Search results for: carbon efficiency

Authors: Dorottya Guban, Irina Borbath, Istvan Bakos, Peter Nemeth, Andras Tompos

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One of the greatest challenges of the implementation of polymer electrolyte membrane fuel cells (PEMFCs) is to find active and durable electrocatalysts. The cell performance is always limited by the oxygen reduction reaction (ORR) on the cathode since it is at least 6 orders of magnitude slower than the hydrogen oxidation on the anode. Therefore high loading of Pt is required. Catalyst corrosion is also more significant on the cathode, especially in case of mobile applications, where rapid changes of loading have to be tolerated. Pt-Sn bulk alloys and SnO2-decorated Pt3Sn nanostructures are among the most studied bimetallic systems for fuel cell applications. Exclusive formation of supported Sn-Pt alloy phases with different Pt/Sn ratios can be achieved by using controlled surface reactions (CSRs) between hydrogen adsorbed on Pt sites and tetraethyl tin. In this contribution our results for commercial and a home-made 20 wt.% Pt/C catalysts modified by tin anchoring via CSRs are presented. The parent Pt/C catalysts were synthesized by modified NaBH4-assisted ethylene-glycol reduction method using ethanol as a solvent, which resulted either in dispersed and highly stable Pt nanoparticles or evenly distributed raspberry-like agglomerates according to the chosen synthesis parameters. The 20 wt.% Pt/C catalysts prepared that way showed improved electrocatalytic performance in the ORR and stability in comparison to the commercial 20 wt.% Pt/C catalysts. Then, in order to obtain Sn-Pt/C catalysts with Pt/Sn= 3 ratio, the Pt/C catalysts were modified with tetraethyl tin (SnEt4) using three and five consecutive tin anchoring periods. According to in situ XPS studies in case of catalysts with highly dispersed Pt nanoparticles, pre-treatment in hydrogen even at 170°C resulted in complete reduction of the ionic tin to Sn0. No evidence of the presence of SnO2 phase was found by means of the XRD and EDS analysis. These results demonstrate that the method of CSRs is a powerful tool to create Pt-Sn bimetallic nanoparticles exclusively, without tin deposition onto the carbon support. On the contrary, the XPS results revealed that the tin-modified catalysts with raspberry-like Pt agglomerates always contained a fraction of non-reducible tin oxide. At the same time, they showed increased activity and long-term stability in the ORR than Pt/C, which was assigned to the presence of SnO2 in close proximity/contact with Pt-Sn alloy phase. It has been demonstrated that the content and dispersion of the fcc Pt3Sn phase within the electrocatalysts can be controlled by tuning the reaction conditions of CSRs. The bimetallic catalysts displayed an outstanding performance in the ORR. The preparation of a highly dispersed 20Pt/C catalyst permits to decrease the Pt content without relevant decline in the electrocatalytic performance of the catalysts.

Keywords: anode catalyst, cathode catalyst, controlled surface reactions, oxygen reduction reaction, PtSn/C electrocatalyst

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Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

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Authors: Sunday Olufemi Adesogan

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The supply of potable water at least is a very important index in national development. Water tariffs depend on the treatment cost which carries the highest percentage of the total operation cost in any water supply scheme. In order to keep water tariffs as low as possible, treatment costs have to be minimized. The University of Ibadan, Nigeria, water supply scheme consists of a treatment plant with three distribution stations (Amina way, Kurumi and Lander) and two raw water supply sources (Awba dam and Eleyele dam). An operational study of the scheme was carried out to ascertain the efficiency of the supply of potable water on the campus to justify the need for water supply schemes in tertiary institutions. The study involved regular collection, processing and analysis of periodic operational data. Data collected include supply reading (water production on daily basis) and consumers metered reading for a period of 22 months (October 2013 - July 2015), and also collected, were the operating hours of both plants and human beings. Applying the required mathematical equations, total loss was determined for the distribution system, which was translated into monetary terms. Adequacies of the operational functions were also determined. The study revealed that water supply scheme is justified in tertiary institutions. It was also found that approximately 10.7 million Nigerian naira (N) is lost to leakages during the 22-month study period; the system’s storage capacity is no longer adequate, especially for peak water production. The capacity of the system as a whole is insufficient for the present university population and that the existing water supply system is not being operated in an optimal manner especially due to personnel, power and system ageing constraints.

Keywords: development, panacea, supply, water

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Dana Alina Magdas, Nicoleta Simona Vedeanu, Ioana Feher, Rares Stiufiuc

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Food and beverages authentication using rapid and non-expensive analytical tools represents nowadays an important challenge. In this regard, the potential of vibrational techniques in food authentication has gained an increased attention during the last years. For wines discrimination, Raman spectroscopy appears more feasible to be used as compared with IR (infrared) spectroscopy, because of the relatively weak water bending mode in the vibrational spectroscopy fingerprint range. Despite this, the use of Raman technique in wine discrimination is in an early stage. Taking this into consideration, the wine discrimination potential of surface-enhanced Raman scattering (SERS) technique is reported in the present work. The novelty of this study, compared with the previously reported studies, concerning the application of vibrational techniques in wine discrimination consists in the fact that the present work presents the wines differentiation based on the individual signals obtained from deconvoluted spectra. In order to achieve wines classification with respect to variety, geographical origin and vintage, the peaks intensities obtained after spectra deconvolution were compared using supervised chemometric methods like Linear Discriminant Analysis (LDA). For this purpose, a set of 20 white Romanian wines from different viticultural Romanian regions four varieties, was considered. Chemometric methods applied directly to row SERS experimental spectra proved their efficiency, but discrimination markers identification found to be very difficult due to the overlapped signals as well as for the band shifts. By using this approach, a better general view related to the differences that appear among the wines in terms of compositional differentiation could be reached.

