers practical insights for aligning executive involvement with KAM demands. It presents a set of ten role templates for executive involvement in KAM and concludes with limitations and suggestions for future research.PhD in Leadership and Managemen

Evaluation of the impact of coagulant choice on phosphorus removal from municipal wastewater

Jefferson, Bruce - Associate SupervisorPhosphorus removal is a critical objective in municipal wastewater treatment due to its role in eutrophication and the tightening of regulatory discharge limits. Chemical coagulation remains the most widely adopted method for phosphorus control; however, its effectiveness is influenced by coagulant type, pH conditions, dosing location, and wastewater matrix composition. This thesis aimed to advance the understanding of how these operational and chemical variables govern the mechanisms of phosphorus removal, with the goal of optimising coagulant selection and application strategies under real-world conditions. A comprehensive screening of 17 coagulants, including ferric, aluminium, rare earth, zinc, and calcium-based formulations, was conducted under both uncontrolled and pH-adjusted conditions. Ferric sulphate, polyaluminium chloride (PACL), and aluminium sulphate emerged as the most effective agents, achieving residual total phosphorus concentrations as low as 0.35 mg/L, 0.15 mg/L and 0.6 mg/L, respectively, under controlled pH conditions, particularly under neutral pH, where stable hydroxide flocs are favoured. Rare earth coagulants demonstrated high phosphate affinity but formed fragile flocs, limiting their practical application. Floc characterisation revealed that compact, shear-resistant aggregates correlated strongly with higher removal efficiency. To investigate the role of pH, a detailed comparative analysis of ferric sulphate (FS), aluminium sulphate (ALS), and PACL was performed across a pH range of 4-8. The results confirmed that coagulant solubility, hydrolysis potential, and metal speciation significantly impact phosphorus removal efficiency. FS and ALS were better than PACL under acidic conditions due to more complete hydrolysis and formation of stable flocs. Phosphorus fractionation and turbidity data supported these trends, identifying pH 6-7 as the optimal window for coagulant performance and floc settleability. The final phase of the study examined how dosing location in the crude influent, after primary settling tanks (PST), and in the final effluent (FE) influences coagulant performance. FS showed enhanced phosphorus removal even in high-strength crude wastewater, though required careful pH control to avoid over-acidification. ALS and PACL were more effective at PST and FE, where organic loading and particulate interference were lower. A two-point dosing strategy applied to crude wastewater was found to enhance phosphorus removal while reducing total coagulant demand, offering a practical route for chemical cost optimisation. Collectively, this thesis delivers critical insights into the physicochemical and operational factors driving chemical phosphorus removal. The findings inform coagulant selection and deployment in diverse wastewater environments, support compliance with future phosphorus discharge standards, and contribute to the development of cost-effective and environmentally sustainable treatment strategies.PhD in Wate

Immersed boundary method with improved implicit direct-forcing for fluid–structure interaction problems

An improved implicit direct-forcing immersed boundary method (DF-IBM) is proposed for simulating interactions between incompressible fluid flows and complex rigid structures undergoing arbitrary free motion, commonly referred to as fluid–rigid body interaction problems. The proposed approach harnesses the pressure implicit with splitting of operators (PISO) algorithm to efficiently handle the dual constraints of the fluid–solid system in a segregated manner. Consequently, the divergence-free condition is maintained throughout the Eulerian domain, while the kinematic no-slip velocity boundary condition is exactly enforced on the immersed boundary, also termed as the fluid–structure interface. A new pressure Poisson equation (PPE) is derived, incorporating the boundary force directly where the no-slip condition is satisfied. This approach avoids altering the coefficient matrix of the PPE, which could otherwise introduce convergence issues, enabling the use of fast iterative PPE solvers without modifications. The improvement involves integrating Lagrangian weight methods, having better reciprocity over the IBM-related linear operators, within the implicit formulation. An additional force initialization scheme is introduced to accelerate the convergence of the no-slip boundary condition, thereby improving the algorithm’s performance. The Navier-Stokes equations are coupled with the rigid body dynamics, described by the Newton-Euler equations, within the improved DF-IBM framework. Both explicit and implicit coupling algorithms are developed to address weakly and strongly coupled fluid–rigid body interaction problems, respectively, under a partitioned approach. Stability and convergence issues, particularly stemming from critical solid–fluid density ratios and/or the rigid body approximation of the internal mass effects (IME) in rotational dynamics, are mitigated using a fixed relaxation technique for the rigid body kinematics. For implicit coupling, a fixed-point strategy is employed, complemented by the relaxation technique used for the IME to ensure robustness. Additionally, the proposed coupling algorithms leverage the DF-IBM formulation and the predictor-corrector strategy of the PISO solution algorithm, by excluding the momentum predictor step and the time-intensive corrector loops from the implicit iterations. The proposed method is validated through various stationary, prescribed, and freely moving immersed boundary cases, with results compared against experimental and numerical data from the literature. The method demonstrates robustness, accuracy, and efficiency in handling the complex dynamics of fluid–rigid body interactions across a range of challenging scenarios. The suggested improvements integrate seamlessly into existing incompressible fluid solvers with minimal adjustments to the original system of equations, highlighting their ease of implementation. Finally, the present work is implemented within the cell-centred finite volume approach inside the open-source C++ toolbox OpenFOAM environment, version 7.0 of the OpenFOAM Foundation variant.PhD in Energy and Powe

