Computer Aided Thermal Design of a Solar Dryer

COMPUTER AIDED THERMAL DESIGN FOR A
SOLAR DRYER
PROJECT REPORT

SUBMITTED BY:

Achal Gupta
(2005AE01BIV)
B.TECH (AGRICULTURAL ENGINEERING)

Project Advisor:
Dr. Y. K. Yadav
DEPARTMENT OF AGRICULTRAL, PROCESSING AND
ENERGY
COLLEGE OF AGRICULTURAL ENGG. & TECH.
CCS HARYANA AGRICULTURAL UNIVERSITY
HISAR-125004
2009

CERTIFICATE

This is to certify that this project entitled, “Computer Aided Thermal Design of a Solar
Dryer” submitted for Bachelor of Technology in Agricultural Engineering by Mr. Achal Gupta,
Admission No. 2005AE01BIV, is based upon the project carried out by the student for the
project course APE-482 and that no part of the project has been submitted for any other degree
program.

Date: Achal Gupta

(2005AE01BIV)

(DR. Y. K. YADAV ) (DR. Y. K. YADAV )
MAJOR ADVISOR HEAD
DEPTT. OF AGRICULTURAL DEPTT. OF AGRICULTURAL
PROCESSING & ENERGY PROCESSING & ENERGY
COAE&T, CCS HAU COAE&T,CCS HAU
HISAR-125004 HISAR-125004

(DR. M. K. GARG)
DEAN
COAE&T
CCS HAU
HISAR-125004

i

ABSTRACT
Title of Project : Computer Aided Thermal Design for Solar Dryer
Full Name : Achal Gupta
Admission No. : 2005AE01BIV

Title of Degree : Bachelor of Technology (Agricultural Engineering)

Advisor : Dr. Y. K. Yadav
Head, Department of Agricultural Processing and Energy

ASHRAE provides the information for predicting of solar radiations at a particular place
on the specified day for a clear sky. A Computer program was developed using the ASHRAE
model on VISUAL BASIC platform. On clear days or cloudless skies, the predicted solar
radiation by window based computer program using ASHRAE method were found in close
agreement with the observed radiations.

Knowing the drying properties of food products and the solar radiation data estimated by
the model the computer program was extended for the design of solar dryer for a particular
location.

Graphs generated by the program for average daily solar radiations at a particular place
for a day of the year can give a better insight of solar data geometry for that place and could
predict the performance of solar dryer.

Therefore, the developed mathematical model can be used to predict the dryer
performance at different places by using the input data for that location.

Advisor Signature of student

Head of Department

ii

A CK N O W L E D G E M E N T
It is my privilege to express my sincere and deepest gratitude to my major advisor
Dr. Y. K. Yadav Head Department of Agricultural Processing and Energy, for his learned
counsel, proper guidance, continuous encouragement, constructive criticism and untiring
enthusiasm in solving problems encountered during the work and preparation of this report.

I sincerely wish to thank Dr. M. K. Garg, Dean College of Agricultural Engineering &
Technology for providing all the necessary facilities. I am also thankful to Dr. D. K. Sharma
and Er. Surjeet Jain and all the staff members of Department of Agricultural Processing and
Energy for their co-operation and advice.

I bow with reverence to my parents who made innumerable sacrifice for me. I also thank
to all my friends and well wishers who from time to time showed great concern for my entire
project and encouraged me.

Last but not the least I am thankful to all those who helped me directly or indirectly but
whose name do not find a mention in the endeavor.

(Achal Gupta)

iii

CONTENTS

Chapter Description Page(s)
1 Introduction 1-3
2 Review of Literature 4-7
3 Materials and Methods 8-21
4 Results And Discussion 22-29
5 Summary And Conclusions 30
6 References 31-32
Symbols and Abbreviations 33-34
Appendices 35-58

iv

Chapter 1

INTRODUCTION

Drying is a very important method in the processing of food items especially the
preservation of fruits and vegetables. Use of proper drying techniques can significantly
reduce the post-harvest losses of fruits and vegetables. Traditionally drying had been
accomplished by the open sun drying. Then electricity had been used to accelerate the
process of drying by use of tray dryers etc. Open sun drying is still the dominant one
however; there exist many technical problems associated with open sun drying namely
cloudiness and rain, insect infestation, high level of dirt and atmospheric pollution and
intrusions from animals and men. Recently several solar drying techniques and
equipments have been developed for drying various foods. In solar drying method, faster
drying takes place which result a significant reduction in drying time. Product dried in
solar dryer are superior in quality (colour and flavour). Though the same superior quality
product can be obtained by using electricity or electric power, but the electric operations
are expensive and are not within the reach of our rural and tribal population. India

receives enormous amount of solar energy on an average of the order of 5 kWh/m2/day
for about 300 days in a year. Therefore, there is abundant supply of sun’s energy which
can be utilized. With the use of solar dryers there has been a good effort to save the world
from energy crises at the same time being able to attain sustainable development.
Solar dryer is a device for drying agricultural product under controlled conditions.
The controlled drying means controlling the drying parameters like drying air
temperature, humidity, drying rate and air flow rate. A solar dryer must be designed
carefully keeping all the above drying parameters in mind. Since there are many options
in the design of solar dryers, there is large variety of solar dryers. The dryers have been
classified into several categories depending upon the mode of heating or the operational
mode of heat derived from the solar radiations, and its subsequent use to remove the

1

moisture from the wet product. The solar dryers may be classified in the 3 categories: e.g.
direct type dryer, indirect type solar Dryer and forced circulation type dryers or continues
flow type dryers.
In the direct type solar dryer the agricultural product is placed in shallow layer in
an enclosure with a transparent cover. The solar radiations are directly absorbed by the
product itself. The food product is heated up and the moisture from the product
evaporates and goes out by the natural convection these kinds of dryers are popular in the
developing countries. The various problems associated with these simple dryers are; slow
drying, not much control on temperature and humidity, small quantities can be dried and
some products due to direct exposure to the sun change colour and flavor. The example
of these kinds of dryers is: rack or shelf type solar dryer, cabinet type solar dryers and
green house type solar dryers.
In indirect type solar dryer the product is not directly exposed to the solar
radiations. These dryers use a drying chamber where food is placed. The air is heated in a
solar air heater and then blown through the drying chamber. In some of the designs dryers
receive direct solar radiations and also heated air from the solar air heater. In some other
designs, the drying chamber receives hot air only from the air heater. These dryers are
little superior then the direct type because here the drying temperature, humidity and the
drying rates can be controlled to some extent. The considerable manipulation of the
material feed is necessary because the temperature of air coming from the solar collector
changes considerably with time.
In forced circulation dryers hot air is continuously blown over the food product.
The food product itself is loaded or unloaded continuously or periodically. This type of
dryer is comparatively thermodynamically efficient, faster and can be used for drying
large agricultural products.
Information regarding solar energy availability at a particular location is essential
in order to perform any activity regarding management, design and research of solar
appliances. Since the solar radiations availability varies seasonally, daily and hourly as
well as with the orientation, it is necessary to know the optimum orientation for a
particular geographical location considering other climatic parameters that would receive
the maximum solar radiations. In most of the agricultural applications simple flat plate

2

solar collectors are used and optimization of their orientations is important for achieving
maximum effectiveness.
Solar radiations, ambient conditions are different at different places on the earth.
As these all factors affect the drying process in a solar dryer therefore there is a need to
be able to make solar dryers as per the conditions at any particular place so as to get the
maximum possible efficiency. The development of simulation model is a powerful tool
for prediction of performance and can help designers to optimize the dryer geometry at
various operating conditions without having to test experimentally the dryer performance
at each condition. Therefore, the present study is undertaken with the following specific
objectives:
To develop a window based computer program for prediction of solar radiations.
To develop a window based computer program for solar dryer design and its
validation

3

Chapter 2

REVIEW OF LITERATURE

The solar drying is the elaboration of the traditional methods of sun drying to enhance the
effectiveness of drying. Development of simulation model of solar drying is a valuable tool for
prediction of performance of solar drying systems. There has been continuous improvement in
the model and efforts to perfect the drying time and its characteristics. Work done in the past has
been reviewed and described in this chapter.

