Search results for: energy efficiency measures

Authors: Daniel Icaza, Federico Córdova, Chiristian Castro, Fernando Icaza, Juan Portoviejo

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In this article, the mathematical model is presented, and simulations were carried out using specialized software such as MATLAB before the construction of a 900-W wind turbine. The present study was conducted with the intention of taking advantage of the rotation of the blades of the wind generator after going through a process of amplification of speed by means of a system of gears to finally mechanically couple two electric generators of similar characteristics. This coupling allows generating a maximum voltage of 6 V in DC for each generator and putting in series the 12 V DC is achieved, which is later stored in batteries and used when the user requires it. Laboratory tests were made to verify the level of power generation produced based on the wind speed at the entrance of the blades.

Keywords: smart grids, wind turbine, modeling, renewable energy, robust control

Procedia PDF Downloads 221

Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Sergey Kuznetsov, Yuri Urman

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We present an approach to investigate non-linear dynamical effects occurring in the noncontact superconducting and diamagnetic suspensions, when levitated body has finite size. This approach is based on the calculation of interaction energy between spherical finite size superconducting or diamagnetic body with external magnetic field. Effects of small deviations from spherical shape may be also taken into account by introducing small corrections to the energy. This model allows investigating dynamical effects important for practical applications, such as nonlinear resonances, change of vibration plane, coupling of rotational and translational motions etc. We also show how the geometry of suspension affects various dynamical effects and how an inverse problem may be formulated to enforce or diminish various dynamical effects.

Keywords: levitation, non-linear dynamics, superconducting, diamagnetic stability

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Authors: Shahab Azimi, Siamak Arzanpour, Anahita Sayyar

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Asthma and Chronic obstructive pulmonary disease (COPD) are common lung diseases that have a significant global impact. Pressurized metered dose inhalers (pMDIs) are widely used for treatment, but they can have limitations such as high medication release speed resulting in drug deposition in the mouth or oral cavity and difficulty achieving proper synchronization with inhalation by users. Spacers are add-on devices that improve the efficiency of pMDIs by reducing the release speed and providing space for aerosol particle breakup to have finer and medically effective medication. The aim of this study is to optimize the size and cylindrical shape of spacers to enhance their drug delivery performance. The study was based on fluid dynamics theory and employed Ansys software for simulation and optimization. Results showed that optimization of the spacer's geometry greatly influenced its performance and improved drug delivery. This study provides a foundation for future research on enhancing the efficiency of inhalation therapy for lung diseases.

Keywords: asthma, COPD, pressurized metered dose inhalers, spacers, CFD, shape optimization

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Authors: Hui Zhu, Yuan Wang, Shibo Kuang, Aibing Yu

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The inertial difference induced by the microfluidics inside a curved micro-channel has great potential to provide a fast, inexpensive, and portable solution to the separation of micro- and sub-micro particles in many applications such as aerosol collections, airborne bacteria and virus detections, as well as particle sortation. In this work, the separation behaviors of different sized particles inside a reported curved micro-channel have been studied by a combined approach of computational fluid dynamics for gas and discrete element model for particles (CFD-DEM). The micro-channel is operated by controlling the gas flow rates at all of its branches respectively used to load particles, introduce gas streams, collect particles of various sizes. The validity of the model has been examined by comparing by the calculated separation efficiency of different sized particles against the measurement. On this basis, the separation mechanisms of the inertial microfluidic separator are elucidated in terms of the interactions between particles, between particle and fluid, and between particle and wall. The model is then used to study the effect of feed solids concentration on the separation accuracy and efficiency. The results obtained from the present study demonstrate that the CFD-DEM approach can provide a convenient way to study the particle separation behaviors in micro-channels of various types.

Keywords: CFD-DEM, inertial effect, microchannel, separation

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Authors: Shirley Lamptey, Lingling Li, Junhong Xie

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Agriculture in the semi-arid is often challenged by overuse of N, inadequate soil water, and heavy carbon emissions thereby threatening sustainability. Field experiments were conducted to investigate the effect of nitrogen fertilization levels (0-N₀, 100-N₁₀₀, 200-N₂₀₀, and 300 kg ha⁻¹-N₃₀₀) on soil water dynamics, soil respiration (Rs), net ecosystem production (NEP), and biomass yield. Zero nitrogen soils decreased Rs by 23% and 16% compared to N₃₀₀ and N₂₀₀ soils, respectively. However, biomass yield was greatest under N₃₀₀ compared with N₀, which therefore translated into increased net primary production (NPP) by 89% and NEP by 101% compared to N₀. To a lesser extent, N₂₀₀ increased net primary production by 69% and net ecosystem production by 79% compared to N₀. Grain yields were greatest under N₃₀₀ compared with N₁₀₀ and N₀, which therefore translated into increased carbon emission efficiency (CEE) by 53%, 39% and 3% under N₃₀₀ compared to N₀, N₁₀₀, and N₂₀₀ treatments respectively. Under the conditions of this study, crop yield and CEE may be optimized at nitrogen application rates in the range of 200-300 kg ha⁻¹. Based on these results, there appears potential for 200 kg N ha⁻¹ to be used to improve yield and increase CEE in the context of the rainfall-limiting environment.