Keywords: chemometry, SERS, variety, wines discrimination

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Authors: Mohammed Panthakkal Abdul Muthalif, Shanmugasundaram Kanagaraj, Jumi Park, Hangyu Park, Youngson Choe

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The present study reports the incorporation of calcium ions into the CuS counter electrodes (CEs) in order to modify the photovoltaic performance of quantum dot-sensitized solar cells (QDSSCs). Metal ion-doped CuS thin film was prepared by the chemical bath deposition (CBD) method on FTO substrate and used directly as counter electrodes for TiO₂/CdS/CdSe/ZnS photoanodes based QDSSCs. For the Ca-doped CuS thin films, copper nitrate and thioacetamide were used as anionic and cationic precursors. Calcium nitrate tetrahydrate was used as doping material. The surface morphology of Ca-doped CuS CEs indicates that the fragments are uniformly distributed, and the structure is densely packed with high crystallinity. The changes observed in the diffraction patterns suggest that Ca dopant can introduce increased disorder into CuS material structure. EDX analysis was employed to determine the elemental identification, and the results confirmed the presence of Cu, S, and Ca on the FTO glass substrate. The photovoltaic current density – voltage characteristics of Ca-doped CuS CEs shows the specific improvements in open circuit voltage decay (Voc) and short-circuit current density (Jsc). Electrochemical impedance spectroscopy results display that Ca-doped CuS CEs have greater electrocatalytic activity and charge transport capacity than bare CuS. All the experimental results indicate that 20% Ca-doped CuS CE based QDSSCs exhibit high power conversion efficiency (η) of 4.92%, short circuit current density of 15.47 mA cm⁻², open circuit photovoltage of 0.611 V, and fill factor (FF) of 0.521 under illumination of one sun.

Keywords: Ca-doped CuS counter electrodes, surface morphology, chemical bath deposition method, electrocatalytic activity

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Authors: Ali Elshabrawy

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Cloud computing is expected to be important for e Government in near future. Governments need it for solving some of its e Government, financial, infrastructure, legacy systems and integration problems. It reduces information technology (IT) infrastructure needs and support costs, and offers on-demand infrastructure and computational power, improved collaboration capabilities, which are important for e Government projects start up and sustainability. Budget pressures will continue to drive more and more government IT to hybrid and even public clouds, and more cooperation between cloud service providers and governmental agencies are expected, Or developing governmental private, community clouds. Motivation to convince governments to use cloud computing services, will create a pressure on cloud service providers to cope with government's requirements for interoperability, security standards, open data and integration between their cloud systems There will be significant legal action arising out of governmental uses of cloud computing, and legislation addressing both IT and business needs and consumer fears and protections. Cloud computing is a considered a revolution for IT and E business in general and e commerce, e Government in particular. As governments faces increasing challenges regarding IT infrastructure required for e Government projects implementation. As a result of Lack of required financial resources allocated for e Government projects in developed and developing countries. Cloud computing can play a major role to solve some of e Government projects challenges such as, lack of financial resources, IT infrastructure, Human resources trained to manage e Government applications, interoperability, cost efficiency challenges. If we could solve some security issues related to cloud computing usage which considered critical for e Government projects. Pretty sure it’s Just a matter of time before cloud service providers will find out solutions to attract governments as major customers for their business.

Keywords: cloud computing, e-government, adoption, supply side barriers, e-government requirements, challenges

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Authors: Anna Yagodnitsyna, Alexander Kovalev, Artur Bilsky

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The efficiency of certain technological processes in two-phase microfluidics such as emulsion production, nanomaterial synthesis, nitration, extraction processes etc. depends on two-phase flow regimes in microchannels. For practical application in chemistry and biochemistry it is very important to predict the expected flow pattern for a large variety of fluids and channel geometries. In the case of immiscible liquids, the plug flow is a typical and optimal regime for chemical reactions and needs to be predicted by empirical data or correlations. In this work flow patterns of immiscible liquid-liquid flow in a rectangular microchannel with T-junction are investigated. Three liquid-liquid flow systems are considered, viz. kerosene – water, paraffin oil – water and castor oil – paraffin oil. Different flow patterns such as parallel flow, slug flow, plug flow, dispersed (droplet) flow, and rivulet flow are observed for different velocity ratios. New flow pattern of the parallel flow with steady wavy interface (serpentine flow) has been found. It is shown that flow pattern maps based on Weber numbers for different liquid-liquid systems do not match well. Weber number multiplied by Ohnesorge number is proposed as a parameter to generalize flow maps. Flow maps based on this parameter are superposed well for all liquid-liquid systems of this work and other experiments. Plug length and velocity are measured for the plug flow regime. When dispersed liquid wets channel walls plug length cannot be predicted by known empirical correlations. By means of particle tracking velocimetry technique instantaneous velocity fields in a plug flow regime were measured. Flow circulation inside plug was calculated using velocity data that can be useful for mass flux prediction in chemical reactions.