Threlked and Jordan (1958) provided the values of constants A, B and C for different
month during a year that was used for predicting of solar radiations.

The American Society of Heating, Refrigeration and air-conditioning Engineers
(ASHRAE) (1977) has given a method for estimating the hourly variation of global and diffuse
solar radiation falling on a horizontal surface on a clear day. The equations are based on the
exponential decay model in which the beam radiation decreases with increase in the distance
traversed through the atmosphere.

Pande (1980) developed an improved solar cabinet dryer made up of MS sheet provided
with a glass roof. It was reported that the improved cabinet dryer with chimney is suitable for
drying all types of fruits and vegetables within two to five days.

Athwal and Neal (1981) developed a computer model to predict the solar radiation
intensity at the ground level for a specific spectral region. The daily variations in the atmospheric
water vapour and aerosol contents had introduced errors upto + 10% in the computed radiation
levels.

Mani and Rangarajan (1982) proposed a theoretical model to compute clear sky noon
radiation. The accuracy of the model was found 1% to 2% and 3% to 5% at noon for direct and
diffuse solar radiation respectively.

Venkatesh and Prasad (1982) described the procedure to compute the spectral intensity of
solar radiations using an atmospheric model.

Malviya and Gupta (1987) designed and fabricated a cabinet dryer with chimney. They
reported that drying of chilli from 80 to 6 per cent (wb) moisture content was achieved in four

4

days during the month of March as against six days in dryer without chimney. The organoleptic
quality of product was found better.

Virgnola and McDaniels (1989) described the relationship between direct radiations on
horizontal and titled surfaces, examined on a daily and monthly average basis. The direct ratio
factor, often called Rb. is shown to vary with beam intensity. A comparison is made between Rb
calculated from hourly beam data from the Pacific Northwest, and Rb predicted using the
atmospheric weighting model and other direct ration models.

Davis and McKay (1989) evaluated selected models for estimation solar radiation on
horizontal surfaces. Twelve models which simulate solar irradiance on horizontal surfaces were
evaluated with data from seven countries. Simple , widely applicable models were considered
which use standard meteorological observations.

The principal components of a solar drying system are solar flat plate collector and
drying unit. Solar flat plate collector (also called solar air heater) is used for heating the ambient
air. Then the heated air from the solar collectors, passes to the drying unit. The drying takes
place in a drying unit where air extracts moisture from the product to be dried.(Sodha and
Chandra, 1994)

Sharan and Kumar (1995) have developed fourier representation of ambient temperature
and global radiation for several locations of the country. These may be useful for developing
models for solar appliances, dryers, green houses, etc.

When biological products, including cereal grains, are dried in a batch rather than as
individual particles, they will initially display a constant rate drying period (Brooker et al.,
1997). Because of the difference in drying behaviour of individual kernels and a bed of kernels,
separate analysis is required for thin layer and deep bed drying. Drying with crop bed thickness
less than 200 mm is termed as thin layer drying whereas, drying with crop bed thickenss more
than 200 mm, it is called deep bed drying (Chakraverty, 1995).

In convection drying, the constant drying rate of a biological product can be represented
by the adiabatic evaporation of moisture from the surface of a wet bulb thermometre. The rate of
drying during constant rate period is function of three external drying parameters: (i) Air
velocity, (ii) air temperature and (iii) air humidity. (Henderson et al., 1997)

A number of biological products, when dried as single particles or in thin layer under
constant external conditions, exhibit a constant rate moisture loss during the initial drying period

5

followed by a falling rate drying period. Cereal grain kernels, however, usually dry entirely
within the falling rate period, whereas high moisture products like fruits and vegetables dry
under constant rate and falling rate period. Knowledge of drying principles is essential for
simulation and optimal design of solar drying systems (Bala, 1998).

Marion and George (2001) used METSTAT (meteorological/statistical) model to
calculate hourly values of direct normal, diffuse horizontal, and global horizontal solar radiation
for locations throughout the world. Opaque cloud cover, a key input parameter in METSTAT
model, is derived from the DATSAV2 (database) layered cloud cover information. This model
has got worldwide potential.

Karim and Hawlader (2004) performed an experimental study of three types of solar air
collector, namely flat plate, finned and v-corrugated towards achieving an efficient design of air
collector suitable for a solar dryer. A series of experiments were conducted, based on the
ASHRAE standard and concluded that v-corrugated collector was found to be most efficient
collector and flat plate collector the least efficient. They also studied double pass operation of the
collector led to further improvement of the efficiency compared to the single pass operation. The
improvement in efficiency for the double pass mode was most significant in flat plate collector
and least in the v-groove collector.

Mohamed et al. (2005) conducted convective solar drying experiments in thin layers of
Citrus aurantium leaves grown in Marrakech, morocco. The air temperature was varied from 50
to 60 °C; the relative humidity from 41% to 53%; and the drying air flow rate from 0.0277 to
0.0833 m3/s. A nonlinear regression analysis using a statistical computer program was used to
evaluate the constants of the models.

Janjai and Tung (2005) used roof integrated solar collectors for drying herbs and spices
and its performance was tested. The dryer was a bin type with a rectangular perforated floor. The
bin had a dimension of 1.0 m×2.0 m×0.7 m. Hot air was supplied to the dryer from fiberglass-
covered solar collectors, which also functioned as the roof of a farmhouse. The dryer can be used
to dry 200 kg of rosella flowers and lemon-grasses within 4 and 3 days, respectively. The solar
air heater had an average daily efficiency of 35% and it performs well both as a solar collector
and a roof of a farmhouse.

6

Shanmugam and Natarajan (2006) experimentally investigated the forced convection and
desiccant integrated solar dryer under the hot and humid climatic conditions of Chennai. The
system consisted of a flat plate solar air collector, drying chamber and a desiccant unit. The
desiccant unit is designed to hold 75 kg of CaCl2-based solid desiccant consisting of 60%
bentonite, 10% calcium chloride, 20% vermiculite and 10% cement. Drying experiments were
performed for green peas at different air flow rate. The equilibrium moisture content Me was
reached in 14 h at an air flow rate of 0.03 kg/m2 s.

Sacilik, et al. (2006) performed experiments on thin layer solar drying of organic tomato
using mathematical modelling on solar tunnel dryer under ecological conditions of Ankara,
Turkey. During the experiments, organic tomatoes were dried to the final moisture content of
11.50 from 93.35% w.b. in four days of drying in the solar tunnel dryer. Experimental drying
curves showed only a falling drying rate period. The approximation of diffusion model has
shown a better fit to the experimental drying data as compared to other models. This system can
be used for drying various agricultural products.

Mwithiga and Kigo (2006) designed and tested a small solar dryer with limited sun
tracking capabilities. The dryer had a mild steel absorber plate and a polyvinyl chloride (pvc)
transparent cover and could be adjusted to track the sun in increments of 15°. The performance
was tested by adjusting the angle the dryer made with the horizontal either once, three, five or
nine times a day when either loaded with coffee beans or under no load conditions. The
temperature inside the plenum chamber could reach a maximum of 70.4 °C and the dryer could
lower the moisture content of coffee beans from 54.8% to below 13% (w.b.) in 2 days as
opposed to the 5–7 days required in sun drying. Tracking the sun though allowing a faster rate of
drying did not offer a significant advantage in terms of length of drying duration.

7

Chapter 3

MATERIALS AND METHODS

Estimation of solar radiations
The total irradiation on a surface is the sum of the direct solar radiation, ID, the diffuse
sky radiation, Id and solar radiation reflected from surrounding surfaces, Ir.

For the prediction of the solar radiations there is a need to understand the solar radiation
geometry.