Keywords: carbon emission, carbon emission efficiency, C sequestration, N rates, semi-arid

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Authors: Zouari Ezzeddine, Ghraieb Ikram

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From the results of the academic literature which evokes the limitations of previous studies, this article shows the reasons for multidimensionality Prediction of financial bubbles. A new framework for modeling study predicting financial bubbles by linking a set of variable presented on several dimensions dictating its multidimensional character. It takes into account the preferences of financial actors. A multicriteria anticipation of the appearance of bubbles in international financial markets helps to fight against a possible crisis.

Keywords: classical measures, predictions, financial bubbles, multidimensional, artificial neural networks

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Authors: Mabtho Moreroa-Monyelo, Grace Ijoma, Rosina Nkuna, Tonderayi Matambo

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A moving bed biofilm reactor (MBBR) was used for the bioremediation of high strength chemical oxygen demand (COD) Fisher-Tropsch (FT) wastewater. The aerobic MBBR system was operated over 60 days. For metagenomics profile assessment of the targeted 16S sequence of bacteria involved in the bioremediation of the chemical compounds, sludge samples were collected every second day of operation. Parameters such as pH and COD were measured daily to compare the system efficiency as the changedin microbial diversity progressed. The study revealed that pH was a contributing factor to microbial diversity, which further affected the efficiency of the MBBR system. The highest COD removal rate of 86.4% was achieved at pH 8.3. It was observed that when there was more, A higher bacterial diversity led to an improvement in the reduction of COD. Furthermore, an OTUof 4530 was obtained, which were divided into 12 phyla, 27 classes, 44 orders, 74 families, and 138 genera across all sludge samples from the MBBR. A determination of the relative abundance of microorganisms at phyla level indicates that the most abundant phylum on day it was Firmicutes (50%); thereafter, the most abundant phylum changed toProteobacteria.

Keywords: biodegradation, fischer-tropsch wastewater, metagenomics, moving bed biofilm reactor

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Authors: Ting Pan, Jiacheng Wang, Pengcheng Lin, Ying Chen, Songping Mo

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Phase change materials (PCMs) are widely used in latent heat thermal energy storage because of their good properties such as high energy storage density and constant heat-storage/release temperature. Microencapsulation techniques can prevent PCMs from leaking during the liquid-solid phase transition and enhance thermal properties. This technique has been widely applied in architectural materials, thermo-regulated textiles, aerospace fields, etc. One of the most important processes during the synthesis of microcapsules is to form a stable emulsion of the PCM core and reactant solution for the formation of the shell of the microcapsules. The use of surfactants is usually necessary for the formation of a stable emulsion system because of the difference in hydrophilia/lipophilicity of the PCM and the solvent. Unfortunately, the use of surfactants may cause pollution to the environment. In this study, modified kaolinite was used as an emulsion stabilizer for the microencapsulation of octodecane as PCM. Microcapsules were synthesized by phase inversion emulsification method, and the shell of polymethyl methacrylate (PMMA) was formed through free radical polymerization. The morphologies, crystalloid phase, and crystallization properties of microcapsules were investigated using scanning electron microscopy (SEM), X-ray diffractometer (XRD), and Fourier transforms infrared spectrometer (FTIR). The thermal properties and thermal stability were investigated by a differential scanning calorimeter (DSC) and a thermogravimetric analyzer (TG). The FT-IR, XRD results showed that the octodecane was well encapsulated in the PMMA shell. The SEM results showed that the microcapsules were spheres with an average size of about 50-100nm. The DSC results indicated that the latent heat of the microcapsules was 152.64kJ/kg and 164.23kJ/kg. The TG results confirmed that the microcapsules had good thermal stability due to the PMMA shell. Based on the results, it can be concluded that the modified kaolinite can be used as an emulsifier for the synthesis of PCM microcapsules, which is valid for reducing part of the possible pollution caused by the utilization of surfactants.

