Biomass is a renewable energy resource and its utilization has received great attention due to its life cycle carbon-neutrality and the... Show moreBiomass is a renewable energy resource and its utilization has received great attention due to its life cycle carbon-neutrality and the potential to substitute fossil fuel to produce a variety of energy-related products. Thermochemical gasification is an important route for conversion of biomass that results in a product gas mainly consisting of H2, CO, CO2, CH4 and other light hydrocarbons that can be used as fuel gas to generate power, or as well as raw material to produce a variety of chemicals. Among the existing gasifiers, fluidized beds (FB) offer many advantages such as high conversion efficiency and great flexibility over types of feedstock.More than 200 data sets of biomass gasification in fluidized bed were collected featuring a wide range of operating condition and fuel types. An axiom-based reasoning was used to develop a multiphase statistical pathway needed as a precondition to effectively quantify the entanglements of different important factors in the process.Specifically, by creating an interconnected chain of analysis based on trigonometric functions, geometric projections, and design of a statistical inference tool utilizing neural network units, multiple partial measures of associations between biomass constituents, and operating condition were effectively consolidated and embedded in a single characteristic matrix that consequently led to detection of monotonic relationships for prediction of carbon conversion efficiency and product gas yield. The black box model in comparison to three different models showed better accuracy in predicting four major components of product gas, over the largest applicable range of all the influential parameters of the process, namely, temperature, air equivalent ratio, steam to biomass ratio, and type of fuel. In part of our methodology, we introduce a novel technique for obtaining a dynamical property value for stationary objects, based on a “specific computational time” of an “abstract mechanical operation on characteristics matrices”. The specific computational time (sct) showed excellent capability in capturing the non-equilibrium factor of the process which itself was function of several interrelated variables. Show less