In order to find the beam energy falling on a surface having any orientation, it is
necessary to convert the value of the beam flux coming from the direction of the sun to
an equivalent value corresponding to the normal direction to the surface. Relationship for
making this conversion is as:

…….(3.1)

where:

Ib is the equivalent flux falling normal to the surface

Ibn is the Solar flux

θ is angle between an incident beam of flux and the normal to a plane

The angle θ can be related by a general equation to φ the latitude, δ the declination, γ the surface
azimuth angle, ω the hour angle, and β the slope. Each of them is defined below:

The Latitude φ of a location is the angle made by the radial line joining the location the location
to the centre of the earth with the projection of the line on the equatorial plane. By convention,
the latitude is measured as positive for the northern hemisphere.

The Declination δ is the angle made by the line joining the centers of the sun and the eath with
its projection on the equatorial plane. It arises by virtue of the fact that the earth rotates about an
axis which makes an angle of approximately 66.5˚ with the plane of its rotation around the sun.
the declination angle varies from a maximum value of +23.45˚ on June 21 to a maximum of -

8

23.45 on Dec. 21. It is zero on the two equinox days of Mar. 21 and Sep. 22. The following
simple relation prepared by Cooper (1969) was used for calculating of declination.

……. ( P. I. Cooper 1969)(3.2)

Where,

n is the day of the year.

The Surface Azimuth Angle γ is the angle made in the horizontal plane between the line due
south and the projection of the normal to the surface on the horizontal plane. By convention, the
angle is taken to be positive if the normal is east of south and negative if west of south.

The Hour Angle ω is an angular measure of time and is equivalent to 15˚ per hour. It is
measured from noon based on local apparent time (LAT), being positive in the morning and
negative in the afternoon.

The Slope β is the angle made by the plane surface with the horizontal. It is taken to be positive
for the surface sloping towards the south and negative for surface sloping towards the north.

It can be shown that:

…….(3.3)

This equation can be simplified for the various particular conditions as:

For Horizontal Surface β = 0˚

Therefore:

…….(3.4)

The angle in this case is called the Zenith angle and will be denoted by the symbol θz .

9

Local Apparent Time (LAT)

The time used for the calculating the hour angle in the equations (3.3) to (3.5) is the local
apparent time. This can be calculated by using the standard time observed on a clock by applying
two corrections. The first correction arises because of the difference between the longitude of a
location and the meridian of which the standard time is based. The correction has a magnitude of
4 minutes for every degree difference in longitude. The second correction called the equation of
time correction is due to the fact that the earth’s orbit and rate of rotation are subject to small
fluctuations.

LAT = Standard time 4(standard time longitude – longitude of location)

+ Equation of time correction …….(3.5)

The negative sign in the first correction is applicable for the eastern hemisphere, while the
positive sign is applicable for the western hemisphere.

Equation of time is given by:

…….(3.6)

Where B is given by equation:

…….(3.7)

Hourly global and diffuse radiation on clear days

ASHRAE has given a method for estimating the hourly variation of global and diffuse solar
radiation falling on a horizontal surface on a clear day. The equations are based on an
exponential decay model in which the beam radiation decreases with increase in the distance
traversed through atmosphere. The global radiation (Ig) reaching a horizontal surface on the earth
is given by

Ig = Ib + Id …….(3.8)

Where:

Ig = hourly global radiation

Ib = hourly beam radiation

10

Id = hourly diffuse radiation

Now,

Ib = Ibn . cosθz

Where

Ibn = beam radiation in the direction of the rays

θz = angle of incidence on a horizontal surface, i.e. the zenith angle.

Thus,

Ig = Ibn . cosθz + Id

In the ASHRAE model, it is postulated that for a clear cloudless day

Ibn = A exp[-B/cosθz]

And Id = C. Ibn

Where A,B and C are constants whose values were obtained from analysis given by Threlkeld
and Jordan(1958).

Values of the Constants A, B and C used for predicting hourly solar radiation on clear days are
as follows:

Month A (W/m2) B C
January 21 1228 0.142 0.058
February 21 1213 0.144 0.060
March 21 1185 0.156 0.071
April 21 1134 0.180 0.097
May 21 1103 0.196 0.121
June 21 1087 0.205 0.134
July 21 1084 0.207 0.136
August 21 1106 0.201 0.122
September 21 1150 0.177 0.092
October 21 1191 0.160 0.073
November 21 1219 0.149 0.063
December 21 1232 0.142 0.057

The values have been determined for each month since they change during the year because of
seasonal changes in the dust and water vapour content of the atmosphere, and also because of the
changing earth-sun distance.

11

Solar radiations on tilted surfaces

Most solar equipment (e.g. flat plate collectors) for absorbing radiation are tilted at an angle to
the horizontal. It therefore becomes necessary to calculate the flux which falls on a tilted surface.
This flux Is the sum of the beam and diffuse radiations falling directly on the surface and the
radiation reflected on to the surface from the surroundings.

IT = Ib.Rb + Id.Rd + (Ib + Id) .Rr …….(3.9)

Beam radiation (Rb)

The ratio of the beam radiation flux falling on a tilted surface to that falling on a horizontal
surface is called the tilt factor for beam radiation. It is denoted by the symbol Rb. for the case of a
tilted surface facing south (i.e. γ = 0˚)

…….(3.10)

While for a horizontal surface

Hence

…….(3.11)

Similar expressions could be derived for other situation

Diffuse Radiation (Rd)

The tilt factor Rd for diffuse radiation is the ratio of the diffuse radiation flux falling on the tilted
surface to that falling on a horizontal surface. The value of this tilt factor depends upon the
distribution of diffuse radiation over the sky and on the portion of the sky dome seen by the titled
surface. Assuming that that the sky is an isotropic source of diffuse radiation, we have

…….(3.12)

Since is the radiation shape factor for a tilted surface with respect to the sky.

12

Reflected Radiation (Rr)

Since is the radiation shape factor for a tilted surface with respect to the sky, it follows

that is the radiation shape factor for the surface with respect to the surrounding ground.
Assuming that the reflection of the beam and diffuse radiations falling on the ground is diffuse
and isotropic, and that the reflectivity is ρ, the tilt factor for reflected radiation is given by

…….(3.13)

Flux on a titled surface

The flux IT falling on a tilted surface at any instant is thus given by:

IT = Ib.Rb + Id.Rd + (Ib + Id) .Rr …….(3.14)

It should be noted that this equation is valid for a south-facing surface. Ratio of flux falling on a
tilted surface at any instant to that on a horizontal surface can be found out as:

…….(3.15)

Value of ρ is generally taken around 0.2 with surface of concrete or grass.

Calculation of efficiency of solar flat plate collector (air heater)
The useful heat gain rate for the collector is given by

qu = FRAP [S-Ul (Tfi-Ta)] …….(3.16)

where

qu = useful heat gain rate (W)

FR = Collector heat removal factor

AP = Area of collect plate (m2)

S = Solar flux(W/m2)

13

Ul = Overall heat loss coefficient (W/m2-k)

Tfi = Temperature at collector inlet (ºC)

Ta = Ambient air temperature (ºC)

Instantaneous efficiency of collector is calculated as:

Useful heat gain rate
ηi =
solar flux incident on collector face x collector plate area

…….(3.17)

Collector air temperature is obtained from the energy balance equation:

qu = Ma . Cp (Tfo – Tfi) …….(3.18)

where,

Ma = Air mass flow rate (Kg/sec)

Cp = Specific heat of the air(J/Kg-ºC)

Tfi = Temperature at collector inlet (ºC)

Tfo = Temperature at collector outlet (ºC)

qu = The useful heat gain rate for the collector

Design of Solar Dryer
Calculation of amount of water removed from the product

Mass of water to be removed from the product, Ww (kg) is calculated as:

…….(3.19)

Where,

14

Ww = Mass of water evaporated from a given quantity of
product (kg)

Wg = Initial mass of the product (kg)

Mi = Initial moisture content (% wet basis)

Mf = Final moisture content (% wet basis)

Total heat required to evaporate water from the product in KJ

…….(3.20)

Where,

L is latent heat of vaporization in KJ

Calculation of quantity of air flow required for drying

The quantity of air required for drying is calculated from energy-balance equation:

WwL = Ma CP (To – Ti) …….(3.21)

Where,

Ma = Mass of drying air (kg)

L = Latent heat of vapourization of water from the product (MJ/kg)
= 2.8 (Exell, 1980)

CP = Specific heat capacity of air at constant pressure (kJ/kg°C)

= 1.02

Ti = Temperature of the drying air at the inlet of solar air heater (°C)

To = Temperature of the drying air at the outlet of solar heater (°C)

Air flow due to wind

The effect of wind force in moving air through a building varies with velocity, prevailing
direction, seasonal and daily variation in velocity and direction and local obstruction such as

15

nearby building, trees or hill. Wind velocity is usually lower in summer than in winter and varies
in direction between summer and winter season.

