Search results for: simulink simulation model
10833 The Delaying Influence of Degradation on the Divestment of Gas Turbines for Associated Gas Utilisation: Part 1
Authors: Mafel Obhuo, Dodeye I. Igbong, Duabari S. Aziaka, Pericles Pilidis
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An important feature of the exploitation of associated gas as fuel for gas turbine engines is a declining supply. So when exploiting this resource, the divestment of prime movers is very important as the fuel supply diminishes with time. This paper explores the influence of engine degradation on the timing of divestments. Hypothetical but realistic gas turbine engines were modelled with Turbomatch, the Cranfield University gas turbine performance simulation tool. The results were deployed in three degradation scenarios within the TERA (Techno-economic and environmental risk analysis) framework to develop economic models. An optimisation with Genetic Algorithms was carried out to maximize the economic benefit. The results show that degradation will have a significant impact. It will delay the divestment of power plants, while they are running less efficiently. Over a 20 year investment, a decrease of $0.11bn, $0.26bn and $0.45bn (billion US dollars) were observed for the three degradation scenarios as against the clean case.Keywords: economic return, flared associated gas, net present value, optimization
Procedia PDF Downloads 14010832 Multi-Sender MAC Protocol Based on Temporal Reuse in Underwater Acoustic Networks
Authors: Dongwon Lee, Sunmyeng Kim
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Underwater acoustic networks (UANs) have become a very active research area in recent years. Compared with wireless networks, UANs are characterized by the limited bandwidth, long propagation delay and high channel dynamic in acoustic modems, which pose challenges to the design of medium access control (MAC) protocol. The characteristics severely affect network performance. In this paper, we study a MS-MAC (Multi-Sender MAC) protocol in order to improve network performance. The proposed protocol exploits temporal reuse by learning the propagation delays to neighboring nodes. A source node locally calculates the transmission schedules of its neighboring nodes and itself based on the propagation delays to avoid collisions. Performance evaluation is conducted using simulation, and confirms that the proposed protocol significantly outperforms the previous protocol in terms of throughput.Keywords: acoustic channel, MAC, temporal reuse, UAN
Procedia PDF Downloads 35510831 The Projections of Urban Climate Change Using Conformal Cubic Atmospheric Model in Bali, Indonesia
Authors: Laras Tursilowati, Bambang Siswanto
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Urban climate change has short- and long-term implications for decision-makers in urban development. The problem for this important metropolitan regional of population and economic value is that there is very little usable information on climate change. Research about urban climate change has been carried out in Bali Indonesia by using Conformal Cubic Atmospheric Model (CCAM) that runs with Representative Concentration Pathway (RCP)4.5. The history data means average data from 1975 to 2005, climate projections with RCP4.5 scenario means average data from 2006 to 2099, and anomaly (urban climate change) is RCP4.5 minus history. The results are the history of temperature between 22.5-27.5 OC, and RCP4.5 between 25.5-29.5 OC. The temperature anomalies can be seen in most of northern Bali that increased by about 1.6 to 2.9 OC. There is a reduced humidity tendency (drier) in most parts of Bali, especially the northern part of Bali, while a small portion in the south increase moisture (wetter). The comfort index of Bali region in history is still relatively comfortable (20-26 OC), but on the condition RCP4.5 there is no comfortable area with index more than 26 OC (hot and dry). This research is expected to be useful to help the government make good urban planning.Keywords: CCAM, comfort index, IPCC AR5, temperature, urban climate change
Procedia PDF Downloads 14710830 Design of Black-Seed Pulp biomass-Derived New Bio-Sorbent by Combining Methods of Mineral Acids and High-Temperature for Arsenic Removal
Authors: Mozhgan Mohammadi, Arezoo Ghadi
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Arsenic is known as a potential threat to the environment. Therefore, the aim of this research is to assess the arsenic removal efficiency from an aqueous solution, with a new biosorbent composed of a black seed pulp (BSP). To treat BSP, the combination of two methods (i.e. treating with mineral acids and use at high temperature) was used and designed bio-sorbent called BSP-activated/carbonized. The BSP-activated and BSP-carbonized were also prepared using HCL and 400°C temperature, respectively, to compare the results of each three methods. Followed by, adsorption parameters such as pH, initial ion concentration, biosorbent dosage, contact time, and temperature were assessed. It was found that the combination method has provided higher adsorption