Keywords: flow patterns, hydrodynamics, liquid-liquid flow, microchannel

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Authors: Waqas Hassan Tanveer, Yoon Ho Lee, Taehyun Park, Wonjong Yu, Yaegeun Lee, Yusung Kim, Suk Won Cha

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Nickel-Gadolinium Doped Ceria (Ni-GDC) cermet anodic thin films were prepared on Scandia Stabilized Zirconia (ScSZ) electrolyte supports by radio frequency (RF) sputtering, with a range of different sputtering powers (50 – 200W) and background Ar gas pressures (30 – 90mTorr). The effects of varying sputtering power and pressure on the properties of Ni-GDC films were studied using Focused Ion Beam (FIB), X-ray Photoelectron Spectroscopy (XPS), X-ray Diffraction (XRD), Energy Dispersive X-ray (EDX), and Atomic Force Microscopy (AFM) techniques. The Ni content was found to be always higher than the Ce content, at all sputtering conditions. This increased Ni content was attributed to significantly higher energy transfer efficiency of Ni ions as compared to Ce ions with Ar background sputtering gas. The solid oxide fuel cell configuration was completed by using lanthanum strontium manganite (LSM/YSZ) cathodes on the other side of ScSZ supports. Performance comparison of cells was done by Voltage-Current-Power (VIP) curves, while the resistances of various cell components were observed by nyquist plots. Initial results showed that anode films made by higher powered RF sputtering performed better than lower powered ones for a specific Ar pressure. Interestingly, however, anodes made at highest power and pressure, were not the ones that showed the maximum power output at an intermediate solid oxide fuel cell temperature of 800°C. Finally, an optimal sputtering condition was reported for high performance Ni-GDC anodes.

Keywords: intermediate temperature solid oxide fuel cells, nickel-cermet anodic thin films, nyquist plots, radio frequency sputtering

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Authors: Ashish Bhattarai, Bishnu Bhatta, Hem Raj Joshi, Nabin Neupane, Pankaj Yadav

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This report concerns the design, development, and analysis of the combined Darrieus and Savonius wind turbine. Vertical Axis Wind Turbines (VAWT's) are of two type's viz. Darrieus (lift type) and Savonius (drag type). The problem associated with Darrieus is the lack of self-starting while Savonius has low efficiency. There are 3 straight Darrieus blades having the cross-section of NACA(National Advisory Committee of Aeronautics) 0018 placed circumferentially and a helically twisted Savonius blade to get even torque distribution. This unique design allows the use of Savonius as a method of self-starting the wind turbine, which the Darrieus cannot achieve on its own. All the parts of the wind turbine are designed in CAD software, and simulation data were obtained via CFD(Computational Fluid Dynamics) approach. Also, the design was imported to FlashForge Finder to 3D print the wind turbine profile and finally, testing was carried out. The plastic material used for Savonius was ABS(Acrylonitrile Butadiene Styrene) and that for Darrieus was PLA(Polylactic Acid). From the data obtained experimentally, the hybrid VAWT so fabricated has been found to operate at the low cut-in speed of 3 m/s and maximum power output has been found to be 7.5537 watts at the wind speed of 6 m/s. The maximum rpm of the rotor blade is recorded to be 431 rpm(rotation per minute) at the wind velocity of 6 m/s, signifying its potentiality of wind power production. Besides, the data so obtained from both the process when analyzed through graph plots has shown the similar nature slope wise. Also, the difference between the experimental and theoretical data obtained has shown mechanical losses. The objective is to eliminate the need for external motors for self-starting purposes and study the performance of the model. The testing of the model was carried out for different wind velocities.

Keywords: VAWT, Darrieus, Savonius, helical blades, CFD, flash forge finder, ABS, PLA

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Authors: Eyob Messele Sefene, Atinkut Atinafu Yilma

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The highest strength-to-weight ratio criterion has fascinated increasing curiosity in virtually all areas where weight reduction is indispensable. One of the recent advances in manufacturing to achieve this intention endears friction stir welding (FSW). The process is widely used for joining similar and dissimilar non-ferrous materials. In FSW, the mechanical properties of the weld joints are impelled by property-selected process parameters. This paper presents verdicts of optimum process parameters in attempting to attain enhanced mechanical properties of the weld joint. The experiment was conducted on a 5 mm 6061 aluminum alloy sheet. A butt joint configuration was employed. Process parameters, rotational speed, traverse speed or feed rate, axial force, dwell time, tool material and tool profiles were utilized. Process parameters were also optimized, making use of a mixed L18 orthogonal array and the Grey relation analysis method with larger is better quality characteristics. The mechanical properties of the weld joint are examined through the tensile test, hardness test and liquid penetrant test at ambient temperature. ANOVA was conducted in order to investigate the significant process parameters. This research shows that dwell time, rotational speed, tool shape, and traverse speed have become significant, with a joint efficiency of about 82.58%. Nine confirmatory tests are conducted, and the results indicate that the average values of the grey relational grade fall within the 99% confidence interval. Hence the experiment is proven reliable.

Keywords: friction stir welding, optimization, 6061 AA, Taguchi

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Authors: Blanca A. Pichardo, Victor H. Lopez, Melchor Salazar, Rafael Garcia, Alberto Ruiz