Sources, characterisation and exposure risk of airborne microplastic emissions from municipal solid waste dumping site in Nigeria

Walton, Christopher - Associate SupervisorAirborne microplastics (AMPs) represent an emerging environmental and public health challenge, with their sources, transport mechanisms, and impacts still poorly understood, particularly in developing regions with inadequate waste management systems. This research addresses three key gaps: the need for cost-effective and efficient AMP sampling tools, the AMP flux estimations under different environmental conditions, and the modelling of AMP dispersion to understand their transport and potential exposure risks downwind. This research tackles these challenges by developing a low-cost sampler for AMP collection. The low-cost sampler was validated against the commercial sampler (SKC Deployable Sampler equipped with a Total Suspended Particulate (TSP) head), with a focus on fibres, fragments, and films across diverse environmental conditions. The emission of AMPs was quantified using a modified Fick’s law, which incorporates sitespecific parameters such as wind speed, temperature, and particle properties. Seasonal variation in AMP emissions was analysed by collecting and processing 226 environmental samples (42 soil and 184 air) from the municipal solid waste disposal site and its environment during dry and wet seasons. Dispersion modelling was conducted using SCREEN3 to simulate the downwind transport of AMPs. A low-cost sampler (LCS) was developed and evaluated against a commercial sampler, demonstrating a strong correlation (ρ = 0.976) and high accuracy (94.12%) compared to a reference sampler. The LCS effectively captured seasonal variations in AMP abundance. Polymer analysis identified five predominant polymers, with nylon (fibres), PVC (fragments), and PE (films) accounting for the majority of microplastics. The cost analysis revealed that the LCS offers 61% savings over second-hand and 98% over new commercial samplers, making it a reliable and affordable tool for AMP research in resource-limited settings. The airborne microplastics measured on-site reveal seasonal variations in concentrations. Notably, the dry season reveals higher concentrations (mean: 14.37 ± 3.87 MP/m³) comparable to the wet season (mean: 11.31 ± 3.00 MP/m³). Upwind concentrations were considerably lower, averaging 4.25 ± 1.17 MP/m³ during the dry season and 2.75 ± 1.43 MP/m³ during the wet season, reflecting contributions from distant fibre-rich sources, likely indoor emissions. On-site, films exhibited the lowest emissions but retained moderate mobility during the wet season. Fibres showed the highest diffusion coefficients, indicating potential for long-range transport. Fragments were the most abundant microplastic type (55% dry, 53% wet), with high emission factors (188 µg/day dry, 170 µg/day wet). Rising velocities were higher during the dry season due to favourable wind conditions, with values of 0.1056 m/s for nylon fibres, 0.0835 m/s for PVC fragments, and 0.0742 m/s for PE films. The rising velocities and flux measurements highlighted the influence of soil porosity and wind speed on resuspension and transport of microplastics. The SCREEN3 dispersion model reveals distinct seasonal variations in the transport of AMP from MSW sites. Peak AMP concentrations occurred at 100–107 m downwind, with wet season levels (fibres: 2.28 × 10⁻² μg/m³, fragments: 6.81 × 10⁻² μg/m³, films: 2.41 × 10⁻³ μg/m³) exceeding dry season concentrations by 2.1–2.2 times. Fragments posed the highest health risks (Level III), particularly during short-term exposures, while fibres and films showed lower risks. SCREEN3 agreed well with ground measurements (R2 = 0.98 to 0.96) and identified key drivers such as stability classes and precipitation, affirming its utility for AMP transport modelling and risk assessment. This study highlights the significant environmental and health implications of airborne microplastic (AMP) emissions from municipal solid waste (MSW) sites. Fragments pose the greatest risks, particularly during the wet season. The development of a lowcost sampler and advanced dispersion modelling provides essential tools for AMP monitoring. To mitigate AMP impacts, improved waste management practices, such as minimising open burning, are necessary. Integrating AMP data into air quality monitoring frameworks and prioritising seasonal mitigation measures are also recommended. Future studies should investigate long-range transport mechanisms, refine emission factor models, and chronic exposure risks to develop comprehensive strategies for mitigating AMP impacts globally.PhD in Energy and Powe

