Search results for: batch and fixed bed study

Authors: Alessandra Chiara Maraschin, Estelle Trengove

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In South Africa, only 23% of engineering students attain their degrees in the minimum time of 4 years. This begs the question: Why is the 4-year throughput rate so low? Improving the throughput rate is crucial in assisting students to the shortest possible path to completion. The Electrical Engineering programme has a fixed curriculum and students must pass all courses in order to graduate. In South Africa, as is the case in several other countries, many students rely on external funding such as bursaries from companies in industry. If students fail a course, they often lose their bursaries, and most might not be able to fund their 'repeating year' fees. It is thus important to improve the throughput rate, since for many students, graduating from university is a way out of poverty for an entire family. In Electrical Engineering, it has been found that the Software Development I course (an introduction to C++ programming) is a significant hurdle course for students and has been found to have a low pass rate. It has been well-documented that students struggle with this type of course as it introduces a number of new threshold concepts that can be challenging to grasp in a short time frame. In an attempt to mitigate this situation, a part-time night-school for Software Development I was introduced in 2015 as an intervention measure. The course includes all the course material from the Software Development I module and allows students who failed the course in first semester a second chance by repeating the course through taking the night-school course. The purpose of this study is to determine whether the introduction of this intervention course could be considered a success. The success of the intervention is assessed in two ways. The study will first look at whether the night-school course contributed to improving the pass rate of the Software Development I course. Secondly, the study will examine whether the intervention contributed to improving the overall throughput from the 2nd year to the 3rd year of study at a South African University. Second year academic results for a sample of 1216 students have been collected from 2010-2017. Preliminary results show that the lowest pass rate for Software Development I was found to be in 2017 with a pass rate of 34.9%. Since the intervention course's inception, the pass rate for Software Development I has increased each year from 2015-2017 by 13.75%, 25.53% and 25.81% respectively. To conclude, the preliminary results show that the intervention course is a success in improving the pass rate of Software Development I.

Keywords: academic performance, electrical engineering, engineering education, intervention course, low pass rate, software development course, throughput

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Authors: Yogi Wibisono Budhi, Ferry Iskandar, Veinardi Suendo, Muhammad Fakhrudin, Neng Tresna Umi Culsum

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Oil palm empty fruit bunch (OPEFB), an abundant agro-waste in Indonesia, is being studied as raw material of Cellulose Nanocrystals (CNC) synthesis. Instead of conventional acid mineral, phosphotungstic acid (H₃PW₁₂O₄₀, HPW) was used to hydrolyze cellulose due to recycling ability and easy handling. Before hydrolysis process, dried EFB was treated by 4% NaOH solution at 90oC for 2 hours and then bleached using 2% NaClO₂ solution at 80oC for 3 hours to remove hemicellulose and lignin. Hydrolysis reaction parameters such as temperature, acid concentration, and reaction time were optimized with fixed solid-liquid ratio of 1:40. Response surface method was used for experimental design to determine the optimum condition of each parameter. HPW was extracted from the mixed solution and recycled with diethyl ether. CNC was separated from the solution by centrifuging and washing with distilled water and ethanol to remove degraded sugars and unreacted celluloses. In this study, pulp from dried EFB produced 44.8% yield of CNC. Dynamic Light Scattering (DLS) analysis showed that most of CNC equivalent diameter was 140 nm. Crystallinity index was observed at 73.3% using X-ray Diffraction (XRD) analysis. Thus, a green established process for the preparation of CNC was achieved.

Keywords: acid hydrolysis, cellulose nanocrystals, oil palm empty fruit bunch, phosphotungstic acid

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Authors: Shun-Chang Yen, You-Lun Peng, Kuo-Ching San

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A numerical study on a bluff-body structure with multiple holes was conducted using ANSYS Fluent computational fluid dynamics analysis. The effects of the hole number and jet inclination angles were considered under a fixed gas flow rate and nonreactive gas. The bluff body with multiple holes can transform the axial momentum into a radial and tangential momentum as well as increase the swirl number (S). The concentration distribution in the mixing of a central carbon dioxide (CO2) jet and an annular air jet was utilized to analyze the mixing efficiency. Three bluff bodies with differing hole numbers (H = 3, 6, and 12) and three jet inclination angles (θ = 45°, 60°, and 90°) were designed for analysis. The Reynolds normal stress increases with the inclination angle. The Reynolds shear stress, average turbulence intensity, and average swirl number decrease with the inclination angle. For an unsymmetrical hole configuration (i.e., H = 3), the streamline patterns exhibited an unsymmetrical flow field. The highest mixing efficiency (i.e., the lowest integral gas fraction of CO2) occurred at H = 3. Furthermore, the highest swirl number coincided with the strongest effect on the mass fraction of CO2. Therefore, an unsymmetrical hole arrangement induced a high swirl flow behind the porous disc.

