Simulation and optimization of a solar dryer
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Date
2005
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CCSHAU
Abstract
On clear days or cloudless skies, the predicted solar radiation by ASHRAE
method was about 20 per cent higher than the observed value. Thus for prediction of
solar radiation at Hisar a clearness number of 0.8 was taken for estimation of solar
radiation. There was a close agreement between the observed and predicted values of
solar radiation for different seasons at Hisar when the clearness number was taken as
0.8.
During summer maximum solar radiation was predicted when the south facing
collector was tilted at 10-15°C from horizontal and during winter the maximum solar radiation was observed at about 50° tilt from horizontal. However, it becomes difficult
for the users to modify the tilt according to seasons. Thus for maximum solar
radiation collection, a collector tilt of 30°C (latitude of place) was taken for the design
of solar collector..
A computer based mathematical model was developed for a solar dryer for
predicting solar radiation, drying air temperature, product temperature in trays,
moisture removal rate and drying efficiency. The developed model was used for
studying the performance of solar dryer and was tested for its validation. No
significant difference was obtained between the observed and predicted values. On the
basis of design data, a natural convection solar dryer was got fabricated for drying of
fruits and vegetables. The capacity of dryer was about 20 kg and the collector area
was 2 m2.
Average collector outlet temperature during no-load testing was comparatively
higher than that of collector temperature during load testing and there was little
variation of collector temperature between the predicted and observed values.
From the experimental studies, it was observed that the cauliflower dried in 14
hrs (2 days) from initial moisture content of 82.02 per cent (wb) to final moisture
content of 10.26 per cent (wb).
It was seen that for drying of less quantity of product natural circulated air is
sufficient and for drying of large amount of product, external source like blower or fan
is required.
Therefore, the developed mathematical model can be used to predict the dryer
performance at different places by changing the input data only.