Keywords: kaolinite, microencapsulation, PCM, thermal energy storage

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Authors: Mengyue Gong, Xinyi Li, Amarjeet Bassi

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Harvesting by-products while recovering biodiesel is considered a potentially valuable approach to increase the market feasibility of microalgae industry. Lutein is a possible by-product from microalgae that promotes eye health. The extraction efficiency and the expensive drying process of wet algae represent the major challenges for the utilization of microalgae biomass as a feedstock for lipids, proteins, and carotenoids. A wet extraction method was developed to extract lipids and lutein from microalga Chlorella vulgaris. To evaluate different solvent (mixtures) for the extraction, a quantitative analysis was established based on the polarity of solvents using Nile Red as the polarity (ETN) indicator. By the choice of binary solvent system then adding proper amount of water to achieve phase separation, lipids and lutein can be extracted simultaneously. Some other parameters for lipids and lutein production were also studied including saponification time, temperature, choice of alkali, and pre-treatment methods. The extraction efficiency with wet algae was compared with dried algae and shown better pigment recovery. The results indicated that the product pattern in each extracted phase was polarity dependent. Lutein and β-carotene were the main carotenoids extracted with ethanol while lipids come out with hexane.

Keywords: biodiesel, Chlorella vulgaris, extraction, lutein

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: W. Jahouach-Rabai, J. Aribi, Z. Azzouz-Berriche, R. Lahsni, F. Hosni

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Gamma irradiation applied in removing pharmaceutical contaminants from wastewater is an effective advanced oxidation process (AOP), considered as an alternative to conventional water treatment technologies. In this purpose, the degradation efficiency of several detected contaminants under gamma irradiation was evaluated. In fact, radiolysis of organic pollutants in aqueous solutions produces powerful reactive species, essentially hydroxyl radical ( ·OH), able to destroy recalcitrant pollutants in water. Pharmaceuticals considered in this study are aqueous solutions of paracetamol, ibuprofen, and diclofenac at different concentrations 0.1-1 mmol/L, which were treated with irradiation doses from 3 to 15 kGy. The catalytic oxidation of these compounds by gamma irradiation was investigated using hydrogen peroxide (H₂O₂) as a convenient oxidant. Optimization of the main parameters influencing irradiation process, namely irradiation doses, initial concentration and oxidant volume (H₂O₂) were investigated, in the aim to release high degradation efficiency of considered pharmaceuticals. Significant modifications attributed to these parameters appeared in the variation of degradation efficiency, chemical oxygen demand removal (COD) and concentration of radio-induced radicals, confirming them synergistic effect to attempt total mineralization. Pseudo-first-order reaction kinetics could be used to depict the degradation process of these compounds. A sophisticated analytical study was released to quantify the detected radio-induced radicals (electron paramagnetic resonance spectroscopy (EPR) and high performance liquid chromatography (HPLC)). All results showed that this process is effective for the degradation of many pharmaceutical products in aqueous solutions due to strong oxidative properties of generated radicals mainly hydroxyl radical. Furthermore, the addition of an optimal amount of H₂O₂ was efficient to improve the oxidative degradation and contribute to the high performance of this process at very low doses (0.5 and 1 kGy).

Keywords: AOP, COD, hydroxyl radical, EPR, gamma irradiation, HPLC, pharmaceuticals

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Authors: Deniz Ünal Özpalamutcu, Burcu Altman

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Actuaria uses mathematics, statistic and financial information when analyzing the financial impacts of uncertainties, risks, insurance and pension related issues. In other words, it deals with the likelihood of potential risks, their financial impacts and especially the financial measures. Handling these measures require some long-term payment and investments. So, it is obvious it is inevitable to plan the periodic payments with equal time intervals considering also the changing value of money over time. These series of payment made specific intervals of time is called annuity or rant. In literature, rants are classified based on start and end dates, start times, payments times, payments amount or frequency. Classification of rants based on payment amounts changes based on the constant, descending or ascending payment methods. The literature about handling the annuity is very limited. Yet in a daily life, especially in today’s world where the economic issues gained a prominence, it is very crucial to use the variable annuity method in line with the demands of the customers. In this study, the types of annuities with flexible payment are discussed. In other words, we focus on calculating payment amount of a period by adding a certain percentage of previous period payment was studied. While studying this problem, formulas were created considering both start and end period payments for cash value and accumulated. Also increase of each period payment by r interest rate each period payments calculated with previous periods increases. And the problem of annuities (rants) of which each period payment increased with previous periods’ increase by r interest rate has been analyzed. Cash value and accumulated value calculation of this problem were studied separately based on the period start/end and their relations were expressed by formulas.

