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Optimization of electric vehicle drivetrain fluid with a new system-level approach
No full textThis paper uses a newly developed tribology-based system-level transmission efficiency model to investigate the influence of e-fluid properties on electric vehicle (EV) drivetrain losses. The model considers gear meshing losses using a thermally-coupled mixed friction prediction, bearing losses using existing models, and gear churning using a new experimentally-derived regression equation. The key advantages of the approach are: (i) it is a system-level approach that accounts for the interdependency of different sources of losses by predicting the evolution of temperature distribution in the entire electric drive unit (EDU) including the transmission, e-motor and heat exchanger; (ii) it can discriminate between two oils of the same specification in terms of their impact on overall losses by using measured lubricant rheology; and (iii) it predicts total energy loss over any vehicle duty cycle. The model is validated by comparing its temperature predictions to in-situ measurements made on a real EV in a series of road tests. Application of the model to a typical modern EV shows that it is possible to identify an optimum e-fluid viscosity for minimum transmission losses over any given drive cycle. The exact value of this optimum strongly depends on vehicle duty: it is higher for a city cycle such as the New York City Cycle (NYCC), which has low average speed and frequent start-stops, conditions where gear tooth friction is shown to dominate, and lower for highway driving or the worldwide harmonized light-duty vehicles test cycle (WLTC), where bearing losses dominate. The presented approach provides an efficient tool for optimization of lubricant selection and EDU design
Factor models for conditional asset pricing
No full textThis paper develops a methodology, building on a local-PCA approach, for inference on the pricing ability of conditional asset pricing models designed to mitigate the effect of omitted risk factors and misspecified conditional dynamics. The methodology is designed to exploit the rich information available in large cross-sections of individual stocks. Monte Carlo experiments and an empirical application demonstrate the benefits of this methodology over existing approaches
Changing gastrointestinal transit time alters microbiome composition and bile acid metabolism: a cross‐over study in healthy volunteers
No full textBackground
The specific influence of whole gut transit time (WGTT) on microbiome dynamics and bile acid metabolism remains unclear, despite links between changes in WGTT and certain gastrointestinal disorders. Our investigation aimed to determine the impact of WGTT changes on the composition of the fecal microbiome and bile acid profile.
Methods
Healthy volunteers (n = 18) received loperamide, to decrease bowel movement frequency, and senna, a laxative, each over a 6-day period, in a randomized sequence, with a minimum 16-day interval between each treatment. Stool samples were analyzed for microbiome by shotgun sequencing and bile acid composition determined with high-performance liquid chromatography coupled to tandem mass spectrometry. Sera were examined for markers of bile acid synthesis.
Key Results
Senna or loperamide decreased or increased WGTT, respectively. Treatment altered stool characteristics, bowel movement frequency, and stool weight. The senna-treated group had increased primary and secondary fecal bile acids; serum levels of fibroblast growth factor 19 were significantly reduced. Increasing WGTT with loperamide led to an increase in bile salt hydrolase genes, along with elevated bacterial species richness (p = 0.04). Thirty-six species exhibiting significant differences were identified, several of which have notable implications for gut health. WGTT displayed negative correlations with total primary (particularly chenodeoxycholic acid) and secondary bile acids (ursodeoxycholic acid and glycochenodeoxycholic acid). Treatment-induced changes in microbiome composition and bile acid metabolism reverted back to baseline within 16 days.
Conclusion
Whole gut transit time changes significantly affect fecal microbiome composition and function, as well as bile acid composition and synthesis in healthy subjects. This consideration is likely to have long-term implications
Co-designing interventions with multiple stakeholders to address barriers and promote equitable access to HIV Pre-Exposure Prophylaxis (PrEP) in Black women in England
No full textBackground:
Black women are among the populations most underserved by HIV pre-exposure prophylaxis (PrEP) in England, despite higher risk of HIV acquisition. Previous research mostly focused on men who have sex with men (MSM), often neglecting Black women, and overfocused on patient-level barriers while overlooking provider and system-level factors. This study addresses these gaps by investigating barriers and facilitators to PrEP access by involving multiple stakeholders and exploring co-design strategies to tackle these barriers.
Methods:
The study used a structured two-phased qualitative approach. In Phase 1, focus groups (FG) were undertaken across three stakeholder streams: Black women, healthcare professionals (HCPs), and a group combining Black women and HCPs. FG allowed for consensus-building exercises on key barriers and facilitators to PrEP access, and their transcripts were analysed via thematic framework analysis using the Capability, Opportunity, Motivation and Behaviour model of behaviour change. In Phase 2, co-design workshops were conducted with the same stakeholder groups to develop interventions targeting the barrier identified as most important using the Behaviour Change Wheel framework. Interventions were evaluated against the APEASE criteria.
