Lin Ma’s research while affiliated with The University of Sheffield and other places

When undertaking wind assessment around buildings using large eddy simulation (LES), the implementation of the integral length scale at the inlet for inflow generation is controversial, as real atmospheric length scales require huge computational domains. While length scales significantly influence inflow generation in the domain, their effect on the downstream flow field has not yet, been investigated. In this paper, we validate the effectiveness and accuracy of implementing a reduced turbulence integral length scale for inflow generation in LES results at the rooftop of low-rise buildings and develop a technique to estimate the real local length scales using simulation results. We measure the wind locally and calculate the turbulence length scales from the energy spectrum of the wind data and simulation data. According to these results, there is an excellent agreement between the length scale from simulation and measurement when they are scaled with their corresponding freestream/inlet value. These results indicate that a reduced integral length scale can be safely used for LES to provide a reliable prediction of the energy spectrum as well as the length scales around complex geometries. The simulation results were confidently employed to obtain the best location for a wind turbine installation on low-rise buildings.

The tendency of ash particles to stick under high temperatures is dictated by the ash chemistry, particle physical properties, deposit surface properties and furnace operation conditions. A model has been developed in order to predict the particle sticking efficiency for fly ash deposition at high temperatures. The model incorporates the particle properties relevant to the ash chemistry, particle kinetic energy and furnace operation conditions and takes into consideration the partial sticking behaviour and the deposit layer. To test the model, the sticking behaviours of synthetic ash in a drop tube furnace are evaluated and the slagging formation from coal combustion in a down-fired furnace is modelled. Compared with the measurements, the proposed model presents reasonable prediction performance on the particle sticking behaviour and the ash deposition formation. Through a sensitivity analysis, furnace operation conditions (velocity and temperature), contact angle and particle size have been found to be the significant factors in controlling the sticking behaviours for the synthetic ash particles. The ash chemistry and furnace temperature dictate the wetting potential of the ash particles and the melting ability of the deposit surface; particle size and density not only control the particle kinetic energy, but also affect the particle temperature. The furnace velocity condition has been identified as being able to influence the selective deposition behaviour, where the maximum deposition efficiency moves to smaller particles when increasing the gas velocity. In addition, the thermophoresis effect on the arrival rate of the particles reduces with increasing the gas velocity. Further, increasing the melting degree of the deposit layer could greatly enhance the predicted deposition formation, in particular for the high furnace velocity condition.

Correct prediction of the recovery of wind turbine wakes in terms of the wind velocity and turbulence downstream of the turbine is of paramount importance for the accurate simulations of turbine interactions, overall wind farm energy output and the impact to the facilities downstream of the wind farm. Conventional turbulence models often result in an unrealistic recovery of the wind velocity and turbulence downstream of the turbine. In this paper, a modified k – ω turbulence model has been proposed together with conditions for achieving a zero streamwise gradient for all the fluid flow variables in neutral atmospheric flows. The new model has been implemented in the simulation of the wakes of two different wind turbines and the commonly used actuator disk model has been employed to represent the turbine rotors. The model has been tested for different wind speeds and turbulence levels. The comparison of the computational results shows good agreement with the available experimental data, in both near and far wake regions for all the modeled wind turbines. A zero streamwise gradient has been maintained in the far wake region in terms of both wind speed and turbulence quantities.

Biochemical reactions occurring during anaerobic digestion have been modelled using reaction kinetic equations such as first-order, Contois and Monod which are then combined to form mechanistic models. This work considers models which include between one and three biochemical reactions to investigate if the choice of the reaction rate equation, complexity of the model structure as well as the inclusion of inhibition plays a key role in the ability of the model to describe the methane production from the semi-continuous anaerobic digestion of green waste (GW) and food waste (FW). A parameter estimation method was used to investigate the most important phenomena influencing the biogas production process. Experimental data were used to numerically estimate the model parameters and the quality of fit was quantified. Results obtained reveal that the model structure (i.e. number of reactions, inhibition) has a much stronger influence on the quality of fit compared with the choice of kinetic rate equations. In the case of GW there was only a marginal improvement when moving from a one to two reaction model, and none with inclusion of inhibition or three reactions. However, the behaviour of FW digestion was more complex and required either a two or three reaction model with inhibition functions for both ammonia and volatile fatty acids. Parameter values for the best fitting models are given for use by other authors.