Keywords: actuaria, annuity, flexible payment, rant

Procedia PDF Downloads 211

Authors: Zhihao Peng, Qiong Zhang, Xiyao Li, Yongzhen Peng

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Nowadays, conventional nitrogen removal process (nitrification and denitrification) was adopted in most wastewater treatment plants, but many problems have occurred, such as: high aeration energy consumption, extra carbon sources dosage and high sludge treatment costs. The emergence of anammox has bring about the great revolution to the nitrogen removal technology, and only the ammonia and nitrite were required to remove nitrogen autotrophically, no demand for aeration and sludge treatment. However, there existed many challenges in anammox applications: difficulty of biomass retention, insufficiency of nitrite substrate, damage from complex organic etc. Much effort was put into the research in overcoming the above challenges, and the payment was rewarded. It was also imperative to establish an innovative process that can settle the above problems synchronously, after all any obstacle above mentioned can cause the collapse of anammox system. Therefore, in this study, a two-stage process was established that the sequencing batch reactor (SBR) and upflow anaerobic sludge blanket (UASB) were used in the pre-stage and post-stage, respectively. The domestic wastewater entered into the SBR first and went through anaerobic/aerobic/anoxic (An/O/A) mode, and the draining at the aerobic end of SBR was mixed with domestic wastewater, the mixture then entering to the UASB. In the long term, organic and nitrogen removal performance was evaluated. All along the operation, most COD was removed in pre-stage (COD removal efficiency > 64.1%), including some macromolecular organic matter, like: tryptophan, tyrosinase and fulvic acid, which could weaken the damage of organic matter to anammox. And the An/O/A operating mode of SBR was beneficial to the achievement and maintenance of partial nitrification (PN). Hence, sufficient and steady nitrite supply was another favorable condition to anammox enhancement. Besides, the flexible mixing ratio helped to gain a substrate ratio appropriate to anammox (1.32-1.46), which further enhance the anammox. Further, the UASB was used and gas recirculation strategy was adopted in the post-stage, aiming to achieve granulation by the selection pressure. As expected, the granules formed rapidly during 38 days, which increased from 153.3 to 354.3 μm. Based on bioactivity and gene measurement, the anammox metabolism and abundance level rose evidently, by 2.35 mgN/gVss·h and 5.3 x109. The anammox bacteria mainly distributed in the large granules (>1000 μm), while the biomass in the flocs (<200 μm) and microgranules (200-500 μm) barely displayed anammox bioactivity. Enhanced anammox promoted the advanced autotrophic nitrogen removal, which increased from 71.9% to 93.4%, even when the temperature was only 12.9 ℃. Therefore, it was feasible to enhance anammox in the multiple favorable conditions created, and the strategy extended the application of anammox to the full-scale mainstream, enhanced the understanding of anammox in the aspects of culturing conditions.

Keywords: anammox, granules, nitrite accumulation, nitrogen removal efficiency

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Authors: R. Vetrimurugan, Terry Lim, M. J. Goodson, R. Nagarajan

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This study investigates the cleaning performance of high intensity 360 kHz frequency on the removal of nano-dimensional and sub-micron particles from various surfaces, uniformity of the cleaning tank and run to run variation of cleaning process. The uniformity of the cleaning tank was measured by two different methods i.e 1. ppbTM meter and 2. Liquid Particle Counting (LPC) technique. In the second method, aluminium metal spacer components was placed at various locations of the cleaning tank (such as centre, top left corner, bottom left corner, top right corner, bottom right corner) and the resultant particles removed by 360 kHz frequency was measured. The result indicates that the energy was distributed more uniformly throughout the entire cleaning vessel even at the corners and edges of the tank when megasonic sweeping technology is applied. The result also shows that rinsing the parts with 360 kHz frequency at final rinse gives lower particle counts, hence higher cleaning efficiency as compared to other frequencies. When megasonic sweeping technology is applied each piezoelectric transducers will operate at their optimum resonant frequency and generates stronger acoustic cavitational force and higher acoustic streaming velocity. These combined forces are helping to enhance the particle removal and at the same time improve the overall cleaning performance. The multiple extractions study was also carried out for various frequencies to measure the cleaning potential and asymptote value.

Keywords: power distribution, megasonic sweeping, cavitation intensity, particle removal, laser particle counting, nano, submicron

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Authors: Ananda Perera

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Diet therapy has a positive impact on many diseases in General Practice. If a meal plan can be generated as easily as writing a drug prescription for dyspepsia, then the evidence and practice gap in nutrition therapy can be narrowed. Meal plans of 50 diet prescriptions were compared with the criteria for a healthy diet given by Australian authorities. The energy value of each meal plan was compared with the recommended daily energy requirements of the authorities for Diet Prescription Generator (DPG) accuracy. Meal plans generated were within the criteria laid down by the Australian authorities for a healthy diet.

