Abstract: A functional industrial ammonia plant has been simulated using the plant data. All the unit operations, including definition and formation of reactions set have been performed in Aspen HYSYS V8.8. The simulated results compared with the plant data indicate reasonable agreement. The process optimization was performed using the optimization techniques such as BOX, Mixed and Sequential Quadratic Programming in Aspen HYSYSV8.8. The SQP, Mixed and BOX optimization algorithms gave optimum variables at quick convergence with reasonable iterative numbers. It was therefore deduced that the SQP, Mixed and BOX algorithms were more appropriate for the multi-step ammonia process. From the algorithms, the optimum operating conditions that increased the yield of ammonia production are 43.97oC, 4839kPa and 25670kg/hr for natural gas and 280.6oC 21490.0kPa for the ammonia production respectively given the percentage of ammonia to increase from 24.37 to 41.04 mole percent. The performance criterion which was Energy consumption was the objective function which was minimized in the reforming sections. The results showed that there was reduction of energy from 125.36Gcal/hr to 75.095Gcal/hr in the primary reformer and from 43.021Gcal/hr to 34.37Gcal/hr in the secondary reformer respectively. The effect of process parameters on the component performance was performed. It was observed that temperature, pressure and mass flow rate of the natural gas greatly influenced the yield of ammonia. Comparison of the plant, simulated and optimized results were done in terms of operating process parameters and compositions of sour gas, desulfurized gas and ammonia synthesis converter products.
Abstract: The design models of isothermal batch and continuous stirred tank reactors are presented for bioremediation of crude oil in water environment. The reactor design equations were formulated based on conservation principle of mass and the reactor functional parameters simulated using MATLAB. The reactors were designed to treat crude oil at 95 to 99% degree of conversion with 79.5m3 volume of crude oil in water required to be treated daily. The results obtained showed that residence time for the batch reactor increased with increase in crude oil removed, which took approximately 2 hours. In addition, the heat generated per unit volume decreases with increase in residence time, which ranged from 6594 kJ/h.m3 to 6455 kJ/h.m3 at residence time of 1.904 to 1.984 hours and 95 to 99% crude oil removal. Similarly, the CTSR results showed that the volume and space time increased with increase in crude oil removed. The volume of CSTR ranged from 6.722 to 9.209m3, while space time ranged from 2.029 to 2.780 hours at 95 to 99% removal efficiency respectively. Conversely, the space velocity and heat generated per unit reactor volume decreased with increase in fractional conversion. The space velocity ranged from 0.493 to 0.36 h-1, while heat generated per unit reactor volume ranged from 1223 to 930.4kJ/hr.m3 at 95 to 99% removal efficiency respectively. Hence, the time required to remove one volume of crude oil fed into the reactor was higher in CSTR compared to the batch reactor, and at 79.5m3 of crude oil removal per day, the batch reactor will require 5 batches to complete the treatment. However, the heat generated per unit reactor volume was higher in batch reactor compared to the CSTR.
Abstract: Quinizarin, an anthraquinone derivative, was used as “antifraud marker”. It was added in three several amounts (0.25%, 0.5% and 1.0%) in water-based disperse ink-jet inks. Surface tension, viscosity, conductivity and pH of the ink formulations were monitored over a period of 90 days in order to estimate the ink stability and the compatibility of the “antifraud” active agents with the ink constituents. The inks were used for ink-jet printing to polyester and polyamide samples. Fastness (light, wash and rub) and also color properties of the samples were measured. Finally, qualitative and quantitative determination of the active agent was made from the printed samples with extraction.
Abstract: In Ethiopia, the weather condition is different at different places due to change in altitude, the usage of water temperature in casting the concrete place an important role. In the present research study it has an examined the eﬀects of different mixing water temperature on the performance on fresh and harden concrete properties which are made with locally available cement. In this research testing is done for both plastic and hardened concrete with different temperatures of water at 150 C, 25 °C and 40 °C with constant water - binder ratio 0.5. Based on our experimental results and observations, we concluded that decrease in compressive and flexural strength at 100 and increase in strength for 400. Similarly it was observed in workability also. Hence in practical there is no need of change in mix design / take additional precaution for change in temperature of water up to 400 C. The higher temperature of mixing water in bleeding, segregation and other properties can be added for further relative study.