Keywords: bluff body with multiple holes, computational fluid dynamics, swirl-jet flow, mixing efficiency

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Authors: Rawan Aljabbari, Thamer Alomayri, Faisal G. Al-Maqate, Abeer Al Suwat

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For environmentally friendly innovative technologies and a sustainable future, fly ash/TiO₂ thin film nanocomposites are essential. Fly ash will be doped with titanium dioxide in this work in order to better understand its optical characteristics and employ it in semiconductor electrical devices. This study focused on the structure, morphology, and optical properties of fly ash/TiO₂ thin films. The spin-coating technique was used to create thin coatings of fly ash/TiO₂. For the first time, the doping of TiO₂ in the fly ash host at ratios of 1, 2, and 3 wt% was investigated with the thickness of all samples fixed. When compared to undoped thin films, the surface morphology of the doped thin films was improved. The weakly crystalline structure of the doped fly ash films was verified by XRD. The optical bandgap energy of these films was successfully reduced by the TiO₂ doping, going from 3.9 to 3.5 eV. With increasing dopant concentration, the value of Urbach energy is increasing. The optical band gap is clearly in opposition to the disorder. While it considerably improved the optical conductivity to a value of 4.1 x 10^9 s^(-1), it also raised the refractive index and extinction coefficient. Depending on the TiO₂ doping ratio, the transmittance decreased, and the reflection increased. As the TiO₂ concentration rises, the absorption of photon energy rises, and the absorption coefficient of photon energy is reduced. results in their possible use as solar energy and semiconductor materials.

Keywords: fly ash, structural analysis, optical properties, morphology

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Authors: Farzad Danaei, Yilmaz Akkaya

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In many civil engineering applications, especially in the construction of large concrete structures, the early age behavior of concrete has shown to be a crucial problem. The uneven rise in temperature within the concrete in these constructions is the fundamental issue for quality control. Therefore, developing accurate and fast temperature prediction models is essential. The thermal properties of concrete fluctuate over time as it hardens, but taking into account all of these fluctuations makes numerical models more complex. Experimental measurement of the thermal properties at the laboratory conditions also can not accurately predict the variance of these properties at site conditions. Therefore, specific heat capacity and the heat conductivity coefficient are two variables that are considered constant values in many of the models previously recommended. The proposed equations demonstrate that these two quantities are linearly decreasing as cement hydrates, and their value are related to the degree of hydration. The effects of changing the thermal conductivity and specific heat capacity values on the maximum temperature and the time it takes for concrete to reach that temperature are examined in this study using numerical sensibility analysis, and the results are compared to models that take a fixed value for these two thermal properties. The current study is conducted in 7 different mix designs of concrete with varying amounts of supplementary cementitious materials (fly ash and ground granulated blast furnace slag). It is concluded that the maximum temperature will not change as a result of the constant conductivity coefficient, but variable specific heat capacity must be taken into account, also about duration when a concrete's central node reaches its max value again variable specific heat capacity can have a considerable effect on the final result. Also, the usage of GGBFS has more influence compared to fly ash.

Keywords: early-age concrete, mass concrete, specific heat capacity, thermal conductivity coefficient

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Authors: Djouhou Fowe Michelle Carole

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In the last few decades, there have been considerable efforts by the international community to develop strategies that reduce global poverty and hunger. Despite the modest success in reducing food insecurity, there are still around 795 million people worldwide who remain undernourished, the majority of whom are in sub-Saharan Africa. In many of these impoverished communities, agriculture still remains one of the most important sectors in driving economic growth and reducing poverty. For the growing population, with higher food demand and fixed agricultural land, sustainable intensification is proposed as an important strategy to respond to the challenges of low yields, environmental degradation, and adaptation to climate change. Adoption of agroforestry technologies is increasingly being promoted as a promising solution. This study was conducted to determine the perceptions of the Cameroonian population and farmers on agroforestry. The methodology used was based on a survey to determine their knowledge level of agroforestry, their representation of its advantages and disadvantages, and the reasons that might motivate them whether or not to adopt agroforestry. Participants were randomly selected and received a questionnaire. Data were subjected to a descriptive analysis using SPSS software. The obtained results showed that less than 50% of the general population had already heard about agroforestry at least once; they have basic knowledge about this concept and its advantages. Farmers had been particularly sensitive to tree's food production function and seemed to value their environmental assets. However, various constraints could affect the possible adoption of agroforestry techniques.

