Search results for: external energy sources

Authors: Hosam A. Shawky, Amr A. Abdel Fatah, Moustafa M. S. Abo ElFad, Abdel Hameed M. El-Aassar

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Water desalination projects based on reverse osmosis technology are being introduced in Egypt to combat drinking water shortage in remote areas. Reverse osmosis (RO) desalination is a pressure driven process. This paper focuses on the design of an integrated brackish water and seawater RO desalination and solar Photovoltaic (PV) technology. A small Mobile PV driven RO desalination plant prototype without batteries is designed and tested. Solar-driven reverse osmosis desalination can potentially break the dependence of conventional desalination on fossil fuels, reduce operational costs, and improve environmental sustainability. Moreover, the innovative features incorporated in the newly designed PV-RO plant prototype are focusing on improving the cost effectiveness of producing drinkable water in remote areas. This is achieved by maximizing energy yield through an integrated automatic single axis PV tracking system with programmed tilting angle adjustment. An autonomous cleaning system for PV modules is adopted for maximizing energy generation efficiency. RO plant components are selected so as to produce 4-5 m3/day of potable water. A basic criterion in the design of this PV-RO prototype is to produce a minimum amount of fresh water by running the plant during peak sun hours. Mobility of the system will provide potable water to isolated villages and population as well as ability to provide good drinking water to different number of people from any source that is not drinkable.

Keywords: design, reverse osmosis, photovoltaic, energy, desalination, Egypt

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Authors: Andi Mursidi

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This study aims to investigate why the internal quality assurance system as the basis for the assessment of external quality assurance systems is not well developed at universities in Indonesia. To answer this problem, technical analysis used single instrumental case study with the respondents from ten universities. The findings of this study are the internal quality assurance system that is applied so far (1) only to gain accreditation; and (2) considered as a liability rather than as a necessity to meet the demands of quality standards. It needs strong commitment from internal stakeholders at the college/university to establish internal quality assurance systems that exceed the national standards of higher education. A high quality college/ university will have a good accreditation rank.

Keywords: internal stakeholders, internal quality assurance system, commitment, higher education

Procedia PDF Downloads 270

Authors: Farnaz Fotovvatikhah, Javad Akbari

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Test time of a test architecture is an important factor which depends on the architecture's delay and test patterns. Here a new architecture to store the test results based on network on chip is presented. In addition, simple analytical model is proposed to calculate link test time for built in self-tester (BIST) and external tester (Ext) in multiprocessor systems. The results extracted from the model are verified using FPGA implementation and experimental measurements. Systems consisting 16, 25, and 36 processors are implemented and simulated and test time is calculated. In addition, BIST and Ext are compared in terms of test time at different conditions such as at different number of test patterns and nodes. Using the model the maximum frequency of testing could be calculated and the test structure could be optimized for high speed testing.

Keywords: test, nano on-chip network, JTAG, modelling

Procedia PDF Downloads 468

Authors: Kimberly Samaha

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The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding biomass as a feedstock for power plants. Yet the lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. This study analyzed data and submittals to the Born Global Maine Innovation Challenge. The Innovation Challenge was a global innovation challenge to identify process innovations that could address a ‘whole-tree’ approach of maximizing the products, byproducts, energy value and process slip-streams into a circular zero-waste design. Participating companies were at various stages of developing bioproducts and included biofuels, lignin-based products, carbon capture platforms and biochar used as both a filtration medium and as a soil amendment product. This case study shows the QCA (Qualitative Comparative Analysis) methodology of the prequalification process and the resulting techno-economic model that was developed for the maximizing profitability of the Bio-Hub Ecosystem through continuous expansion of system waste streams into valuable process inputs for co-hosts. A full site plan for the integration of co-hosts (biorefinery, land-based shrimp and salmon aquaculture farms, a tomato green-house and a hops farm) at an operating forestry-based biomass to energy plant in West Enfield, Maine USA. This model and process for evaluating the profitability not only proposes models for integration of forestry, aquaculture and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. In this particular study, profitability is assessed at two levels CAPEX (Capital Expenditures) and in OPEX (Operating Expenditures). Given that these projects start with repurposing facilities where the industrial level infrastructure is already built, permitted and interconnected to the grid, the addition of co-hosts first realizes a dramatic reduction in permitting, development times and costs. In addition, using the biomass energy plant’s waste streams such as heat, hot water, CO₂ and fly ash as valuable inputs to their operations and a significant decrease in the OPEX costs, increasing overall profitability to each of the co-hosts bottom line. This case study utilizes a proprietary techno-economic model to demonstrate how utilizing waste streams of a biomass energy plant and/or biorefinery, results in significant reduction in OPEX for both the biomass plants and the agriculture and aquaculture co-hosts. Economically viable Bio-Hubs with favorable environmental and community impacts may prove critical in garnering local and federal government support for pilot programs and more wide-scale adoption, especially for those living in severely economically depressed rural areas where aging industrial sites have been shuttered and local economies devastated.