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Clad pipes in comparison to plain carbon steel pipes offer the oil and gas industry high corrosion resistance, reduction in economic losses due to pipeline failures and maintenance, lower labor risk, prevent pollution and environmental damage due to hydrocarbons spills caused by deteriorated pipelines. In this context, it is paramount to establish reliable welding procedures to join bimetallic plates or pipes. Thus, the aim of this work is to study the microstructure and mechanical behavior of clad plates welded by the gas metal arc welding (GMAW) process. A clad of 316L stainless steel was deposited onto API 5L X-60 plates by overlay welding with the GMAW process. Welding parameters were, 22.5 V, 271 A, heat input 1,25 kJ/mm, shielding gas 98% Ar + 2% O₂, reverse polarity, torch displacement speed 3.6 mm/s, feed rate 120 mm/s, electrode diameter 1.2 mm and application of an electromagnetic field of 3.5 mT. The overlay welds were subjected to macro-structural and microstructural characterization. After manufacturing the clad plates, a single V groove joint was machined with a 60° bevel and 1 mm root face. GMA welding of the bimetallic plates was performed in four passes with ER316L-Si filler for the root pass and an ER70s-6 electrode for the subsequent welding passes. For joining the clad plates, an electromagnetic field was applied with 2 purposes; to improve the microstructural characteristics and to assist the stability of the electric arc during welding in order to avoid magnetic arc blow. The welds were macro and microstructurally characterized and the mechanical properties were also evaluated. Vickers microhardness (100 g load for 10 s) measurements were made across the welded joints at three levels. The first profile, at the 316L stainless steel cladding, was quite even with a value of approximately 230 HV. The second microhardness profile showed high values in the weld metal, ~400 HV, this was due to the formation of a martensitic microstructure by dilution of the first welding pass with the second. The third profile crossed the third and fourth welding passes and an average value of 240 HV was measured. In the tensile tests, yield strength was between 400 to 450 MPa with a tensile strength of ~512 MPa. In the Charpy impact tests, the results were 86 and 96 J for specimens with the notch in the face and in the root of the weld bead, respectively. The results of the mechanical properties were in the range of the API 5L X-60 base material. The overlap welding process used for cladding is not suitable for large components, however, it guarantees a metallurgical bond, unlike the most commonly used processes such as thermal expansion. For welding bimetallic plates, control of the temperature gradients is key to avoid distortions. Besides, the dissimilar nature of the bimetallic plates gives rise to the formation of a martensitic microstructure during welding.

Keywords: clad pipe, dissimilar welding, gas metal arc welding, magnetic fields

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Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi

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The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.

Keywords: almost strictly positive real (ASPR), doubly-fed induction generator (DIFG), simple adaptive control (SAC), subsynchronous oscillations, wind turbine

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Authors: Nguyen Chi Quang, Nguyen Duong Tri Nguyen

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This article is the first step to research and outline the structure of the geotechnical database in the geological survey of a power project; in the context of this report creating the database that has been carried out for the Bac Ai pumped storage hydropower project. For the purpose of providing a method of organizing and storing geological and topographic survey data and experimental results in a spatial database, the RockWorks software is used to bring optimal efficiency in the process of exploiting, using, and analyzing data in service of the design work in the power engineering consulting. Three-dimensional (3D) geotechnical models are created from the survey data: such as stratigraphy, lithology, porosity, etc. The results of the 3D geotechnical model in the case of Bac Ai pumped storage hydropower project include six closely stacked stratigraphic formations by Horizons method, whereas modeling of engineering geological parameters is performed by geostatistical methods. The accuracy and reliability assessments are tested through error statistics, empirical evaluation, and expert methods. The three-dimensional model analysis allows better visualization of volumetric calculations, excavation and backfilling of the lake area, tunneling of power pipelines, and calculation of on-site construction material reserves. In general, the application of engineering geological modeling makes the design work more intuitive and comprehensive, helping construction designers better identify and offer the most optimal design solutions for the project. The database always ensures the update and synchronization, as well as enables 3D modeling of geological and topographic data to integrate with the designed data according to the building information modeling. This is also the base platform for BIM & GIS integration.

Keywords: database, engineering geology, 3D Model, RockWorks, Bac Ai pumped storage hydropower project

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Authors: Vishnu V. Pillai, Sunil P. Lonkar, Akhil M. Abraham, Saeed M. Alhassan

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An effectual technology for wastewater treatment is a great demand now in order to encounter the water pollution caused by organic pollutants. Photocatalytic oxidation technology is widely used in removal of such unsafe contaminants. Among the semi-conducting metal oxides, robust and thermally stable TiO2 has emerged as a fascinating material for photocatalysis. Enhanced catalytic activity was observed for nanostructured TiO2 due to its higher surface, chemical stability and higher oxidation ability. However, higher charge carrier recombination and wide band gap of TiO2 limits its use as a photocatalyst in the UV region. It is desirable to develop a photocatalyst that can efficiently absorb the visible light, which occupies the main part of the solar spectrum. Hence, in order to extend its photocatalytic efficiency under visible light, TiO2 nanoparticles are often doped with metallic or non-metallic elements. Non-metallic doping of TiO2 has attracted much attention due to the low thermal stability and enhanced recombination of charge carriers endowed by metallic doping of TiO2. Amongst, sulfur doped TiO2 is most widely used photocatalyst in environmental purification. However, the most of S-TiO2 synthesis technique uses toxic chemicals and complex procedures. Hence, a facile, scalable and environmentally benign preparation process for S-TiO2 is highly desirable. In present work, we have demonstrated new and facile solid-state reaction method for S-TiO2 synthesis that uses abundant elemental sulfur as S source and moderate temperatures. The resulting nano-sized S-TiO2 has been successfully employed as visible light photocatalyst in methylene blue dye removal from aqueous media.