Developing the through-transmission technique in pulsed thermography for material characterisation

Zhao, Yifan - Associate SupervisorPulsed Thermography (PT) is a reliable, non-contact, and non-intrusive non- destructive testing (NDT) technique for assessing the structural health of materials. Based on the relative positioning of the thermal excitation source and the infrared radiometer, measurements can be conducted in either reflection or transmission mode. While reflection mode is widely adopted due to its single- sided accessibility, transmission mode offers superior lateral resolution but remains limited in use due to the lack of reliable depth quantification methods. In the context of thermal diffusivity evaluation, the transmission mode has demonstrated greater reliability; however, the existing literature lacks a deterministic approach to systematically assess this in laboratory settings. This research investigates the current state-of-the-art in through-transmission thermography and identifies key knowledge gaps. A transparent and repeatable methodology is developed to evaluate thermal diffusivity using both finite element models (FEM) and controlled laboratory experiments. The FEM is also used to assess the temporal behaviour of a sample containing subsurface defects, and a physical sample is fabricated to validate the simulation results. A novel method for defect depth quantification is then proposed by establishing a relationship with the Fourier number. This approach demonstrated a 63% improvement in depth estimation accuracy (from a 29.3% measurement error to 10.75%) compared to the Log Second Derivative (LSD) method derived from thermographic signal reconstruction (TSR) in the simulation environment across all defect sizes and depths. Additionally, the technique shows potential for estimating impact damage in carbon fibre-reinforced polymer (CFRP) samples subjected to varying impact energy levels. By addressing the challenges of thermal property measurement and depth quantification within the transmission mode, this thesis provides a foundation for improved material characterisation and supports renewed research interest in through-transmission pulsed thermography.PhD in Manufacturin

Ammonia partitioning and recovery from industrial wastewater - exploring precipitation, stripping, and sorption technologies