capacity so that up to ~99% arsenic removal was observed with BSP-activated/carbonized at pH of 7.0 and 40°C. The adsorption capacity for BSP-carbonized and BSP-activated were 87.92% (pH: 7, 60°C) and 78.50% (pH: 6, 90°C), respectively. Moreover, adsorption kinetics data indicated the best fit with the pseudo-second-order model. The maximum biosorption capacity, by the Langmuir isotherm model, was also recorded for BSP-activated/carbonized (53.47 mg/g). It is notable that arsenic adsorption on studied bio sorbents takes place as spontaneous and through chemisorption along with the endothermic nature of the biosorption process and reduction of random collision in the solid-liquid phase.Keywords: black seed pulp, bio-sorbents, treatment of sorbents, adsorption isotherms
Procedia PDF Downloads 10310829 Structural Equation Modeling Approach: Modeling the Impact of Social Marketing Programs on Combating Female Genital Mutilation in the Sudanese Society
Authors: Nada Abdelsadig Moahamed Saied
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Female Genital Mutilation (FGM) and other similar traditional cultural practices pose a significant problem for Sudanese society. Such actions are severe and seriously detrimental to people's health since they are based on false social perceptions. To address these problems, numerous institutions and organizations were compelled to act rapidly. Female circumcision, or FGM, is one of the riskiest practices. It is referred to as the excision of the genitalia. Any surgeries involving the total or partial removal of the external female genitalia for non-medical reasons fall under this category. The results of FGM can vary depending on the kind and degree of the operation. These can be categorized as short-term, mid-term, or long-term issues. Infections, including the Human, blood, discomfort, and difficulty urinating are the immediate effects. FGM is defined by the World Health Organization (WHO) as practices that purposefully damage or modify female genital organs for non-medical purposes. It often takes place between the ages of one and fifteen. The girl's right to decide on important choices affecting her sexual and reproductive health is violated because the act is usually performed without her consent and frequently against her will. UNICEF, the United Nations International Children's Emergency Fund, aggressively combats the issue of FGM in Sudan. Numerous programs were started by NGOs to stop the practice. To our knowledge, no scientific study has been conducted to evaluate the effects of such social marketing techniques on simulating and comprehending society’s feelings surrounding FGM. This study proposes the development of a structural equation model aiming to determine the impact of awareness programs on people’s intentions to adopt the behavior of abandoning FGM based on theoretical models of behavior change. The model incorporates all the relevant factors that contribute to FGM and possible strategic actions to tackle this problem. The theoretical backdrop for FGM is presented in the next section, which also explains the practice's history, justifications, and potential treatments. The methodology section that follows describes the structural equation model. The proposed model, which compiles all the pertinent elements into a single image, is presented in the fourth part. Finally, conclusions are reached, and suggestions for further research are made.Keywords: social marketing, policy-making, behavioral change, female genital mutilation, culture
Procedia PDF Downloads 8010828 Possibilities, Challenges and the State of the Art of Automatic Speech Recognition in Air Traffic Control
Authors: Van Nhan Nguyen, Harald Holone
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Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Traffic Control (ATC), such as air traffic control simulation and training, monitoring live operators for with the aim of safety improvements, air traffic controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this field. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air traffic control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as specific approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed.Keywords: automatic speech recognition, asr, air traffic control, atc
Procedia PDF Downloads 40310827 CFD Analysis of Flow Regimes of Non-Newtonian Liquids in Chemical Reactor
Authors: Nenashev Yaroslav, Russkin Oleg
