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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