Keywords: ecofriendly, nanomaterials, methylene blue, photocatalysts

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Authors: Ruphi Naz, Altaf Ahmad, Mohammad Anis

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Sialic acid (5-Acetylneuraminic acid, Neu5Ac) is a common sugar found as a terminal residue on glycoconjugates in many animals. Humans brain and the central nervous system contain the highest concentration of sialic acid (as N-acetylneuraminic acid) where these acids play an important role in neural transmission and ganglioside structure in synaptogenesis. Due to its important biological function, sialic acid is attracting increasing attention. To understand metabolic networks, fluxes and regulation, it is essential to be able to determine the cellular and subcellular levels of metabolites. Genetically-encoded fluorescence resonance energy transfer (FRET) sensors represent a promising technology for measuring metabolite levels and corresponding rate changes in live cells. Taking this, we developed a genetically encoded FRET (fluorescence resonance energy transfer) based nanosensor to analyse the sialic acid level in living cells. Sialic acid periplasmic binding protein (sia P) from Haemophilus influenzae was taken and ligated between the FRET pair, the cyan fluorescent protein (eCFP) and Venus. The chimeric sensor protein was expressed in E. coli BL21 (DE3) and purified by affinity chromatography. Conformational changes in the binding protein clearly confirmed the changes in FRET efficiency. So any change in the concentration of sialic acid is associated with the change in FRET ratio. This sensor is very specific to sialic acid and found stable with the different range of pH. This nanosensor successfully reported the intracellular level of sialic acid in bacterial cell. The data suggest that the nanosensors may be a versatile tool for studying the in vivo dynamics of sialic acid level non-invasively in living cells

Keywords: nanosensor, FRET, Haemophilus influenzae, metabolic networks

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Authors: Omojokun G. Aju, Adedayo O. Sule

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ZigBee wireless sensor and control network is one of the most popularly deployed wireless technologies in recent years. This is because ZigBee is an open standard lightweight, low-cost, low-speed, low-power protocol that allows true operability between systems. It is built on existing IEEE 802.15.4 protocol and therefore combines the IEEE 802.15.4 features and newly added features to meet required functionalities thereby finding applications in wide variety of wireless networked systems. ZigBee‘s current focus is on embedded applications of general-purpose, inexpensive, self-organising networks which requires low to medium data rates, high number of nodes and very low power consumption such as home/industrial automation, embedded sensing, medical data collection, smart lighting, safety and security sensor networks, and monitoring systems. Although the ZigBee design specification includes security features to protect data communication confidentiality and integrity, however, when simplicity and low-cost are the goals, security is normally traded-off. A lot of researches have been carried out on ZigBee technology in which emphasis has mainly been placed on ZigBee network performance characteristics such as energy efficiency, throughput, robustness, packet delay and delivery ratio in different scenarios and applications. This paper investigate and analyse the data accuracy, network implementation difficulties and security challenges of ZigBee network applications in star-based and mesh-based topologies with emphases on its home monitoring application using the ZigBee ProBee ZE-10 development boards for the network setup. The paper also expose some factors that need to be considered when designing ZigBee network applications and suggest ways in which ZigBee network can be designed to provide more resilient to network attacks.

Keywords: home monitoring, IEEE 802.14.5, topology, wireless security, wireless sensor network (WSN), ZigBee

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Authors: Anshu Siwach, Qianlai Zhuang, Ratul Baishya

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Context: This study focuses on the influence of moss cover and seasonality on soil microbial biomass and enzymatic activity in different Central Himalayan temperate forest types. Soil microbial biomass and enzymes are key indicators of microbial communities in soil and provide information on soil properties, microbial status, and organic matter dynamics. The activity of microorganisms in the soil varies depending on the vegetation type and environmental conditions. Therefore, this study aims to assess the effects of moss cover, seasons, and different forest types on soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN), and soil enzymatic activity in the Central Himalayas, Uttarakhand, India. Research Aim: The aim of this study is to evaluate the levels of SMBC, SMBN, and soil enzymatic activity in different temperate forest types under the influence of two ground covers (soil with and without moss cover) during the rainy and winter seasons. Question Addressed: This study addresses the following questions: 1. How does the presence of moss cover and seasonality affect soil microbial biomass and enzymatic activity? 2. What is the influence of different forest types on SMBC, SMBN, and enzymatic activity? Methodology: Soil samples were collected from different forest types during the rainy and winter seasons. The study utilizes the chloroform-fumigation extraction method to determine SMBC and SMBN. Standard methodologies are followed to measure enzymatic activities, including dehydrogenase, acid phosphatase, aryl sulfatase, β-glucosidase, phenol oxidase, and urease. Findings: The study reveals significant variations in SMBC, SMBN, and enzymatic activity under different ground covers, within the rainy and winter seasons, and among the forest types. Moss cover positively influences SMBC and enzymatic activity during the rainy season, while soil without moss cover shows higher values during the winter season. Quercus-dominated forests, as well as Cupressus torulosa forests, exhibit higher levels of SMBC and enzymatic activity, while Pinus roxburghii forests show lower levels. Theoretical Importance: The findings highlight the importance of considering mosses in forest management plans to improve soil microbial diversity, enzymatic activity, soil quality, and health. Additionally, this research contributes to understanding the role of lower plants, such as mosses, in influencing ecosystem dynamics. Conclusion: The study concludes that moss cover during the rainy season significantly influences soil microbial biomass and enzymatic activity. Quercus and Cupressus torulosa dominated forests demonstrate higher levels of SMBC and enzymatic activity, indicating the importance of these forest types in sustaining soil microbial diversity and soil health. Including mosses in forest management plans can improve soil quality and overall ecosystem dynamics.

