Search results for: super efficiency

Authors: Z. B. Ibrahim, N. Ismail, K. I. Othman

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Fuzzy Differential Equations (FDEs) play an important role in modelling many real life phenomena. The FDEs are used to model the behaviour of the problems that are subjected to uncertainty, vague or imprecise information that constantly arise in mathematical models in various branches of science and engineering. These uncertainties have to be taken into account in order to obtain a more realistic model and many of these models are often difficult and sometimes impossible to obtain the analytic solutions. Thus, many authors have attempted to extend or modified the existing numerical methods developed for solving Ordinary Differential Equations (ODEs) into fuzzy version in order to suit for solving the FDEs. Therefore, in this paper, we proposed the development of a fuzzy version of three-point block method based on Block Backward Differentiation Formulas (FBBDF) for the numerical solution of first order FDEs. The three-point block FBBDF method are implemented in uniform step size produces three new approximations simultaneously at each integration step using the same back values. Newton iteration of the FBBDF is formulated and the implementation is based on the predictor and corrector formulas in the PECE mode. For greater efficiency of the block method, the coefficients of the FBBDF are stored at the start of the program. The proposed FBBDF is validated through numerical results on some standard problems found in the literature and comparisons are made with the existing fuzzy version of the Modified Simpson and Euler methods in terms of the accuracy of the approximated solutions. The numerical results show that the FBBDF method performs better in terms of accuracy when compared to the Euler method when solving the FDEs.

Keywords: block, backward differentiation formulas, first order, fuzzy differential equations

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Authors: Hamed K. Esfahani, Bithin Datta

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Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

Procedia PDF Downloads 240

Authors: Alafara A. Baba, Kuranga I. Ayinla, Folahan A. Adekola, Rafiu B. Bale

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Due to increasing demands and diverse applications of copper oxide as pigment in ceramics, cuprammonium hydroxide solution for rayon, p-type semi-conductor, dry cell batteries production and as safety disposal of hazardous materials, a study on the hydrometallurgical operations involving leaching, solvent extraction and precipitation for the recovery of copper for producing high grade copper oxide from a Nigerian chalcopyrite ore in chloride media has been examined. At a particular set of experimental parameter with respect to acid concentration, reaction temperature and particle size, the leaching investigation showed that the ore dissolution increases with increasing acid concentration, temperature and decreasing particle diameter at a moderate stirring. The kinetics data has been analyzed and was found to follow diffusion control mechanism. At optimal conditions, the extent of ore dissolution reached 94.3%. The recovery of the total copper from the hydrochloric acid-leached chalcopyrite ore was undertaken by solvent extraction and precipitation techniques, prior to the beneficiation of the purified solution as copper oxide. The purification of the leach liquor was firstly done by precipitation of total iron and manganese using Ca(OH)2 and H2O2 as oxidizer at pH 3.5 and 4.25, respectively. An extraction efficiency of 97.3% total copper was obtained by 0.2 mol/L Dithizone in kerosene at 25±2ºC within 40 minutes, from which ≈98% Cu from loaded organic phase was successfully stripped by 0.1 mol/L HCl solution. The beneficiation of the recovered pure copper solution was carried out by crystallization through alkali addition followed by calcination at 600ºC to obtain high grade copper oxide (Tenorite, CuO: 05-0661). Finally, a simple hydrometallurgical scheme for the operational extraction procedure amenable for industrial utilization and economic sustainability was provided.

