Jun Kobayashi

High temperature air-blown woody biomass gasification model for the estimation of an entrained down-flow gasifier

A high temperature air-blown gasification model for woody biomass is developed based on an air-blown gasification experiment. A high temperature air-blown gasification experiment on woody biomass in an entrained down-flow gasifier is carried out, and then the simple gasification model is developed based on the experimental results. In the experiment, air-blown gasification is conducted to demonstrate the behavior of this process. Pulverized wood is used as the gasification fuel, which is injected directly into the entrained down-flow gasifier by the pulverized wood banner. The pulverized wood is sieved through 60 mesh and supplied at rates of 19 and 27kg/h. The oxygen-carbon molar ratio (O/C) is employed as the operational condition instead of the air ratio. The maximum temperature achievable is over 1400K when the O/C is from 1.26 to 1.84. The results show that the gas composition is followed by the CO-shift reaction equilibrium. Therefore, the air-blown gasification model is developed based on the CO-shift reaction equilibrium. The simple gasification model agrees well with the experimental results. From calculations in large-scale units, the cold gas is able to achieve 80% efficiency in the air-blown gasification, when the woody biomass feedrate is over 1000kg/h and input air temperature is 700K.

A new method for identifying rigid link models of lower limbs

A new method for identifying rigid link models of human lower limbs has been proposed in this paper. The method was motivated by necessity of simulating human body movements for rehabilitation or for design of assistive devices. The method is based on combination of random search and least squares estimation techniques. Simulation and experimental results are given to illustrate the effectiveness of the proposed method.

A new method for identifying rigid link model of lower limb

A new method for identifying rigid link models of human lower limbs has been proposed in this paper. The method was motivated by necessity of simulating human body movements for rehabilitation or for design of assistive devices. The method is based on combination of random search and least squares estimation techniques. Simulation and experimental results are given to illustrate the effectiveness of the proposed method.