Keywords: dieting, obesity, diabetes, weight loss, computerized decision support systems, dieting software, CDSS, meal plans

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Authors: Wu Xiaojun, Liu Ruiping, Yu Xingzhan, Wu Qian

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In precision grinding, utilizing the elastic matrix ball has higher processing efficiency and better superficial quality than traditional grinding. The diversity of characteristics which elastic abrasive tool contact with bend surface results in irregular wear abrasion，and abrasive tool machining status get complicated. There is no theoretical interpretation that parameters affect the grinding accuracy.Aiming at corrosion resistance, wear resistance and other characteristics of M 300 material, it is often used as a material on aerospace precision components. The paper carried out grinding and polishing experiments by using material of M 300,to theoretically show the relationship between stress magnitude and grinding efficiency，and predict the optimal combination of grinding parameter for effective grinding, just for the high abrasion resistance features of M 300, analyzing the micro-contact of elastic ball abrasive tool (Whetstone), using mathematical methods deduce the functional relationship between residual peak removal rate and the main parameters which impact the grinding accuracy on the plane case.Thus laying the foundation for the study of elastic abrasive prediction and compensation.

Keywords: flexible abrasive tool, polishing parameters, Hertz theory, removal rate

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Authors: Roy B. Clariana, Ryan L. Solnosky

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Structural feedback is any form of feedback that aims to improve the quality of students’ domain-normative conceptual interrelationships. Research with structural feedback points to the potential mediating role of network graphs as feedback for tuning students’ conceptual understanding; for example, improved content knowledge and motivation were observed for undergraduate students who accessed the instructor’s networks of course content. This exploratory study uses a one-group pretest-posttest design to examine the effects of instructor-provided network feedback during lectures on students’ knowledge structure measured using a concept sorting task at the pretest and posttest. Undergraduate students in an architectural engineering course (n = 32) completed a lesson module and then an end-of-unit quiz on building with wood and wood framing. Three weeks later, as a review, students completed a sorting task that used 26 terms from that lesson, then a week later, the sorting task data were used to create a group-average network, this network along with the instructor’s expert network were added to that week’s lecture slides and were compared and discussed during class time. A week later, students completed the sorting task again. The pre and post-sorting data were rendered into pathfinder networks, and then these students’ networks were compared to five referent networks, specifically the textbook chapter network, the lecture slides network, a network of the end-of-unit quiz, the actual expert network that served as the feedback intervention, and the group-average network. Inspection of means shows that knowledge structure measures improved for all five measures from pre-to-post, becoming more like the lesson content and like the expert. Repeated measures analysis with follow-up paired samples t-tests showed pre-to-post significant increases for both the end-of-unit quiz and the expert network referents. The findings show that instructor presentation of structural feedback as networks improved or ‘tuned’ students’ knowledge structure of the lesson content. This approach only takes a few extra minutes of class time and is fairly simple to implement in ordinary classrooms, and so it has wide potential to support classroom instruction and student learning. Further research is needed to determine how critical it is to present both the group-average network along with the expert network for comparison in order to highlight group-level misconceptions, or is presenting only the expert network sufficient? If a group-level network is necessary, then a simple clicker-like classroom tool could be developed to collect sorting task data during lectures that could then immediately provide the group-average network for class discussion and reflection.

Keywords: classroom instruction, engineering education, knowledge structure, pathfinder networks, structural feedback

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Authors: Tadewos Awugchew Wudineh

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Health and safety issues have always been a major problem and concern in the building construction industry. The health and safety regulations are stated to eliminate the potential hazards and to reduce the consequential risks. However, the importance of the regulations seems to be overlooked in building construction sites of Hawassa City. Accordingly, many companies don’t follow the regulations as construction workers are more likely to be injured and killed by construction accident than any other type of employment. This paper aimed to identify factors that affect the implementation of construction health and safety regulations, their effects and mitigation measures in building construction project sites of Hawassa City. To reach this objective, a review of literature as well as the Ethiopian construction health and safety regulations have been undertaken. Mainly a five-point Likert scale questionnaire was distributed, and statistical analysis was used to summarize, interpret the data, and to find the significances of the responses. In addition, interviews were carried out. Accordingly, the findings indicate that the top factors which affect the implementation of CHS regulations are, availability and development of a clear health and safety policy, health and safety inspections by top management, conducting health and safety training and orientation, provision of healthy and safe working environment and employment of trained safety officers. The study revealed that implementation or non-implementation of CHS regulations have effects on the worker’s productivity, job satisfaction, rate of accidents, and cost greatly. Thus, the suggestion to minimize the impact on worker’s job performance are, developing of a clear health and safety policy, management commitment towards implementation of health and safety regulations, health and safety education and training and conducting regular health and safety inspections. It was concluded from the study that good implementation of health and safety regulations are the results from administrative and management commitment which calls for more attention to be paid to improve the implementation of CHS regulations in building construction sites of Hawassa City.

