Koji Kuramoto

An artificial neural network as a model for chaotic behavior of a three-phase fluidized bed

Abstract Non-linear hydrodynamic behavior of bubble motion and that of particle motion in a three-phase fluidized bed have been modeled by resorting to an artificial neural network (ANN). The experiments were performed in a transparent acrylic resin column with an inner diameter of 0.184 m and a height of 2.0 m. Subsequently, the ANN was trained with the time-series data comprising temporal intervals, each of which was the period between two sequential signals of bubbles or particles from an optical transmittance probe. By successively adapting its output to input, the ANN has regenerated time-series data at any superficial gas velocity, Ug, thereby yielding the bifurcation diagrams of both bubble and particle motion. These diagrams exhibit complex behavior over a wide range of Ug, thus demonstrating that the ANN is capable of predicting and modeling non-linear dynamics of three-phase fluidized beds often behaving chaotically.

Coal gasification with a subcritical steam in the presence of a CO2 sorbent: products and conversion under transient heating

Pulverized Taiheiyo coal (Japanese subbituminous coal) was gasified with steam in the presence of CO2 sorbent (Ca(OH)2) under relatively high pressure (approximately 20 MPa; subcritical condition) using a tubing-bomb microreactor (TB reactor). The transient characteristics in the conversion of coal and the formation of gaseous products during the gasification were investigated. During initial heating period, 40–50 wt.% of the coal initially loaded was rapidly converted to gas or tar. In the presence of Ca(OH)2, the yield of gaseous products was apparently increased owing to the catalytic effects of Ca(OH)2 on coal gasification. No CO2 was observed in the produced gas at any soaking time in the gasification with Ca(OH)2, suggesting that CO2 sorption by Ca(OH)2 took place effectively under high-pressure conditions. A rigid agglomeration of char and CO2 sorbent was observed at relatively high temperature, which is attributed to the formation of melts of the CO2 sorbent.

Effects of Impurities Contained in Coal-Derived Syngas on the Performance of SOFCs

Power generation tests using a single-cell SOFC fueled by coal-derived syngas were conducted under a constant voltage of -0.8 V versus air (reference). The syngas was produced in the steam gasification of pulverized coal in a laboratory-scale fluidized-bed gasifier and was supplied to SOFC anode with different gas cleaning conditions: with/without filtrations and water washing. It was possible to generate the electrical current by the coal-derived syngas for several hours and we found that the degradation behavior of SOFC anode was notably affected by gas cleaning conditions. A SEM-EDX analysis confirmed that the micro-scale change in morphology of SOFC anode occurred due to the sintering of Ni particles over the anode layer, suggesting that eutectic melting of Ni might be enhanced by some impurities contained in the coal derived syngas.

Estimation of thermodynamic properties of liquid fuel from biomass pyrolysis

Estimation method for thermodynamic properties of organics in liquid fuel are proposed in this work. Especially this method can be applied to bio-oil produced from biomass pyrolysis. Thermodynamic properties of more than 600 compounds, which can be obtained in NIST chemistry webbook, were investigated for the estimation of thermodynamic properties. Simple estimation methods for the heat capacity and heating value are successfully provided with only the elemental composition of unknown compounds.