Dr Fabrizio Bonatesta

Road vehicles are a large contributor to nitrogen oxides (NOx) pollution. The routine roadside monitoring stations, however, may underrepresent the severity of personal exposure in urban areas because long-term average readings cannot capture the effects of momentary, high peaks of air pollution. While numerical modelling tools historically have been used to propose an improved distribution of monitoring stations, ultra-high resolution Computational Fluid Dynamics models can further assist the relevant stakeholders in understanding the important details of pollutant dispersion and exposure at a local level. This study deploys a 10-cm-resolution CFD model to evaluate actual high peaks of personal exposure to NOx from traffic by tracking the gases emitted from the tailpipe of moving vehicles being dispersed towards the roadside. The investigation shows that a set of four Euro 5-rated diesel vehicles travelling at a constant speed may generate momentary roadside concentrations of NOx as high as 1.25 mg/m3, with a 25% expected increase for doubling the number of vehicles and approximately 50% reduction when considering Euro 6-rated vehicles. The paper demonstrates how the numerical tool can be used to identify the impact of measures to reduce personal exposure, such as protective urban furniture, as traffic patterns and environmental conditions change.

A novel calibration methodology is presented to accurately predict the fundamental characteristics of high-pressure fuel sprays for Gasoline Direct Injection (GDI) applications. The model was developed within the Siemens Simcenter STARCD 3D CFD software environment and used the Lagrangian–Eulerian solution scheme. The simulations were carried out based on a quiescent, constant volume, computational vessel to reproduce the real spray testing environment. A combination of statistic and optimisation methods was used for spray model selection and calibration and the process was supported by a wide range of experimental data. A comparative study was conducted between the two most commonly used models for fuel atomisation: Kelvin–Helmholtz/Rayleigh–Taylor (KH–RT) and Reitz–Diwakar (RD) break-up models. The Rosin–Rammler (RR) mono-modal droplet size distribution was tuned to assign initial spray characteristics at the critical nozzle exit location. A half factorial design was used to reveal how the various model calibration factors influence the spray properties, leading to the selection of the dominant ones. Numerical simulations of the injection process were carried out based on space-filling Design of Experiment (DoE) schedules, which used the dominant factors as input variables. Statistical regression and nested optimisation procedures were then applied to define the optimal levels of the model calibration factors. The method aims to give an alternative to the widely used trial-and-error approach and unveils the correlation between calibration factors and spray characteristics. The results show the importance of the initial droplet size distribution and secondary break-up coefficients to accurately calibrate the entire spray process. RD outperformed KH–RT in terms of prediction when comparing numerical spray tip penetration and droplet size characteristics to the experimental counterparts. The calibrated spray model was able to correctly predict the spray properties over a wide range of injection pressure. The work presented in this paper is part of the APC6 DYNAMO project led by Ford Motor Company.

This paper presents the details of a Computational Fluid Dynamics methodology to accurately model the process of mixture preparation in modern Gasoline Direct Injection engines, with particular emphasis on liquid film as one of the main causes of Particulate Matter formation. The proposed modelling protocol, centred on the Bai-Onera approach of droplets-wall interaction and on multi-component surrogate fuel blend models, is validated against relevant published data and then applied to a modern small-capacity GDI engine, featuring centrally-mounted spray-guided injection system. The work covers a range of part-load, stoichiometric and theoretically-homogeneous operating conditions, for which experimental engine data and engine-out Particle Number measurements were available. The results, based on the parametric variation of start of injection timing and injection pressure, demonstrate how both fuel mal-distribution and liquid film retained at spark timing, may contribute to PN emissions, whilst their relative importance vary depending on operating conditions and engine control strategy. Control of PN emissions and compliance with future, more stringent regulations remain large challenges for the engine industry. Renewed and disruptive approaches, which also consider the sustainability of the sector, appear to be essential. This work, developed using Siemens Simcenter CFD software as part of the Ford-led APC6 DYNAMO project, aims to contribute to the development of a reliable and cost-effective digital toolset, which supports engine development and diagnostics through a more fundamental assessment of engine operation and emissions formation.