Keywords: chalcopyrite ore, Nigeria, copper, copper oxide, solvent extraction

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Authors: Kateryna Zharan, Jan C. Bongaerts

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In recent years, economic attractiveness of renewable energy (RE) for the mining industry, especially for off-grid mines, and a negative environmental impact of fossil energy are stimulating to use RE for mining needs. Being that remote area mines have higher energy expenses than mines connected to a grid, integration of RE may give a mine economic benefits. Regarding the literature review, there is a lack of business models for adopting of RE at mine. The main aim of this paper is to develop an optimized model of RE integration into the German mining industry (GMI). Hereby, the GMI with amount of around 800 mill. t. annually extracted resources is included in the list of the 15 major mining country in the world. Accordingly, the mining potential of Germany is evaluated in this paper as a perspective market for RE implementation. The GMI has been classified in order to find out the location of resources, quantity and types of the mines, amount of extracted resources, and access of the mines to the energy resources. Additionally, weather conditions have been analyzed in order to figure out where wind and solar generation technologies can be integrated into a mine with the highest efficiency. Despite the fact that the electricity demand of the GMI is almost completely covered by a grid connection, the hybrid energy system (HES) based on a mix of RE and fossil energy is developed due to show environmental and economic benefits. The HES for the GMI consolidates a combination of wind turbine, solar PV, battery and diesel generation. The model has been calculated using the HOMER software. Furthermore, the demonstrated HES contains a forecasting model that predicts solar and wind generation in advance. The main result from the HES such as CO2 emission reduction is estimated in order to make the mining processing more environmental friendly.

Keywords: diesel generation, German mining industry, hybrid energy system, hybrid optimization model for electric renewables, optimized model, renewable energy

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Authors: Muhammad Iqbal, Hafiz Muhammad Tauqeer, Hamza Rafaqat, Muhammad Naveed, Muhammad Awais Irshad

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Soil pollution with chromium (Cr) has become one of the most important concerns due to its toxicity for humans. To date, various remediation approaches have been employed for the remediation and management of Cr contaminated soils. Phytoextraction is an eco-friendly and emerging remediation approach which has gained attention due to several advantages over conventional remediation approach. The use of energy crops for phytoremediation is an emerging trend worldwide. These energy crops have high tolerance against various environmental stresses, the potential to grow in diverse ecosystems and high biomass production make them a suitable candidate for phytoremediation of contaminated soils. The removal efficiency of plants in phytoextraction depends upon several soil and plant factors including solubility, bioavailability and metal speciation in soils. A pot scale experiment was conducted to evaluate the phytoextraction potential of Arundo donax L. with the application of acetic acid (A.A) in Cr contaminated soils. Plants were grown in pots filled with 5 kg soils for 90 days. After 30 days plants acclimatization in pot conditions, plants were treated with various levels of Cr (2.5 mM, 5 mM, 7.5 mM, 10 mM) and A.A (Cr 2.5 mM + A.A 2.5 mM, Cr 5 mM + A.A 2.5 mM, Cr 7.5 mM + A.A 2.5 mM, Cr 10 mM + A.A 2.5 mM). The application of A.A significantly increased metal uptake and in roots and shoots of A. donax. This increase was observed at Cr 7.5 mM + A.A 2.5 mM but at high concentrations, visual symptoms of Cr toxicity were observed on leaves. Similarly, A.A applications also affect the activities of key enzymes including catalase (CAT), superoxidase dismutase (SOD), and ascorbate peroxidase (APX) in leaves of A. donax. Based on results it is concluded that the applications of A.A acid for phytoextraction is an alternative approach for the management of Cr affected soils and synthetic chelators should be replaced with organic acids.

Keywords: acetic acid, A. donax, chromium, energy crop, phytoextraction

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Authors: Long Long Chen, Xinwei Liao, Shanfa Tang, Shaojing Jiang, Ruijia Tang, Rui Wang, Shu Yun Feng, Si Yao Wang

