Batch reactive distillation was studied in packed bed column. Esterification of methanol with acetic acid to produce methyl acetate and water with homogenous sulfuric acid as a catalyst was considered. This system was chosen because the reaction is reversible and the boiling point of reactant and products are different.
The reaction was carried out with and without distillation column and shows that the reactive distillation is more efficient from the conventional process (reactor and then separation). The conversion of acetic acid and concentration of methyl acetate increase by (30.43% and 75.14%) respectively at the best condition (reflux ratio 2, feed mole ratio 2 and batch time 90 minute).
The influence of various parameters, such as batch time, reflux ratio, and feed mole ratio (methanol to acetic acid) on the performance of the batch reactive distillation column was studied, through the effect of the concentration of product and conversion of reactant.
The results obtained for the non-ideal packed bed reactive batch distillation column show that the conversion of acetic acid is 90% at the best condition reflux ratio 2, feed mole ratio 2, and batch time 90 minute
Seeds of five cultivars of oats (Avena sativa) were introduced from Italy in 2009. Seeds were propagated on the farm of the Dept. of Field Crops Sci. / Coll. of Agric. / Univ. of Baghdad in the season 2009 – 2010. The cultivars Anatolia, Alguda, Hamel, Pimula and Genzania were planted under 3 irrigation intervals; 3, 4 and 5 weeks to give water depth of 480, 400 and 320 mm, respectively . The depth of water was 80 mm each irrigation. A factorial experiment with RCBD of 4 replicates was conducted in 2 consecutive seasons in 2010 – 2011 and 2011 – 2012. The cultivar Alguda gave highest grain yield (8.07 t/ ha) under 480 mm, and 7.02 t / ha average of 3 water depths. This cultivar was characterized by high growth rate (13.2 g/m2/ d) that
... Show MoreThe world's population growth and the increasing demand for new infrastructure facilities and buildings , present us with the vision of a higher resources consumption, specially in the form of more durable concrete such as High Performance Concrete (HPC) . Moreover , the growth of the world pollution by plastic waste has been tremendous. The aim of this research is to investigate the change in mechanical properties of HPC with added waste plastics in concrete. For this purpose 2.5%, 5% and 7.5% in volume of natural fine aggregate in the HPC mixes were replaced by an equal volume of Polyethylene Terephthalate (PET) waste , got by shredded PET bottles. The mechanical propert
... Show MoreBackground: Health information systems in most countries are inadequate in providing the needed management support and the current health information systems are therefore widely seen as management obstacles rather than as tools,Objectives: the current study is an attempt to assess the behavioral and organizational determinants of health information system performance in Iraq.Methods: A cross-sectional study was conducted by interviewed a total of 189 respondents selected from six Iraqi governorates. The Organizational and Behavioral Assessment Tool was used to measure the behavioral and organizational determinants of health information system performance, it is one of the PRISM package tools that are used to assess the health informatio
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In this paper, introduce a proposed multi-level pseudo-random sequence generator (MLPN). Characterized by its flexibility in changing generated pseudo noise (PN) sequence according to a key between transmitter and receiver. Also, introduce derive of the mathematical model for the MLPN generator. This method is called multi-level because it uses more than PN sequence arranged as levels to generation the pseudo-random sequence. This work introduces a graphical method describe the data processing through MLPN generation. This MLPN sequence can be changed according to changing the key between transmitter and receiver. The MLPN provides different pseudo-random sequence lengths. This work provides the ability to implement MLPN practically
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The sensors based on Nickel oxide doped chromic oxide (NiO: Cr2O3) nanoparticals were fabricated using thick-film screen printing of sol-gel grown powders. The structural, morphological investigations were carried out using XRD, AFM, and FESEM. Furthermore, the gas responsivity were evaluated towards the NH3 and NO2 gas. The NiO0.10: Cr2O3 nanoparticles exhibited excellent response of 95 % at 100oC and better selectivity towards NH3 with low response and recovery time as compared to pure Cr2O3 and can stand as reliable sensor element for NH3 sensor related applications.
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so
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Autonomous systems are these systems which power themselves from the available ambient energies in addition to their duties. In the next few years, autonomous systems will pervade society and they will find their ways into different applications related to health, security, comfort and entertainment. Piezoelectric harvesters are possible energy converters which can be used to convert the available ambient vibration energy into electrical energy. In this contribution, an energy harvesting cantilever array with magnetic tuning including three piezoelectric bimorphs is investigated theoretically and experimentally. Other than harvester designs proposed before, this array is easy to manufacture and insensitive to manufacturi
... Show MoreThe Sliding Mode Control (SMC) has been among powerful control techniques increasingly. Much attention is paid to both theoretical and practical aspects of disciplines due to their distinctive characteristics such as insensitivity to bounded matched uncertainties, reduction of the order of sliding equations of motion, decoupling mechanical systems design. In the current study, two-link robot performance in the Classical SMC is enhanced via Adaptive Sliding Mode Controller (ASMC) despite uncertainty, external disturbance, and coulomb friction. The key idea is abstracted as follows: switching gains are depressed to the low allowable values, resulting in decreased chattering motion and control's efforts of the two-link robo
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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