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Transcript of 1 Breeding a Better Stove the use of Genetic Algorithms and Computational Fluid Dynamics to Improve...
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Breeding a Better Stovethe use of Genetic Algorithms and Computational Fluid Dynamics to Improve Stove Design
H Burnham-Slipper MJ CliffordSJ Pickering
IntroductionAppropriate and Inappropriate StovesExperimental WorkComputer Modelling
CFDGenetic Algorithm
ResultsConclusions
Outline
Global problem – half the world cooks on wood burning stoves
Indigenous stoves can be inefficient, dangerous, smoky, hazardous to health
Introduced stoves can be unpopular
Our approach is to combine local indigenous knowledge and preferences with advanced computer modelling techniques to develop an improved stove for use in Eritrea
Introduction / Motivation
Appropriate and Inappropriate Stoves
Classic Eritrean mogogo – smoky, inefficient, but free
Eritrea Research and Training Center Mogogo - $40
Appropriate and Inappropriate Stoves
MIRT – improved efficiency, but developed in Ethiopia. “The stove of our enemies”
Appropriate and Inappropriate Stoves
Aprovecho design – improved efficiency, but heavy use of material and poor thermal distribution
Appropriate and Inappropriate Stoves
CleanCook alcohol stove – unfamiliar technology and materials. Unsuitable for cooking injera
Appropriate and Inappropriate Stoves
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Experimental Set-up
Experimental aim: – mass-rate data– temperature data
Apparatus:– regular wood cribs– mass balance– K-type
thermocouples– extractor hood– a tiny bit of fire-
lighter
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Experimental Results
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Numerical Model FormulationAssume:
– char combustion limited by diffusion of oxygen through species boundary layer
– volatile release limited by conduction of heat through char layer
– volatiles burn in air, limited by turbulent mixing
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Numerical Model Formulation
Fluent 6.2 CFD code:– buoyancy-driven
flow– k-ε turbulence
model– species transport– DO radiation model– UDF fuel model– lumpiness
function
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Numerical Model Results
Fluent 6.2 CFD code:– burn-rate agrees with
experimental– temperature & velocity
fields agree with experiment & literature
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Stove Modelling
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Stove Characterisation
Aprovecho rocket, HBS rocket, mogogo, 3-stone firewith & without grate
Stoves have evolved over hundreds (maybe thousands) of years
There may be good reasons why stoves are the way they are
A genetic algorithm can speed up the natural evolution of stove design
Genetic Algorithm
Genetic Algorithm
Take two stoves
Allow the stoves to mate
Define ten children (new stoves) using randomly selected genes from parent stoves
Test the efficiency of the new stoves using CFD
Discard all but the best two stoves
Repeat
(The method can be adapted to include genetic abnormalities / random mutations)
Genetic Algorithm
Genetic Algorithm Progress
Genetic Algorithm Result
Conclusions and Further Work
Engineers need to take many factors into account when designing stoves
Respecting local stoves and building on indigenous knowledge is vital if a new design is to be successful
Combining genetic algorithms and CFD represents a novel approach to stove design, mimicking the natural evolution of stoves
It remains to be seen if the new design can be manufactured and tested, we also have a lot of field work to do