William Kendal Bushe

Associate Professor

Research Interests

Numerical Simulation of Turbulent Combustion
Reacting Flows
Energy Conversion Systems
clean energy

Relevant Degree Programs

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I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.


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I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.
I am open to hosting Visiting International Research Students (non-degree, up to 12 months).
I am interested in supervising students to conduct interdisciplinary research.

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Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - Nov 2019)
Application of conditional filtering to simulation of turbulence, chemistry, and their interactions (2019)

Combustion technology has been applied in human society for millennia and, since the industrial revolution, has become an integral part of most energy supply chains. Simulation is an important tool in modern combustor design; this thesis aims to improve the quality of combustion simulation tools, and thereby facilitate the design of improved combustors. More specifically, it aims to examine how generalizing and/or relaxing the definition of conditional filtering – a common technique in turbulence-chemistry interaction modelling – can produce novel turbulence and combustion models. The work begins with an extension of the Conditional Source-term Estimation (CSE) model for turbulence-chemistry interaction modelling. A novel variation of the algorithm, termed CSE with Geometric Conditioning Variables (CSE-GCV) is proposed as a method of circumventing the theoretical and practical issues associated with traditional CSE ensemble division. In CSE-GCV, the concept of the conditional filter is generalized by introducing geometric (position-based) variables as conditioning variables. CSE-GCV is tested and found to be workable; a theoretical analysis demonstrates that CSE-GCV also generally has the advantage of reduced computational complexity compared to traditional CSE. In a separate study, the stabilization procedure employed in traditional dynamic sub-filter modelling for Large Eddy Simulation (LES) is re-interpreted as a form of conditional filtering based on position. This re-interpretation is used as the starting point for a "conditional dynamic" sub-filter model in which the stabilization procedure is based on filtering conditionally on scalar fields. Both the traditional and conditional models are applied to a turbulent flame; results suggest that the two models perform similarly, although performance of both is sub-optimal in the case considered. The final, two-part, study is based around the suggestion that, with sufficient conditioning, conditionally-filtered fields should be independent of position. It is found that assuming this uniformity produces a novel turbulence-chemistry interaction model, termed the Uniform Conditional State (UCS) model, in which the conditional scalar dissipation model is the key un-closed parameter. The UCS model is applied to a series of turbulent non-premixed flames, and is found to predict their properties to good accuracy, with details showing some sensitivity to the conditional scalar dissipation model.

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Turbulent premixed combustion simulation with Conditional Source-term Estimation and Linear-Eddy Model formulated PDF and SDR models (2017)

Computational fluid dynamics (CFD) is indispensable in the development of complex engines due to its low cost and time requirement compared to experiments. Nevertheless, because of the strong coupling between turbulence and chemistry in premixed flames, the prediction of chemical reaction source terms continues to be a modelling challenge. This work focuses on the improvement of turbulent premixed combustion simulation strategies requiring the use of presumed probability density function (PDF) models. The study begins with the development of a new PDF model that includes the effect of turbulence, achieved by the implementation of the Linear-Eddy Model (LEM). Comparison with experimental burners reveals that the LEM PDF can capture the general PDF shapes for methane-air combustion under atmospheric conditions with greater accuracy than other presumed PDF models. The LEM is additionally used to formulate a new, pseudo-turbulent scalar dissipation rate (SDR) model. Conditional Source-term Estimation (CSE) is implemented in the Large Eddy Simulation (LES) of the Gülder burner as the closure model for the chemistry-turbulence interactions. To accommodate the increasingly parallel computational environments in clusters, the CSE combustion module has been parallelised and optimised. The CSE ensembles can now dynamically adapt to the changing flame distributions by shifting their spatial boundaries and are no longer confined to pre-allocated regions in the simulation domain. Further, the inversion calculation is now computed in parallel using a modified version of an established iterative solver, the Least-Square QR-factorisation (LSQR). The revised version of CSE demonstrates a significant reduction in computational requirement — a reduction of approximately 50% — while producing similar solutions as previous implementations. The LEM formulated PDF and SDR models are subsequently implemented in conjunction with the optimised version of CSE for the LES of a premixed methane-air flame operating in the thin reaction zone. Comparison with experimental measurements of temperature reveals that the LES results are very comparable in terms of the flame height and distribution. This outcome is encouraging as it appears that this work represents a significant step towards the correct direction in developing a complete combustion simulation strategy that can accurately predict flame characteristics in the absence of ad hoc parameters.