Keywords: bio-economy, biomass energy, financing, zero-waste

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Authors: Young Nam Chun, Mun Sup Lim, Byeo Ri Jeong

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Sewage sludge is regarded as the residue produced by the waste water treatment process, during which liquids and solids are being separated. Thermal treatments are interesting techniques to stabilize the sewage sludge for disposal. Among the thermal treatments, pyrolysis and/or gasification has been being applied to the sewage sludge. The final goal of our NRF research is to develop a microwave In-line Drying-Pyrolysis-Gasification (IDPG) technology for the dewatered sewage sludge for the bio-waste to energy conversion. As a first step, the pyrolysis characteristics in a bench scale electric furnace was investigated at 800℃ for the dewatered sludge and dried sludge samples of which moisture contents are almost 80% and 0%, respectively. Main components of producer gas are hydrogen and carbon dioxide. Particularly, higher hydrogen for the dewatered sludge is shown as 75%. The hydrogen production for the dewatered sludge and dried sludge are 56% and 32%, respectively. However, the pyrolysis for the dried sludge produces higher carbon dioxide and other gases, while higher methane and carbon dioxide are given to 74% and 53%, respectively. Tar also generates during the pyrolysis process, showing lower value for case of the dewatered sludge. Gravimetric tar is 195 g/m3, and selected light tar like benzene, naphthalene, anthracene, pyrene are 9.4 g/m3, 2.1 g/m3, 0.5 g/m3, 0.3 g/m3, respectively. After the pyrolysis process, residual char for the dewatered sludge and dried sludge remain 1g and 1.3g, showing weight reduction rate of 93% and 57%, respectively. Through the results, this could be known that the dewatered sludge can be used to produce a clean hydrogen-rich gas fuel without the drying process. Therefore, the IDPG technology can be applied effectively to the energy conversion for dewater sludge waste without a drying pretreatment. Acknowledgment: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (No. 2015R1A2A2A03003044).

Keywords: pyrolysis, gasification, sewage sludge, tar generation, producer gas, sludge char, biomass energy

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Authors: Melek Akay

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Turkey's agricultural commodity prices are prone to fluctuation but have gradually over time. A considerable amount of literature examines the changes in these prices by dealing with other commodities such as energy. Links between agricultural and energy markets have therefore been extensively investigated. Since red meat prices are becoming increasingly volatile in Turkey, this paper analyses the price volatility of veal, lamb and the relationship between red meat and crude oil, exchange rates by applying the generalize all period unconstraint volatility model, which generalises the GARCH (p, q) model for analysing weekly data covering a period of May 2006 to February 2017. Empirical results show that veal and lamb prices present volatility during the last decade, but particularly between 2009 and 2012. Moreover, oil prices have a significant effect on veal and lamb prices as well as their previous periods. Consequently, our research can lead policy makers to evaluate policy implementation in the appropriate way and reduce the impacts of oil prices by supporting producers.

Keywords: red meat price, volatility, crude oil, exchange rates, GARCH models, Turkey

Procedia PDF Downloads 113

Authors: Anna Suvorova

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Classical motivation theories hold that there are two kinds of motivation, intrinsic and extrinsic. Leaders are looking for effective motivation techniques, but frequently external influences do not work or, even worse, reduce team productivity. We see only the tip of the iceberg -human behavior. However, beneath the surface of the water are factors that directly affect our behavior -desires. Believing that employees need to be motivated, companies design a motivation system based on the principle: do it and get a reward. As a matter of fact, we all have basic desires. Everybody is motivated but to different extents. Following the principle "intrinsic motivation over extrinsic rewards", we need to create an environment that will support intrinsic motivation and potential of employees, and team, rather than individual work.

Keywords: motivation profile, motivation techniques, agile HR, basic desires, agile people, human behavior, people management

Procedia PDF Downloads 95

Authors: Kei Kamada, Rikito Murakami, Masahiko Ito, Mototaka Arakawa, Yasuhiro Shoji, Toshiyuki Ueno, Masao Yoshino, Akihiro Yamaji, Shunsuke Kurosawa, Yuui Yokota, Yuji Ohashi, Akira Yoshikawa

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Techniques of energy harvesting y have been widely developed in recent years, due to high demand on the power supply for ‘Internet of things’ devices such as wireless sensor nodes. In these applications, conversion technique of mechanical vibration energy into electrical energy using magnetostrictive materials n have been brought to attention. Among the magnetostrictive materials, Fe-Ga and Fe-Al alloys are attractive materials due to the figure of merits such price, mechanical strength, high magnetostrictive constant. Up to now, bulk crystals of these alloys are produced by the Bridgman–Stockbarger method or the Czochralski method. Using these method big bulk crystal up to 2~3 inch diameter can be grown. However, non-uniformity of chemical composition along to the crystal growth direction cannot be avoid, which results in non-uniformity of magnetostriction constant and reduction of the production yield. The micro-pulling down (μ-PD) method has been developed as a shaped crystal growth technique. Our group have reported shaped crystal growth of oxide, fluoride single crystals with different shape such rod, plate tube, thin fiber, etc. Advantages of this method is low segregation due to high growth rate and small diffusion of melt at the solid-liquid interface, and small kerf loss due to near net shape crystal. In this presentation, we report the shaped long plate crystal growth of Fe-Ga and Fe-Al alloys using the μ-PD method. Alloy crystals were grown by the μ-PD method using calcium oxide crucible and induction heating system under the nitrogen atmosphere. The bottom hole of crucibles was 5 x 1mm² size. A <100> oriented iron-based alloy was used as a seed crystal. 5 x 1 x 320 mm³ alloy crystal plates were successfully grown. The results of crystal growth, chemical composition analysis, magnetostrictive properties and a prototype vibration energy harvester are reported. Furthermore, continuous crystal growth using powder supply system will be reported to minimize the chemical composition non-uniformity along the growth direction.

