Biomedical Engineering Reference
In-Depth Information
most effective tools for this purpose. Engineering optimization involves opti-
mizing the reactor configuration to enhance its operability, maintainability,
and cost reduction.
8.11.1 Process Optimization
Process optimization enhances gasifier performance in terms of the following
indicators:
Cold- and hot-gas efficiency
Unconverted carbon and tar concentration in the product gas
Composition and heating value of the product gas
One can approach optimization either through experiments or through
kinetic modeling.
Experiments are the best and most reliable means of optimizing process
parameters, as they are based on the actual or prototype gasifier. However,
they have several limitations and are expensive. Furthermore, practical
difficulties may not allow all operational parameters to be explored. An
alternative is to conduct tests in a controlled laboratory-scale unit and to
calibrate the resulting data to the full-scale unit. This allows the scale-up of
data from the laboratory to the full-scale unit with a reasonable degree of
confidence.
8.11.1.1 Optimization Through Kinetic Modeling
With a kinetic model, we can predict the performance of a gasifier already
designed because it utilizes both configuration and dimensions of the reactor.
Kinetic modeling can help optimize or fine-tune the operating parameters for
best performance in a given situation. Section 7.6 describes a kinetic model
for gasifiers.
8.12 PERFORMANCE AND OPERATING ISSUES
Gasifier performance is measured in terms of both quality and quantity of
gas produced. The amount of biomass converted into gas is expressed by
gasification efficiency. The product quality is measured in terms of heating
value as well as amount of desired product gas.
8.12.1 Gasification Efficiency
The efficiency of gasification is expressed as cold-gas efficiency, hot-gas
efficiency, or net gasification efficiency. These are described in the follow-
ing subsections:
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