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Numerical Simulation of Turbulent Premixed Flames with Conditional Source-Term Estimation (2012)

Conditional Source-term Estimation (CSE) is a closure model for turbulence-chemistryinteractions. This model is based on the conditional moment closure hypothesis for the chemical reaction source terms. The conditional scalar field is estimated by solving an integral equation using inverse methods. CSE was originally developed for - and has been used extensively in- non-premixed combustion. This work is the first application of this combustion model to predictive simulations of turbulent premixed flames. The underlying inverse problem is diagnosed with rigorous mathematical tools. CSE is coupled with a Trajectory Generated Low-Dimensional Manifold (TGLDM) model for chemistry. The CSE-TGLDM combustion model is used with both Reynolds-Averaged Navier-Stokes (RANS) and Large-Eddy Simulation (LES) turbulence models to simulate two different turbulent premixed flames. Also in this work, the Presumed Conditional Moment (PCM) turbulent combustion model is employed. This is a simple flamelet model which is used with the Flame Prolongation of ILDM (FPI) chemistry reductiontechnique. The PCM-FPI approach requires a presumption for the shape of the probability density function of reaction progress variable. Two shapes have been examined: the widely used beta-function and the Modified Laminar Flamelet PDF (MLF-PDF). This model is used in both RANS and large-eddy simulation of a turbulent premixed Bunsen burner. Radial distributions of the calculated temperature field, axial velocity and chemical species mass fraction have been compared with experimental data. This comparison shows that using the MLF-PDF leads to predictions that are similar, and often superior to those obtained using the beta-PDF. Given that the new PDF is based on the actual chemistry - as opposed to the ad hocnature of the beta-PDF - these results suggest that it is a better choice for the statistical description of the reaction progress variable.

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The Development of Optical Measurement Techniques for Gas Species and Surface Temperature on a Planar SOFC Methane-Stream Reformer (2011)

This thesis presents the development of an experimental apparatus and methods to allow the application of gaseous Raman spectroscopy to the challenging and original application of a small-scale, high-temperature methane/steam reformer developed to be representative of the technologies used in solid oxide fuel cell (SOFC) applications. The research is placed in the context of global energy trends and SOFC’s, with specific reference to the challenges related to directly internally reforming medium-temperature SOFC’s and the case for the development of non-intrusive measurement techniques for gas species and temperature is made. The practical aspects of the development of the broadband 308 nm Raman system are examined and previous works in this area are highlighted. The excitation light source is evaluated, the use of a liquid potassium hydrogen phthalate filter as a means to reduce Rayleigh line effects is demonstrated, and background fluorescence suppression through polarization of the 308 nm light source is presented. The arrangements of the experimental set-up, gas supply, metering, and humidification are shown, as are the optical arrangements for laser sheet formation and light collection. A description of the calibration experiments, procedures, and methodologies that are used to define the normalised relative differential Raman scattering cross sections of the major species of interest in this study is presented. The observation of an unexpected leakage of air into the reformer is described and a hypothesis is presented to explain the ingress of air. Finally, results are presented that describe the response of the optically-accessed reformer to variations in; operating temperature, humidification factor, total volume flow rate, methane volume flow rate, and the methane residency time within the reformer channel. From these results it was possible to conclude that increased reformer temperature increased reaction rate, increased gas residency time in the channel increased hydrogen production, and reactant streams with higher inlet mole fractions of methane resulting in increased reaction rates and amounts of hydrogen production. The performance of the reformer rig and the suitability of optical diagnostic techniques to the application of a SOFC scale reformer are discussed.

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Master's Student Supervision (2010 - 2018)
Combustion modelling in spark-ignition engines using conditional source-term estimation (2013)

Conditional Source-term Estimation (CSE) is a chemical closure model for the simulation of turbulent combustion. In this work, CSE has been explored for modelling combustion phenomena in a spark-ignition (SI) engine. In the arbitrarily complex geometries imposed by industrial design, estimation of conditionally averaged scalars is challenging. The key underlying requirement of CSE is that conditionally averaged scalars be calculated within spatially localized sub-domains. A domain partitioning algorithm based on space-filling curves has been developed to construct localized ensembles of points necessary to retain the validity of CSE. Algorithms have been developed to evenly distribute points to the maximum extent possible while maintaining spatial locality. A metric has been defined to estimate relative inter-partition contact as an indicator of communication in parallel computing architectures. Domain partitioning tests conducted on relevant geometries highlight the performance of the method as an unsupervised and computationally inexpensive domain partitioning tool.In addition to involving complex geometries, SI engines pose the challenge of accurately modelling the transient ignition process. Combustion in a homogeneous-charge natural gas fuelled SI engine with a relatively simple chamber geometry has been simulated using an empirical model for ignition. An oxygen based reaction progress variable is employed as the conditioning variable and its stochastic behaviour is approximated by a presumed probability density function (PDF). A trajectory generated low-dimensional manifold has been used to tabulate chemistry in a hyper-dimensional space described by the reaction progress variable, temperature and pressure. The estimates of pressure trace and pollutant emission trends obtained using CSE accurately match experimental measurements.

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