Thus, natural ventilation system may be designed for wind velocities of half the average
seasonal velocity. The air exchange caused by wind velocity may be calculated by:

Vw = E .A .v …….(3.22)

Where,

Vw = Air flow (m3/s)

A = Free area of inlet opening (m2)

v = Wind velocity (m/s)

E = Effectiveness of openings

= 0.5 to 0.6 for perpendicular to the opening wind

and 0.25 to 0.35 for diagonal winds.

Air flow due to thermal forces

Thermal forces can be complementary to wind forces in providing air exchange through
naturally ventilated structures. During times when there is effectively no wind force, thermal
forces must be relied on entirely. The thermal (buoyancy) forces due to difference in air density
at different temperature can cause air flow due to stack surfaces. It is estimated as:

…….(3.23)

Where,

Vth = Air flow (m3/s)

A = Free area of inlet or outlets (m2)

g = Acceleration due to gravity (9.81 m2/s)

h = Height from inlet to outlet (m)

16

θ = Ratio of flow with friction and other losses to frictionless flow

= 0.3 to 0.5

Ti = Inlet absolute temperature (°K)

To = Outlet absolute temperature (°K)

Now Vt = volume of drying air(m3/Hr) is given by

Vt = (Vth + Vw) *3600 …….(3.24)

From Gas law

PV = Ma RT

Ma = PV/RT …….(3.25)

Where,

P = Atmospheric pressure(kPa) = 101.3

R = Gas constant (kPa/kg °K) = 0.291

T = Average temperature of the product (°K)

V = Volume of air needed for drying of product (m3)

Ma = Mass of drying air (kg)

Calculation of drying time

Collector area of the solar dryer is calculated as:

…….(3.26)

Where,

A = Collector area of the solar dryer (m2)

Qt = Total heat required to evaporate water from the product(kJ)

17

IT = Daily average of solar radiation intensity (W/m2)

η = Efficiency of dryer (%)

ddays = Drying time (days)

Calculation of number of trays

W = txdxA …….(3.27)

Where,

W = Total capacity of tray (kg)

t = Thickness of material (m)

d = Bulk density of the material (kg/m3)

A = Area of the tray (m2)

Assume

Area of one tray (A1) = (0.95 X 0.45) m2

Number of trays (n) = Area of the tray / Area of one tray

18

Parameters used for design:
Solar Radiation data

Latitude of the place
Longitude of the place
Time of the day
Day of the year

Solar collector data

Length of collector
Breadth of collector
Gap between cover and plate
Average air velocity
Ambient temperature
Inside mean temperature

Solar dryer data

Length of the tray
Breadth of tray
Thickness of material to be kept in the tray
Bulk density of the material to be dried
Initial and final moisture content of the material to be dried

Solar Collector parameters

Type Flat Plate Type

Gross Dimensions 200x100 cm2

Area of Absorbing Surface: 198x97 cm2

Absorbing Surface Black Painted G.I sheet

Inlet Air gap Four no.(20 x 5 cm each)

Transfer Fluid Air

Collector Tilt Angle 30

Cover Plate plain glass Sheet

19

Instrumentation for experimental data

Pyranometer for radiation measurement
Multichannel temperature recorder for temperature measurement
Hot wire Anemometer for air velocity measurement
Vane Anemometer for wind velocity measurement

Method used for the validation of the simulation model;

Real time values of solar radiations were obtained by the use of Surya Mapi and were validated
against the values predicted by the program using the Statistical methods:

Two-Sample t-test for independent Samples

Let X1, X2,X3, ……Xn1 and Y1, Y2, Y3,……Yn2 in be two independent random samples of sizes
n1 and n2 from two normal populations N(µ1,σ12) and N(µ2,σ22)

Assumptions:

1) Populations are normal
2) Samples are drawn independently and at randomly
3) Population variances σ12 and σ22 are unknown but equal.
4) Samples are small

Null hypothesis

Ho µ1 = µ2

Alternate hypothesis

H1: µ1 ≠ µ2 (Two tailed test)

H1: µ1 > µ2 (Right tailed test)

H1: µ1 < µ2 (Left tailed test)

20

From the samples compute means , and the variances s12 and s22 and then find the pooled
variance:

Test statistic

If , reject Ho , otherwise accept Ho

21

Chapter 4

RESULTS AND DISCUSSIONS

For the design of the solar dryer first step was to record the solar radiation data.
Readings for the insolation were recorded at the Renewable Energy Lab between the time period
8:30 to 4:30 at an interval of 1 hour. Readings were taken for two orientation i.e. horizontal and
inclined surface:

Insolation on horizontal surface

Readings were taken on the horizontal surface and tabulated. Program developed in Visual Basic
was used to predict the solar radiation data for the same period on horizontal surface, the detailed
program with code is given in the APPENDIX A: Listing 2.

Comparison was then made for the measured and predicted values so as to validate the
developed model.

Results of the study are presented in the Table 4.1 and Figure 4.1

In the observed values for horizontal insolation the maximum value was 953 W/m2 at 12:30 p.m.
and minimum 313 W/m2 at 8:30 a.m. while the maximum value for the predicted insolation was
891 W/m2 at 12:30 a. m. and minimum 397 W/m2 at 4:30 p.m.

T- test was applied on the predicted and observed values. The tabulated value for 16 degrees of
freedom and 5% level of significance is 2.12. Calculated T- value is 0.48 which is in accordance
to the tabulated values so it can be safely assumed that the predicted values by the model can be
used to calculate insolation at any given place and time.

Insolation on inclined surface (β = 30°)

Readings were taken on the inclined surface (β = 30°) and tabulated. Program developed in
Visual Basic was used to predict the solar radiation data for the same period on inclined surface,
the detailed program with code is given in the APPENDIX A: Listing 2.

Comparison was then made for the measured and predicted values so as to validate the
developed model.

Results of the study are presented in the Table 4.2 and Figure 4.2

22

In the observed values for inclined insolation the maximum value was 1040 W/m2 at 12:30 p.m.
and minimum 353 W/m2 at 8:30 a.m. while the maximum value for the predicted insolation was
919 W/m2 at 12:30 a. m. and minimum 413 W/m2 at 4:30 p.m.

T- test was applied on the predicted and observed values. The tabulated value for 16 degrees of
freedom and 5% level of significance is 2.12. Calculated T- value is 0.64 which is in accordance
to the tabulated values so it can be safely assumed that the predicted values by the model can be
used to calculate insolation at any given place and time.

Thermal performance testing of solar flat plate collector(air heater).

For the calculation of the flat plate solar collector efficiency following parameters were
recorded:

Ambient Temperature

Average surrounding air velocity

Mean plate temperature

Air flow rate through the chimney

Standard formulas were used for the evaluation of the efficiency of the flat plate solar collector
with the help of the program developed in the Visual Basic. The details of the program and code
is given in the APPENDIX A: Listing 4. The results of the study are presented in the Table 4.3
and various graphs for the performance of the solar dryer are plotted in Figure 4.3(a), Figure
4.3(b) and Figure 4.3(c).

The result show that mean plate temperature rises for a time and remains constant for some time
even after the insolation has reached is maximum value at 12:30 after which it starts to decline.
Max value of the mean plate temperature observed was 68 °C at 12:30 p.m. and minimum 33 °C
at 8:30 a.m. ambient temperature follows the same trend.