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The mixing process is one of the most important and critical stages in many industrial sectors, such as chemistry, pharmaceuticals, and the food industry. When designing equipment with mixing impellers, technology developers often encounter working environments with complex physical properties and rheology. In such cases, the use of computational fluid dynamics tools is an excellent solution to mitigate risks and ensure the stable operation of the equipment. The research focuses on one of the designed reactors with mixing impellers intended for polymer synthesis. The study describes an approach to modeling reactors of similar configurations, taking into account the complex properties of the mixed liquids using the computational fluid dynamics (CFD) method. To achieve this goal, a complex 3D model was created, accurately replicating the functionality of chemical equipment. The model allows for the assessment of the hydrodynamic behavior of the reaction mixture inside the reactor, consideration of heat release due to the reaction, and the heat exchange between the reaction mixture and the cooling medium. The results indicate that the choice of the type and size of the mixing device significantly affects the efficiency of the mixing process inside the chemical reactor.Keywords: CFD, mixing, blending, chemical reactor, non-Newton liquids, polymers
Procedia PDF Downloads 4610826 Educational Data Mining: The Case of the Department of Mathematics and Computing in the Period 2009-2018
Authors: Mário Ernesto Sitoe, Orlando Zacarias
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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.Keywords: evasion and retention, cross-validation, bagging, stacking
Procedia PDF Downloads 8710825 A Review of Intelligent Fire Management Systems to Reduce Wildfires
Authors: Nomfundo Ngombane, Topside E. Mathonsi
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Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires
Procedia PDF Downloads 8410824 Formulating the Stochastic Finite Elements for Free Vibration Analysis of Plates with Variable Elastic Modulus
Authors: Mojtaba Aghamiri Esfahani, Mohammad Karkon, Seyed Majid Hosseini Nezhad, Reza Hosseini-Ara
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In this study, the effect of uncertainty in elastic modulus of a plate on free vibration response is investigated. For this purpose, the elastic modulus of the plate is modeled as stochastic variable with normal distribution. Moreover, the distance autocorrelation function is used for stochastic field. Then, by applying the finite element method and Monte Carlo simulation, stochastic finite element relations are extracted. Finally, with a numerical test, the effect of uncertainty in the elastic modulus on free vibration response of a plate is studied. The results show that the effect of uncertainty in elastic modulus of the plate cannot play an important role on the free vibration response.Keywords: stochastic finite elements, plate bending, free vibration, Monte Carlo, Neumann expansion method.
Procedia PDF Downloads 40010823 Analysis of Wire Coating for Heat Transfer Flow of a Viscoelastic PTT Fluid with Slip Boundary Conditions
Authors: Rehan Ali Shah, A. M. Siddiqui, T. Haroon
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Slip boundary value problem in wire coating analysis with heat transfer is examined. The fluid is assumed to be viscoelastic PTT (Phan-Thien and Tanner). The rheological constitutive equation of PTT fluid model simulates various polymer melts. Therefore, the current consequences are valuable in a number of realistic situations. Effects of slip parameter γ as well as εDec^2 (viscoelastic index) on the axial velocity, shear stress, normal stress, average velocity, volume flux, thickness of coated wire, shear stress, force on the total wire and temperature distribution profiles have been investigated. A new direction is explored to analyze the flow with the slip parameter. The slippage at the boundaries plays an important role in thickness of coated wire. It is noted that as the slip parameter increases the flow rate and thickness of coated wire increases while, temperature distribution decreases. The results reduce to no slip when the slip parameter is vanished. Furthermore, we can obtain the results for Maxwell and viscous model by setting ε and λ equal to zero respectively.Keywords: wire coating, straight annular die, PTT fluid, heat transfer, slip boundary conditions
Procedia PDF Downloads 36810822 Investigation of Static Stability of Soil Slopes Using Numerical Modeling
Authors: Seyed Abolhasan Naeini, Elham Ghanbari Alamooti
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Static stability of soil slopes using numerical simulation by a finite element code, ABAQUS, has been investigated, and safety factors of the slopes achieved in the case of static load of a 10-storey building. The embankments have the same soil condition but different loading distance from the slope heel. The numerical method for estimating safety factors is 'Strength Reduction Method' (SRM). Mohr-Coulomb criterion used in the numerical simulations. Two steps used for measuring the safety factors of the slopes: first is under gravity loading, and the second is under static loading of a building near the slope heel. These safety factors measured from SRM, are compared with the values from Limit Equilibrium Method, LEM. Results show that there is good agreement between SRM and LEM. Also, it is seen that by increasing the distance from slope heel, safety factors increases.Keywords: limit equilibrium method, static stability, soil slopes, strength reduction method
Procedia PDF Downloads 16810821 The Study of Elementary School Teacher’s Behavior of Using E-books by UTAUT Model
