Study On Gasification Characteristics Of Biomass Catalytic Cracking

Using sawdust as biomass raw material, the catalytic cracking characteristicswere investigated in a home-made two-stage fixed bed reactor. By means of theexperiment data, the effects of experiment conditions on the apparent activationenergy were analyzed; then the study which catalysts and experiment conditionaffected gas energy yield was also conducted; the last the Artificial Neural Network(ANN) models were established for simulation and prediction of biomass catalyticcracking.At first, using low-cost porous clinker catalysts (the porous high-clay clinker andthe porous high-alumina clinker), the catalytic cracking experiments were conductedat different conditions, such as gasificated liquids, pyrolysis temperature, particlediameter of material, catalyst size, and steam input or not, et al. The results show thatthe porous high-clay clinker has much lower effective than porous high-aluminaclinker on tar conversation on same pyrolysis temperature whether steam input or not;the gasification characteristics with steam were improved; the particle diameter ofmaterial has little influence on catalytic effect, compare with larger diameter ofbiomass material, the diameter of0.1~1mm biomass material was beneficial tocatalytic cracking; the smaller catalyst size of1~3mm has positive influence oncatalytic cracking.For analyzing biomass catalytic cracking characteristics in theory, reactionkinetic model has been established, and the kinetic parameters have been obtained.The results show that the apparent activation energy without using catalyst is largestamong the three conditions. The apparent activation energy become smaller afterusing porous high-alumina clinker as catalyst, which indicate that poroushigh-alumina clinker was beneficial to tar catalytic cracking. The apparent activationenergy is the smallest under using porous high-alumina clinker as catalyst and steaminput, it shows that this condition is more beneficial to tar catalytic cracking.The purpose of this chapter was to get high gas energy yield by catalytic cracking reaction of biomass. The tar conversion rate and gas energy yield wereinvestigated with the special coke, calcined dolomite, and porous high-aluminaclinker as catalysts. The results show that the special coke is the most effective amongthree kinds of catalysts, catalytic effect of dolomite is worse than the special coke andporous clinker is the worst. Gas energy yield is the highest when the special coke isused; and the gas energy yield using dolomite as catalyst is higher than that of porousclinker. The microstructure of catalysts was observed by scanning electronmicroscopy (SEM), and the influence of catalyst's microstructure on gas energy yieldwas studied, it can conclude that activity of catalyst is influenced by surface area,porosity, pore size distribution and disorder degree of pore structure, etc.Microstructure of catalysts greatly influences gas energy yield of biomass.For predicting biomass catalytic cracking gasification characteristics, three kindsof BP Artificial Neural Network (ANN) models had been set up. Model1: usingpyrolysis temperature and cracking temperature as input variables under the conditionof using porous clinker as catalyst; Model2: using specific surface area and crackingtemperature as input variables under the condition of using calcined dolomite ascatalyst; Model3: using S/B value and cracking temperature as input variables underthe condition of using the special coke as catalyst. The max relative errors of Model1,Model2and Model3were1.9601%,－8.6932%and8.0022%respectively. Theresults show that the three kinds of ANN models were effective for simulation andprediction of biomass catalytic cracking gasification characteristics in certaincondition.