Keywords: crystal growth, micro-pulling-down method, Fe-Ga, Fe-Al

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Authors: Seyed Sadegh Naseralavi

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This paper presents a Kernel parallelization equation for damage identification in structures under unknown periodic excitations. Herein, the dynamic differential equation of the motion of structure is viewed as a mapping from displacements to external forces. Utilizing this viewpoint, a new method for damage detection in structures under periodic loads is presented. The developed method requires only two periods of load. The method detects the damages without finding the input loads. The method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering the concept, kernel parallelization equation (KPE) is derived for damage detection under unknown periodic loads. The method is verified for a case study under periodic loads.

Keywords: Kernel, unknown periodic load, damage detection, Kernel parallelization equation

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Authors: Yohannes Haile, Dipo Onipede, Jr., Omar Ashour

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The main thrust of our research is to determine Industry 4.0 readiness of small and mid-size manufacturing companies in our region and assist them to implement Cyber Physical Production System (CPPS) capabilities. Adopting CPPS capabilities will help organizations realize improved quality, order delivery, throughput, new value creation, and reduced idle time of machines and work centers of their manufacturing operations. The key metrics for the assessment include the level of intelligence, internal and external connections, responsiveness to internal and external environmental changes, capabilities for customization of products with reference to cost, level of additive manufacturing, automation, and robotics integration, and capabilities to manufacture hybrid products in the near term, where near term is defined as 0 to 18 months. In our initial evaluation of several manufacturing firms which are profitable and successful in what they do, we found low level of Physical-Digital-Physical (PDP) loop in their manufacturing operations, whereas 100% of the firms included in this research have specialized manufacturing core competencies that have differentiated them from their competitors. The level of automation and robotics integration is low to medium range, where low is defined as less than 30%, and medium is defined as 30 to 70% of manufacturing operation to include automation and robotics. However, there is a significant drive to include these capabilities at the present time. As it pertains to intelligence and connection of manufacturing systems, it is observed to be low with significant variance in tying manufacturing operations management to Enterprise Resource Planning (ERP). Furthermore, it is observed that the integration of additive manufacturing in general, 3D printing, in particular, to be low, but with significant upside of integrating it in their manufacturing operations in the near future. To hasten the readiness of the local and regional manufacturing companies to Industry 4.0 and transitions towards CPPS capabilities, our working group (ADMAR Working Group) in partnership with our university have been engaged with the local and regional manufacturing companies. The goal is to increase awareness, share know-how and capabilities, initiate joint projects, and investigate the possibility of establishing the Center for Cyber Physical Production Systems Innovation (C2P2SI). The center is intended to support the local and regional university-industry research of implementing intelligent factories, enhance new value creation through disruptive innovations, the development of hybrid and data enhanced products, and the creation of digital manufacturing enterprises. All these efforts will enhance local and regional economic development and educate students that have well developed knowledge and applications of cyber physical manufacturing systems and Industry 4.0.

Keywords: automation, cyber-physical production system, digital manufacturing enterprises, disruptive innovation, new value creation, physical-digital-physical loop

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Authors: Eric Pla Erra, Mariana Jimenez Martinez

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While aggregated loads at a community level tend to be easier to predict, individual household load forecasting present more challenges with higher volatility and uncertainty. Furthermore, the drastic changes that our behavior patterns have suffered due to the COVID-19 pandemic have modified our daily electrical consumption curves and, therefore, further complicated the forecasting methods used to predict short-term electric load. Load forecasting is vital for the smooth and optimized planning and operation of our electric grids, but it also plays a crucial role for individual domestic consumers that rely on a HEMS (Home Energy Management Systems) to optimize their energy usage through self-generation, storage, or smart appliances management. An accurate forecasting leads to higher energy savings and overall energy efficiency of the household when paired with a proper HEMS. In order to study how COVID-19 has affected the accuracy of forecasting methods, an evaluation of the performance of a state-of-the-art LGBM (Light Gradient Boosting Model) will be conducted during the transition between pre-pandemic and lockdowns periods, considering day-ahead electric load forecasting. LGBM improves the capabilities of standard Decision Tree models in both speed and reduction of memory consumption, but it still offers a high accuracy. Even though LGBM has complex non-linear modelling capabilities, it has proven to be a competitive method under challenging forecasting scenarios such as short series, heterogeneous series, or data patterns with minimal prior knowledge. An adaptation of the LGBM model – called “resilient LGBM” – will be also tested, incorporating a concept drift detection technique for time series analysis, with the purpose to evaluate its capabilities to improve the model’s accuracy during extreme events such as COVID-19 lockdowns. The results for the LGBM and resilient LGBM will be compared using standard RMSE (Root Mean Squared Error) as the main performance metric. The models’ performance will be evaluated over a set of real households’ hourly electricity consumption data measured before and during the COVID-19 pandemic. All households are located in the city of Barcelona, Spain, and present different consumption profiles. This study is carried out under the ComMit-20 project, financed by AGAUR (Agència de Gestiód’AjutsUniversitaris), which aims to determine the short and long-term impacts of the COVID-19 pandemic on building energy consumption, incrementing the resilience of electrical systems through the use of tools such as HEMS and artificial intelligence.

