Educational Process of Medical Students in Basic Sciences in Birjand University of Medical Sciences

Background & Objective : Identifying faculty members' educational needs and level of their skills in teaching affairs would improve planning for faculty members’ development and sublimity. This study was performed to assess attitude of faculty members who are teaching practical courses towards their educational needs and level of skills in teaching methods of practical courses. Methods : In this descriptive study, 83 faculty members teaching practical courses in Isfahan University of Medical Sciences were selected by stratified random sampling and completed a reliable and valid questionnaire consisted of 14 items about educational needs and skill level of teaching methods in practical courses. Results : The mean (±SD) score of faculty members' skill level was 2.71(±0.4) out of four. Faculty members’ skill level was low (mean score less than 2.5) in analysis and interpretation of the test questions (38.9%), evaluation methods of practical skills (53.5%), designing performance tests (52.8%) and making educational films (47.9%). Mean (±SD) total score of educational needs was 3.45(±0.89) out of five. According to these results, faculty members were in need of all 14 aforementioned items. Educational needs included critical thinking, motivating methods and information resources in order of priority. Conclusion : Faculty members expressed need for education and improving their skills in teaching practical courses. Considering mentioned educational needs and skills, it seems that teaching method and student assessment workshops need to be revised and the content of the workshops should be designed according to faculty members’ educational needs together with implementing different educational methods. Keywords: Practical teaching, Faculty members, Teaching methods, Skill, Need assessment

Particle Swarm algorithm with Fuzzy decision making for a multi-objective economic and environmental optimization of design of a thermal system

Multi-Objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the thermoeconomic and Environmental aspects have been considered, simultaneously. The environmental objective function has been defined and expressed in cost terms. One of the most suitable optimization techniques developed using a particular class of search algorithms known as; Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been used here. This approach has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of fuzzy decision-making with the aid of Bellman-Zadeh approach has been presented and a final optimal solution has been introduced

A review of the technical challenges and solutions in maximising the potential use of second life batteries from electric vehicles

The increasing number of electric vehicles (EVs) on the roads has led to a rise in the number of batteries reaching the end of their first life. Such batteries, however, still have a capacity of 75–80% remaining, creating an opportunity for a second life in less power-intensive applications. Utilising these second-life batteries (SLBs) requires specific preparation, including grading the batteries based on their State of Health (SoH); repackaging, considering the end-use requirements; and the development of an accurate battery-management system (BMS) based on validated theoretical models. In this paper, we conduct a technical review of mathematical modelling and experimental analyses of SLBs to address existing challenges in BMS development. Our review reveals that most of the recent research focuses on environmental and economic aspects rather than technical challenges. The review suggests the use of equivalent-circuit models with 2RCs and 3RCs, which exhibit good accuracy for estimating the performance of lithium-ion batteries during their second life. Furthermore, electrochemical impedance spectroscopy (EIS) tests provide valuable information about the SLBs’ degradation history and conditions. For addressing calendar-ageing mechanisms, electrochemical models are suggested over empirical models due to their effectiveness and efficiency. Additionally, generating cycle-ageing test profiles based on real application scenarios using synthetic load data is recommended for reliable predictions. Artificial intelligence algorithms show promise in predicting SLB cycle-ageing fading parameters, offering significant time-saving benefits for lab testing. Our study emphasises the importance of focusing on technical challenges to facilitate the effective utilisation of SLBs in stationary applications, such as building energy-storage systems and EV charging stations

The Effects of Port Water Injection on Spark Ignition Engine Performance and Emissions Fueled by Pure Gasoline, E5 and E10

It has been proven that vehicle emissions such as oxides of nitrogen (NOx) are negatively affecting the health of human beings as well as the environment. In addition, it was recently highlighted that air pollution may result in people being more vulnerable to the deadly COVID-19 virus. The use of biofuels such as E5 and E10 as alternatives of gasoline fuel have been recommended by different researchers. In this paper, the impacts of port injection of water to a spark ignition engine fueled by gasoline, E5 and E10 on its performance and NOx production have been investigated. The experimental work was undertaken using a KIA Cerato engine and the results were used to validate an AVL BOOST model. To develop the numerical analysis, design of experiment (DOE) method was employed. The results showed that by increasing the ethanol fraction in gasoline/ethanol blend, the brake specific fuel consumption (BSFC) improved between 2.3% and 4.5%. However, the level of NOx increased between 22% to 48%. With port injection of water up to 8%, there was up to 1% increase in engine power whereas NOx and BSFC were reduced by 8% and 1%, respectively. The impacts of simultaneous changing of the start of combustion (SOC) and water injection rate on engine power and NOx production was also investigated. It was found that the NOx concentration is very sensitive to SOC variation

Particulate number emissions during cold-start with diesel and biofuels: A special focus on particle size distribution

The share of biofuels in the transportation sector is increasing. Previous studies revealed that the use of biofuels decreases the size of particles (which is linked to an increase in particulate toxicity). Current emission regulations do not consider small particles (sub-23 nm); however, there is a focus in future emissions regulations on small particles. These and the fact that within cold-start emissions are higher than during the warmed-up operation highlight the importance of a research that studies particulate matter emissions during cold-start. This research investigates the influence of biofuel on PN and PM concentration, size distribution, median diameter and cumulative share at different size ranges (including sub-23 nm and nucleation mode) during cold-start and warm-up operations using diesel and 10, 15 and 20% mixture (coconut biofuel blended with diesel). During cold-start, between 19 and 29% of total PN and less than 0.8% of total PM were related to the nucleation mode (sub-50 nm). Out of that, the share of sub-23 nm was up to 9% for PN while less than 0.02% for PM. By using biofuel, PN increased between 27 and 57% at cold-start; while, the increase was between 4 and 19% during hot-operation. The median diameter also decreased at cold-start and the nucleation mode particles (including sub-23 nm particles) significantly increased. This is an important observation because using biofuel can have a more adverse impact within cold-start period which is inevitable in most vehicles’ daily driving schedules.<br/