Results:
Phase 1 identified six key barriers: HIV/PrEP knowledge gaps, restrictive policies, cultural stigma, healthcare system distrust, gendered relationship dynamics, and suboptimal PrEP use. Six facilitators emerged, including improved knowledge, increased accessibility, and addressing discrimination. All stakeholder groups voted for lack of awareness and knowledge as the priority barrier to address. All co-designed interventions consisted of a multimodal PrEP awareness campaign tailored to Black communities, with an emphasis on Black women’s involvement to foster trust and engagement. However, the workshops produced different approaches, with Black women focusing on community-led initiatives, and HCPs advocating for government-backed, broader strategies despite known distrust of institutions.
Conclusions:
This study highlights the importance of co-designing interventions with Black women to address multi-level barriers to PrEP access. It underscores the need for community education, healthcare system reforms, and the inclusion of Black women in decision-making processes to reduce PrEP equity gaps. The co-designed interventions provided a tailored, context-specific strategy that could improve PrEP uptake among Black women in England
Unpacking experimentation in design thinking: contributions to innovation performance and the moderating role of digital technologies
No full textDesign thinking is an innovation approach that emphasizes developing and testing hypotheses about the desirability, feasibility, and viability of an idea through iterative experimentation. Although widely used, there is limited empirical evidence to support the effectiveness of experimentation practices in design thinking projects. Similarly, the impact of integrating digital technologies into experimentation processes remains underexplored. This study addresses these gaps by analyzing data from 246 design thinking projects to examine how early and frequent experimentation influences innovation performance, specifically in terms of effectiveness and efficiency. It also examines how the use of digital technologies moderates these relationships. The results show that both early and frequent experimentation positively influence innovation effectiveness, while only early experimentation significantly improves innovation efficiency. Moreover, the use of digital technologies strengthens the positive effects of early experimentation on both effectiveness and efficiency. This research provides valuable theoretical and practical insights by deepening our understanding of how experimentation and digital tools drive innovation performance in design thinking projects
The role of conic curvature and surface-wall roughness in gas cyclones and hydrocyclones
No full textStatic centrifugal classifiers, such as gas cyclones and hydrocyclones, are crucial in mineral processing for particle separation. While gas cyclones remove particles from gas streams, hydrocyclones function as classifiers but suffer from high bypass in ball-mill circuits. This thesis explores the impact of conic curvature and surface wall roughness in both cyclone and hydrocyclone performance.
Using Computational Fluid Dynamics (CFD) and laboratory experiments with 3D-printed prototypes, the study investigates cyclone behavior under varying surface roughness. A novel expandable chamber method was developed for particle size measurement. CFD simulations of 31 mm gas cyclones reveal that convex conic designs produce coarser cut sizes, enhancing classification efficiency over standard designs. Response Surface Methodology and Monte Carlo simulations further validate convex designs as optimal for coarser classification.
Experimental results confirm that convex gas cyclones reduce fine particle separation while improving the classification of coarser fractions. Further, these insights are transferred to hydrocyclones. In 75 mm hydrocyclones, convex designs mitigate fines bypass, reducing re-grinding costs in ball-mill circuits. Additionally, surface roughness effects differ between gas cyclones and hydrocyclones: rough surfaces lower tangential velocities in gas cyclones, reducing separation efficiency, whereas increased downward axial velocities in rough hydrocyclones improve solids recovery and concentration, benefiting dewatering applications.
This thesis advances cyclone design through CFD and experimental validation, providing insights for more efficient classification and industrial-scale applications.Open Acces
Effective emergency management prevented larger catastrophe after climate change fueled heavy rains in Central Mississippi river valley
No full textAdvanced bayesian modelling for the analysis of outbreaks and shifting epidemiological dynamics
No full textThe emergence, spread, and establishment of an infectious disease within a population brings about a plethora of challenges for public health organisations, whose aim is to reduce disease burden while having access to limited information. In this thesis, we develop statistical models and analyses to support public health response, addressing uncertainties that are inherent to epidemics. The work is divided into two parts, focusing on the last century’s biggest pandemics.