Keywords: construction health and safety regulations, effects, factors, mitigation

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Authors: Tehreem Fatima, Enjun Xia

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The research investigates the relationship between total oil consumption and transport oil consumption, GDP, oil price, and oil reserve in order to forecast future oil demand in China. Annual time series data is used over the period of 1980 to 2015, and for this purpose, an oil demand function is estimated by applying structural time series model (STSM). The technique also uncovers the Underline energy demand trend (UEDT) for China oil demand and GDP, oil reserve, oil price and UEDT are considering important drivers of China oil demand. The long-run elasticity of total oil consumption with respect to GDP and price are (0.5, -0.04) respectively while GDP, oil reserve, and price remain (0.17; 0.23; -0.05) respectively. Moreover, the Estimated results of long-run elasticity of transport oil consumption with respect to GDP and price are (0.5, -0.00) respectively long-run estimates remain (0.28; 37.76;-37.8) for GDP, oil reserve, and price respectively. For both model estimated underline energy demand trend (UEDT) remains nonlinear and stochastic and with an increasing trend of (UEDT) and based on estimated equations, it is predicted that China total oil demand somewhere will be 9.9 thousand barrel per day by 2025 as compare to 9.4 thousand barrel per day in 2015, while transport oil demand predicting value is 9.0 thousand barrel per day by 2020 as compare to 8.8 thousand barrel per day in 2015.

Keywords: china, forecasting, oil, structural time series model (STSM), underline energy demand trend (UEDT)

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Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

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The carbon footprint of the aviation sector in total measured 3.8% in 2017, and it is expected to triple by 2050. New combustion approaches and fuel types are necessary to prevent this. This paper will focus on using propane, methane, and hydrogen as fuel replacements for kerosene and implement a trapped vortex combustor design to increase efficiency. Reacting simulations were conducted for axisymmetric trapped vortex combustor to investigate the static pressure drop, combustion efficiency and pattern factor for various cavity aspect ratios for 0.3, 0.6 and 1 and air mass flow rates for 14 m/s, 28 m/s and 42 m/s. Propane, methane and hydrogen are used as alternative fuels. The combustion model was anchored based on swirl flame configuration with an emphasis on high fidelity of boundary conditions with favorable results of eddy dissipation model implementation. Reynolds Averaged Navier Stokes (RANS) k-ε model turbulence model for the validation effort was used for turbulence modelling. A grid independence study was conducted for the three-dimensional model to reduce computational time. Preliminary results for 24 m/s air mass flow rate provided a close temperature profile inside the cavity relative to the experimental study. The investigation will be carried out on the effect of air mass flow rates and cavity aspect ratio on the combustion efficiency, pattern factor and static pressure drop in the combustor. A comparison study among pure methane, propane and hydrogen will be conducted to investigate their suitability for trapped vortex combustors and conclude their advantages and disadvantages as a fuel replacement. Therefore, the study will be one of the milestones to achieving 2050 zero carbon emissions or reducing carbon emissions.

Keywords: computational fluid dynamics, aerodynamic, aerospace, propulsion, trapped vortex combustor

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Authors: Farhan E Shafrin, Khandaker Shabbir Ahmed

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Natural ventilation strategies continue to be a key alternative to costly mechanical ventilation systems, especially in healthcare facilities, due to increasing energy issues in developing countries, including Bangladesh. Besides, overcrowding and insufficient ventilation strategies remain significant causes of thermal discomfort and hospital infection in Bangladesh. With the proper location of inlet and outlet windows, uniform flow is possible in the occupancy area to achieve thermal comfort. It also determines the airflow pattern of the ward that decreases the movement of the contaminated air. This paper aims to establish a relationship between the location of the windows and the thermal comfort of the occupants in a naturally ventilated hospital ward. It defines the openings and ventilation variables that are interrelated in a way that enhances or limits the health and thermal comfort of occupants. The study conducts a full-scale experiment in one of the naturally ventilated wards in a primary health care hospital in Manikganj, Dhaka. CFD simulation is used to explore the performance of various opening positions in ventilation efficiency and thermal comfort in the study area. The results indicate that the opening located in the hospital ward has a significant impact on the thermal comfort of the occupants and the airflow pattern inside the ward. The findings can contribute to design the naturally ventilated hospital wards by identifying and predicting future solutions when it comes to relationships with the occupants' thermal comforts.