Keywords: agroforestry, quality and sustainable agriculture, perceptions, advantages, limits

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Authors: Amor Jnifene, Cedric Cocaud

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One of the most constraining problems facing the development of autonomous vehicles is the limitations of current technologies. Guidance and navigation controllers need to be faster and more robust. Communication data links need to be more reliable and secure. For an Unmanned Aerial Vehicles (UAV) to be useful, and fully autonomous, one important feature that needs to be an integral part of the navigation system is autonomous trajectory planning. The work discussed in this paper presents a method for on-line trajectory planning for UAV’s. This method takes into account various constraints of different types including specific vectors of approach close to target points, multiple objectives, and other constraints related to speed, altitude, and obstacle avoidance. The trajectory produced by the proposed method ensures a smooth transition between different segments, satisfies the minimum curvature imposed by the dynamics of the UAV, and finds the optimum velocity based on available atmospheric conditions. Given a set of objective points and waypoints a skeleton of the trajectory is constructed first by linking all waypoints with straight segments based on the order in which they are encountered in the path. Secondly, vectors of approach (VoA) are assigned to objective waypoints and their preceding transitional waypoint if any. Thirdly, the straight segments are replaced by 3D curvilinear trajectories taking into account the aircraft dynamics. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircrafts, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircraft, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers.

Keywords: trajectory planning, unmanned autonomous air vehicle, vector of approach, waypoints

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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In this paper, we treat a model that falls in the area of protecting targeted systems from intelligent threats including terrorism. We introduce the concept of system survivability, in the context of continuous attacks, as the probability that a system under attack will continue operation up to some fixed time t. We define a constant attack rate (CAR) process as an attack on a targeted system that follows an exponential distribution. We consider the superposition of several CAR processes. From the attacker side, we determine the optimal attack strategy that minimizes the system survivability. We also determine the optimal strengthening strategy that maximizes the system survivability under limited defensive resources. We use operations research techniques to identify optimal strategies of each antagonist. Our results may be used as interesting starting points to develop realistic protection strategies against intentional attacks.

Keywords: CAR processes, defense/attack strategies, exponential failure, survivability

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Authors: Donatella Cimini, Sergio D’ambrosio, Saba Sadiq, Chiara Schiraldi

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Chondroitin sulfate (CS), as well as modified CS, and unsulfated chondroitin, are largely applied in research today. CS is a linear glycosaminoglycan normally present in cartilage-rich tissues and bones in the form of proteoglycans decorated with sulfate groups in different positions. CS is used as an effective non-pharmacological alternative for the treatment of osteoarthritis, and other potential applications in the biomedical field are being investigated. Some bacteria, such as E. coli K4, produce a polysaccharide that is a precursor of CS (unsulfated chondroitin). This work focused on the construction of integrative E. coli K4 recombinant strains overexpressing genes (kfoA, kfoF, pgm and galU in different combinations) involved in the biosynthesis of the nucleotide sugars necessary for polysaccharide synthesis. Strain growth and polymer production were evaluated using renewable waste materials as substrates in shake flasks and small-scale batch fermentation processes. Results demonstrated the potential to replace pure sugars with cheaper medium components to establish environmentally sustainable and cost-effective production routes for potential industrial development. In fact, although excellent fermentation results have been described so far by employing strains that naturally produce chondroitin-like polysaccharides on semi-defined media, there is still the need to reduce manufacturing costs by providing a cost-effective biotechnological alternative to currently used animal-based extraction procedures.

Keywords: E. coli K4, chondroitin, microbial cell factories, glycosaminoglycans, renewable resources

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Authors: Dara Satyadileep, Abdallah S. Berrouk

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Selective absorption of Hydrogen Sulphide (H2S) using methyldiethanol amine (MDEA) has become a point of interest as means of minimizing capital and operating costs of gas sweetening plants. This paper discusses the prominence of optimum design of column internals to best achieve H2S selectivity using MDEA. To this end, a kinetics-based process simulation model has been developed for a commercial gas sweetening unit. Trends of sweet gas H2S & CO2 contents as function of fraction active area (and hence residence time) have been explained through analysis of interdependent heat and mass transfer phenomena. Guidelines for column internals design in order to achieve desired degree of H2S selectivity are provided. Also the effectiveness of various operating conditions in achieving H2S selectivity for an industrial absorber with fixed internals is investigated.

Keywords: gas sweetening, H2S selectivity, methyldiethanol amine, process simulation, residence time

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Authors: Luis F. Bianchessi, Gustavo G. Shimamoto, Matthieu Tubino