Keywords: concept drift, forecasting, home energy management system (HEMS), light gradient boosting model (LGBM)

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Authors: Stefano M. Spagocci

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The efficiency of photovoltaic panels can be calculated with such software packages as RETScreen that allow design engineers to take financial as well as technical considerations into account. RETScreen is interfaced with meteorological databases, so that efficiency calculations can be realistically carried out. The author has recently contributed to the development of solar modules with accumulation capability and an embedded water purifier, aimed at off-grid users such as users in developing countries. The software packages examined do not allow to take ancillary equipment into account, hence the decision to implement a technical and financial model of the system. The author realized that, rather than re-implementing the quite sophisticated model of RETScreen - a mathematical description of which is anyway not publicly available - it was possible to drastically simplify it, including the meteorological factors which, in RETScreen, are presented in a numerical form. The day-by-day efficiency of a photovoltaic solar panel was parametrized by the product of factors expressing, respectively, daytime duration, solar right ascension motion, solar declination motion, cloudiness, temperature. For the sun-motion-dependent factors, positional astronomy formulae, simplified by the author, were employed. Meteorology-dependent factors were fitted by simple trigonometric functions, employing numerical data supplied by RETScreen. The accuracy of our model was tested by comparing it to the predictions of RETScreen; the accuracy obtained was 11%. In conclusion, our study resulted in a model that can be easily implemented in a spreadsheet - thus being easily manageable by non-specialist personnel - or in more sophisticated software packages. The model was used in a number of design exercises, concerning photovoltaic solar panels and ancillary equipment like the above-mentioned water purifier.

Keywords: clean energy, energy engineering, mathematical modelling, photovoltaic panels, solar energy

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Authors: Jihen Bennaceur, Wissem Zouaghi, Ali Mabrouk

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The major aim of cyber threat intelligence (CTI) is to provide sophisticated knowledge about cybersecurity threats to ensure internal and external safeguards against modern cyberattacks. Inaccurate, incomplete, outdated, and invaluable threat intelligence is the main problem. Therefore, data analysis based on AI algorithms is one of the emergent solutions to overcome the threat of information-sharing issues. In this paper, we propose a supervised machine learning-based algorithm to improve threat information sharing by providing a sophisticated classification of cyber threats and data. Extensive simulations investigate the accuracy, precision, recall, f1-score, and support overall to validate the designed algorithm and to compare it with several supervised machine learning algorithms.

Keywords: threat information sharing, supervised learning, data classification, performance evaluation

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Authors: Linda Kauškale, Ineta Geipele

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Due to the rapidly changing external environment, portfolio management strategies became closely interconnected with real estate industry development and macroeconomic development tendencies. The aim of the research is to analyze sustainable real estate market development influencing factors, with particular focus on its economic and management aspects that influences real estate investment decisions as well. Scientific literature and article analysis, data analysis, expert evaluation, and other quantitative and qualitative research methods were used in the research. Developed real estate market sustainability model and index analysis approach can be applied by investors and real estate companies in real estate asset management and can help in risk minimization activities in international entrepreneurship. Future research directions have been identified in the research as well.

Keywords: indexes, investment decisions, real estate market, sustainability

Procedia PDF Downloads 343

Authors: Miroslav Mrlik, Marketa Ilcikova, Martin Cvek, Josef Osicka, Michal Sedlacik, Vladimir Pavlinek, Jaroslav Mosnacek