Keywords: CFD simulation, hospital ward, natural ventilation, thermal comfort, window location

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Authors: Gizem Kodak, Birsen Koldemir

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The Turkish Straits are at the crossroads of Europe and Asia continents and are unique waterways connecting the Black Sea countries to the rest of the world. Because of the geostrategic value of the location, passage of trade and war ships through the Turkish Straits has become a vital attraction and importance for the great powers and the riparian states throughout the history. This study contains a temporal analysis of the legal measures implemented in the Turkish Straits System. In this context, the historical alternation of the Turkish Straits has been examined, taking into account the relevant national and international regulations. In other words, relevant national and international regulations have been examined in this study according to historical time schedules. Parallel to the main concept mentioned above, the first chapter focuses on international regulations. These arrangements are organized according to date order and in three subheadings: Sèvres Treaty (1920), Lausanne Treaty (1923) and Montreux Convention (1936). Another topic, the national regulations, has been examined under five subheadings. These; (1982), Port Regulations of Canakkale (1982), Marine Traffic Regulations of the Turkish Straits and Marmara Region (1994) and Maritime Traffic Regulations for the Turkish Straits (1998). In doing so, the aim was to identify the differences in legal arrangements throughout the time regarding the navigation through the Turkish Straits. The current situation of the Turkish Straits has been presented in detail in the last part of the work, taking Montreux Convention into consideration. In this context, the articles of the Convention which regulate the passage of trade vessels have been examined from two perspectives; Peace time and war time. As for the measures that can be implemented in time of war, three options put forward depending on Turkey's stance: ‘Turkey not being belligerent’, ‘Turkey being belligerent’ and ‘situation in which Turkey considers herself threatened with imminent danger of war’.

Keywords: temporal analysis, maritime law, Turkish straits, maritime accidents

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Authors: Swadha Singh

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International Solar Alliance is the foremost treaty-based global organization concerned with tapping the potential of sun-abundant nations between the Tropics of Cancer and Capricorn and enables co-operation among them. As a founding member of the International Solar Alliance, India exhibits its positioning as an upcoming leader in clean energy. India has set ambitious goals and targets to expand the share of solar in its energy mix and is playing a proactive role both at the regional and global levels. ISA aims to serve multiple goals- bring about scale commercialization of solar power, boost domestic manufacturing, and leverage solar diplomacy in African countries, amongst others. Against this backdrop, this paper attempts to examine the ways in which ISA as an intergovernmental organization under Indian leadership can leverage the cause of clean energy (solar) diplomacy and effectively shape partnerships and collaborations with other developing countries in terms of sharing solar technology, capacity building, risk mitigation, mobilizing financial investment and providing an aggregate market. A more specific focus of ISA is on the developing countries, which in the absence of a collective, are constrained by technology and capital scarcity, despite being naturally endowed with solar resources. Solar rich but finance-constrained economies face political risk, foreign exchange risk, and off-taker risk. Scholars argue that aligning India’s climate change discourse and growth prospects in its engagements, collaborations, and partnerships at the bilateral, multilateral and regional level can help promote trade, attract investments, and promote resilient energy transition both in India and in partner countries. For developing countries, coming together in an action-oriented way on issues of climate and clean energy is particularly important since it is developing and underdeveloped countries that face multiple and coalescing challenges such as the adverse impact of climate change, uneven and low access to reliable energy, and pressing employment needs. Investing in green recovery is agreed to be an assured way to create resilient value chains, create sustainable livelihoods, and help mitigate climate threats. If India is able to ‘green its growth’ process, it holds the potential to emerge as a climate leader internationally. It can use its experience in the renewable sector to guide other developing countries in balancing multiple similar objectives of development, energy security, and sustainability. The challenges underlying solar expansion in India have lessons to offer other developing countries, giving India an opportunity to assume a leadership role in solar diplomacy and expand its geopolitical influence through inter-governmental organizations such as ISA. It is noted that India has limited capacity to directly provide financial funds and support and is not a leading manufacturer of cheap solar equipment, as does China; however, India can nonetheless leverage its large domestic market to scale up the commercialization of solar power and offer insights and learnings to similarly placed abundant solar countries. The paper examines the potential of and limits placed on India’s solar diplomacy.

Keywords: climate diplomacy, energy security, solar diplomacy, renewable energy

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Authors: Om Prakash Bharti, Aanchal Verma, R. K. Saket

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The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.

Keywords: doubly-fed induction generator, wind turbine, wind energy conversion system, induction generator, transfer function, proportional, integral, derivatives

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Authors: Tuğçe Yücel

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A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.