Jefferson, Bruce - Associate SupervisorCircular economy in wastewater management is increasingly applied, with ammonia recovery playing a critical role. Established ammonia partitioning technologies, being precipitation, typically as struvite, stripping and scrubbing, and sorption, have been predominantly applied to manure, anaerobic digestate, urine and municipal wastewater. Industrial effluents also hold potential for ammonia recovery and have been increasingly targeted by research. These effluents comprise a wide category of wastewaters with diverse physicochemical characteristics, generated by different sectors, including food/drink processing, mining, agro-industrial processes, manufacturing, metallurgy, etc. Some of these effluents contain high ammonia loads alongside significant concentrations of ions, metals, and recalcitrant organic compounds, contributing to complex chemical compositions that can pose challenges for conventional recovery technologies. Despite the increasing focus on industrial wastewaters, there remains limited understanding of how to effectively select and operate recovery technologies, based on the effluent composition and desired recovery outcomes. This research aimed to advance the understanding of how several physicochemical factors impact the mechanisms enabling ammonia partitioning into gas, liquid and solid phases, in order to establish optimum transfer pathways. The key knowledge gaps addressed in this research were i) determination of main criteria for ammonia recovery technology selection for a range of industrial wastewaters, ii) understanding the feasibility and recovery performance of struvite precipitation and ammonia stripping at demonstration scale from distillery wastewater, iii) understanding and quantifying the impact of transition metals and acidic organic compounds on ammonia stripping, iv) assessment and comparison of ammonia separation performance via ion and ligand exchange media and influence of operation parameters (e.g. pH, buffer capacity, metal load, N concentration). The findings are utilised to generate an informed decision process for technology/strategy selection and the operational requirements and potential challenges posed by selected factors, with relevance for industry stakeholders, technology providers, and consultants. A specific focus was placed on distillery wastewater as a case study, a sector concerned with ammonia management and potentially suitable for recovery, particularly in Scotland. A review of the literature found that struvite precipitation is the most widely implemented method with industrial effluents, yet stripping and sorption processes may be preferred for their ability to deliver versatile, ammonia-rich solutions. The identified technology-selection criteria included the feed concentration of ammonia and competing cations, and the struvite formation potential. Based on the practical recommendations developed in this study, an ammonia recovery strategy for distillery wastewater was established, integrating anaerobic digestion with chemical precipitation and ammonia stripping coupled with scrubbing. The performance of this treatment train had never been tested before for filtered digestate of distillery effluent, addressing a key gap in understanding for full scale applications. Demonstration scale trials allowed to understand how the expected performance translated with real digested distillery wastewater and to validate its feasibility. The results demonstrated its technical viability, achieving 76% N removal and 80% P removal, while generating high- quality struvite and ammonia sulphate solution. Moreover, the findings highlighted the critical impact of pH and addressed operational challenges, improving readiness for full-scale application. Beyond distillery effluents, this thesis examined broader challenges in industrial wastewaters treatment, addressing gaps identified in the literature review, relevant for a range of industrial wastewaters, including from metallurgy and agro/food processing. Specifically, the impacts of species found in some of these effluents, such as transition metals (as Ni, Cu, Zn) and organic, acidic compounds (as humic acids), on the stripping process were investigated. Results showed that elevated levels of such species can reduce ammonia availability for stripping, via complex formation and electrostatic interactions. This highlighted the need for mitigation strategies to maintain stripping efficiency with these streams. Additionally, the metal-ammonia bond potential was further explored to assess ligand exchange (LEX) sorption mechanism as alternative to ion exchange (IEX), a mechanism often limited by high concentrations of ammonia and competing cations. Although various media have been tested in literature, comparative studies on their performance under different conditions are lacking, along with insights on how factors such as pH, transition metal and cations load can impact their mechanisms and effectiveness. In this study, two zinc-hybridised sorption media were tested and benchmarked against IEX media, in synthetic and real wastewaters (distillery, municipal). The results showed effective removal, although limited by self-inhibiting pH changes, with a zinc-hybridised media matching or exceeding IEX resin’s performance only when pH 9-10 was maintained (75 meq N/g). pH, buffer capacity and Zn/Na loads were demonstrated to be critical factors to enable or limit IEX and LEX mechanisms. The findings established operational requirements for hybridized sorption media and provided research directions for further improvement. Overall, this work advanced knowledge on the impact of key species on ammonia recovery technologies, with implications for industrial effluents treatment in general and distillery wastewater management in particular. The findings contributed to developing recommendations for selection and operation of ammonia partitioning strategies, optimizing metal-hybridized sorption media, and improving process feasibility for full-scale implementationPhD in Wate

Investigation of procurement risk management strategies in the post-contract award phase