Keywords: moss cover, seasons, soil enzymes, soil microbial biomass, temperate forest types

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Authors: Leizhang Wang, Baocang Wang

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General Sieve Kernel (G6K) is considered as currently the fastest algorithm for the shortest vector problem (SVP) and record holder of open SVP challenge. We study the lattice basis quality improvement effects of the Workout proposed in G6K, which is composed of a series of pumps to solve SVP. Firstly, we use a low-dimensional pump output basis to propose a predictor to predict the quality of high-dimensional Pumps output basis. Both theoretical analysis and experimental tests are performed to illustrate that it is more computationally expensive to solve the LWE problems by using a G6K default SVP solving strategy (Workout) than these lattice reduction algorithms (e.g. BKZ 2.0, Progressive BKZ, Pump, and Jump BKZ) with sieving as their SVP oracle. Secondly, the default Workout in G6K is optimized to achieve a stronger reduction and lower computational cost. Thirdly, we combine the optimized Workout and the Pump output basis quality predictor to further reduce the computational cost by optimizing LWE instances selection strategy. In fact, we can solve the TU LWE challenge (n = 65, q = 4225, = 0:005) 13.6 times faster than the G6K default Workout. Fourthly, we consider a combined two-stage (Preprocessing by BKZ- and a big Pump) LWE solving strategy. Both stages use dimension for free technology to give new theoretical security estimations of several LWE-based cryptographic schemes. The security estimations show that the securities of these schemes with the conservative Newhope’s core-SVP model are somewhat overestimated. In addition, in the case of LAC scheme, LWE instances selection strategy can be optimized to further improve the LWE-solving efficiency even by 15% and 57%. Finally, some experiments are implemented to examine the effects of our strategies on the Normal Form LWE problems, and the results demonstrate that the combined strategy is four times faster than that of Newhope.

Keywords: LWE, G6K, pump estimator, LWE instances selection strategy, dimension for free

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Authors: Rabin Paudel, Dambar Bahadur Mahato, Prabin Poudel, Bijaya Neupane, Sakar Jha

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Understanding Human-Elephant Conflict (HEC) is very important in countries like Nepal, where solutions to escalating conflicts are urgently required. However, most of the HEC mitigation measures implemented so far have been done on an ad hoc basis without the detailed understanding of nature and extent of the damage. This study aims to assess the current scenario of HEC in regards to crop and property damages by Wild Asian Elephant and people’s perception towards existing mitigating measures and elephant conservation in Buffer zone area of Bardia National Park. The methods used were a questionnaire survey (N= 178), key-informant interview (N= 18) and focal group discussions (N= 6). Descriptive statistics were used to determine the nature and extent of damage and to understand people’s perception towards HEC, its mitigation measures and elephant conservation. Chi-square test was applied to determine the significance of crop and property damages with respect to distance from the park boundary. Out of all types of damage, crop damage was found to be the highest (51%), followed by house damage (31%) and damage to stored grains (18%) with winter being the season with the greatest elephant damage. Among 178 respondents, the majority of them (82%) were positive towards elephant conservation despite the increment in HEC incidents as perceived by 88% of total respondents. Among the mitigation measures present, the most applied was electric fence (91%) followed by barbed wire fence (5%), reinforced concrete cement wall (3%) and gabion wall (1%). Most effective mitigation measures were reinforced concrete cement wall and gabion wall. To combat increasing crop damage, the insurance policy should be initiated. The efficiency of the mitigation measures should be timely monitored, and corrective measures should be applied as per the need.

Keywords: crop and property damage, elephant conflict, Asiatic wild elephant, mitigation measures

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Authors: Gozel Judakova, Markus Bause

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We present and analyze reliable numerical techniques for simulating complex flow and transport phenomena related to natural gas transportation in pipelines. Such kind of problems are of high interest in the field of petroleum and environmental engineering. Modeling and understanding natural gas flow and transformation processes during transportation is important for the sake of physical realism and the design and operation of pipeline systems. In our approach a two fluid flow model based on a system of coupled hyperbolic conservation laws is considered for describing natural gas flow undergoing hydratization. The accurate numerical approximation of two-phase gas flow remains subject of strong interest in the scientific community. Such hyperbolic problems are characterized by solutions with steep gradients or discontinuities, and their approximation by standard finite element techniques typically gives rise to spurious oscillations and numerical artefacts. Recently, stabilized and discontinuous Galerkin finite element techniques have attracted researchers’ interest. They are highly adapted to the hyperbolic nature of our two-phase flow model. In the presentation a streamline upwind Petrov-Galerkin approach and a discontinuous Galerkin finite element method for the numerical approximation of our flow model of two coupled systems of Euler equations are presented. Then the efficiency and reliability of stabilized continuous and discontinous finite element methods for the approximation is carefully analyzed and the potential of the either classes of numerical schemes is investigated. In particular, standard benchmark problems of two-phase flow like the shock tube problem are used for the comparative numerical study.

Keywords: discontinuous Galerkin method, Euler system, inviscid two-fluid model, streamline upwind Petrov-Galerkin method, twophase flow

Procedia PDF Downloads 329

Authors: Rukshika S Hewawasam, Sisira K. Weliwegamage, Sanath Rajapakse, Subramanium Sotheeswaran