An experimental investigation was carried out to investigate Particulate Number (PN) emissions from a modern, small-capacity Gasoline Direct Injection (GDI) engine. The first part of the study focused on improving measurement repeatability using the Cambustion DMS-500 device. Results showed that sampling near the exhaust valve – while dampening the pressure oscillations in the sampling line – can significantly improve the repeatability. It was also found that uncontrolled phenomena such as deposition in the exhaust system from earlier engine operation can undermine the accuracy of measurements taken at tailpipe level. The second part of the work investigated PN emissions from three types of gasoline fuel, Pump-grade, Performance and Reference. Fuel chemical composition was found to have an appreciable impact on PN, but the magnitude of this effect differs in various operating points, being more pronounced at higher engine load. The Reference fuel was found to have the lowest PN emission tendency, conceivably because of its lower aromatics, olefins and heavy hydrocarbons content. A sweep of operating parameters showed that higher injection pressure reduces PN, but the extent of the reduction depends on fuel physical properties such as volatility.

Despite improvements in thermal efficiency and fuel economy, gasoline direct injection (GDI) engines have been identified as a prominent source of ultrafine particulate matter (PM) in the atmosphere. Adverse impacts caused by PM on the environment and public health motivate the need to deepen the understanding of PM emissions from GDI engines. Hence, an integrated modeling approach is formulated to investigate PM processes in a wall-guided GDI engine by bridging the gap between computational fluid dynamics (CFD) and chemical kinetics. Serving as the gasoline surrogate, a reduced and validated toluene reference mechanism is selected. Spray, turbulence, fuel impingement, liquid film, spark ignition, combustion, and PM emissions are modeled by a complete set of CFD submodels. The dynamic multizone partitioning is introduced within the CFD framework for computational expenditure while soot modeling is addressed through the sectional method. In-cylinder pressures, number density, and mass density of PM are reproduced across engine speeds of 1600–3000 rpm and loads with torques of 60–120 N m. Under a homogeneous stoichiometric mode, dominant formation mechanisms of PM are highlighted as the emergence of fuel-rich regions and the presence of residual liquid fuel droplets at the spark timing. The former is attributed to film stripping and evaporation due to spray-wall interactions while the latter stems from poor droplet vaporization from fuel injected, rebounded, splashed, and/or stripped from the liquid film. Optimized control strategies for GDI engine operations should target to minimize these sources for effective PM abatement.

Transpired Solar Collectors (TSCs) are simple low maintenance air heating systems which have been widely used for agricultural and industrial applications. In spite of their potential, these systems have not been yet widely employed in residential buildings as they are unable to generate high grade heat for moderate and low ventilation demands. Hence there is an opportunity for optimisation studies in order to enhance the thermal performance of these systems.

Optimisation and parametric studies can be costly and time consuming if carried out by physical experiments. CFD models however offer a more flexible and less expensive tool to carry out such studies. This research has aimed to optimise the geometry of the solar absorber plate using a validated CFD model which accounts for a wide range of the key factors affecting TSC performance.

A 2nd order polynomial predictive model was developed based on the CFD results with Root Mean Squared Error (RMSE) of 3.8%. The predictive model was used to identify an optimal geometry which delivers a Heat Exchange Effectiveness (HEE) of 0.739. The optimised geometry demonstrated 43% increase in HEE whilst using 28% less material compared to the baseline geometry under the same operating conditions. This geometry can be integrated with other performance enhancement techniques to further improve the thermal performance of TSCs.

The exposure of pistons to extreme mechanical and thermal loads in modern combustion engines has necessitated the use of efficient and detailed analysis methods to facilitate their design. The finite element analysis has become a standard design optimisation tool for this purpose. In literature two different approaches have been suggested for reducing the geometry of the cylinder and crank slider mechanism, to idealise piston finite element analysis load models,whilst trying to maintain realistic boundaries to obtain accurate results. The most widely used geometry is the combination of piston and gudgeon pin while the second geometry includes some portion of the connecting rod’s small end and cylinder in addition to the piston and gudgeon pin.No clear analyses have been made in literature about the relative effectiveness of the two approaches in terms of model accuracy. In this work both approaches have been carried out and analysed with respect to a racing piston. The results suggest that the latter approach is more representative of the load conditions that the piston is subjected to in reality.