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Tight oil reservoirs have poor physical properties, insufficient formation energy, and low natural productivity; it is necessary to effectively improve their crude oil recovery. CO₂ flooding is an important technical means to enhance oil recovery and achieve effective CO₂ storage in tight oil reservoirs, but its heterogeneity is strong, which makes CO₂ flooding prone to gas channeling and poor recovery. Aiming at the problem of gas injection channeling, combined with the excellent performance of low interfacial tension viscoelastic fluid (GOBTK), the research on CO₂-low interfacial tension viscoelastic fluid synergistic oil displacement in tight reservoirs was carried out, and the synergy of CO₂ and low interfacial tension viscoelastic fluid was discussed. Oil displacement mechanism. Experiments show that GOBTK has good injectability in tight oil reservoirs (Kg=0.141～0.793mD); CO₂-0.4% GOBTK synergistic flooding can improve the recovery factor of low permeability layers (31.41%) under heterogeneous (gradient difference of 10) conditions the) effect is better than that of CO₂ flooding (0.56%) and 0.4% GOBT-water flooding (20.99%); CO₂-GOBT synergistic oil displacement mechanism includes: 1) The formation of CO₂ foam increases the flow resistance of viscoelastic fluid, forcing the displacement fluid to flow 2) GOBTK can emulsify and disperse residual oil into small oil droplets, and smoothly pass through narrow pores to produce; 3) CO₂ dissolved in GOBTK synergistically enhances the water wettability of the core, and the use of viscosity Elastomeric fluid injection and stripping of residual oil; 4) CO₂-GOBTK synergy superimposes multiple mechanisms, effectively improving the swept volume and oil washing efficiency of the injected fluid to the reservoir.

Keywords: tight oil reservoir, CO₂ flooding, low interfacial tension viscoelastic fluid flooding, synergistic oil displacement, EOR mechanism

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Authors: Sujata Gupta Kedar, J. N. Tulika

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Early researchers suggested that imprisonment had negative psychological and physical effects on its inmates, leading to psychological deterioration. The term “prisons” in the Consensus Statement of WHO is intended to denote, as those institutions which hold people who have been sentenced to a period of imprisonment by the courts for offences against the law. Thus “prisons” if local circumstances justify it, may also be taken to include secure institutions holding on a compulsory basis on any of the following categories of people: remand prisoners; civil prisoners; juvenile detainees; immigration detainees; some categories of mentally disordered patients; asylum seekers; refugees; people detained pending expulsion, deportation, exile, exclusion or any other form of compulsory transfer to other countries or areas of the country; people detained in police cells; and any other compulsorily detained group. Prisons are aimed to cure the criminal and their behavior but their records are not encouraging. Instead the imprisonment affects all prisoners in different way. From withstanding the shock of entry to the new culture, which is very different from their own, prisoners must try to determine how to spend the time in prison, since the hours appears to be endless in prisons. There is also the fear of deterioration. This article aims to provide an overview of the psychological well being of female prisoners in the prison environment in five areas- satisfaction, efficiency, sociability, mental health and interpersonal relations. Research was done on two different types of imprisonment- under trial prisoner and convict. Total sample included 22 female prisoners of Nagaon Special Jail of Assam. The instrument used for the study was based on Psychological Well Being Scale. Statistical analysis was done with t-test and one way anova test. The result demonstrated that there is no significant difference in the psychological wellbeing of female prisoners in the prison and that there is no significant difference in the psychological well being of different types of female prisoners involved in different crimes but there is significant difference in the mental health of the female prisoners in prison.

Keywords: psychological effect, female prisoners, prison, well being of prisoners

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Authors: Gabriel Woldu, Maria Sassi

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Coffee performs a pivotal role in Ethiopia's GDP, revenue, employment, domestic demand, and export earnings. Ethiopia's coffee production and exports show high variability in the amount of production and export earnings. Despite being the continent's fifth-largest coffee producer, Ethiopia has not developed its ability to shine as a major exporter in the globe's green coffee exports. Ethiopian coffee exports were not stable and had high volume and earnings fluctuations. The main aim of this study was to analyze the dynamics of the export of coffee variation to different importing nations using a first-order Markov Chain model. 14 years of time-series data has been used to examine the direction and structural change in the export of coffee. A compound annual growth rate (CAGR) was used to determine the annual growth rate in the coffee export quantity, value, and per-unit price over the study period. The major export markets for Ethiopian coffee were Germany, Japan, and the USA, which were more stable, while countries such as France, Italy, Belgium, and Saudi Arabia were less stable and had low retention rates for Ethiopian coffee. The study, therefore, recommends that Ethiopia should again revitalize its market to France, Italy, Belgium, and Saudi Arabia, as these countries are the major coffee-consuming countries in the world to boost its export stake to the global coffee markets in the future. In order to further enhance export stability, the Ethiopian Government and other stakeholders in the coffee sector should have to work on reducing the volatility of coffee output and exports in order to improve production and quality efficiency, so that stabilize markets as well as to make the product attractive and price competitive in the importing countries.