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The use of biodiesel has been diffused in Brazil and all over the world by the trading of biodiesel (B100). In Brazil, the diesel oil currently being sold is a blend, containing 7% biodiesel (B7). In this context, it is necessary to develop methods capable of identifying this blend composition, especially regarding the biodiesel quality used for making these blends. In this study, hydrogen nuclear magnetic resonance spectra (1H-NMR) are proposed as a form of identifying and confirming the quality of type B10 blends (10% of biodiesel and 90% of diesel). Furthermore, the presence of vegetable oils, which may be from fuel adulteration or as an evidence of low degree of transesterification conversion during the synthesis of B100, may also be identified. Mixtures of diesel, vegetable oils and their respective biodiesel were prepared. Soybean oil and macauba kernel oil were used as raw material. The diesel proportion remained fixed at 90%. The other proportion (10%) was varied in terms of vegetable oil and biodiesel. The 1H-NMR spectra were obtained for each one of the mixtures, in order to find a correlation between the spectra and the amount of biodiesel, as well as the amount of residual vegetable oil. The ratio of the integral of the methylenic hydrogen H-2 of glycerol (exclusive of vegetable oil) with respect to the integral of the olefinic hydrogens (present in vegetable oil and biodiesel) was obtained. These ratios were correlated with the percentage of vegetable oil in each mixture, from 0% to 10%. The obtained correlation could be described by linear relationships with R2 of 0.9929 for soybean biodiesel and 0.9982 for macauba kernel biodiesel. Preliminary results show that the technique can be used to monitor the biodiesel quality in commercial diesel-biodiesel blends, besides indicating possible adulteration.

Keywords: biodiesel, diesel, biodiesel quality, adulteration

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Authors: Igor Kuzminov

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Till now, the nature of lightning is not established. A hypothesis of the origin of lightning is proposed. The lightning charge is formed by electromagnetic induction. The role of the conductor is performed by the air mass of the cloud. This conductor moves in the Earth's magnetic field. The upper and lower edges of the cloud are the plates of the capacitor. Lightning is a special case of electromagnetic processes in an atmosphere. The category of lightning occurs in the process of accumulation of a charge. The process of accumulation goes constantly, but the charge is not fixed. Naturally, the hypothesis demands the carrying out of additional experiments and official acknowledgement. As the proof of a hypothesis can serve that the maximal lighting activity in an equatorial zone where cosφ it is close to 1. An experiment conducted privately showed that there is a potential difference in the atmosphere at different levels. The probability of applied value development of power installation is great.

Keywords: electromagnetic induction, Earth's magnetic field, plates of the capacitors, charge accumulation

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Authors: T.C. Balachandra, Habibuddin Shaik

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This paper presents experimental results leading towards a better understanding of pre-breakdown and breakdown behavior of vacuum gaps under variable frequency alternating excitations. The frequency variation is in the range of 30 to 300 Hz in steps of 10 Hz for a fixed gap spacing of 0.5 mm. The results indicate that the pre-breakdown currents show an inverse relation with the breakdown voltage in general though erratic behavior was observed over a certain range of frequencies. A breakdown voltage peak was observed at 130 Hz. This was pronounced when the electrode pair was of stainless steel and less pronounced when copper and aluminum electrodes were used. The experimental results are explained based on F-N emission, I-F emission, and also thermal interaction due to quasi-continuous shower of anode micro-particles. Further, it is speculated that the ostensible cause for time delay between voltage and current peaks is due to the presence of neutral molecules in the gap.

Keywords: anode hot-spots, F-N emission, I-F emission, microparticle, neutral molecules, pre-breakdown conduction, vacuum breakdown

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Authors: Saimir Heta, Ilma Robo, Rialda Xhizdari, Kers Kapaj

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The stability of an ideal disinfectant should be constant regardless of the change in the atmospheric conditions of the environment where it is kept. If the conditions such as temperature or humidity change, it is understood that it will also be necessary to approach possible changes in the holding materials such as plastic or glass bottles with the aim of protecting, for example, the disinfectant from the excessive lighting of the environment, which can also be translated as an increase in the temperature of disinfectant as a fluid. Material and Methods: In this study, an attempt was made to find the most recent published data about the best possible combination of disinfectants indicated for use after dental procedures. This purpose of the study was realized by comparing the basic literature that is studied in the field of dentistry by students with the most published data in the literature of recent years about this topic. Each disinfectant is represented by a number called the disinfectant count, in which different factors can influence the increase or reduction of variables whose production remains a specific statistic for a specific disinfectant. Results: The changes in the atmospheric conditions where the disinfectant is deposited and stored in the environment are known to affect the stability of the disinfectant as a fluid; this fact is known and even cited in the leaflets accompanying the manufactured boxes of disinfectants. It is these cares, in the form of advice, which are based not only on the preservation of the disinfectant but also on the application in order to have the desired clinical result. Aldehydes have the highest constant among the types of disinfectants, followed by acids. The lowest value of the constant belongs to the class of glycols, the predecessors of which were the halogens, in which class there are some representatives with disinfection applications. The class of phenols and acids have almost the same intervals of constants. Conclusions: If the goal were to find the ideal disinfectant among the large variety of disinfectants produced, a good starting point would be to find something unchanging or a fixed, unchanging element on the basis of which the comparison can be made properties of different disinfectants. Precisely based on the results of this study, the role of the specific constant according to the specific disinfectant is highlighted. Finding an ideal disinfectant, like finding a medication or the ideal antibiotic, is an ongoing but unattainable goal.

