The present work examines the NO x emission characteristics of a premixed micro-combustion system with a perforated plate implemented. For this, a three-dimensional (3D) computational model involving a detailed chemical-kinetic mechanism for ammonia-oxygen combustion in the micro-combustor is developed. The model is first validated with the experimental measurements available in the literature before conducting comprehensive analyses. It is found that implementing a perforated plate in the micro-combustion system creates a flow recirculation zone downstream characterized by a low flame temperature and combustion speed. Meanwhile, the conjugate heat transfer between the combustion products and the inner combustor walls is shown to play a key role in the NO generation by relocating the flame in the axial direction and thus changing the chemical reaction rate. Furthermore, the preferential diffusion caused by the variation in the mass diffusivity of different species and the two-dimensionality flow is identified to vary significantly in comparison with the case in the absence of the perforated plate, especially in the vicinity of the recirculation zone. This diffusion effect results in the considerable drop in the N/O atomic ratio, primarily due to the reduction and increase of O 2 and H 2 O, together with less available N 2 , and consequently affecting the NO generation rate. This work confirms that the flow field, the conjugate heat transfer as well as the preferential diffusion effect could be regarded as the potential mechanisms leading to the NO x emission variation in the recirculation zones. Nomenclature 3Dthree-dimensional specific heat of species, CO carbon monoxide CO 2 carbon dioxide CH 4

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To improve the fast and stable walking ability of a humanoid robot, this paper proposes a gait optimization method based on a parallel comprehensive learning particle swarm optimizer (PCLPSO). Firstly, the key parameters affecting the walking gait of the humanoid robot are selected based on the natural zero-moment point trajectory planning method. Secondly, by changing the slave group structure of the PCLPSO algorithm, the gait training task is decomposed, and a parallel distributed multi-robot gait training environment based on RoboCup3D is built to automatically optimize the speed and stability of bipedal robot walking. Finally, a layered learning approach is used to optimize the turning ability of the humanoid robot. The experimental results show that the PCLPSO algorithm achieves a quickly optimal solution, and the humanoid robot optimized possesses a fast and steady gait and flexible steering ability.

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