23

Table 4.1 – Comparison of insolation on horizontal surface
Horizontal Insolation Horizontal Insolation
Time
Observed Calculated
8.30 313 419
9.30 433 615
10.30 747 767
11.30 873 861
12.30 953 891
13.30 907 855
14.30 760 754
15.30 620 598
16.30 433 397
T value calculated 0.48
T tabulated = 2.12

Figure 4. 1

24

Table 4.2 – Comparison of insolation on inclined surface
Time Inclined Insolation Observed Inclined Insolation Calculated
8.30 353 435
9.30 493 637
10.30 787 792
11.30 947 889
12.30 1040 919
13.30 973 882
14.30 827 779
15.30 673 618
16.30 467 413
T- value calculated 0.64
T tabulated = 2.12

Comparison of Inclined Insolation
1200

1000

800
Insolation in W/sq. mts.

600

400

200

0
8.30 9.30 10.30 11.30 12.30 13.30 14.30 15.30 16.30

Time of the day

Observed Calculated

Figure 4. 2

25

Table 4.3 – Solar performance data
Time Insolation Temperature Thermal
Horizontal Inclined Ambient Mean Air Wind efficiency
8.30 353 393 26 Plate
33 velocity
0.4 velocity
1.1 (%) 47
9.30 480 540 28 41 0.6 1.2 45
10.30 753 787 30 56 1.0 1.5 42
11.30 880 947 32 64 1.4 2.0 43
12.30 967 1053 33 68 1.4 2.2 43
13.30 927 987 33 67 1.5 3.1 43
14.30 787 853 35 65 1.1 3.1 46
15.30 613 673 35 60 1.1 2.9 45
16.30 380 413 35 53 0.7 2.1 46

Figure 4. 3(a)

26

Figure 4. 3(b)

Figure 4. 3(c)

27

Computer aided thermal design of solar dryer

Based on the insolation and collector plate efficiency a dryer was designed for the given place
(latitude and longitude). The detailed program used for the calculation is given in the
APPENDIX A: Listing 5 Factors which were taken into account were:

• Weight of the material to be dried

• Initial moisture content

• Desired final moisture content

• Time of drying

Area of the collector plate required for drying the given quantity of the material form initial
moisture content to the desired final moisture content in the given time was calculated.

Following data were considered for the estimation of the drying area.

• Drying time – 2 days

• Initial moisture content 70%

• Final moisture content 12%

To determine the number of tray required to dry the given quantity of the material. The detailed
program used for the calculation is given in the APPENDIX A: Listing 5. The factors which
were considered were:

• Tray size

◦ length – 95 cm

◦ breadth - 45 cm

• Thickness of the material to be kept

• Bulk density of the material

Following data were assumed for the calculation of the no. trays required:

• Thickness of material to be kept in the tray – 10 cm
•
Bulk density of the material – 650 kg/m3

28

Table 4.4 – Design of solar collector
Weight of material(Kg) Area required (m2)
5 0.42
6 0.51
7 0.59
8 0.68
9 0.76
10 0.85
11 0.93
12 1.02
13 1.1
14 1.19
15 1.27
16 1.36
17 1.44
18 1.52
19 1.61
20 1.69

Table 4.5 – Design of trays in the drying chamber
Weight of material (Kg) Number of trays
5 1
10 1
15 2
20 2
25 2

With the above data analysis it can be concluded that the program
developed is a better tool using the Visual Basic user friendly model which is window based and
easy to use for the estimation of solar radiations. The program can thus be used to determine the
optimum drying area and number of trays required to be kept in the drying chamber for the dryer
designed at any given place and given time of the year. And therefore various solar dryer with
varying capacity can be designed with the help of this tool according to the user need, saving a
lot of manual calculations, time, labour, resources and money. This tool can also help the
industries working on the designing of the solar applications, after a little bit of modifications as
the basic need of estimating the solar radiations at a place with accuracy is fulfilled and it adds a
new dimension by window based user interaction to the previously hard to understand and labour
intensive techniques of estimating the insolation and then designing the system based on it.

29

Chapter 5

SUMMARY AND CONCLUSION

The development of simulation model is a powerful tool for prediction of performance and can
help designers to optimize the dryer geometry at various operating conditions.
Commercialization of any drying technology for agro-processing or industrial use needs
thorough performance prediction and evaluation of system in techno-economic perspectives.

Following are some of the conclusion drawn by this project.

1. Estimation of solar radiation at Hisar with the help of ASHRAE model has been in close
agreement with the observed values taking 5% as level of significance. Thus the model
can safely be used to predict isolation at Hisar.
2. The calculated efficiency of the solar plate collector using the readings at different point
in the solar dryer during testing has been consistent and the efficiency of the solar
collector has to be found out to be 44%.

30

Chapter 6

REFERENCES

ASHRAE ,1972, Handbook of fundamentals pp.385-443.

ASHRAE Transactions ,1958. Direct Solar radiation available on clear days,64,45,

Atwall, P. S. and Neal,W.E.J. 1981. Measurements of spectral distribution of solar radiation and
mathematical model validation. Proceedings of Solar World Forum, Vol. 3. International Solar
Energy Society Congress; Brighton, England; Ed. Davis Hall and June Morton. New York.
Pergamon Press. pp. 2439-2442.

Bala, B.K. and Wood, J.L., 1994. Simulation of the indirect natural convection solar
drying of rough rice. Solar Energy 53(3): 259-266.

Brooker, D.B.; Bakker-Arkema, F.W. and Hall, C.W. 1997. Drying and storage of grains and
cereals. CBS Publishers and Distributors, New Delhi (India).

Chakraverty, A. 1995. Post harvest technology of cereals, pulses and oilseeds. III. Edition.
Oxford & IBH Publishing Co. Pvt. Ltd., New Delhi (India).

Davies, J. A. and Mckay D. C. 1989. Evaluation of selected models for estimation solar radiation
on horizontal surfaces. Solar Energy 43(3):153-168.

Henderson, S.M.; Perry, R.L. and Young, J.H. 1997. Principles of process engineering, IV
edition. The Society for Engineering in Agricultural Food and Biological Systems (ASAE),
USA.

Exell, R.H.B. 1980. Basic design theory for simple solar rice dryer. Renewable Energy Review
Journal 1(2): 1-12.

Janjai, S. and Tung P. Performance of a solar dryer using hot air from roof-integrated solar
collectors for drying herbs and spices. Renewable Energy 30(14): 2085-2095.

P. I. Cooper, 1969. The Absorption of Solar Radiation in Solar Stills, Solar Energy, 12,3

Karim, M.A. and Hawlader, M.N.A. 2004. Development of solar air collectors for drying
applications. Energy Conversion and Management 45(3): 329-344.

Kaushik, L. S. 2003. Applied Statistical Methods. Dhanpat Rai & Co. (P) Ltd. pp 11.1-11.9

31

Malaviya, M.K. and Gupta, R.S.R. 1987. Cabinet type natural convection dryer with chimney.
Agricultural Engineering Today 11(4): 37-39.

Mani, Anna and Rangarajan, S., 1982. Solar Radiation over India. Allied Publishers Pvt. Ltd.,
New Delhi.

Marion, W. and George, R. 2001. Calculation of Solar Radiation Using a methodology
with Worldwide Potential. Solar Energy 71(4):273-283
Mathur,A. N.; Ali, Yusuf; Maheshwari, R. C., 1989. Solar Drying

Mohamed, L. et al. Single layer solar drying behaviour of Citrus aurantium leaves under
forced convection. Energy Conversion and Management. 46(9-10):1473-1483

Mwithiga, Gikuru and Kigo, Stephen Njoroge. Performance of a solar dryer with limited sun
tracking capability. Journal of Food Engineering 74(2): 247-252

Sacilik, Kamil etal. Mathematical modelling of solar tunnel drying of thin layer organic tomato.
Journal of Food Engineering 73(3):231-238

Sodha, M.S. and Chandra, R. 1994. Solar drying system and their testing procedures : A review.
Energy Convers. Mgmt.35(3): 219-267.

Sukhatme, S. P., 1988. Principles of Thermal Collection and Storage. pp 66-80,141-147

Shanmugam, V. and Natrajan, E., 2006. Experimental investigation of forced convection
and desiccant integrated solar dryer. Renewable Energy 31(8):1239-1251

Sharan, G. and Kumar, M.K. 1995. Fourier representation of ambient temperature and
solar radiation. Journal of SESI 5(2): 55-66.