Keywords: coffee, CAGR, Markov chain, direction of trade, Ethiopia

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Authors: Amin Nazifi, Amir Raki, Doga Istanbulluoglu

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The incorporation of technological advancements into financial services, commonly referred to as Fintech, is primarily aimed at promoting services that are accessible, convenient, and inclusive, thereby benefiting both consumers and businesses. Fintech services employ a variety of technologies, including Artificial Intelligence (AI), blockchain, and big data, to enhance the efficiency and productivity of traditional services. Cryptocurrency, a component of Fintech, is projected to be a trillion-dollar industry, with over 320 million consumers globally investing in various forms of cryptocurrencies. However, these potentially transformative services can also lead to adverse outcomes. For instance, recent Fintech innovations have been increasingly linked to misconduct and disservice, resulting in serious implications for consumer well-being. This could be attributed to the ease of access to Fintech, which enables adults to trade cryptocurrencies, shares, and stocks via mobile applications. However, there is little known about the darker aspects of technological advancements, such as Fintech. Hence, this study aims to generate scholarly insights into the design of robust and resilient Fintech services that can add value to businesses and enhance consumer well-being. Using a mixed-method approach, the study will investigate the personal and contextual factors influencing consumers’ adoption and usage of technology innovations and their impacts on consumer well-being. First, semi-structured interviews will be conducted with a sample of Fintech users until theoretical saturation is achieved. Subsequently, based on the findings of the first study, a quantitative study will be conducted to develop and empirically test the impacts of these factors on consumers’ well-being using an online survey with a sample of 300 participants experienced in using Fintech services. This study will contribute to the growing Transformative Service Research (TSR) literature by addressing the latest priorities in service research and shedding light on the impact of fintech services on consumer well-being.

Keywords: consumer well-being, financial literacy, Fintech, service innovation

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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: 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: Nadima Dwihusna, Ge Jin, Ali Tura, Narhari Srinivasa Rao, Abdullah E. Al-Otaibi, Shamima Akther

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This research provides valuable insights into applying different types of machine learning for the geologic interpretation of the Raudhatain Field, Kuwait. Facies recognition utilizing machine learning has high potential in reducing uncertainties of reservoir characterization. ML-based algorithm enables automation of interpretation techniques in large portions of data which reduces the seismic and well log interpretation workflows cycle time. Facies classifications through predictive learning were obtained from two case studies: 1) semi-supervised learning to unlabeled well logs and 2) unsupervised learning to unlabeled post-stack seismic data in Raudhatain Field, Kuwait. The first case demonstrates that K-means semi-supervised learning reduces cycle time for facies classification in well logs. Combining petrophysics-based domain knowledge with machine learning increases efficiency in facies classification. In the second case, Self-Organizing Maps (SOM) prove to be a good tool for seismic interpretation. This paper demonstrates the usefulness of leveraging machine learning in the interpretation of facies in Raudhatain Field, Kuwait. SOM is a practical way to identify natural clusters in multi-attribute seismic data. As a lesson learned, the ability to determine a good seismic data set is a deciding factor for a successful SOM analysis and for developing meaningful neural classes. In the end, this K-Means and SOM data-driven approach allows for automation of facies classification in large amount of unlabeled well logs and seismic data, reduces human biased, and permits new possible findings of clusters and characteristics hidden in the data which is essential for reservoir characterization.

Keywords: machine learning, facies, reservoir characterization, petrophysics

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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: 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

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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 61