Light naphtha one of the products from distillation column in oil refineries used as feedstock for gasoline production. The major constituents of light naphtha are (Normal Paraffin, Isoparaffin, Naphthene, and Aromatic). In this paper, we used zeolite (5A) with uniform pores size (5Aº) to separate normal paraffin from light naphtha, due to suitable pore size for this process and compare the behavior of adsorption with activated carbon which has a wide range of pores size (micropores and mesopores) and high surface area. The process is done in a continuous system - Fixed bed reactor- at the vapor phase with the constant conditions of flow rate 5 ml/min, temperature 180oC, pressure 1.6 bar and 100-gram weight of each adsorbents. We notice that the molecular sieve (5A) separated the normal paraffin (C4 – C8) from light naphtha feed until equilibrium (saturation). Activated carbon separated naphthene and aromatics, in addition, the other component of normal paraffin C6 (n-hexane), C7 (n-heptane) and C8 (n-octane). And there is increasing in weight percentage of C4 (n-butane), C5 (n-pentane) and the weight percentage of isoparaffin until equilibrium (Saturation). The study showed the difference in physical adsorption behavior and the effect of pore size on these processes.
A prey-predator interaction model has been suggested in which the population of a predator consists of a two-stage structure. Modified Holling's disk equation is used to describe the consumption of the prey so that it involves the additional source of food for the predator. The fear function is imposed on prey. It is supposed that the prey exhibits anti-predator behavior and may kill the adult predator due to their struggle against predation. The proposed model is investigated for existence, uniqueness, and boundedness. After determining all feasible equilibrium points, the local stability analyses are performed. In addition, global stability analyses for this model using the Lyapunov method are investigated. The chance of occurrence of loc
... Show MoreIn solar-thermal adsorption/desorption processes, it is not always possible to preserve equal operating times for the adsorption/desorption modes due to the fluctuating supply nature of the source which largely affects the system’s operating conditions. This paper seeks to examine the impact of adopting unequal adsorption/desorption times on the entire cooling performance of solar adsorption systems. A cooling system with silica gel–water as adsorbent-adsorbate pair has been built and tested under the climatic condition of Iraq. A mathematical model has been established to predict the system performance, and the results are successfully validated via the experimental findings. The results show that, the system can be operational
... Show MoreThe zeolite's textural properties have a significant effect on zeolite's effectiveness in the different industrial processes. This research aimed to study the textual properties of the NaX and FeX zeolites using the nitrogen adsorption-desorption technique at a constant low temperature. According to the International Union of Pure and Applied Chemistry, the adsorption-desorption isotherm showed that the studied materials were mixed kinds I/II isotherms and H3 type hysteresis. The Brunauer-Emmett-Teller isotherm was the best model to describe the nitrogen adsorption-desorption better than the Langmuir and Freundlich isotherms. The obtained adsorption capacity and Brunauer-Emmett-Teller surface area values for NaX were greater than FeX. Ac
... Show MoreThe solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentratio
... Show MoreOur research is based on the fact that the reflection of entertainment programs in Arab satellite channels on the social behavior of Iraqi youth … a field analysis of the Arab ldol program) and that its importance is the entertainment programs and their reflection on social behavior، which occupies
large areas of time from Satellite channels in the form of various episodes and each episode contains several categories، or in the form of templates and forms of various goals and contents، but the problem of
research boils down to (how far iraqi youth follow the entertainment programs in Arab satellite channels and what are the motives for watching the Program Arab ldol )) by For Iraqi youth and what are the positive and negative
Abstract
The present study investigates the effect of acetic acid on corrosion behavior and its potential of hydrothermally sealed anodized AA2319-Al-alloys. Anodizing treatment was performed in stagnant phosphoric acid electrolyte with or without addition of acetic acid. Hydrothermal sealing was carried out in boiling water for each anodized specimen. The open circuit potential of the unsealed and sealed anodized samples was examined using open circuit potential measurement for the purpose of starting in scanning polarization diagrams. The potentiostatic polarization technique measurements were performed to assess corrosion behavior and sealing quality (i.e., degree of sealing) of
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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