Keywords: different disinfectants, ideal, specific constant, dental procedures

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Authors: Narava Manose

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Distillation is a very old separation technology for separating liquid mixtures that can be traced back to the chemists in Alexandria in the first century A. D. Today distillation is the most important industrial separation technology. By the eleventh century, distillation was being used in Italy to produce alcoholic beverages. At that time, distillation was probably a batch process based on the use of just a single stage, the boiler. The word distillation is derived from the Latin word destillare, which means dripping or trickling down. By at least the sixteenth century, it was known that the extent of separation could be improved by providing multiple vapor-liquid contacts (stages) in a so called Rectifactorium. The term rectification is derived from the Latin words rectefacere, meaning to improve. Modern distillation derives its ability to produce almost pure products from the use of multi-stage contacting. Throughout the twentieth century, multistage distillation was by far the most widely used industrial method for separating liquid mixtures of chemical components.The basic principle behind this technique relies on the different boiling temperatures for the various components of the mixture, allowing the separation between the vapor from the most volatile component and the liquid of other(s) component(s). •Developed a simple non-linear model of a binary distillation column using Skogestad equations in Simulink. •We have computed the steady-state operating point around which to base our analysis and controller design. However, the model contains two integrators because the condenser and reboiler levels are not controlled. One particular way of stabilizing the column is the LV-configuration where we use D to control M_D, and B to control M_B; such a model is given in cola_lv.m where we have used two P-controllers with gains equal to 10.

Keywords: modelling, distillation column, control, binary distillation

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Authors: Nurul Liyana Abdul Aziz, Nur Aidya Hanum Aizam

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Course timetabling problems occur every semester in a university which includes the allocation of resources (subjects, lecturers and students) to a number of fixed rooms and timeslots. The assignment is carried out in a way such that there are no conflicts within rooms, students and lecturers, as well as fulfilling a range of constraints. The constraints consist of rules and policies set up by the universities as well as lecturers’ and students’ preferences of courses to be allocated in specific timeslots. This paper specifically focuses on the preferences of the course timetabling problem in one of the public universities in Malaysia. The demands will be considered into our existing mathematical model to make it more generalized and can be used widely. We have distributed questionnaires to a number of lecturers and students of the university to investigate their demands and preferences for their desired course timetable. We classify the preferences thus converting them to construct one mathematical model that can produce such timetable.

Keywords: university course timetabling problem, integer programming, preferences, constraints

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Authors: Bader Alhumaidi Alsubaei, Zahid H. Akash, Ali Imam Sunny

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The heat transfer coefficient can be improved passively by using a dimpled surface on the tube. The contact area where heat transfer takes place can be enlarged and turbulence will be purposefully produced inside the duct; as a consequence, higher heat transfer quality will be achieved by employing an extended inner or outer surface (dimpled surface). In order to compare the rate and quality of heat transfer between a regular-shaped pipe and a dimpled pipe, a dimpled tube with a fixed dimple radius was created. Numerical analysis of the plain and dimpled pipes was performed using ANSYS. A 23% increase in Nusselt number was seen for dimpled tubes compared to plain tubes. In comparison to plain tubes, dimpled tubes' increase in thermal performance index was found to be between 8% and 10%. An increase in pressure drop of 18% was noted.

Keywords: heat transfer, dimpled tube, CFD, ANSYS

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Authors: J. R. Mudakavi, K. Puttanna

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Chromium in the environment is considered as one of the most toxic elements probably next only to mercury and arsenic. It is acutely toxic, mutagenic and carcinogenic in the environment. Chromium contamination of soil and underground water due to industrial activities is a very serious problem in several parts of India covering Karnataka, Tamil Nadu, Andhra Pradesh etc. Functionally modified Activated Carbon Fabrics (ACF) offer targeted chromium removal from drinking water and industrial effluents. Activated carbon fabric is a light weight adsorbing material with high surface area and low resistance to fluid flow. We have investigated surface modification of ACF using various acids in the laboratory through batch as well as through continuous flow column experiments with a view to develop the optimum conditions for chromium removal. Among the various acids investigated, phosphoric acid modified ACF gave best results with a removal efficiency of 95% under optimum conditions. Optimum pH was around 2 – 4 with 2 hours contact time. Continuous column experiments with an effective bed contact time (EBCT) of 5 minutes indicated that breakthrough occurred after 300 bed volumes. Adsorption data followed a Freundlich isotherm pattern. Nickel adsorbs preferentially and sulphate reduces chromium adsorption by 50%. The ACF could be regenerated up to 52.3% using 3 M NaOH under optimal conditions. The process is simple, economical, energy efficient and applicable to industrial effluents and drinking water.