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Bio fuel is one of the emerging industries around the world due to arise of crisis in petroleum fuel. Fermentation is a cost effective and eco-friendly process in production of bio-fuel. So inventions in microbes, substrates, technologies in fermentation cause new modifications in fermentation. One major problem in microbial ethanol fermentation is the low resistance of conventional microorganisms to the high ethanol concentrations, which ultimately lead to decrease in the efficiency of the process. In the present investigation, an ethanol resistant bacterium was isolated from sap of Saccharum officinarum (sugar cane). The optimal cultural conditions such as pH, temperature, incubation period, and microbiological characteristics, morphological characteristics, biochemical characteristics, ethanol tolerance, sugar tolerance, growth curve assay were investigated. Isolated microorganism was tolerated to 18% (V/V) of ethanol concentration in the medium and 40% (V/V) glucose concentration in the medium. Biochemical characteristics have revealed as Gram negative, non-motile, negative for Indole test ,Methyl Red test, Voges- Proskauer`s test, Citrate Utilization test, and Urease test. Positive results for Oxidase test was shown by isolated bacterium. Sucrose, Glucose, Fructose, Maltose, Dextrose, Arabinose, Raffinose, Lactose, and Sachcharose can be utilized by this particular bacterium. It is a significant feature in effective fermentation. The fermentation process was carried out in glucose medium under optimum conditions; pH 4, temperature 30˚C, and incubated for 72 hours. Maximum ethanol production was recorded as 12.0±0.6% (V/V). Methanol was not detected in the final product of the fermentation process. This bacterium is especially useful in bio-fuel production due to high ethanol tolerance of this microorganism; it can be used to enhance the fermentation process over conventional microorganisms. Investigations are currently conducted on establishing the identity of the bacterium

Keywords: bacterium, bio-fuel, ethanol tolerance, fermentation

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Authors: Layan Moussa, Darine Salam, Samir Mustapha

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Heavy metal contamination in agricultural soils in Lebanon poses serious environmental and health problems. Intensive efforts are employed to improve existing quantification methods of heavy metals in contaminated environments since conventional detection techniques have shown to be time-consuming, tedious, and costly. The implication of hyperspectral remote sensing in this field is possible and promising. However, factors impacting the efficiency of hyperspectral imaging in detecting and quantifying heavy metals in agricultural soils were not thoroughly studied. This study proposes to assess the use of hyperspectral imaging for the detection of Ni in agricultural clay soil collected from the Bekaa Valley, a major agricultural area in Lebanon, under different contamination levels and soil moisture content. Soil samples were contaminated with Ni, with concentrations ranging from 150 mg/kg to 4000 mg/kg. On the other hand, soil with background contamination was subjected to increased moisture levels varying from 5 to 75%. Hyperspectral imaging was used to detect and quantify Ni contamination in the soil at different contamination levels and moisture content. IBM SPSS statistical software was used to develop models that predict the concentration of Ni and moisture content in agricultural soil. The models were constructed using linear regression algorithms. The spectral curves obtained reflected an inverse correlation between both Ni concentration and moisture content with respect to reflectance. On the other hand, the models developed resulted in high values of predicted R2 of 0.763 for Ni concentration and 0.854 for moisture content. Those predictions stated that Ni presence was well expressed near 2200 nm and that of moisture was at 1900 nm. The results from this study would allow us to define the potential of using the hyperspectral imaging (HSI) technique as a reliable and cost-effective alternative for heavy metal pollution detection in contaminated soils and soil moisture prediction.

Keywords: heavy metals, hyperspectral imaging, moisture content, soil contamination

Procedia PDF Downloads 101

Authors: Som Pal Baliyan

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The purpose of this quantitative study was to analyze farm management skills in broiler poultryproducers in Botswana. The study adopted a descriptive and correlation research design. The population of the study was the poultry farm operators who had been in broiler poultry farming at least for two years. Based on the information from literature, a questionnaire was constructed for data collection on seven areas of farm management skills namely; planning skills, accounting and financial management skills, production management skills, product procurement and marketing skills, decision making skills, risk management skills, and specific technical skills. The validity and reliability of the questionnaire were accomplished by a panel of experts and by calculating the Cronbach’s alpha coefficient, respectively. Data were collected through a survey of 60 randomly sampled poultry farm operators in Botswana. Data were analyzed through descriptive statistical tools whereby the level of farm management skills were determined by calculating means and standard deviations of the management skills among the broiler producers. The level of farm management skills in broilers producers was discussed. All the seven farm management skills were ranked based on their calculated means. The specific technical skills and risk management skills were the highest and the lowest ranked farm management skills, respectively.Findings revealed that the broiler producers had skills above the average level only in specific technical skills whereas the skill levels in the remaining six farm management skills under study were found below the average level. This prevailing low level of farm management skills can be justified asthe cause of failure or poor performance of the broiler poultry farms in Botswana. Therefore, in order to improve the efficiency and productivityin broiler production in the country, it was recommended that the broiler poultry producers should be adequately trained in areas of planning skills, financial management skills, production management skills, product procurement and marketing skills, decision making skills and risk management skills.

Keywords: poultry production, broiler production, management skills, levels of skills

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Authors: Ubaid Ur Rahman, Waqar Younas, Sooraj Kumar Chhabira

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Environmentally sustainable building construction has experienced significant growth during the past 10 years at international level. This paper shows that the conceptual framework adopts sustainability techniques in construction to develop environment friendly building called green building. Waste occurs during the different construction phases which causes the environmental problems like, deposition of waste on ground surface creates major problems such as bad smell. It also gives birth to different health diseases and produces toxic waste agent which is specifically responsible for making soil infertile. Old recycled building material is used in the construction of new building. Sustainable construction is economical and saves energy sources. Sustainable construction is the major responsibility of designer and project manager. The designer has to fulfil the client demands while keeping the design environment friendly. Project manager has to deliver and execute sustainable construction according to sustainable design. Steel is the most appropriate sustainable construction material. It is more durable and easily recyclable. Steel occupies less area and has more tensile and compressive strength than concrete, making it a better option for sustainable construction as compared to other building materials. New technology like green roof has made the environment pleasant, and has reduced the construction cost. It minimizes economic, social and environmental issues. This paper presents an overview of research related to the material use of green building and by using this research recommendation are made which can be followed in the construction industry. In this paper, we go through detailed analysis on construction material. By making suitable adjustments to project management practices it is shown that a green building improves the cost efficiency of the project, makes it environmental friendly and also meets future generation demands.