(GDI) combustion systems are gaining popularity among the automotive industry. This is

because GDI engines offer less pumping and heat losses, enhanced fuel economy and improved transient response. Nonetheless, the technology is often associated with the emission of ultra-fine particulate matter (PM) to the atmosphere. With the increasingly stringent emission regulations, detailed understanding of PM formation within GDI engine configurations is very crucial. To complement the findings based on experimental and optical techniques, computational fluid dynamics (CFD) modeling has been widely utilized to study the in-cylinder physical and chemical events. The success of CFD simulations also requires an accurate representation of gasoline fuel kinetics. Set against the background, the present review reports on the recent developments in chemical kinetic modeling of gasoline fuels and CFD numerical studies for GDI engines emphasizing the combustion and emission stages. Regarding fuel kinetics, the use of primary reference fuel (PRF) and ternary reference fuel (TRF) mechanisms is evaluated. In addition, the current trend portrays a progression towards multi-component surrogate models to account for the complex mixture of practical fuels. It is however observed that many reaction mechanisms proposed in the literature are validated under homogeneous charge compression ignition (HCCI) engine conditions rather than GDI-related ones. CFD modeling of GDI engines typically covers the simulations of spray, mixture formation and combustion processes. Progress in combustion modeling for both homogeneous and stratified charge modes is discussed thoroughly. Still in its infancy, soot modeling studies for GDI engines are reviewed in which several soot models adapted are appraised. The majority of soot models have been previously applied in diesel combustion systems and flame configurations. Significant efforts are currently carried out to improve the model predictions of soot emission from GDI engines.

Transpired Solar Collectors (TSCs) are building-integrated air-heating systems that are able to fully or partially meet the heating demands of buildings. They convert solar radiation into warm air that can either be used for ventilation, or to heat thermal storage media. TSCs are becoming an increasingly viable alternative to conventional fossil fuel-based heating systems or, more commonly, can be used in a way that is complementary to these systems such that reliance on fossil fuels is reduced. As a consequence TSCs have a potentially important role in meeting future carbon reduction goals.

This research has produced a comprehensive numerical model for TSCs based on Computational Fluid Dynamic (CFD) analyses. The model allows parametric studies of key variables and is differentiated from previous models in that it takes full account of factors such as: wind speed and direction, non-uniform flow, turbulent flow, solar radiation intensity, sun position and flow suction rates. It comprises a full size section of cassette-panel TSC that can be easily morphed to reflect a wide range of geometries. A multi-block meshing approach has been employed to reduce grid size and to also resolve jet flows and boundary layers taking place in the plenum and around the absorber plate. Accuracy of the CFD model has been validated against experimental data.

Modeling demonstrated that factors such as wind angle have unexpectedly significant adverse effects on system thermal performance. The studies also furthered understanding of key performance attributes including the effects of suction ratio in terms of optimising performance, and the relationship between sun angle and system operating temperature  (important for  effective operation of heat storage systems). Consideration of these factors is essential if the future performance of TSCs is to be optimised and the technology developed to its fullest potential.

The model comprises a full size section of a typical TSC that can be easily morphed. A multi-block meshing approach was used to reduce grid size and to capture jet flows taking place in the plenum region through the perforations. When compared to experimental data over a wide range of climatic conditions, the modeled values of outlet temperatures at the absorber plate and plenum demonstrated a high level of accuracy, giving assurance regarding the validity of the approach. To the authors’ best knowledge, the model represents the most comprehensive TSC simulation tool so far developed.

The charge burn characteristics of a port-injected spark ignition engine with a pent-roof combustion chamber and variable valve timing have been investigated experimentally. The engine was run under stoichiometric mixture operating conditions over ranges of intake and exhaust valve timings, engine speed, and engine load. Empirical functions have been developed for the 0-90 per cent mass fraction burned angle and the form factor, which define Wiebe function fits to the mass fraction burned variation in the crank angle domain. The burn angle and form factor have been related to the level of charge dilution by burned gas, engine speed, ignition timing, and charge density at spark timing. The dilution level has the strongest influence on the burn rate and profile. The dilution level varied with intake and exhaust valve timings, external exhaust gas recirculation, and engine load. The results indicate that intake and exhaust valve timings influence combustion primarily by modifying the charge dilution with burned gas and charge density.