Keywords: activated carbon fabric, hexavalent chromium, adsorption, drinking water

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Authors: Anne Elain, Magali Le Fellic

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Halogenated Aromatic Compounds (HAC) are major organic pollutants that are detected in several environmental compartments as a result of their widespread use as solvents, pesticides and other industrial chemicals. The degradation of HAC simultaneously at low temperature and under saline conditions would be useful for remediation of polluted sites. Hence, microbial processes based on the metabolic activities of anaerobic bacteria are especially attractive from an economic and environmental point of view. Metabolites are generally less toxic, less likely to bioaccumulate and more susceptible for further degradation. Studies on biological reductive dehalogenation have largely been restricted to chlorinated compounds while relatively few have focussed on other HAC i.e., fluorinated, brominated or iodinated compounds. The objectives of the present work were to investigate the biodegradation of a mixture of triiodoaromatic molecules in industrial wastewater by an enriched bacterial consortium. Biodegradation of the mixture was studied during batch experiments in an anaerobic reactor. The degree of mineralization and recovery of halogen were monitored by HPLC-UV, TOC analysis and potentiometric titration. Providing ethanol as an electron donor was found to stimulate anaerobic reductive dehalogenation of HAC with a deiodination rate up to 12.4 mg.L-1 per day. Sodium chloride even at high concentration (10 mM) was found to have no influence on the degradation rates nor on the microbial viability. An analysis of the 16S rDNA (MicroSeq®) revealed that at least 6 bacteria were predominant in the enrichment, including Pseudomonas aeruginosa, Pseudomonas monteilii, Kocuria rhizophila, Ochrobacterium anthropi, Ralstonia pickettii and Rhizobium rhizogenes.

Keywords: halogenated aromatics, anaerobic biodegradation, deiodination, bacterial consortium

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Authors: Safa'a M. Rasheed, Saba A. Gheni, Wadood T. Mohamed

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Phenolic compounds are the most carcinogenic pollutants in waste water in effluents of refineries and pulp industry. Catalytic wet air oxidation is an efficient industrial treatment process to oxidize phenolic compounds into unharmful organic compounds. Mode of flow of the fluid to be treated is a dominant factor in determining effectiveness of the catalytic process. The present study aims to obtain a mathematical model describing the conversion of phenolic compounds as a function of the process variables; mode of flow (trickling and pulsing), temperature, pressure, along with a high concentration of phenols and a platinum supported alumina catalyst. The model was validated with the results of experiments obtained in a fixed bed reactor. High pressure and temperature were employed at 8 bar and 140 °C. It has been found that conversion of phenols is highly influenced by mode of flow and the change is caused by changes occurred in hydrodynamic regime at the time of pulsing flow mode, thereby a temporal variation in wetting efficiency of platinum prevails; which in turn increases and/or decreases contact time with phenols in wastewater. The model obtained was validated with experimental results, and it is found that the model is a good agreement with the experimental results.

Keywords: wastewater, phenol, pulsing flow, wet oxidation, high pressure

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: A. Elmethnani, A. Jroud

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This coastal crude oil refinery is situated north of a big city west of Tripoli; the city then could be highly prone to downwind refinery emissions where the NNE wind direction is prevailing through most seasons of the year. Furthermore, due to the absence of an air quality monitoring network and scarce emission data available for the neighboring community, nearby residents have serious worries about the impacts of the oil refining operations on local air quality. In responding to these concerns, a short term survey has performed for three consecutive days where a semi-continues mobile monitoring approach has developed effectively in this study; the monitoring station (Compact AQM 65 AeroQual) was mounted on a vehicle to move quickly between locations, measurements of 10 minutes averaging of 60 seconds then been taken at each fixed sampling point. The downwind ambient concentration of CO, H₂S, NOₓ, NO₂, SO₂, PM₁, PM₂.₅ PM₁₀, and TSP were measured at carefully chosen sampling locations, ranging from 200m nearby the fence-line passing through the city center up to 4.7 km east to attain best spatial coverage. Results showed worrying levels of PM₂.₅ PM₁₀, and TSP at one sampling location in the city center, southeast of the refinery site, with an average mean of 16.395μg/m³, 33.021μg/m³, and 42.426μg/m³ respectively, which could be attributed to road traffic. No significant concentrations have been detected for other pollutants of interest over the study area, as levels observed for CO, SO₂, H₂S, NOₓ, and NO₂ haven’t respectively exceeded 1.707 ppm, 0.021ppm, 0.134 ppm, 0.4582 ppm, and 0.0018 ppm, which was at the same sampling locations as well. Although it wasn’t possible to compare the results with the Libyan air quality standards due to the difference in the averaging time period, the technique was adequate for the baseline air quality screening procedure. Overall, findings primarily suggest modeling of dispersion of the refinery emissions to assess the likely impact and spatial-temporal distribution of air pollutants.

