Fuel production models

Pex, P.P.A.C. and Y.C. van Delft, Silica membranes for hydrogen fuel production by membrane water gas shift reaction and development of a mathematical model for a membrane reactor, in Carbon Dioxide Capture for Storage in Deep Geologic Formations—Results from the C02 Capture Project Capture and Separation of Carbon Dioxide from Combustion Sources, eds., D. Thomas, and B. Sally, Vol. 1, Chapter 17, 2005. 

The present research has treated important parts of the modeling of combustion and NOx formation in a biomass grate furnace. All parts resulted in useful approaches. For all these approaches successful first steps were taken. Currently, more research is underway to obtain improved results NH3 production is measured in the grid reactor with the tunable diode laser, detailed kinetics will be attached to the front propagation model, including the measured NH3 release functionalities, and for the turbulent combustion model heat losses are taken into account. In addition, the fuel layer model has to be coupled to the turbulent combustion model in the furnace. 

The importance of materials characterization in fuel cell modeling cannot be overemphasized, as model predictions can be only as accurate as their material property input. In general, the material and transport properties for a fuel cell model can be organized in five groups (1) transport properties of electrolytes, (2) electrokinetic data for catalyst layers or electrodes, (3) properties of diffusion layers or substrates, (4) properties of bipolar plates, and (5) thermodynamic and transport properties of chemical reactants and products. 

Of the several approaches that have been used to calculate fuel generation rates from solid materials in CFD-based fire growth calculations, the simplest are empirical models. Instead of attempting to model the physical processes that lead to gaseous fuel production inside decomposing solids, empirical data that can be measured (transient heat release or mass loss rate) or inferred (heat of gasification) from common bench-scale fire tests such as the Cone Calorimeter are used to characterize fuel generation processes. 

Production costs per tonne of base oil are calculated by dividing the total annual costs by the total annual production of base oils. Net feedstock cost can be calculated in several ways, but it will not necessarily be identical to the cost of crude oil. As the base oil plant in a sense competes with fuel production units for feedstock, the basic feedstock cost to the lubricant base oil complex should be determined by the alternative value of that feedstock if it were used to make mainstream fuels products. The by-products of base oil manufacture also have values for blending into fuel streams or in some cases for direct sale as speciality products, such as waxes and bitumen. Credit must be given for these products so that the net value of the hydrocarbon content of the base oil can be calculated. Refineries use sophisticated linear programming computer models to optimise refinery operations based on different crude oil input, process yields, market prices, production targets, etc. 

Fuel cells may be slow in coming. Fuel cell stacks are feasible in commercial form and the projected date of 2010 is a time DaimlerChrysler is comfortable with, after years of research and development. Complex fuel processors that can handle gasoline, like the system developed by Arthur D. Little, have been proved to work, but actual production models are still being developed. 

WTW results depend heavily on the assumptions regarding fuel production efficiencies and fuel-cell vehicle fuel economy. The GREET model can readily test alternative assumptions and provide WTW energy and emission results. 

Biomass Fuel Product Demand (Model Results)... 

M. King Hubbert s Resource Model (Hubbert, 1981), which I will call the HR Model, will be used to project fossil fuel production into the future. Projections of future fossil fuel production will be converted to CO2 emissions. There is a 3-month lag between fossil fuel production and use, which is negligible compared to the time frame of this study. In the simplest sense, the HR Model for an exhaustible resource shows the production curve will rise to some peak and them come back down, eventually to zero. The area under the production curve is the ultimate cumulative production of the resource. An aggressive rise in the future fossil fuel production curve will be chosen to set an upper limit for future atmospheric CO2 levels. 

For the purpose of developing the long-term projections in this paper, all fossil fuel resource data used will be that available in 1993 and projections shown in the figures start at 1990. Published data from 1990 to 2001 for anthropogenic CO2 emissions and atmospheric CO2 levels will be used to test the model. The cumulative production of world fossil fuel (oil, gas and coal) and a projection into the future are shown in Fig. 1. The projection was made using the HR Model (Hubbert, 1981) and is based on known, proved reserves only. The total area under the curve in Fig. 1 is47,330 quads (Barabba, 1989 Taylor, 1989 Kilgore, 1993 West, 1993). The curve in Fig. 1 will be used to develop the low estimate of fossil fuel production. 

Kim, Y., Yun, C., Park, S. B., Park, S., and Fan, L. An integrated model of supply network and production planning for multiple fuel products of multi-site refineries. Computers Chemical Engineering, 32(11) 2529 - 2535, 2008. 

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