Keywords: sustainable construction, green building, recycled waste material, environment

Procedia PDF Downloads 245

Authors: Fangyuan Shao, Wei Liu, Deli Gao

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Polycrystalline diamond compact (PDC) bits have occupied a large market of unconventional oil and gas drilling. The application of PDC bits benefits from the efficient rock breaking of PDC cutters. In response to increasingly complex formations, many shaped cutters have been invited, but many of them have not been solved by the mechanism of rock breaking. In this paper, two kinds of PDC cutters: a new axe-shaped (NAS) cutter and cylindrical cutter (benchmark) were studied by laboratory experiments. NAS cutter is obtained by optimizing two sides of axe-shaped cutter with curved surfaces. All the cutters were put on a vertical turret lathe (VTL) in the laboratory for cutting tests. According to the cutting distance, the VTL tests can be divided into two modes: single-turn rotary cutting and continuous cutting. The cutting depth of cutting (DOC) was set at 1.0 mm and 2.0 mm in the former mode. The later mode includes a dry VTL test for thermal stability and a wet VTL test for wear resistance. Load cell and 3D optical profiler were used to obtain the value of cutting forces and wear area, respectively. Based on the findings of the single-turn rotary cutting VTL tests, the performance of A NAS cutter was better than the benchmark cutter on elastoplastic material cutting. The cutting forces (normal forces, tangential force, and radial force) and special mechanical energy (MSE) of a NAS cutter were lower than that of the benchmark cutter under the same condition. It meant that a NAS cutter was more efficient on elastoplastic material breaking. However, the wear resistance of a new axe-shaped cutter was higher than that of a benchmark cutter. The results of the dry VTL test showed that the thermal stability of a NAS cutter was higher than that of a benchmark cutter. The cutting efficiency can be improved by optimizing the geometric structure of the PDC cutter. The change of thermal stability may be caused by the decrease of the contact area between cutter and rock at given DOC. The conclusions of this paper can be used as an important reference for PDC cutters designers.

Keywords: axe-shaped cutter, PDC cutter, rotary cutting test, vertical turret lathe

Procedia PDF Downloads 204

Authors: Shirin Ghatrehsamani

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Higher efficiency and lower environmental impact are the consequence of using advanced technology in farming. They also help to decrease yield variability by diminishing weather variability impact, optimizing nutrient and pest management as well as reducing competition from weeds. A better understanding of the pros and cons of applying technology and finding the main reason for preventing the utilization of the technology has a significant impact on developing technology adoption among farmers and producers in the digital agriculture era. The results from two surveys carried out in 2019 and 2021 were used to investigate whether the crop types had an impact on the willingness to utilize technology on the farms. The main focus of the questionnaire was on utilizing precision agriculture (PA) technologies among farmers in some parts of the united states. Collected data was analyzed to determine the practical application of various technologies. The survey results showed more similarities in the main reason not to use PA between the two crop types, but the present application of using technology in specialty crops is generally five times larger than in row crops. GPS receiver applications were reported similar for both types of crops. Lack of knowledge and high cost of data handling were cited as the main problems. The most significant difference was among using variable rate technology, which was 43% for specialty crops while was reported 0% for row crops. Pest scouting and mapping were commonly used for specialty crops, while they were rarely applied for row crops. Survey respondents found yield mapping, soil sampling map, and irrigation scheduling were more valuable for specialty crops than row crops in management decisions. About 50% of the respondents would like to share the PA data in both types of crops. Almost 50 % of respondents got their PA information from retailers in both categories, and as the second source, using extension agents were more common in specialty crops than row crops.

Keywords: precision agriculture, smart farming, digital agriculture, technology adoption

Procedia PDF Downloads 114

Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Amr Sultan, Sara Elgazzar, Breksal Elmiligy

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The airline industry nowadays is becoming a more growing industry facing a severe competition. It is an influential issue in this context to utilize revenue management (RM) concept and practice in order to develop the pricing strategy. There is an unfathomable necessity for RM to assist the airlines and their associates to disparage the cost and recuperate their revenue, which in turn will boost the airline industry performance. The complexity of RM imposes enormous challenges on the airline industry. Several studies have been proposed on the RM adaptation in airlines industry while there is a limited availability of implementing RM and its complexity in the developing countries such as Egypt. This research represents a research schema about the implementation of the RM to the Egyptian airline industry. The research aims at investigating and demonstrating the complexities face implementing RM in the airline industry, up on which the research provides a comprehensive understanding of how to overcome these complexities while adapting RM in the Egyptian airline industry. An empirical study was conducted on the Egyptian airline sector based on a sample of four airlines (Egyptair, Britishair, KLM, and Lufthansa). The empirical study was conducted using a mix of qualitative and quantitative approaches. First, in-depth interviews were carried out to analyze the Egyptian airline sector status and the main challenges faced by the airlines. Then, a structured survey on the three different parties of airline industry; airlines, airfreight forwarders, and passengers were conducted in order to investigate the main complexity factors from different parties' points of view. Finally, a focus group was conducted to develop a best practice framework to overcome the complexities faced the RM adaptation in the Egyptian airline industry. The research provides an original contribution to knowledge by creating a framework to overcome the complexities and challenges in adapting RM in the airline industry generally and the Egyptian airline industry particularly. The framework can be used as a RM tool to increase the effectiveness and efficiency of the Egyptian airline industry performance.

Keywords: revenue management, airline industry, revenue management complexity, Egyptian airline industry

Procedia PDF Downloads 403