Keywords: air quality, mobil monitoring, oil refinery

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Authors: Soheila Sadeghi

Abstract:

In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Sofiene Amara, Mohamed Ali Bahri, Sabri Gaied Chortane

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The purpose of this study was to examine the effect of personal goal setting on psychological parameters (cognitive anxiety, somatic anxiety, and self-confidence) and the 50m freestyle performance. 30 young swimmers participated in this investigation, and was divided into three groups, the first group (G1, n = 10, 14 ± 0.7 years old) was prepared for the competition without a fixed target (method 1), the second group (G2, n = 10, 14 ± 0.9 years old) was oriented towards a vague goal 'Do your best' (method 2), while the third group (G3, n = 10, 14 ± 0, 5 years old) was invited to answer a goal that is difficult to reach according to a goal-setting interval (GST) (method 3). According to the statistical data of the present investigation, the cognitive and somatic anxiety scores in G1 and G3 were higher than in G2 (G1-G2, G3-G2: cognitive anxiety, P = 0.000, somatic anxiety: P = 0.000 respectively). On the other hand, the self-confidence score was lower in G1 compared with the other two groups (G1-G2, G3-G2: P = 0.02, P = 0.03 respectively). Our assessment also shows that the 50m freestyle time performance was improved better by method 3 (pre and post-Test: P = 0.006, -2.5sec, 7.83%), than by method 2 (pre and Post-Test: P = 0.03; -1sec; 3.24%), while, performance remained unchanged in G1 (P > 0.05). To conclude, the setting of a difficult goal by GST is more effective to improve the chronometric performance in the 50m freestyle, but at the same time increased the values ​​of the cognitive and somatic anxiety. For this, the mental trainers and the staff technical, invited to develop models of mental preparation associated with this method of setting a goal to help swimmers on the psychological level.

Keywords: cognitive anxiety, goal setting, performance of swimming freestyle, self-confidence, somatic anxiety

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Authors: Georgios Koronis, Arlindo Silva

Abstract:

This study seeks to understand the mechanical behavior of a natural fiber reinforced composite (epoxy/flax) in more depth, utilizing both experimental and numerical methods. It is attempted to identify relationships between the design parameters and the product performance, understand the effect of noise factors and reduce process variations. Optimization of the mechanical performance of manufactured goods has recently been implemented by numerous studies for green composites. However, these studies are limited and have explored in principal mass production processes. It is expected here to discover knowledge about composite’s manufacturing that can be used to design artifacts that are of low batch and tailored to niche markets. The goal is to reach greater consistency in the performance and further understand which factors play significant roles in obtaining the best mechanical performance. A prediction of response function (in various operating conditions) of the process is modeled by the DoE. Normally, a full factorial designed experiment is required and consists of all possible combinations of levels for all factors. An analytical assessment is possible though with just a fraction of the full factorial experiment. The outline of the research approach will comprise of evaluating the influence that these variables have and how they affect the composite mechanical behavior. The coupons will be fabricated by the vacuum infusion process defined by three process parameters: flow rate, injection point position and fiber treatment. Each process parameter is studied at 2-levels along with their interactions. Moreover, the tensile and flexural properties will be obtained through mechanical testing to discover the key process parameters. In this setting, an experimental phase will be followed in which a number of fabricated coupons will be tested to allow for a validation of the design of the experiment’s setup. Finally, the results are validated by performing the optimum set of in a final set of experiments as indicated by the DoE. It is expected that after a good agreement between the predicted and the verification experimental values, the optimal processing parameter of the biocomposite lamina will be effectively determined.

Keywords: design of experiments, flax fabrics, mechanical performance, natural fiber reinforced composites

Procedia PDF Downloads 203

Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

Abstract:

Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

Procedia PDF Downloads 102

Authors: M. H. Hussain, I. Musirin, A. F. Abidin, S. R. A. Rahim

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This paper presents the implementation of Artificial Bees Colony (ABC) algorithm in solving Directional OverCurrent Relays (DOCRs) coordination problem for near-end faults occurring in fixed network topology. The coordination optimization of DOCRs is formulated as linear programming (LP) problem. The objective function is introduced to minimize the operating time of the associated relay which depends on the time multiplier setting. The proposed technique is to taken as a technique for comparison purpose in order to highlight its superiority. The proposed algorithms have been tested successfully on 8 bus test system. The simulation results demonstrated that the ABC algorithm which has been proved to have good search ability is capable in dealing with constraint optimization problems.