Threlkeld, J. L. and Jordan, R. C. 1958. Direct Solar Radiation Available on clear days.
ASHRAE Transactions 64,45(1958)

Venkatesh, P. and Prasad, C. R. 1982, Computation of solar spectral irradiance. Proceedings of
National Solar Energy Convention, New Delhi, Allied Publishers, Pvt. Limited, pp. 5.030-5.033.

Vignola, F. and McDaniels, D. K. 1989. Direct Radiation: Ratio between Horizontal and Tilted
Surfaces. Solar Energy 43(3):183-190.

32

SYMBOLS AND ABBREVIATIONS

°C : Degree celsius

°K : Degree in kelvin

% : Per cent

ρ : Density of air

µ : Viscosity of air

σ : Stefen-Boltzman constant (5.67 x 10-8 W/m2 k4)

η : Efficiency

cm : Centimetre

cu m : Cubic metre

db : Dry basis

et al. : And others

exp : Exponential

Fig. : Figure

g : Acceleration due to gravity

hc : Convective heat transfer coefficient

Hr : Hour

Id : Solar insolation

K : Thermal conductivity of air

kg : Kilogram

L : length of collector

Lv : Latent heat of vapourization

m : Metre

mc : Moisture content

33

P : Atmospheric pressure

Pa : Water vapour pressure in the air

rh, RH : Relative humidity

s : Second

sq. m. : Square metre

t : Drying time

t : Thickness of material

Ta : Ambient temperature

v : Wind velocity

wb : Wet basis

34

APPENDIX A: Listing 1

Program to Load the Starting Screen of the Project and Introduce to the user about the
Project.

Purpose: The program called the Splash Screen Loads the Main Project and gives the
user the information about the development work and team of the project.
Usage: program uses Objects like Frame, Labels, Timer control for the GUI. The code
consists of the Sub Procedures for Timer and form loading.
Input Formats: nothing has to be provided by the user
Output: Information about the Project
Running: Following is the Run mode Screen of the Form1 of the Project.

35

Code for the Form Splash:

Private Sub Timer1_Timer()
Static count As Integer

If count = 0 Then
lblWarning.Caption = "Loading Project....."
End If

If count = 1 Then
lblWarning.Caption = "Starting Processes....."
End If

If count = 2 Then
lblWarning.Caption = "Welcome"
End If

If count = 3 Then
Unload Me
Form1.Show
End If

count = count + 1
End Sub

36


Program to estimate solar radiation falling on a surface :

Purpose: The program estimates solar radiation falling on a surface (Horizontal and
Tilted) corresponding to the given values of latitude and longitude of place in degrees and
day of the year ( 1 to 365).
Usage: program uses one Main Form and the Objects like List Boxes, Labels, Text
Boxes, Combo Box, Option Buttons and Command Buttons for the GUI. The code
consists of the Sub Procedures for various Command Buttons and the List Boxes.
Input Formats: Selecting of Month, Day of the month, Latitude and Longitude, Time
Period of the Day and Tilt of the Surface
Output: Output consists of Global, Beam and Diffused radiation on a horizontal surface
and Insolation on a tilted surface.
Running: Following is the Run mode Screen of the Form1 of the Project

37

Code for the Form1

Private Sub Combo1_Click()

If List1.ListIndex = -1 Then
MsgBox ("Please select a Month before selecting a day")
Combo1.Text = ""
List1.SetFocus
Else
If Combo1.Text < 21 Then
diff = 9 + Val(Combo1.Text)
a.Text = Round(ac + (aa - ac) * diff / 30, 0)
b.Text = Round(bc + (ba - bc) * diff / 30, 3)
c.Text = Round(cc + (ca - cc) * diff / 30, 3)
Inter = n + Val(Combo1.Text) - 21
ElseIf Combo1.Text > 21 Then
diff = Val(Combo1.Text) - 21
a.Text = Round(aa + (ab - aa) * diff / 30, 0)
b.Text = Round(ba + (bb - ba) * diff / 30, 3)
c.Text = Round(ca + (cb - ca) * diff / 30, 3)
Inter = n + Val(Combo1.Text) - 21
Else
a.Text = aa
b.Text = ba
c.Text = ca
End If

End If

End Sub

Private Sub Command1_Click()

If List1.ListIndex = -1 Then
MsgBox ("Please Select a Month")
List1.SetFocus
ElseIf Combo1.Text = "" Then
MsgBox ("Please Select a date and then continue")
Combo1.SetFocus
ElseIf List2.ListIndex = -1 And Option1.Value = True Then
MsgBox ("Please Select the Place or Type the co-ordinated")
List2.SetFocus
ElseIf Option2.Value = True And (la.Text = "" Or lo.Text = "") Then
MsgBox ("Please enter the co-ordinated of the place")
la.SetFocus
ElseIf List3.ListIndex = -1 Then
MsgBox ("Please Select the time of the day")

38

List3.SetFocus
ElseIf Text2.Text = "" Then
MsgBox ("Please enter the tilt angle")
Text2.SetFocus
Else

del = 23.45 * Sin(2 * 3.14 * (284 + Inter) / 365)
sinla = Sin(Val(la.Text) * 2 * 3.14 / 360)
sindel = Sin(del * 2 * 3.14 / 360)
cosla = Cos(Val(la.Text) * 2 * 3.14 / 360)
cosdel = Cos(del * 2 * 3.14 / 360)
cosw = Cos(w * 2 * 3.14 / 360)
cosz = sinla * sindel + cosla * cosdel * cosw
expo = 0 - (Val(b.Text) / cosz)

Ibn = (36 * Val(a.Text)) * Exp(expo)
Id = Val(c.Text) * Ibn
Ig = Ibn * cosz + Id
Ib = Ibn * cosz

globalRad.Text = Str(Int(Ig / 36))
diffuse.Text = Str(Int(Id / 36))
beam.Text = Str(Int(Ib / 36))

beta = Val(Text2.Text) * 2 * 3.14 / 360 ' now beta is in radians
sinDiff = Sin(Val(la.Text) * 2 * 3.14 / 360 - beta)
cosDiff = Cos(Val(la.Text) * 2 * 3.14 / 360 - beta)
cosQ = sinla * sinDiff + cosla * cosw * cosDiff
Rb = cosQ / cosz
Rd = (1 + Cos(beta)) / 2
Rr = 0.2 * (1 - Cos(beta)) / 2
Sflux = (Ib * Rb + Id * Rd + (Ib + Id) * Rr) / 36

Text1.Text = Round(Sflux, 0)
End If

End Sub

Form2.Show
End Sub

Form5.Show
End Sub

39

Form4.Show
End Sub

Form3.Show
End Sub

End
End Sub

Private Sub Form_Load()
For nt = 1 To 28
Combo1.AddItem nt
Next nt
End Sub

Private Sub List1_MouseMove(Button As Integer, Shift As Integer, X As Single, Y As
Single)
If List1.ListIndex = 0 Then
aa = 1228
ba = 0.142
ca = 0.058
ab = 1213
bb = 0.144
cb = 0.058
ac = 1232
bc = 0.142
cc = 0.057
n = 21
eqTime = -10
For nt = 0 To Combo1.ListCount - 1
Combo1.RemoveItem 0
Next nt

For nt = 1 To 31
Combo1.AddItem nt
Next nt
End If

aa = 1213
ba = 0.144
ca = 0.06
ab = 1185

40

bb = 0.156
cb = 0.071
ac = 1228
bc = 0.142
cc = 0.058
n = 52
eqTime = -14
Combo1.RemoveItem 0
Next nt
For nt = 1 To 28
Combo1.AddItem nt
Next nt
End If

aa = 1185
ba = 0.156
ca = 0.071
ab = 1134
bb = 0.18
cb = 0.097
ac = 1213
bc = 0.144
cc = 0.06
n = 80
eqTime = -10
Combo1.RemoveItem 0
Next nt
For nt = 1 To 31
Combo1.AddItem nt
Next nt
End If

aa = 1134
ba = 0.18
ca = 0.097
ab = 1103
bb = 0.196
cb = 0.121
ac = 1185
bc = 0.156
cc = 0.071
n = 111