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Magnetorheological elastomers (MREs) are a unique type of materials consisting of two components, magnetic filler, and elastomeric matrix. Their properties can be tailored upon application of an external magnetic field strength. In this case, the change of the viscoelastic properties (viscoelastic moduli, complex viscosity) are influenced by two crucial factors. The first one is magnetic performance of the particles and the second one is off-state stiffness of the elastomeric matrix. The former factor strongly depends on the intended applications; however general rule is that higher magnetic performance of the particles provides higher MR performance of the MRE. Since magnetic particles possess low stability properties against temperature and acidic environment, several methods how to improve these drawbacks have been developed. In the most cases, the preparation of the core-shell structures was employed as a suitable method for preservation of the magnetic particles against thermal and chemical oxidations. However, if the shell material is not single-layer substance, but polymer material, the magnetic performance is significantly suppressed, due to the in situ polymerization technique, when it is very difficult to control the polymerization rate and the polymer shell is too thick. The second factor is the off-state stiffness of the elastomeric matrix. Since the MR effectivity is calculated as the relative value of the elastic modulus upon magnetic field application divided by elastic modulus in the absence of the external field, also the tuneability of the cross-linking reaction is highly desired. Therefore, this study is focused on the controllable modification of magnetic particles using a novel monomeric system based on 2-(1H-pyrrol-1-yl)ethyl methacrylate. In this case, the short polymer chains of different chain lengths and low polydispersity index will be prepared, and thus tailorable stability properties can be achieved. Since the relatively thin polymer chains will be grafted on the surface of magnetic particles, their magnetic performance will be affected only slightly. Furthermore, also the cross-linking density will be affected, due to the presence of the short polymer chains. From the application point of view, such MREs can be utilized for, magneto-resistors, piezoresistors or pressure sensors especially, when the conducting shell on the magnetic particles will be created. Therefore, the selection of the pyrrole-based monomer is very crucial and controllably thin layer of conducting polymer can be prepared. Finally, such composite particle consisting of magnetic core and conducting shell dispersed in elastomeric matrix can find also the utilization in shielding application of electromagnetic waves.

Keywords: atom transfer radical polymerization, core-shell, particle modification, electromagnetic waves shielding

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Authors: Christopher Baiyegunhi, Kuiwu Liu, Oswald Gwavava

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Grain size analysis is a vital sedimentological tool used to unravel the hydrodynamic conditions, mode of transportation and deposition of detrital sediments. In this study, detailed grain-size analysis was carried out on thirty-five sandstone samples from the Ecca Group in the Eastern Cape Province of South Africa. Grain-size statistical parameters, bivariate analysis, linear discriminate functions, Passega diagrams and log-probability curves were used to reveal the depositional processes, sedimentation mechanisms, hydrodynamic energy conditions and to discriminate different depositional environments. The grain-size parameters show that most of the sandstones are very fine to fine grained, moderately well sorted, mostly near-symmetrical and mesokurtic in nature. The abundance of very fine to fine grained sandstones indicates the dominance of low energy environment. The bivariate plots that the samples are mostly grouped, except for the Prince Albert samples that show scattered trend, which is due to the either mixture of two modes in equal proportion in bimodal sediments or good sorting in unimodal sediments. The linear discriminant function (LDF) analysis is dominantly indicative of turbidity current deposits under shallow marine environments for samples from the Prince Albert, Collingham and Ripon Formations, while those samples from the Fort Brown Formation are fluvial (deltaic) deposits. The graphic mean value shows the dominance of fine sand-size particles, which point to relatively low energy conditions of deposition. In addition, the LDF results point to low energy conditions during the deposition of the Prince Albert, Collingham and part of the Ripon Formation (Pluto Vale and Wonderfontein Shale Members), whereas the Trumpeters Member of the Ripon Formation and the overlying Fort Brown Formation accumulated under high energy conditions. The CM pattern shows a clustered distribution of sediments in the PQ and QR segments, indicating that the sediments were deposited mostly by suspension and rolling/saltation, and graded suspension. Furthermore, the plots also show that the sediments are mainly deposited by turbidity currents. Visher diagrams show the variability of hydraulic depositional conditions for the Permian Ecca Group sandstones. Saltation is the major process of transportation, although suspension and traction also played some role during deposition of the sediments. The sediments were mainly in saltation and suspension before being deposited.

Keywords: grain size analysis, hydrodynamic condition, depositional environment, Ecca Group, South Africa

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Authors: César Ramírez-Dolores, Jorge Wong-Loya, Jorge Andaverde, Caleb Becerra

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Low-depth geothermal energy can take advantage of the use of the subsoil as an air conditioning technique, being used as a passive system or coupled to an active cooling and/or heating system. This source of air conditioning is possible because at a depth less than 10 meters, the subsoil temperature is practically homogeneous and tends to be constant regardless of the climatic conditions on the surface. The effect of temperature fluctuations on the soil surface decreases as depth increases due to the thermal inertia of the soil, causing temperature stability; this effect presents several advantages in the context of sustainable energy use. In the present work, the thermal behavior of a horizontal Air-Water Heat Exchanger (AWHE) is evaluated, and the thermal effectiveness and temperature of the air at the outlet of the prototype immersed in groundwater is experimentally determined. The thermohydraulic aspects of the heat exchanger were evaluated using the Number of Transfer Units-Efficiency (NTU-ε) method under conditions of groundwater flow in a coastal region of sandy soil (southeastern Mexico) and air flow induced by a blower, the system was constructed of polyvinyl chloride (PVC) and sensors were placed in both the exchanger and the water to record temperature changes. The results of this study indicate that when the exchanger operates in groundwater, it shows high thermal gains allowing better heat transfer, therefore, it significantly reduces the air temperature at the outlet of the system, which increases the thermal effectiveness of the system in values > 80%, this passive technique is relevant for building cooling applications and could represent a significant development in terms of thermal comfort for hot locations in emerging economy countries.

