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adapted based on the abilities and needs of patients. Moreover, automatic intelligent algorithms will be developed in to make the control intuitive, natural and adaptive. Such that the model can learn new
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an emerging waste recovery and treatment technology using advanced gasification processes that can recover the useful materials in the waste in addition to harvesting the energy. Computational modelling will be
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and computational modelling. A failed pitch bearing raceway will be destructively investigated to characterise the surface and subsurface damages using optical microscopy (OM) and scanning electron
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has been used on large scale biogas plants but the optimal operation has not been fully investigated. Existing validated models will be used to design the process conditions to give optimal conversion
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Research and Innovation Network. There will be the opportunity to develop models of these initiation processes in parallel with the experimental investigation. Funding Notes 1st or 2:1 degree in Engineering
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the wind farm to reduce the turbine wake effects and maximize the wind farm power output. Advanced mathematical and computational fluid dynamics modeling techniques will be employed with supplementary
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of the aerodynamics of the turbine blades which have a significant impact on the efficiency of power generation, the level of noise produced and the durability of the wind turbine. Advanced computational fluid dynamics
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on and closely linked to existing research on the aerodynamics of the wind turbines. Advanced computational fluid dynamics modeling techniques will be employed to analyse the aerodynamic response
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experimental and computer modelling techniques. The research is expected to fill the important gaps in knowledge of combustion of low volatile coal and potentially lead to innovative designs of burners
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Ava Shahrokhi Application Deadline: Applications accepted all year round Details Computational Wind Engineering has been developing rapidly over the last couple of decades. Among the numerical