41

eqTime = 0
Combo1.RemoveItem 0
Next nt
For nt = 1 To 30
Combo1.AddItem nt
Next nt
End If

aa = 1103
ba = 0.196
ca = 0.121
ab = 1087
bb = 0.205
cb = 0.134
ac = 1134
bc = 0.18
cc = 0.097
n = 141
eqTime = 4
Combo1.RemoveItem 0
Next nt
For nt = 1 To 31
Combo1.AddItem nt
Next nt
End If

aa = 1087
ba = 0.205
ca = 0.134
ab = 1084
bb = 0.207
cb = 0.136
ac = 1103
bc = 0.196
cc = 0.121
n = 172
eqTime = 0
Combo1.RemoveItem 0
Next nt
For nt = 1 To 30
Combo1.AddItem nt

42

Next nt
End If

aa = 1084
ba = 0.207
ca = 0.136
ab = 1106
bb = 0.201
cb = 0.122
ac = 1087
bc = 0.205
cc = 0.134
n = 202
eqTime = -5
Combo1.RemoveItem 0
Next nt
For nt = 1 To 31
Combo1.AddItem nt
Next nt
End If

aa = 1106
ba = 0.201
ca = 0.122
ab = 1150
bb = 0.177
cb = 0.092
ac = 1084
bc = 0.207
cc = 0.136

n = 232
eqTime = -5
Combo1.RemoveItem 0
Next nt
For nt = 1 To 31
Combo1.AddItem nt
Next nt
End If

aa = 1150

43

ba = 0.177
ca = 0.092
ab = 1191
bb = 0.16
cb = 0.073
ac = 1106
bc = 0.201
cc = 0.122
n = 263
eqTime = 5
Combo1.RemoveItem 0
Next nt
For nt = 1 To 30
Combo1.AddItem nt
Next nt
End If

aa = 1191
ba = 0.16
ca = 0.073
ab = 1219
bb = 0.149
cb = 0.063
ac = 1150
bc = 0.177
cc = 0.092
n = 293
eqTime = 15
Combo1.RemoveItem 0
Next nt
For nt = 1 To 31
Combo1.AddItem nt
Next nt
End If

aa = 1219
ba = 0.149
ca = 0.063
ab = 1232
bb = 0.142
cb = 0.057
ac = 1191

44

bc = 0.16
cc = 0.073
n = 324
eqTime = 15
Combo1.RemoveItem 0
Next nt
For nt = 1 To 30
Combo1.AddItem nt
Next nt
End If

aa = 1232
ba = 0.142
ca = 0.057
ab = 1228
bb = 0.142
cb = 0.058
ac = 1219
bc = 0.149
cc = 0.063
n = 354
eqTime = 5
Combo1.RemoveItem 0
Next nt
For nt = 1 To 31
Combo1.AddItem nt
Next nt
End If

End Sub

Single)
la.Text = "28.55"
lo.Text = "77.12"
End If

la.Text = "19.11"
lo.Text = "72.51"
End If

45

la.Text = "21.10"
lo.Text = "79.05"
End If

la.Text = "29.16"
lo.Text = "75.75"
End If

la.Text = "22.2"
lo.Text = "88.45"
End If

la.Text = "23.05"
lo.Text = "73.02"
End If

la.Text = "13.05"
lo.Text = "80.18"
End If

la.Text = "34.1"
lo.Text = "74.85"
End If

End Sub

Single)
w = 52.5
End If

w = 37.5
End If

w = 22.5
End If

46

w = 7.5
End If

w = -7.5
End If

w = -22.5
End If

w = -37.5
End If

w = -52.5
End If

w = -67.5
End If

latDiff = (4 * (82.5 - Val(lo.Text))) + eqTime
wDiff = latDiff / 4
w = w + wDiff

End Sub

Private Sub Option1_Click()
If Option1.Value = True Then
List2.Enabled = True
la.Enabled = False
lo.Enabled = False
End If

End Sub

Private Sub Option2_Click()
If Option2.Value = True Then
List2.Enabled = False
la.Enabled = True
lo.Enabled = True
End If
End Sub

47


Program to draw the graph showing the global radiations falling on a horizontal surface
and also to calculate the average Insolation falling for the whole day.

Purpose: The program draws a graph for a particular place showing the global radiations
falling for whole day a particular place
Usage: program uses one Main Form and the Objects like Labels and Command Buttons
for the GUI. The code consists of the Sub Procedures for various Command Buttons.
Input Formats: program takes the input of the latitude, longitude and day of the year
provided by the user in the previous form automatically.
Output: Output consist of a graph showing the global radiations falling a the place and
also the average Insolation for that place.

48

Code:

Dim s As Double
Dim ST As Double

Label12.Caption = Form1.List2.Text
Label16.Caption = Form1.List1.Text
Line1.Visible = True
Line2.Visible = True
DrawWidth = 2

Line (0, 140)-(200, 140)
Line (20, 0)-(20, 200)

DrawWidth = 1
Line (80, 0)-(80, 140)
Line (20, 40)-(200, 40)
Line (20, 90)-(200, 90)
DrawWidth = 2

For i = 52.5 To -67.5 Step -0.1
cosw = Cos((i + wDiff) * 2 * 3.14 / 360)
cosz = sinla * sindel + cosla * cosdel * cosw
expo = 0 - (Val(Form1.b.Text) / cosz)
Ibn = (3.6 * Val(Form1.a.Text)) * Exp(expo)
Id = Val(Form1.c.Text) * Ibn
Ig = Ibn * cosz + Id
Ib = Ibn * cosz

beta = Val(Form1.Text2.Text) * 2 * 3.14 / 360 ' now beta is in radians
sinDiff = Sin(Val(Form1.la.Text) * 2 * 3.14 / 360 - beta)
cosDiff = Cos(Val(Form1.la.Text) * 2 * 3.14 / 360 - beta)
cosQ = sinla * sinDiff + cosla * cosw * cosDiff
Rb = cosQ / cosz
Rd = (1 + Cos(beta)) / 2
Rr = 0.2 * (1 - Cos(beta)) / 2
Sflux = (Ib * Rb + Id * Rd + (Ib + Id) * Rr) / 36
ST = ST + Sflux

Ig = Ig / 36
s = s + Ig
t=t+1

PSet (j, Ig), QBColor(0)

49

Next i
inso = Round(10 * s / t, 1)
Savg = Round(10 * ST / t, 1)
Label18.Caption = Str(inso) + " W/sq m"

End Sub

PrintForm
End Sub

Form4.Cls
End Sub

ScaleMode = 6
End Sub

50


Programme to estimate solar collector efficiency:

Purpose: The program estimates Solar Collector Efficiency
Usage: program uses one Main Form and the Objects like Labels, Text Boxes and
Command Buttons for the GUI. The code consists of the Sub Procedures for various
Command Buttons.
Input Formats: input of length of collector, width of collector, gap between cover and
plate, average air velocity, inlet air temperature, ambient temperature and mean
temperature.
Output: gives the solar collector efficiency.