Keywords: convection, earth, geothermal energy, thermal comfort

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Authors: Malik Abid Hussain Khokhar, Muhammad Naveed Tahir, Muhammad Amin

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Energy demand has been increased manifold due to increasing population, urban sprawl and rapid socio-economic improvements. Low water capacity in dams for continuation of hydrological power, land cover and land use are the key parameters which are creating problems for more energy production. Overall installed hydropower capacity of Pakistan is more than 35000 MW whereas Pakistan is producing up to 17000 MW and the requirement is more than 22000 that is resulting shortfall of 5000 - 7000 MW. Therefore, there is a dire need to develop small hydropower to fulfill the up-coming requirements. In this regards, excessive rainfall, snow nurtured fast flowing perennial tributaries and streams in northern mountain regions of Pakistan offer a gigantic scope of hydropower potential throughout the year. Rivers flowing in KP (Khyber Pakhtunkhwa) province, GB (Gilgit Baltistan) and AJK (Azad Jammu & Kashmir) possess sufficient water availability for rapid energy growth. In the backdrop of such scenario, small hydropower plants are believed very suitable measures for more green environment and power sustainable option for the development of such regions. Aim of this study is to estimate hydropower potential sites for small hydropower plants and stream distribution as per steam network available in the available basins in the study area. The proposed methodology will focus on features to meet the objectives i.e. site selection of maximum hydropower potential for hydroelectric generation using well emerging GIS tool SWAT as hydrological run-off model on the Neelum, Kunhar and the Dor Rivers’ basins. For validation of the results, NDWI will be computed to show water concentration in the study area while overlaying on geospatial enhanced DEM. This study will represent analysis of basins, watershed, stream links, and flow directions with slope elevation for hydropower potential to produce increasing demand of electricity by installing small hydropower stations. Later on, this study will be benefitted for other adjacent regions for further estimation of site selection for installation of such small power plants as well.

Keywords: energy, stream network, basins, SWAT, evapotranspiration

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Authors: Andrii Natochii

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The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.

Keywords: beam monitoring, channeling, particle tracking, Timepix detector

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Authors: Yi-Hao Pai, Wen-Feng Chen

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The planting area of Pomelo in Hualien, Taiwan amounts to thousands of hectares. Especially in the blooming season of Pomelo, it is an important producing area for Pomelo honey, and it is also a good test field for promoting the "Under-forest Economy". However, in the current Pomelo garden planting and management operations, the large amount of agricultural waste generated by the pruning of the branches causes environmental sanitation concerns, which can lead to the hiding of pests or the infection of the Pomelo tree, and indirectly increase the health risks of bees. Therefore, how to deal with the pruning of the branches and avoid open burning is a topic of social concern in recent years. In this research, afeasibility study evaluating energy conversion efficiency through agricultural waste gasification from the Pomelo garden, Taiwan, is demonstrated. we used a high-temperature gasifier to convert the pruning of the branches into syngas and biochar. In terms of syngas composition and calorific value assessment, we use the biogas monitoring system for analysis. Then, we used Raman spectroscopy and electron microscopy (EM) to diagnose the microstructure and surface morphology of biochar. The results indicate that the 1 ton of pruning of the branches can produce 1797.03m3 of syngas, corresponding to a calorific value of 9.1MJ/m3. The main components of the gas include CH4, H2, CO, and CO2, and the corresponding gas composition ratio is 16.8%, 7.1%, 13.7%, and 24.5%. Through the biomass syngas generator with a conversion efficiency of 30% for power generation, a total of 1,358kWh can be obtained per ton of pruning of the branches. In the research of biochar, its main characteristics in Raman spectroscopy are G bands and D bands. The first-order G and D bands are at 1580 and 1350 cm⁻¹, respectively. The G bands originates from the in-plane tangential stretching of the C−C bonds in the graphitic structure, and theD band corresponds to scattering from local defects or disorders present in carbon. The area ratio of D and G peaks (D/G) increases with the decrease of reaction temperature. The larger the D/G, the higher the defect concentration and the higher the porosity. This result is consistent with the microstructure displayed by SEM. The study is expected to be able to reuse agricultural waste and promote the development of agricultural and green energy circular economy.

