In this paper, a theoretical analysis of optimum bed thickness operates under mass transfer control for realizing a high efficiency and reaction conversion of an electrochemical reactor has been made based on flowthrough porous electrode (FTPE) configuration. Many models have been used to represent the optimum bed thickness by taking a look into previous works concerned and collecting all related information, data, and models. The parameters that affect the optimum bed thickness have been visualized and reviewed, and almost all of them have been examined by experimental data from different sources and based on the various models. It has been found that the increase in electrolyte flow rate, concentration, limiting current density, and specific surface area reduce the optimum bed thickness, and the increase in electrolyte conductivity, void fraction, and overpotential range increases optimum bed thickness. The most important design parameter that has a great effect on optimum bed thickness is found to be the electrolyte flow rate for any certain operation. It has been concluded that the most appropriate two models to represent the optimum bed thickness of FTPE electrochemical reactor operating under mass transfer control based on the results are those predicted theoretically and stated by Kreysa in (1978) and Doherty et al. in (1996).
The catalytic wet air oxidation (CWAO) of phenol has been studied in a trickle bed reactor
using active carbon prepared from date stones as catalyst by ferric and zinc chloride activation (FAC and ZAC). The activated carbons were characterized by measuring their surface area and adsorption capacity besides conventional properties, and then checked for CWAO using a trickle bed reactor operating at different conditions (i.e. pH, gas flow rate, LHSV, temperature and oxygen partial pressure). The results showed that the active carbon (FAC and ZAC), without any active metal supported, gives the highest phenol conversion. The reaction network proposed account
... Show MorePurpose: This study aimed to assess the thickness of alveolar bone of maxillary and mandibular incisors from orthodontics perspective. Materials and Method: A total of 73 Cone beam computed tomography for Iraqi patients (47 females and 26 males) were included in this study. The selected images were captured and imported to AutoCAD database software to perform the measurement. To measure alveolar bone thickness, a reference line was drawn through the long axis of each incisor, from the incisal edge to the root apex. Then, labial and lingual/palatal perpendicular lines were drawn to the reference line at 3, 6, and 9mm apically from the cemento-enamel junction (CEJ). Results: The buccal bone is generally thinner than the lingual/palata
... Show MoreThis study deals with knowing the types of research in public relations studies at the Faculty of Mass Communication for the period from 1989 to 2007 and knowing the methods that researchers used in their studies, as well as knowing the methods and tools of scientific research that were used, and whether one method or tool is used more than others, and knowing Samples used in the analysis. As well as the contents and types of this research The institutions that were subjected to the study, and the preparation of the respondents This research aims to answer the following questions:. A- What are the types of research and methods that were used in university theses that dealt with the topic? Public Relations at the Faculty of Media from 1989
... Show MoreThin films of CdTe were prepared with thickness (500, 1000) nm on the glass substrate by vacuum evaporation technique at room temperature then treated different annealing temperatures (373,473,and 573)K for one hour. Results of the Hall Effect and the electrical conductivity of (I-V) characteristics were measured in darkness and light.at different annealing temperature results show that the thin films have ability to manufacture solar cells, and found that the efficient equal to (2.18%) for structure solar cell (Algrid / CdS / CdTe /glass/ Al) and the efficient equal to (1.12%) for structure solar cell (Algrid / CdS / CdTe /Si/ Al) with thick ness of (1000) nm with CdTe thin films at RT.
A study has been done to find the optimum separators pressures of separation stations. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid discharged from a higher pressure separator into the lower pressure separator. The set of working separators pressures which yield maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures which is the target of this work.
Computer model is used to find the optimum separators pressures. The model employs the Peng-Robinson equation of state for volatile oil. Application of this model shows good improvement of al
Waveform flow of non-Newtonian fluid through a porous medium of the non-symmetric sloping canal under the effect of rotation and magnetic force, which has applied by the inclined way, have studied analytically and computed numerically. Slip boundary conditions on velocity distribution and stream function are used. We have taken the influence of heat and mass transfer in the consideration in our study. We carried out the mathematical model by using the presumption of low Reynolds number and small wave number. The resulting equations of motion, which are representing by the velocity profile and stream function distribution, solved by using the method of a domain decomposition analysis a
Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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