Abstract: In this work, a mathematical model has been developed for the simulation of multiple effect evaporators (MEE) system from a set of non-linear equations, Evaporation is the most energy intensive unit in pulp and paper industries, feed and product flashing, condensate, boiling point rise, vapour bleeding, etc are considered to reduce energy consumption. An inquiry into PZ PLC, a manufacturing industry situated in Aba, Abia state; for concentrating liquor using falling film plate evaporator in steam splitting in the first two effects to generate vapour used in vapour bodies within the system. Evaporation is the removal of solvent as vapour from a solution. It is the operation which is used for concentration of solution. There could be single effect evaporator or multiple effect evaporators. With addition of each effect steam economy of the system also increases. Evaporators are integral part of a number of a process industry like Pulp and Paper, Sugar, Caustic Soda, Pharmaceuticals, Desalination, Dairy and Food Processing etc. Caustic Soda Industry is of present interest. The system consists of triple effect having falling film evaporator as each effect. There is forward feed and backward feed flow. This paper describes a steady state model of multiple effect evaporators for simulation purpose. The model includes overall as well as component mass balance equations, energy balance equations and heat transfer rate equations for area calculation for all the effects. Each effect in the process is represented by a number of variables which are related by the energy and material balance equations for the feed, product and vapour flow for forward feed & backward feed, The results of present work with concentration in effect-I at 0.853558 was validated against previous work of (Kumar and Zain, 1996) at 0.7942216 and it shows close agreement. Also considering a backward result of effect-III product L_(3 )as 0.327396 while that of (Kumar and Zain, 1996) as 0.398923 fro
Abstract: An algorithm for the estimation of the kinetic parameters using five lump kinetic schemes for fluid catalytic cracking of vacuum gas oil has been developed. The optimization models were also developed using single point regression analysis to predict the pre-exponential function and activation energies. The mathematical models for the riser reactor were also developed to predict the yields of the various components. Mathematical model were integrated numerically using the fourth order runge-kutta algorithm. The optimization models were solved using Matlab version 8.4. Model predictions from the optimization model were, for activation energies Ei; 36.9920kJ/mol, 44.8125 kJ/mol, 41.8250 kJ/mol, 52.5800 kJ/mol, 57.2977 kJ/mol, 56.5128 kJ/mol, 50.5800 kJ/mol and pre-exponential function ki0; 0.0017400s-1, 0.00002160 s-1, 0.00002024 s-1, 0.00055195 s-1, 0.00006234 s-1, 0.000017464 s-1, 0.002542400 s-1 with a maximum deviation of 30%. The yield from the riser model showed gasoline as been the most obtained essential product and lesser coke formation compared to the yields obtained without optimization.
In this paper, we introduce an Artificial Neural Network (ANN) classifier for
human activity recognition. The proposed system is divided to three stages; first we do
segmentation for raw data collected for two data sets WHARF and UCI-HAR to segment
length 128 and 256 with 50% overlap for WHARF, and 128, 256 and 512 with 50% overlap
for UCI_HAR. Second, for each segment, a set of time and frequency domain features are
extracted and delivered to the ANN classifier. From a practical point of view, activity
classification based on segments of data compared to the use of whole raw data is more
suitable and enables faster classification process, especially for short activities. The
proposed system is tested against other classifiers such as support vector machines (SVM),
naive Bayes, and k-nearest neighbor (KNN) where ANN gives the best recognition rate. For
WHARF dataset, the average accuracy is 68% for segment length 128 and 80% for 256
segment length. On the other hand, employing accelerometer data only in UCI-HAR
dataset, the average accuracy is 93.9% for segment length 128, 94.6% for segment length
256 and 96.3% for segment length 512. While using gyroscope data in the same dataset
results in an average accuracy of 77.96% for segment length 128, 83.75% for segment
length 256 and 88.96% for segment length 512.