PHD-Department of Energy Technology
http://ir-library.ku.ac.ke/handle/123456789/268
2022-09-26T06:48:52ZDesign Optimization of Municipal Solid Waste Incinerators Using Mathematical Modeling and Computer Simulation
http://ir-library.ku.ac.ke/handle/123456789/21236
Design Optimization of Municipal Solid Waste Incinerators Using Mathematical Modeling and Computer Simulation
Sarakikya, Halidini Hatibu
Environmental pollution caused by the Municipal Solid Waste (MSW) incinerators has
raised concerns about the quality of incinerators and the incineration process in Tanzania.
Engineers and Scientists in general have appreciated that the installation of functional
incinerators will increase the incineration process efficiency. Among the methods to
achieve this is the application of mathematical modeling for the incineration process.
Literatures have showed that related study in incinerators, incineration process and
mathematical modeling in general has received little attention.
The broad objective of this study was to optimize the design of municipal solid waste
incinerators by using mathematical modeling and computer simulation. Computation
Thermal Predictions (CTP) mathematical relations applying different types of
incineration parameters including temperature, density, velocity and species
concentration were formulated based on theories of incineration process with proper
assumptions. The solution of the mathematical model developed was done and
accomplished by computational fluid dynamics (CFD).
Finite element method of numerical analysis was applied during the process to govern
temperature and species concentration at different stack height of the model incinerator.
Tests were performed on the physical model incinerator and data were analyzed after
experiments. These data were applied in testing and verification of the mathematical
models and provided the exact temperature and amount of flue gases which can be
released from the stack without polluting the atmosphere.
The results show that it is possible to forecast temperature and flue gases by the
application of mathematical expressions. It also can be applied to develop more and
accurate computational thermal predictions (CTP) model for the simulation of
incineration process and experimentally regulate temperature and species concentration at
different location of the incinerator. The results provided by the computational thermal
predictions (CTP) were very close to those of experiments obtained from physical model.
Therefore, there is an agreement between the empirical model and experiment as they
show true trend of the incineration process.
A Research Thesis Submitted in Fulfillment of the Requirements for the Award of the Degree of Doctor of Philosophy in Sustainable Energy Engineering in the School of Engineering and Technology of Kenyatta University. July, 2020
2020-07-01T00:00:00ZSimulation and Optimisation of a Drying Model for a Forced Convection Grain Dryer
http://ir-library.ku.ac.ke/handle/123456789/18984
Simulation and Optimisation of a Drying Model for a Forced Convection Grain Dryer
Osodo, Booker Onyango
Forced convection grain dryers are more efficient and achieve greater drying rates
than natural convection dryers. However, it is necessary to provide an appropriate
solar air heater in order to achieve the required drying air temperature. Well sized
fan and drying cabinet, as well as an optimal combination of air velocity,
temperature and grain layer thickness are also essential for improved performance of
such a dryer. In order to predict variation of moisture content with time during the
drying process, it is necessary to have an appropriate drying model. In this study
carried out at Njoro, Nakuru County in Kenya, an experimental grain dryer was
sized, fabricated and its performance investigated under different drying conditions.
Simulation of air flow within an initial model of the dryer was done and the results
used to size the fan and drying cabinet. The effect of air velocity, grain layer
thickness, number of trays and temperature on drying efficiency (ratio of energy
used in removing moisture to sum of energy lost by drying air and that used for
running fan) and moisture removal rate (ratio of mass of moisture removed to mass
of wet grain per unit time) was investigated. The Taguchi approach was used to
determine the optimal combination of drying air velocity, temperature and grain
layer thickness that could be used to ensure greatest drying efficiency and Moisture
Removal Rate (MRR). Analysis of Variance (ANOVA) and Least Square
Differences (LSD) tests were used to determine whether change of air velocity and
grain layer thicknesses significantly affected drying efficiency as well as MRR. The
best fitting drying model for drying maize grain was selected and subsequently used
to develop a computer simulation model for predicting drying time. On the basis of
simulation results, number of trays and mass of grain to be dried per batch, the
experimental grain dryer developed was of dimensions 0.5 m x 0.5 m x 1.0 m and
was equipped with a 0.039 kW centrifugal fan. MRR was found to decrease with
increase in grain layer thickness as long as air velocity was kept constant. For
example, at 0.41 m/s air velocity, as grain layer thickness increased from 0.02 to
0.08 m, MRR decreased from 0.061 to 0.022 kg moisture / (kg wet grain. hour).
Drying efficiency decreased with increase in drying air temperature where-as MRR
increased with rise in air temperature as long as air velocity and layer thickness
remained constant. For an air velocity of 0.41 m/s and 0.04 m grain layer thickness,
drying efficiency was 23.5% at 40 °C and reduced to 10.1 % at 55 °C. On the other
hand, MRR increased from 0.045 to 0.058 kg moisture / (kg wet grain. hour) over
the same temperature range. It was found that when drying a given grain layer
thickness, use of two trays did not significantly improve MRR as compared to the
use of one. As a result of the optimisation process, it was also determined that when
drying was done under laboratory conditions, a combination of 0.41 m/s air velocity,
45 °C air temperature and 0.02m layer thickness resulted in greatest MRR and
drying efficiency. The drying model that best describes the drying curve was found
to be the Midilli model. The optimal drying parameters, if applied by the user of the
dryer, will result in optimal drying rate and drying efficiency, and this in turn will
lead to reduced post-harvest grain loss. The computer simulation model developed
will enable the farmer to plan drying schedules. Application of simulation to size the
fan and dryer cabinet should be emulated by those who seek to size dryers. It is
recommended that further study be carried out to determine the effect of grain
porosity on dryer performance. Investigations should also be done to find ways of
utilizing the warm exhaust air from the dryer.
A Thesis Submitted in Partial Fulfillment of the Requirements for the Award of the Degree of Doctor of Philosophy (Renewable Energy Technology) in the Department of Energy Technology in the School of Engineering and Technology of Kenyatta University. November, 2018
2018-01-01T00:00:00Z