Enhancement of an Air-Cooled Battery Thermal Management System Using Liquid Cooling with CuO and Al2O3 Nanofluids under Steady-State and Transient Conditions

Lithium-ion batteries are a crucial part of transportation electrification. Various battery thermal management systems (BTMS) are employed in electric vehicles for safe and optimum battery operation. With the advancement in power demand and battery technology, there is an increasing interest in enhancing BTMS’ performance. Liquid cooling is gaining a lot of attention recently due to its higher heat capacity compared to air. In this study, an air-cooled BTMS is replaced by a liquid cooled with nanoparticles, and the impacts of different nanoparticles and flow chrematistics are modeled. Furthermore, a unique approach that involves transient analysis is employed. The effects of nanofluid in enhancing the thermal performance of lithium-ion batteries are assessed for two types of nanoparticles (CuO and Al2O3) at four different volume concentrations (0.5%, 2%, 3%, and 5%) and three fluid velocities (0.05, 0.075, and 0.1 m/s). To simulate fluid flow behavior and analyze the temperature distribution within the battery pack, a conventional k-ε turbulence model is used. The results indicate that the cooling efficiency of the system can be enhanced by introducing a 5% volume concentration of nanofluids at a lower fluid velocity as compared to pure liquid. Al2O3 and CuO reduce the temperature by 7.89% and 4.73% for the 5% volume concentration, respectively. From transient analysis, it is also found that for 600 s of operation at the highest power, the cell temperature is within the safe range for the selected vehicle with nanofluid cooling. The findings from this study are expected to contribute to improving BTMS by quantifying the benefits of using nanofluids for battery cooling under both steady-state and transient conditions

Evaluation of residence time on nitrogen oxides removal in non-thermal plasma reactor

Non-thermal plasma (NTP) has been introduced over the last few years as a promising after- treatment system for nitrogen oxides and particulate matter removal from diesel exhaust. NTP technology has not been commercialised as yet, due to its high rate of energy consumption. Therefore, it is important to seek out new methods to improve NTP performance. Residence time is a crucial parameter in engine exhaust emissions treatment. In this paper, different electrode shapes are analysed and the corresponding residence time and NOx removal efficiency are studied. An axisymmetric laminar model is used for obtaining residence time distribution numerically using FLUENT software. If the mean residence time in a NTP plasma reactor increases, there will be a corresponding increase in the reaction time and consequently the pollutant removal efficiency increases. Three different screw thread electrodes and a rod electrode are examined. The results show the advantage of screw thread electrodes in comparison with the rod electrode. Furthermore,between the screw thread electrodes, the electrode with the thread width of 1 mm has the highest NOx removal due to higher residence time and a greater number of micro-discharges. The results show that the residence time of the screw thread electrode with a thread width of 1 mm is 21% more than for the rod electrode

Reduction of diesel engine exhaust emissions using non-thermal plasma technology

Non-thermal plasma (NTP) is a promising candidate for controlling engine exhaust emissions. Plasma is known as the fourth state of matter, where both electrons and positive ions co-exist. Both gaseous and particle emissions of diesel exhaust undergo chemical changes when they are exposed to plasma. In this project diesel particulate matter (DPM) mitigation from the actual diesel exhaust by using NTP technology has been studied. The effect of plasma, not only on PM mass but also on PM size distribution, physico-chemical structure of PM and PM removal mechanisms, has been investigated. It was found that NTP technology can significantly reduce both PM mass and number. However, under some circumstances particles can be formed by nucleation. Energy required to create the plasma with the current technology is higher than the benchmark set by the commonly used by the automotive industry. Further research will enable the mechanism of particle creation and energy consumption to be optimised

Residence time investigation in a co-axial dielectric barrier discharge reactor

The residence time distribution (RTD) is a crucial parameter when treating engine exhaust emissions with a Dielectric Barrier Discharge (DBD) reactor. In this paper, the residence time of such a reactor is investigated using a finite element based software: COMSOL Multiphysics 4.3. Non-thermal plasma (NTP) discharge is being introduced as a promising method for pollutant emission reduction. DBD is one of the most advantageous of NTP technologies. In a two cylinder co-axial DBD reactor, tubes are placed between two electrodes and flow passes through the annuals between these barrier tubes. If the mean residence time increases in a DBD reactor, there will be a corresponding increase in reaction time and consequently, the pollutant removal efficiency can increase. However, pollutant formation can occur during increased mean residence time and so the proportion of fluid that may remain for periods significantly longer than the mean residence time is of great importance. In this study, first, the residence time distribution is calculated based on the standard reactor used by the authors for ultrafine particle (10-500 nm) removal. Then, different geometrics and various inlet velocities are considered. Finally, for selected cases, some roughness elements added inside the reactor and the residence time is calculated. These results will form the basis for a COMSOL plasma and CFD module investigation