51

Code:

Dim l, w, b, a As Double
Dim t, av, flow As Double
Dim tInside As Double

l = Val(Text1.Text) ' length of collector(m)
w = Val(Text2.Text) ' width of collector(m)
b = Val(Text3.Text) ' gap between cover and collector plate(m)

a=l*w ' area of collector plate(m2)
Text9.Text = Round(a, 2)
t = 0.85 'Transmissivity
av = Val(Text4.Text) * 5 / 18 ' average air velocity(m/s)for air
ti = Val(Text5.Text) 'air inlet temperature
ta = Val(Text6.Text) 'ambient temperature
tInside = Val(Text7.Text) 'mean fluid temperature
s = Val(Text8.Text) 'solar flux incident on collector face
gp = Val(Text20.Text)
p = 1.077 'density of air
mfa = 4 * 0.08 * 0.06 * 0.6 * av * p * 3600 'air flow rate kg/hr

If tInside > ta Then
mfb = 3600 * p * 4 * 0.08 * 0.06 * 0.5 * ((2 * 9.8 * 2.1) / ((tInside - ta) / tInside)) ^ 0.5
Else
MsgBox ("Please check the values of Inlet temperature ,Ambient temperature or Mean
temperature and then continue")
Exit Sub
End If

mf = mfa + mfb
Text10.Text = Round(mf, 2)
AvgFlow = mf / (p * gp * w * 3600) ' air flow speed through the collector

ut = 6.2 'top loss coefficient
ub = 0.8 'bottom loss coefficient
u = ut + ub 'total loss coefficient
ec = 0.95 'emmisivity of the cover
ep = 0.95 'emmisivity of collector plate
cp = 1.005 'specific heat of air
v = 0.00001985 'viscosity of air
k = 0.0287 'thermal conductivity of air
de = 2 * (l * b) / (l + b) 'equivalent diameter

52

Text11.Text = Round(de, 2)
re = (p * AvgFlow * de) / v 'reynold no
Text12.Text = Round(re, 2)
nu = 0.0158 * (re ^ 0.8) 'nusselt no
hfc = nu * (k / de) 'convective heat transfer heat coefficient
hfp = nu * (k / de) 'convective heat transfer heat coefficient
sigma = 0.0000000567 'stefen boltzman constant
hr = (4 * sigma * ((273.2 + tInside) ^ 3)) / (1 / ep + 1 / ec - 1) 'radiative heat transfer coefficient
Text13.Text = Round(hr, 2)

he = hfc + (hr * hfc / (hr + hfc)) 'effective heat transfer coefficient
Text14.Text = Round(he, 2)

f = 1 / (1 + ((ut + ub) / he)) 'collector efficiency factor
Text15.Text = Round(f, 2)

cons = (mf * cp * 1000) / (3600 * u * a)
fr = cons * (1 - Exp(-f / cons)) 'collector heat removal factor
Text16.Text = Round(fr, 2)

qu = fr * a * (s * t - u * (ti - ta)) 'useful heat gain
Text17.Text = Round(qu, 2)

ef = qu / (s * a) 'efficiency of collector
Text18.Text = Round(ef, 2)

effi = Round(ef, 2)
tfo = (3.6 * qu) / (1.005 * mf) + ti 'air outlet temperature
Text19.Text = Round(tfo, 2)
End Sub

End
End Sub

PrintForm
End Sub

53


Program to estimate solar collector Area and no. of trays required for the fixed capacity
solar dryer in terms of quantity that can be loaded into it:

Purpose: The program estimates Solar collector area required at a particular place for
variable needs of drying needs.
Command Buttons.
Input Formats: giving input of the Quantity of Material, Initial moisture content(wb),
Desired final moisture content(wb), drying time, efficiency of the dryer, thickness of
material to be kept in the trays and the bulk density of the material.
Output: Output consists Collector area required for proper drying of material and no. of
trays required to dry the given quantity of material.

54

Code:

moistx = Val(Text2.Text) - Val(Text3.Text)
quant = Val(Text1.Text)
mr = quant * moistx / (100 - Val(Text3.Text))
Text4.Text = Round(mr, 2)
Text7.Text = Round(mr * 2800, 2) '(in Joules )
effi = Val(Text5.Text) / 100
dryday = Val(Text10.Text)
area = Val(Text7.Text) * 1000 / (9 * 3600 * dryday * Savg * effi)
Text6.Text = Round(area, 2)
End Sub

Dim captray As Double
Dim thick As Double
Dim bulk As Double
Dim notray As Integer
Dim q As Integer

thick = Val(Text8.Text)
bulk = Val(Text9.Text)
q = Val(Text1.Text)
captray = thick * bulk * 0.405 / 100 '( tray 90cm x 45 cm )
notray = q / captray
Text12.Text = Round(notray, 0) + 1
End Sub

Form5.Show
End Sub

PrintForm
End Sub

Text5.Text = Str(effi * 100)
End Sub

55


Program to estimate maximum drying capacity of the solar dryer installed at the college
premises.

Purpose: The program estimates maximum drying capacity of solar dryer in Kg of
material.
Command Buttons.
Input Formats: giving input of the Initial moisture content(wb), Desired final moisture
content(wb), drying time, efficiency of the dryer and area of the collector.
Output: Output consists of maximum drying quantity in given time period.

56

Code:


moistx = Val(Text1.Text) - Val(Text2.Text)
area = Val(Text4.Text) / 100
dryday = Val(Text3.Text)
effi = Val(Text6.Text)
qt = (area * 9 * 3600 * dryday * Savg * effi)
mr = qt / 2800000

quant = mr * (100 - Val(Text2.Text)) / moistx

Text5.Text = Round(quant, 1)

End Sub

Text6.Text = Str(effi * 100)
End Sub

57


Module consisting of all the variables used in the program

Purpose: The module to declare all the variables used in the project in various forms.
Usage: it has a declaration section with all the variables declared

The declaration code is as follows:

Option Explicit

Dim d As Single
Dim moistx As Double
Dim moisty As Double
Dim quant As Double
Dim mr As Single
Dim area As Double
Dim dryday As Single
Dim nt As Byte
Dim diff As Integer

Public n As Integer
Public w As Double
Public del, sinla, sindel, cosla, cosdel, cosw, cosz, expo, Ibn, Id, Ig, Ib As Double
Public total As Double
Public inso As Single
Public latDiff As Single
Public eqTime As Single
Public wDiff As Single
Public bd As Long
Public effi As Double
Public aa, ba, ca, ab, bb, cb, ac, bc, cc As Single
Public Inter As Integer
Public sinDiff, cosDiff, beta, cosQ, Rb, Rd, Rr, Sflux, Savg As Singl

58

RESUME

ACHAL GUPTA
Mob. No.: 9729635866

E-mail: achal4ever@gmail.com

OBJECTIVE

I am looking forward to spend some quality time at a good B-School enhancing my knowledge at
graduation level and learning the nitty gritties and nuances at negotiations, networking etc.

ACADEMIC QUALIFICATION

• Pursuing Bachelor of Technology in Agril. Engg. from CCS HAU HISAR (H.R) with
OGPA 7.43/10 in Jan, 2009.
• Passed Senior Sec. Examination from CBSE with 87.0% in June, 2005.
• Passed Matriculation examination from CBSE with 89.6% in June, 2003.

FIELDS OF STUDY

• Agricultural Processing & Energy
• Soil & Water Conservation Engineering
• Farm Power & Machinery

PROFESSIONAL TRAINING

• One month intensive training at Eicher Tractors a Unit of TMTL, Faridabad from 1st
July to 31st July, 2008.
• One month intensive training at the Central Farm Machinery Training and Testing
Institute, Budni (M.P.) from 1st July to 31st July, 2007.

COMPUTER AWARENESS

• MS-Office, C++, Visual Basic and Oracle
• Good working knowledge of Internet.

59

• Typing speed of 25 wpm
HOBBIES

• Listening to music
• Playing Sudoku, Table Tennis
• Reading novels

HONORS/ACTIVITIES

• ICAR (Indian Council of Agricultural Research) Scholarship Holder for the last 3 years
of graduation.
• President of the Hostel Co-operative mess for 2 Years.
• Participated in 10 Days NSS Annual Camp at University level (Aug 2007).
• NSS Volunteer for two years.
• Participated in various cultural and sports activities at College level.

PERSONAL PROFILE

Name : Achal Gupta
Father’s Name : Sh. Rajan Gupta
Date of Birth : 28th Feb, 1987
Gender : Male
Languages known : English & Hindi
Correspondence Address : Room No. 69, Kailash Hostel
No. 1, CCS HAU, Hisar-125004 (HR.).

DECLARATION

I hereby solemnly declare that all the statement made in the above resume is true and
correct to the best of my knowledge & belief.

Date: ___________ _______________
Place: ___________ (ACHAL GUPTA)

60

Computer Aided Thermal Design of a Solar Dryer

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