ABSTRACT
An experimental and theoretical study of the heat and mass transfer process in the gari frying chamber of an existing gari frying machine was undertaken. Cassava tubers were peeled, grated, fermented and dewatered to make the dough ready for frying. During frying, the temperature readings of the trough, walls, atmosphere, flue gas, flame from the burner and gari were taken at different positions and time interval. Also theoretical analysis was carried out in which the numerical solution was obtained by MATLAB BVP4C code. The experimental results obtained were compared with the theoretical results. The experimental results showed three noticeable stages along the trough. The first was the cooking stage where the temperature rose and came down sharply as a result of temperature distribution of the flame of the burner. The second was the mass transfer stage where the temperature on the trough remained constant. And finally the third stage where drying took place and the temperature rose a little before dropping. For a frying rate of 54kg/hr and fuel consumption of 5 litres per hour, it was found that the useful efficiency was about 24% while the overall efficiency of the machine was 85%.
TABLE OF CONTENTS
TITLE PAGE —————————————– I
CERTIFICATION —————————————– II
DEDICATION —————————————– III
ACKNOWLEDGEMENT ————————————— IV
ABSTRACT —————————————– V
TABLE OF CONTENTS —————————————- VI
LIST OF FIGURES —————————————- VIII
LIST OF TABLES —————————————- XI
INTERPRETATION OF SYMBOLS ————————- XII
CHAPTER ONE: LITERATURE REVIEW ————— 1
- Introduction —————————— 1
CHAPTER TWO: LITERATURE REVIEW
2.1 Literature Review —————————— 6
- Mechanized Methods ——————————- 12
- Discussion and Conclusion ———————— 18
- Objectives ————————————– 21
CHAPTER THREE: EXPERIMENTATION —————- 22
3.1 Preparation of Dough ————————- 22
3.2 Materials —————————————- 24
3.2.1 Cassava —————————————- 24
3.2.2 Fuel —————————————- 26
3.2.3 Diesel Burner ——————————– 27
3.2.4 Trough —————————————- 28
3.2.5 Combustion Chamber ———————— 28
3.2.6 Chimney ————————————— 28
3.2.7 Grinding Machine —————————— 29
3.2.8 Jack Compression Machine ——————————- 30
3.2.9 Metal Sieve ——————————————- 31
3.2.10 Paddles ——————————————- 32
3.2.11 Electric Motor ——————————————- 33
3.2.12 Switch Board ——————————————- 34
3.2.13 Measuring Tape and Calipers ————————— 35
3.2.14 Temperature Measuring Device ———————— 35
3.2.15 Weighing Balance ———————————– 35
3.3 Experimental Data ———————————– 38
3.4 Experimental Results ———————————– 39
CHAPTER FOUR: THEORETICAL ANALYSIS ————– 44
4.1 Derivation of Governing Equations —————— 44
4.1.1 Energy Balance of the System —————— 47
4.1.2 Derivation of Governing Equations —————– 50
4.2 Numerical Solution —————————————- 58
4.3 Theoretical Results —————————————- 62
CHAPTER FIVE: RESULTS AND DISCUSSIONS ——— 65
5.1 Calculated Result ————————————— 65
5.1.1 Calculation of Adiabatic Temperature ——– 65
5.1.2 Calculation of Heat Transfer Coefficient ——– 71
5.1.3 Calculation of Efficiency of the Machine ——– 88
5.2 Result and Discussion ——————————- 95
5.3 Conclusion ———————————————- 102
REFERENCES —————————————————— 104
Appendix A Matlab Program Used in Obtaining the Theoretical Result 108
Appendix B Calculation of Adiabatic Temperature ———————- 109
CHAPTER ONE
INTRODUCTION
1.1 INTRODUCTION
Cassava (Manihot Esculenta Crantz) is one of the most important energy sources in the human diet in the tropics. The estimated annual production ranges from 34 – 42 million tonnes (RMRDC, 2004), with Nigeria accounting for over 70% of the output from West Africa. It is estimated that 172 million tonnes of cassava was produced worldwide in 2000. Africa, Asia, and Latin America and the Caribbean accounted for 54, 28 and 19 per cent of the total world production respectively. The average yield in 2000 was 10.2 tonnes per hectare, but this varied from 1.8 tonnes per hectare in Sudan, to 10.6 tonnes per hectare in Nigeria, and 27.3 tonnes per hectare in Barbados. In 2002 Nigeria produced 34 million tonnes, making it the world’s largest producer. Figure 1.1 shows young cassava plants in a farm, while figure 1.2 shows freshly harvested cassava tubers.
Fresh cassava has a very short post-harvest storage life, and it must be used or processed into durable forms soon after harvest (Ayernor, 1981)
Cassava is used extensively for human and livestock consumption as well as for other industrial products. In Nigeria cassava can be processed into gari, fufu, topioca (sliced chips), flour, starch etc.
Among all the above mentioned products of cassava, gari is the most common and forms the main meal of the day for majority of people in West Africa. Gari production is the most improved technology in cassava processing. It is a pre-gelatinized grit with particle size ranging from below 10µm (fines) to over 2000µm (coarse) (Ayernor, 1981, F.I.I.R.O) Gari processing involves such operation as peeling and washing, grating, fermenting, Dewatering, pulverization, sieving and frying as illustrating in fig 1.3
Fig.1.1 Growing Cassava
Fig.1.2 Harvested Cassava Tubers
Cassava for processing
Figure 1.3 Flow Sheet of Gari Production Starting with Raw Cassava Root.
One major bottleneck in gari processing has been gari frying. Gari frying involves pressing, scraping and stirring of sifted cassava mash over a hot plate at 120 to 200oC in a repetitive manner. Heat transfer from the hot plate results in the toasting of the gari particles, while starch pressed out from the granules coats the gari particles and is partially gelatinized to form a tin enveloping film. Odigboh (1982) has termed this process “garification” to emphasize the fact that gari frying involves more than mere high temperature drying.
The need to upgrade the indigenous food processing techniques calls for the understanding of the fundamental scientific and technological principles involved (Ayernor, 1981, Sefa-Dedeh, 1989). This would be useful in fostering technology improvement. Most of the unit operations in gari production have been mechanized, but to some varying degrees. Attention has been only focused on machine design, fabrication and testing with very little efforts devoted to mathematical modeling and simulation. A better understanding of the machine can be gained by subjecting the machine/processes to detailed mathematical analysis and system optimization. By doing this, many design details and performance parameters can be verified for a large number of operating conditions at a very low cost even before a physical system is built.
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