In the first part, we focus on the emergence of novel pathogens and variants of concern, with applications to SARS-CoV-2. Firstly, we develop an adjustment to early reproduction number estimates, when generations of infections have not been reported. Our adjustment is shown to reduce early biases in simulation studies. Secondly, we develop a multi-strain Bayesian model to describe fluctuations in hospital fatality rates in Brazil following the emergence of the Gamma variant. By synthesising data from separate sources, we estimate the proportion of patients with either variant in hospitals across Brazil, and quantify the impact of healthcare pressures, variant, and location effects.
In the second part of the thesis, we describe changes in transmission dynamics and burden of HIV, using data from the Rakai Community Cohort Study. In the first project, we develop a phylogenetic pipeline to estimate HIV time since infection from viral sequences, and develop statistical models to refine estimates by incorporating testing histories and known transmission network. By dating transmissions, we are able to describe changes in transmission patterns, highlighting shifts in the age-profile of the sources. Finally, we provide detailed descriptions of shifts in the age and gender compositions of the burden of HIV and viraemia in Uganda. We obtain estimates at the age level by developing non-parametric models sharing information across age groups.
We conclude by proposing novel metrics to inform prevention strategies.Open Acces
The consequences of electrolyte engineering in electrochemical nitrogen reduction to ammonia
No full textAnthropogenic nitrogen fixation and ammonia-derived fertiliser have fed the growth of society. However, the nature and economies of scale of the Haber-Bosch process made it a major source of energy consumption and greenhouse gas emissions, while benefiting only a portion of the global population. Electrochemical ammonia production holds potential for decarbonisation and decentralisation.
Aqueous electrolysers are likely impractical due to the intense competition between nitrogen reduction, and proton reduction to hydrogen. Non-aqueous systems circumvent this problem, with a lithium-mediated approach having been rigorously validated to reduce nitrogen at viable rates. In this system, in situ reduced metallic lithium reacts with nitrogen and protons to produce ammonia. Alike battery anodes, lithium reacts with its electrolyte, forming a passivation layer (the solid electrolyte interphase or SEI), which is thought to prompt the selectivity of this reaction.
This thesis examines and addresses the significant energy burden required to maintain the active lithium metal surface through the lens of electrolyte engineering. A true reference electrode was developed to measure this energy burden and elucidate the role of the electrolyte in mitigating it. Electrolytes were formulated based on this understanding, and the interplay between electrolyte properties, SEI chemistry and selectivity was illustrated with overlapping non-linear relations. Such relations can be translated into a linear correlation between the selectivity of nitrogen reduction to ammonia and the activity of Li-ions and protons. While providing descriptors for identifying higher-performing electrolytes, it highlighted that significant energy efficiency gains can only be achieved by breaking free from lithium. Guided by simulations, new electrolytes based on promising alkali metals such as Ca and Mg were investigated to achieve nitrogen fixation beyond lithium. The fundamental insights gained from these studies are expected to enhance the alkali metal chemistries and help overcome their energy bottleneck, toward sustainable and affordable ammonia production.Open Acces
The development of a drone radar system
No full textInterferometric Synthetic Aperture Radar (InSAR) is an active remote sensing technique capable of quantifying millimetric rates of earth surface and structural deformation. Coupled with emerging drone technologies, there is scope for improved spatial and temporal resolutions in the InSAR data. The former is desired for small and complex sites such as nuclear power stations, whilst the latter would provide more comprehensive and flexible time-series analyses. This thesis details the hardware, software, and experimental development of a drone radar system, capable of providing Synthetic Aperture Radar (SAR) imaging for future developments and applications utilising InSAR. These developments are at the forefront of this novel field of research, with few authors demonstrating similar miniaturised radar systems with SAR capabilities. The hardware development includes a custom drone radar payload, with a combination of commercially available and custom components; the latter includes radar antennas manufactured from Copper Clad Laminate (CCL) and tested in an anechoic chamber. Similarly, a range of third party and custom software is tested and developed, including Frequency Modulated Continuous Wave (FMCW) radar in GNU Radio Companion (GRC), and SAR processing in MATLAB. A laboratory experiment is devised to test and demonstrate the hardware and software components, and explore the effect of varied moisture content of a generic topsoil on the phase of InSAR interferograms using Software Defined Radar (SDR). Lastly, a case study is presented for an active landslide adjacent to the M25, where both satellite InSAR and the drone radar system are demonstrated. Importantly, this thesis presents the first SAR image produced using the drone radar system, with clearly defined targets and an improved spatial resolution compared to satellite SAR. Ongoing and future work seeks to expand upon these developments and transition from discrete drone SAR imaging to automated drone InSAR hazard detection.Open Acces