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Free to read on publisher's website Diesel engines are often preferred over gasoline engines because of their fuel efficiency and reliability; however, there are significant issues around their environmental pollution which is controlled by emission regulations. To meet the ever more stringent regulations, reduction in diesel particle matter emissions can be addressed by minimising particle formation and by optimising particle oxidation in the combustion chamber and in the exhaust and diesel particulate filter systems. Soot formation and oxidation processes are the predecessors to the physicochemical properties of diesel particulate matter and are characterised by morphology and nanostructure. These characteristics principally include primary particle size, fractal dimension, fringe length, fringe tortuosity and fringe separation distance. Thus, understanding of these characteristics is necessary for an efficient reduction of particle emissions from diesel engines. Furthermore, understanding these characteristics is important because they affect the aerodynamic behaviour of the diesel particulate matter in the exhaust system, diesel particulate filter systems, and the environment.

This study investigates the combustion instability of a compression ignition engine using dynamical system analysis in the form of a recurrence plot approach. In-cylinder combustion chamber pressure and crank angle are obtained from a six-cylinder, turbocharged diesel engine with a common-rail direct fuel injection system using a piezoelectric transducer and encoder, respectively. The common-rail system keeps the fuel pressure at a constant rate, which helps to minimise the effect of fuel pressure in this study. Constant speed and 4 loads are investigated. The engine emission and operation can be influenced by combustion instabilities and inter-cycle variability. Previous studies reported that ambient temperature, fuel pressure and injection timing, residual gases and fuel properties significantly alter the combustion instability. This study focus on the effect of biodiesel on this phenomena. Considering the CI engine as a dynamical system, the dynamic state of the combustion can indicate its stability. Typically, peak pressure, heat-release rate and indicated mean effective pressure in a range of consecutive cycles are utilised to represent the variability of combustion. The recurrence plot of these data is used to visually study the characteristics of combustion dynamics. Additionally, the recurrence quantitative analysis is used to present the characteristic dynamics of the system. The study finds that the combustion instability is higher for biodiesel compared with diesel, owing to the fuel properties. The results aid in developing our understanding of the complexity of biodiesel combustion in a modern engine and help to advance the combustion control strategy in order to improve the performance of biodiesel fuelled engines.

Generating electricity from low grade waste heat resources can contribute to the energy mix required to reduce carbon emissions and dependence on fossil fuels. The conversion of low grade waste heat can be achieved efficiently using Organic Rankine cycles (ORC). Radial-inflow turbine is one suitable technology for the expander in these cycles. The design of such turbines operating with non-ideal gas is challenging and requires advanced modeling techniques to be developed and validated. This paper proposes a novel and cost-effective solution to develop a design approach that combines numerical modeling and experiments. An ORC loop is developed at Dyn-fluid laboratory for teaching and research purposes. The experimental setup allows experiments of high speed turbines up to 60,000 rpm and 9 kW in a modular way. The first expander to be experimentally and numerically tested will be an adapted compressor from a standard turbocharger. The considered com- pressor wheel has 6 main blades and 6 splitters blades with an outer diameter of 44 mm and a backswept angle of 45°. The expected performance of the compressor used as a turbo expander are then estimated using 3D CFD real gas simulations and will be ultimately validated against the experimental results. The synergy between numerical modeling and experiments is expected to support the reduction in cost of the manufacturing of turbines prototypes, estimated to represent more than 50% of the total cost of the ORC system.

Diffusive mixing between miscible fluids is an important process in many microfluidic applications, especially for biological studies. In microfluidic experiments it is common to observe microscopic fluid dynamics through fluorescence microscopy. Applying this technique to a hydrodynamic focusing device with a core-flow containing ferrofluid and fluorescence, an unexpected physical phenomenon referred to as the ‘saddle-like’ distribution was observed. Lattice Boltzmann (LB) methods have recently gained tremendous popularity as a numerical approach to model microfluidic dynamics. Despite the recent advancements in LB, reports on the application of high-order LB methods to single- phase miscible mixtures in microfluidics have been limited. The work presented here focuses on the application of high-order LB models to the simulation of single-phase binary miscible mixtures in microfluidic systems. We demonstrate the ability of our numerical simulation to capture the characteristics of the ‘saddle-like’ phenomenon and highlight the difficulties and limitations faced when comparing numerical results against experimental fluorescence microscopy with ferrofluids. This work sets the preliminary steps towards a LB model for simulating fluid mixtures in micro- and nanofluidics and allows for future advancements through higher order expansions.

The global energy demand signifies the importance of developing cutting-edge and state of the art heat exchanger technologies. The deployment of porous metal foams in various heat exchangers is one such material that is rapidly gaining attention in the research field. However, an in-depth comparative analysis of fluid flow through metal foams is relatively scarce in the existing literature. This study aims to use computational fluid dynamics (CFD) to examine forced convection of various fluids through digitized samples of porous metal foams. Results have shown that an increase in fluid velocity results in a decline in average fluid temperature. Moreover, the type of fluid has a direct effect on the temperature distribution and spread of the fluid temperature around the foam ligaments. This study aims to address critical queries in the literature namely unravelling forced convection of fluids through metal foams for compact and lightweight heat exchangers. This could potentially serve as a steppingstone to devise ways of mitigating fouling and maximizing heat exchanger performance.

Horizontal chaotic dispersion plays an important role in the distribution and fate of pollutants in coastal waters. Particle dispersion within coastal areas is governed by the combination of local weather events and the interaction of the flow field with local morphological structures, at small and large time scales. The present study investigates the horizontal dispersion and barriers to material transport in a tidal dominated estuary (Moreton Bay) using a combination of a hydrodynamic model and the identification of Lagrangian Coherent Structures (LCS) which acts as transport barriers. In this study, Finite-Time Lyapunov Exponent (FTLE) method has been applied to investigate how the material gets close to the LCS and also to identify the characteristics of the LCS for spring and neap tides.

The global linear stability of the family of rotating boundary layers (that includes discs and cones) is reviewed. Using a velocity-vorticity form of the linearised Navier-Stokes equations, disturbance evolution is impulsively excited for a variety of flow geometries and perturbation parameter settings. For azimuthal mode numbers below a fixed threshold value, disturbance development is dominated by convectively unstable characteristics, even though the flow might be locally absolutely unstable. As the azimuthal mode number is increased to larger values a form of global linear instability emerges that is characterised by a faster than exponential temporal growth. However, this is only observed when the azimuthal mode number is taken to be significantly greater than the conditions necessary for the onset of absolute instability to occur.