Keywords: agricultural waste, gasification, energy conversion, pomelo garden

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Authors: Sohan Sengupta, Arnab Pramanik, Abhrajyoti Ghosh, Maitree Bhattacharyya

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Newly emerged phyto-pathogens and multi drug resistance have been threating the world for last few decades. Actinomycetes, the most endowed group of microorganisms isolated from unexplored regions of the world may be the ultimate solution to these problems. Thus the aim of this study was to isolate several bioactive actinomycetes strains capable of producing antimicrobial secondary metabolite from Sundarbans, the only mangrove tiger land of the world. Fifty four actinomycetes were isolated and analyzed for antimicrobial activity against fifteen test organisms including three phytopathogens. Nine morphologically distinct and biologically active isolates were subjected to polyphasic identification study. 16s rDNA sequencing indicated eight isolates to reveal maximum similarity to the genus streptomyces, whereas one isolate presented only 93.57% similarity with Streptomyces albogriseolus NRRL B-1305T. Seventy-one carbon sources and twenty-three chemical sources utilization assay revealed their metabolic relatedness. Among these nine isolates three specific strains were found to have notably higher degree of antimicrobial potential effective in a broader range including phyto-pathogenic fungus. PCR base whole genome screen for PKS and NRPS genes, confirmed the occurrence of bio-synthetic gene cluster in some of the isolates for novel antibiotic production. Finally the strain SMS_SU21, which showed antimicrobial activity with MIC value of 0.05 mg ml-1and antioxidant activity with IC50 value of 0.242±0.33 mg ml-1 was detected to be the most potential one. True prospective of this strain was evaluated utilizing GC-MS and the bioactive compound responsible for antimicrobial activity was purified and characterized. Rare bioactive actinomycetes were isolated from unexplored heritage site. Diversity of the biosynthetic gene cluster for antimicrobial compound production has also been evaluated. Antimicrobial compound SU21-C has been identified and purified which is active against a broad range of pathogens.

Keywords: actinomycetes, sundarbans, antimicrobial, pks nrps, phyto-pathogens, GC-MS

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Authors: Arvind Kumar, Manoj Kumar, Dattatraya H. Nagaraj, Amanpreet Singh, Jayanthi Prattapati

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In recent years, the use of renewable energy resources instead of pollutant fossil fuels and other forms has increased. Photovoltaic generation is becoming increasingly important as a renewable resource since it does not cause in fuel costs, pollution, maintenance, and emitting noise compared with other alternatives used in power applications. In this paper, Perturb and Observe and Incremental Conductance methods are used to improve energy conversion efficiency under different environmental conditions. PI controllers are used to control easily DC-link voltage, active and reactive currents. The whole system is simulated under standard climatic conditions (1000 W/m2, 250C) in MATLAB and the irradiance is varied from 1000 W/m2 to 300 W/m2. The use of PI controller makes it easy to directly control the power of the grid connected PV system. Finally the validity of the system will be verified through the simulations in MATLAB/Simulink environment.

Keywords: incremental conductance algorithm, modeling of PV panel, perturb and observe algorithm, photovoltaic system and simulation results

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Authors: F. Iberraken, R. Medjoudj, D. Aissani

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The development of the smart grids concept is built around two separate definitions, namely: The European one oriented towards sustainable development and the American one oriented towards reliability and security of supply. In this paper, we have investigated reliability merits enabling decision-makers to provide a high quality of service. It is based on system behavior using interruptions and failures modeling and forecasting from one hand and on the contribution of information and communication technologies (ICT) to mitigate catastrophic ones such as blackouts from the other hand. It was found that this concept has been adopted by developing and emerging countries in short and medium terms followed by sustainability concept at long term planning. This work has highlighted the reliability merits such as: Benefits, opportunities, costs and risks considered as consistent units of measuring power customer satisfaction. From the decision making point of view, we have used the analytic hierarchy process (AHP) to achieve customer satisfaction, based on the reliability merits and the contribution of such energy resources. Certainly nowadays, fossil and nuclear ones are dominating energy production but great advances are already made to jump into cleaner ones. It was demonstrated that theses resources are not only environmentally but also economically and socially sustainable. The paper is organized as follows: Section one is devoted to the introduction, where an implicit review of smart grids development is given for the two main concepts (for USA and Europeans countries). The AHP method and the BOCR developments of reliability merits against power customer satisfaction are developed in section two. The benefits where expressed by the high level of availability, maintenance actions applicability and power quality. Opportunities were highlighted by the implementation of ICT in data transfer and processing, the mastering of peak demand control, the decentralization of the production and the power system management in default conditions. Costs were evaluated using cost-benefit analysis, including the investment expenditures in network security, becoming a target to hackers and terrorists, and the profits of operating as decentralized systems, with a reduced energy not supplied, thanks to the availability of storage units issued from renewable resources and to the current power lines (CPL) enabling the power dispatcher to manage optimally the load shedding. For risks, we have razed the adhesion of citizens to contribute financially to the system and to the utility restructuring. What is the degree of their agreement compared to the guarantees proposed by the managers about the information integrity? From technical point of view, have they sufficient information and knowledge to meet a smart home and a smart system? In section three, an application of AHP method is made to achieve power customer satisfaction based on the main energy resources as alternatives, using knowledge issued from a country that has a great advance in energy mutation. Results and discussions are given in section four. It was given us to conclude that the option to a given resource depends on the attitude of the decision maker (prudent, optimistic or pessimistic), and that status quo is neither sustainable nor satisfactory.

