The hot blast stove is one of the most important equipment devices in the blast furnace iron making process. The temperature and duration of hot air are the crucial parameters to assess the performance of the hot blast stove. In order to sustain the desired high temperature air, it requires rapid completed combustion reaction, stable flue gas flow structure, and uniform temperature distribution throughout the regenerator. In the present work, a 3D numerical model with all essential turbulence, heat transfer, and combustion considerations has been developed to assess the performance of a typical hot air stove. The flow field of the whole domain and temperature distribution within the regenerator were simulated using the model. The predicted results show that the velocity at each nozzle varies substantially due to the uneven pressure distribution in cavity of the traditional hot blast stove, generating the eccentric vortex that leads to nonuniform temperature distribution in the regenerator. In order to solve this problem, a new structure design of top combustion regenerative hot blast stove is proposed. Numerical simulations were then carried out to compare based on the performance of the new hot blast stove design against the traditional hot blast stove.

This paper puts forward one kind of air-fuel ration control method which integrates improved Elman neural network with normal PI control.It constructs a model of the single LPG electro-plating engine and simulation platform for air-fuel ration controlling with GT-Power software which seamless connect to Matlab/Simulink based on JL1P39FMB single cylinder engine and develop the electronic fuel-injected controller based on Intel MCS-96. It also constructs mini LPG electro-plating engine experiment system for air-fuel ration to the LPG Injection System and adopt the new inlet channel injection type of duty ratio controlling injector. Help the throttle percentage-rev- duty cycle pulse spectrum diagram after the calibration bench experiment for the best duty cycle of mini electronic LPG-injected under the steady working conditions. It predicts the air-fuel ration signals of nontransmission delay through the Elman neural network. The normal PI controller which deals with the predictive signals implements