Yates, Nicky - Associate SupervisorThis research empirically investigated how procurement risk management (PRM) strategies are used to manage risks in the post-contract award phase. Through three sequential papers, this study adopted multiple methods to gain insights into the procurement risks, risk management strategies, and risk management tools and techniques used in the post-contract award phase in manufacturing sector. Paper 1 is a literature review of the risk management strategies used in the three procurement phases: pre-contract, selection and contracting, and post-contract award. The author conducted an SLR of 100 peer-reviewed articles published between 2000 and 2025. The key findings of this study are twofold. First, it synthesized four main themes: procurement risks, procurement risk management tools and techniques, procurement risk mitigation strategies, and factors that influence the selection of risk mitigation strategies across the three procurement phases. Second, the findings highlighted that procurement risk management tools and techniques in the post-contract award phase have been neglected in the literature compared to the pre-contract, and selection and contracting phases. Paper 2, an empirical study, adopted a qualitative approach to gain insights into procurement risk management in the post-contract award phase. The author interviewed Procurement professionals (23) from 7 manufacturing industries in the United Kingdom (UK) and highlighted three key findings based on the interview insights. First, the results identified five risk categories: supplier performance, contract design, supplier relationship, ethical, and disruption risks. Second, procurement professionals combined technological tools, such as data analytics and machine learning, with human engagement techniques, including site visits and review meetings, to identify and assess risks and plan mitigation strategies. Third, a combination of preventive and reactive PRM strategies were implemented in the post-contract award phase. Paper 3, an empirical study, examined how sociological mechanisms affect procurement risks and procurement risk management performance during the post-contract award phase. A quantitative survey was conducted among 313 procurement professionals from the US automotive manufacturing industry. This study has four key findings. First, combining trust with information sharing, commitment, and flexibility mitigates the negative effects of switching costs on procurement risk management performance than using trust alone. Second, combining trust with information sharing, commitment, and flexibility mitigates the negative effects of switching costs and negotiation costs on procurement risk management performance than using trust alone. Third, sociological constructs are insufficient as PRM mechanisms to mitigate the negative impact of environmental uncertainties on procurement risk management performance. Fourth, sociological constructs are insufficient as PRM mechanisms to mitigate the negative influence of supplier opportunistic behaviours on procurement risk management performance. Overall, this thesis makes several key contributions and extends the literature in the following ways. This SLR study contributes to the existing literature by aligning the fragmented strands of risk management literature and systematically synthesizing the procurement risks, the tools and techniques for identifying, assessing, and mitigating risks, and the risk mitigation strategies in each procurement phase. Second, it provides a new, empirically based procurement risk management model that integrates procurement risk identification, assessment, and mitigation strategies into the post-contract award phase. Third, it provides new empirical evidence that combining trust with information sharing, commitment, and flexibility mitigates the negative effects of switching costs and negotiation costs on procurement risk management performance more effectively than using trust alone. Fourth, it provides new empirical evidence that combining trust with information sharing, commitment, and flexibility mitigates the negative effects of switching costs and negotiation costs on procurement risk management performance than using trust alone.PhD in Leadership and Managemen

Analysis of active aerodynamics for high-performance vehicles

The pursuit of greater efficiency and performance drives advancements in the automotive and motorsport industries, with active aerodynamics emerging as a promising approach due to their ability to dynamically adapt aerodynamic characteristics to specific operating conditions. However, their development presents challenges, including the need for practical yet accurate simulation methodologies, a deeper understanding of vehicle aerodynamics in dynamic conditions, and a comprehensive assessment of their performance potential. This research addresses these challenges through interdependent studies. A cost-effective Computational Fluid Dynamics (CFD) workflow is developed and validated against experimental and high-fidelity simulation data, complemented by a structured wind tunnel correlation process to ensure reliable aerodynamic predictions. Yaw and cornering effects on flow field characteristics and aerodynamic performance are analysed using wind tunnel experiments and CFD simulations. Finally, active aerodynamic configurations, including 2D systems capable of modulating aerodynamic balance longitudinally and laterally, are designed and examined using minimum lap time simulations to assess performance gains, optimal control strategies, and dependencies on vehicle setup. The CFD workflow demonstrates high predictive accuracy across various aerodynamic conditions, with the structured correlation process improving experimental data interpretation and validation. However, conditions critically dominated by highly unsteady flow phenomena require higher-fidelity simulations. Yaw and cornering conditions induce significant flow field alterations, including underbody interference, enhanced upper surface flow acceleration, and asymmetric wake structures, leading to substantial downforce and drag penalties. Active aerodynamic systems provide significant performance benefits across diverse scenarios, with 2D systems consistently outperforming conventional designs by prioritising aerodynamic loads on underloaded tyres to improve total grip. Overall, this research advances numerical methodologies, deepens understanding of vehicle aerodynamics in dynamic conditions, and demonstrates the performance potential of various active aerodynamic designs. The work establishes a foundation for optimising vehicle performance with active aerodynamic systems, supporting future research and industry innovations in automotive and high-performance vehicle engineering.PhD in Transport System