Keywords: artificial bees colony, directional overcurrent relay coordination problem, relay settings, time multiplier setting

Procedia PDF Downloads 328

Authors: Krasimir Ivanov, Dimitar Dimitrov, Tatyana Tabakova, Stefka Kirkova, Anna Stoilova, Violina Angelova

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It has been suggested that nicotine, CO and tar in mainstream smoke are the most important substances and have been judged as the most harmful compounds, responsible for the health hazards of smoking. As nicotine is extremely important for smoking qualities of cigarettes and the tar yield in the tobacco smoke is significantly reduced due to the use of filters with various content and design, the main efforts of cigarettes researchers and manufacturers are related to the search of opportunities for CO content reduction. Highly active ceria supported gold catalyst was prepared by the deposition-precipitation method, and the possibilities for CO oxidation in the synthetic gaseous mixture were evaluated using continuous flow equipment with fixed bed glass reactor at atmospheric pressure. The efficiently of the catalyst in CO oxidation in the real cigarette smoke was examined by a single port, puf-by-puff smoking machine. Quality assessment of smoking using cigarette holder containing catalyst was carried out. It was established that the catalytic activity toward CO oxidation in cigarette smoke rapidly decreases from 70% for the first cigarette to nearly zero for the twentieth cigarette. The present study shows that there are two critical factors which do not permit the successful use of catalysts to reduce the CO content in the mainstream cigarette smoke: (i) significant influence of the processes of adsorption and oxidation on the main characteristics of tobacco products and (ii) rapid deactivation of the catalyst due to the covering of the catalyst’s grains with condensate.

Keywords: cigarette smoke, CO oxidation, gold catalyst, mainstream

Procedia PDF Downloads 217

Authors: Natia Gavardashvili

Abstract:

From April through June of 2017, the field-scientific studies to ensure the safety of the population of Tbilisi were accomplished in the water catch basin of the river Vere, in the water catch basin of the river Jakhana dry gully. 5 sensitive sites were identified, and areas, 20x20 m each, were marked around them, with their locations fixed with GPS coordinates. The gained areas were plotted on a digital map, and the state of the surface was explored by considering the evaluation of erosive processes. Aiming at evaluating the soils and grounds of the sensitive areas, the ground samples were taken, and average diameter was identified, with its value changing to D0 = 4,67-15,48 mm, and integral curves of the grain size were drafted. By using the obtained data, the transporting capability of mudflow can be identified at the next stage to use to calculate mudflow peak discharges of different provisions in developing the new designs of mudflow-protection structures with the goal of ensuring the safety of Tbilisi population. The studies were accomplished under the financing of Young Scientists’ Grant of Shota Rustaveli National Science Foundation 'The study of erosive-mudflow processes in the water catch basin in the river Vere to ensure the safety of the population of Tbilisi and their consideration in developing new environmental protection plans' (YS15_2.1.5_8)

Keywords: water catch basin, mudflow-protection structures, erosive-mudflow processes, safety

Procedia PDF Downloads 304

Authors: P. Kiran Kumar, S. Vijaya Krishna, Kavita Verma1, V. Himabindu

Abstract:

Concern about global warming and energy security has led to increased biomass utilization as an alternative feedstock to fossil fuels. Biomass is a promising feedstock since it is abundant and cheap and can be transformed into fuels and chemical products. Microalgae biofuels are likely to have a much lower impact on the environment. Microalgae cultivation using sewage with industrial flue gases is a promising concept for integrated biodiesel production, CO₂ sequestration, and nutrients recovery. Autotrophic, Mixotrophic, and Heterotrophic are the three modes of cultivation for microalgae biomass. Several mechanical and chemical processes are available for the extraction of lipids/oily components from microalgae biomass. In organic solvent extraction methods, a prior drying of biomass and recovery of the solvent is required, which are energy-intensive. Thus, the hydrothermal process overcomes the drawbacks of conventional solvent extraction methods. In the hydrothermal process, the biomass is converted into oily components by processing in a hot, pressurized water environment. In this process, in addition to the lipid fraction of microalgae, other value-added products such as proteins, carbohydrates, and nutrients can also be recovered. In the present study was (Scenedesmus quadricauda) was isolated and cultivated in autotrophic, heterotrophic, and mixotrophically using sewage wastewater and industrial flue gas in batch and continuous mode. The harvested algae biomass from S. quadricauda was used for the recovery of lipids and bio-oil. The lipids were extracted from the algal biomass using sonication as a cell disruption method followed by solvent (Hexane) extraction, and the lipid yield obtained was 8.3 wt% with Palmitic acid, Oleic acid, and Octadeonoic acid as fatty acids. The hydrothermal process was also carried out for extraction of bio-oil, and the yield obtained was 18wt%. The bio-oil compounds such as nitrogenous compounds, organic acids, and esters, phenolics, hydrocarbons, and alkanes were obtained by the hydrothermal process of algal biomass. Nutrients such as NO₃⁻ (68%) and PO₄⁻ (15%) were also recovered along with bio-oil in the hydrothermal process.

Keywords: flue gas, hydrothermal process, microalgae, sewage wastewater, sonication

Procedia PDF Downloads 139