Keywords: reliability, AHP, renewable energy resources, smart grids

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Authors: Jingjing Ye, Cijun Fan, Yan Dong

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The development of financial sector plays an important role in shaping industrial structure. However, evidence on the micro-level channels through which this relation manifest remains relatively sparse, particularly for developing countries. In this paper, we compile an industry-by-city dataset based on manufacturing firms and registered banks in 287 Chinese cities from 1998 to 2008. Based on a difference-in-difference approach, we find the highly concentrated banking sector decreases the competitiveness of firms in each manufacturing industry. There are two main reasons: i) bank accessibility successfully fosters firm expansion within each industry, however, only for sufficiently large enterprises; ii) state-owned enterprises are favored by the banking industry in China. The results are robust after considering alternative concentration and external finance dependence measures.

Keywords: bank concentration, China, difference-in-difference, industry structure

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Authors: Hamed Saremi

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study identified indicators of brand equity based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: anfis, dematel, brand, cosmetic product, brand value

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Authors: A. D. Rao, Sachiko Mohanty

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The Internal Waves (IWs) are generated by the flow of barotropic tide over the rapidly varying and steep topographic features like continental shelf slope, subsurface ridges, and the seamounts, etc. The IWs of the tidal frequency are generally known as internal tides. These waves have a significant influence on the vertical density and hence causes mixing in the region. Such waves are also important in submarine acoustics, underwater navigation, offshore structures, ocean mixing and biogeochemical processes, etc. over the shelf-slope region. The seasonal variability of internal tides in the Bay of Bengal with special emphasis on its energetics is examined by using three-dimensional MITgcm model. The numerical simulations are performed for different periods covering August-September, 2013; November-December, 2013 and March-April, 2014 representing monsoon, post-monsoon and pre-monsoon seasons respectively during which high temporal resolution in-situ data sets are available. The model is initially validated through the spectral estimates of density and the baroclinic velocities. From the estimates, it is inferred that the internal tides associated with semi-diurnal frequency are more dominant in both observations and model simulations for November-December and March-April. However, in August, the estimate is found to be maximum near-inertial frequency at all the available depths. The observed vertical structure of the baroclinic velocities and its magnitude are found to be well captured by the model. EOF analysis is performed to decompose the zonal and meridional baroclinic tidal currents into different vertical modes. The analysis suggests that about 70-80% of the total variance comes from Mode-1 semi-diurnal internal tide in both observations as well as in the model simulations. The first three modes are sufficient to describe most of the variability for semidiurnal internal tides, as they represent 90-95% of the total variance for all the seasons. The phase speed, group speed, and wavelength are found to be maximum for post-monsoon season compared to other two seasons. The model simulation suggests that the internal tide is generated all along the shelf-slope regions and propagate away from the generation sites in all the months. The model simulated energy dissipation rate infers that its maximum occurs at the generation sites and hence the local mixing due to internal tide is maximum at these sites. The spatial distribution of available potential energy is found to be maximum in November (20kg/m²) in northern BoB and minimum in August (14kg/m²). The detailed energy budget calculation are made for all the seasons and results are analysed.

Keywords: available potential energy, baroclinic energy flux, internal tides, Bay of Bengal

Procedia PDF Downloads 154

Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Dileep Kumar, Janhavi Ramchandra Rao Kumar, Rao

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COVID-19 has ravaged the globe, and it is spreading its Spectre day by day. In the absence of established drugs, this disease has created havoc. Some of the infected persons are symptomatic or asymptomatic. The respiratory system, cardiac system, digestive system, etc. in human beings are affected by this virus. In our present investigation, we have undertaken a study of the Indian Ayurvedic herb, Ocimum sanctum against SARS-CoV-2 using molecular docking and dynamics studies. The docking analysis was performed on the Glide module of Schrödinger suite on two different proteins from SARS-CoV-2 viz. NSP15 Endoribonuclease and spike receptor-binding domain. MM-GBSA based binding free energy calculations also suggest the most favorable binding affinities of carvacrol, β elemene, and β caryophyllene with binding energies of −61.61, 58.23, and −54.19 Kcal/mol respectively with spike receptor-binding domain and NSP15 Endoribonuclease. It rekindles our hope for the design and development of new drug candidates for the treatment of COVID19.

Keywords: molecular docking, COVID-19, ocimum sanctum, binding energy

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Authors: Alpana Agarwal, Akhil Sharma

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This work presents a fully differential CMOS amplifier consisting of two self-biased gain boosted inverter stages, that provides an alternative to the power hungry operational amplifier. The self-biasing avoids the use of external biasing circuitry, thus reduces the die area, design efforts, and power consumption. In the present work, regulated cascode technique has been employed for gain boosting. The Miller compensation is also applied to enhance the phase margin. The circuit has been designed and simulated in 1.8 V 0.18 µm CMOS technology. The simulation results show a high DC gain of 100.7 dB, Unity-Gain Bandwidth of 107.8 MHz, and Phase Margin of 66.7^o with a power dissipation of 286 μW and makes it suitable candidate for the high resolution pipelined ADCs.

Keywords: CMOS amplifier, gain boosting, inverter-based amplifier, self-biased inverter

Procedia PDF Downloads 284