Keywords: MIP, sensor, telecommunications, WSN

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Authors: Karim Ahmed

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The purpose of this study was to investigate how factoring the impact of natural disasters beyond flooding would affect managed retreat policy eligibility in the United States. For the study design, a correlation analysis method compared weighted measures of flooding and other natural disasters (e.g., wildfires, tornadoes, heatwaves, etc.) to CBSA Populated areas, the prevalence of cropland, and relative poverty on a county level. The study found that the vast majority of CBSAs eligible for managed retreat programs under a policy inclusive of non-flooding events would have already been covered by flood-only managed retreat policies. However, it is noteworthy that a majority of those counties that are not covered by a flood-only managed retreat policy have high rates of poverty and are either heavily populated and/or agriculturally active. The correlation is particularly strong between counties that are subject to multiple natural hazards and those that have both high rates of relative poverty and cropland prevalence. There is currently no managed retreat policy for agricultural land in the United States despite the environmental implications and food supply chain vulnerabilities related to at-risk cropland. The findings of this study suggest both that such a policy should be created and, when it is, that special attention should be paid to non-flood natural disasters affecting agricultural areas. These findings also reveal that, while current flood-based policies in the United States serve many areas that do need access to managed retreat funding and implementation, other vulnerable areas are overlooked by this approach. These areas are often deeply impoverished and are therefore particularly vulnerable to natural disaster; if and when those disasters do occur, these areas are often less financially prepared to recover or retreat from the disaster’s advance and, due to the limitations of the current policies discussed above, are less able to take the precautionary measures necessary to mitigate their risk.

Keywords: flood, hazard, land use, managed retreat, wildfire

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Authors: Ya Lv

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This article presents the application of the semi-analytic method (SAM) in the thermal management solution (TMS) of the energy storage system (ESS). The TMS studied in this work is fluid cooling. In fluid cooling, both effective heat conduction and heat convection are indispensable due to the heat transfer from solid to fluid. Correspondingly, an efficient TMS requires a design investigation of the following parameters: fluid inlet temperature, ESS initial temperature, fluid flow rate, working c rate, continuous working time, and materials properties. Their variation induces a change of thermal performance in the battery module, which is usually evaluated by numerical simulation. Compared to complicated computation resources and long computation time in simulation, the SAM is developed in this article to predict the thermal influence within a few seconds. In SAM, a fast prediction model is reckoned by combining numerical simulation with theoretical/empirical equations. The SAM can explore the thermal effect of boundary parameters in both steady-state and transient heat transfer scenarios within a short time. Therefore, the SAM developed in this work can simplify the design cycle of TMS and inspire more possibilities in TMS design.

Keywords: semi-analytic method, fast prediction model, thermal influence of boundary parameters, energy storage system

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Authors: Bryan D. Llenarizas, Maria Carla F. Manzano

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The rapid growth of electricity demand has led to a pursuit of alternative energy sources with high power output and not harmful to the environment. The fuel cell is a device that generates electricity via chemical reactions between the fuel and oxidant. Fuel cells have been known for decades, but the development of high-power output and durability was still one of the drawbacks of this energy source. This study investigates the potential of layer-by-layer composite for fuel cell applications. A two-electrode electrochemical cell was used for the galvanostatic electrochemical deposition method to fabricate a Polypyrrole/rGO|Polypyrrole/ZnO layer-by-layer composite material for fuel cell applications. In the synthesis, the first layer comprised 0.1M pyrrole monomer and 1mg of rGO, while the second layer had 0.1M pyrrole monomer and variations of ZnO concentration ranging from 0.08M up to 0.12M. A constant current density of 8mA/cm² was applied for 1 hour in fabricating each layer. Scanning electron microscopy (SEM) for the fabricated LBL material shows a globular surface with white spots. These white spots are the ZnO particles confirmed by energy-dispersive X-ray spectroscopy, indicating a successful deposition of the second layer onto the first layer. The observed surface morphology was consistent for each variation of ZnO concentrations. AC measurements were conducted to obtain the AC resistance of the fabricated film. Results show a decrease in AC resistance as the concentration of ZnO increases.

Keywords: anode, composite material, electropolymerization, fuel cell, galvanostatic, polypyrrole

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Authors: Gerardo Ayala-Jaimes, Gilberto Gonzalez-Avalos, Allen A. Castillo, Alejandra Jimenez

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The modeling of a single-phase cycloconverter in Bond Graph is presented, which includes an alternating current power supply, hybrid dynamics, switch control, and resistive load; this approach facilitates the integration of systems across different energy domains and structural analysis. Cycloconverters, used in motor control, demonstrate the viability of graphical modeling. The use of Bonds is proposed to model the hybrid interaction of the system, and the results are displayed through simulations using 20Sim and Multisim software. The motivation behind developing these models with a graphical approach is to design and build low-cost energy converters, thereby making the main contribution of this document the modeling and simulation of a single-phase cycloconverter.

Keywords: bond graph, hybrid system, rectifier, cycloconverter, modelling

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