Authors: Tzong-Shing Cheng, Chen Pei Chen, Shu-Wei Chen
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The purpose of this research is to apply Unified Theory of Acceptance and Use of Technology (UTAUT) model to investigate the factors that influence elementary school teacher’s behavior of using e-books. Based on the literature review, a questionnaire was modified and used to test the elementary school teachers in Changhua. A total of 420 questionnaires were administered and 364 of them were returned, including 328 valid and 36 invalid questionnaires. The effective response rate is 78%. The methods of data analysis include descriptive statistics, factor analysis, Pearson’s correlation coefficient, one way analysis of variance (ANOVA) and simple regression analysis. The results show that: 1. There were significant difference in the Elementary school teachers’ “Performance Expectancy”, “Effort Expectancy”, “Social Influence”, and “Facilitating Conditions” depending on their different “Demographic Variables”. 2. “Performance Expectancy” and “Behavioral Intention to Use” are positively correlated. 3. “Effort Expectancy” and “Behavioral Intention to Use” are positively correlated. 4. There was no significant relationship between “Social Influence” and “Behavioral Intention to Use”. 5. There was significant relationship between “Facilitating Conditions” and “Use Behavior”.Keywords: e-books, UTAUT, elementary school teacher, behavioral intention to use
Procedia PDF Downloads 61910820 A General Framework for Knowledge Discovery Using High Performance Machine Learning Algorithms
Authors: S. Nandagopalan, N. Pradeep
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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.Keywords: active contour, bayesian, echocardiographic image, feature vector
Procedia PDF Downloads 42710819 Polyurethane Membrane Mechanical Property Study for a Novel Carotid Covered Stent
Authors: Keping Zuo, Jia Yin Chia, Gideon Praveen Kumar Vijayakumar, Foad Kabinejadian, Fangsen Cui, Pei Ho, Hwa Liang Leo
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Carotid artery is the major vessel supplying blood to the brain. Carotid artery stenosis is one of the three major causes of stroke and the stroke is the fourth leading cause of death and the first leading cause of disability in most developed countries. Although there is an increasing interest in carotid artery stenting for treatment of cervical carotid artery bifurcation therosclerotic disease, currently available bare metal stents cannot provide an adequate protection against the detachment of the plaque fragments over diseased carotid artery, which could result in the formation of micro-emboli and subsequent stroke. Our research group has recently developed a novel preferential covered-stent for carotid artery aims to prevent friable fragments of atherosclerotic plaques from flowing into the cerebral circulation, and yet retaining the ability to preserve the flow of the external carotid artery. The preliminary animal studies have demonstrated the potential of this novel covered-stent design for the treatment of carotid therosclerotic stenosis. The purpose of this study is to evaluate the biomechanical property of PU membrane of different concentration configurations in order to refine the stent coating technique and enhance the clinical performance of our novel carotid covered stent. Results from this study also provide necessary material property information crucial for accurate simulation analysis for our stents. Method: Medical grade Polyurethane (ChronoFlex AR) was used to prepare PU membrane specimens. Different PU membrane configurations were subjected to uniaxial test: 22%, 16%, and 11% PU solution were made by mixing the original solution with proper amount of the Dimethylacetamide (DMAC). The specimens were then immersed in physiological saline solution for 24 hours before test. All specimens were moistened with saline solution before mounting and subsequent uniaxial testing. The specimens were preconditioned by loading the PU membrane sample to a peak stress of 5.5 Mpa for 10 consecutive cycles at a rate of 50 mm/min. The specimens were then stretched to failure at the same loading rate. Result: The results showed that the stress-strain response curves of all PU membrane samples exhibited nonlinear characteristic. For the ultimate failure stress, 22% PU membrane was significantly higher than 16% (p<0.05). In general, our preliminary results showed that lower concentration PU membrane is stiffer than the higher concentration one. From the perspective of mechanical properties, 22% PU membrane is a better choice for the covered stent. Interestingly, the hyperelastic Ogden model is able to accurately capture the nonlinear, isotropic stress-strain behavior of PU membrane with R2 of 0.9977 ± 0.00172. This result will be useful for future biomechanical analysis of our stent designs and will play an important role for computational modeling of our covered stent fatigue study.Keywords: carotid artery, covered stent, nonlinear, hyperelastic, stress, strain
Procedia PDF Downloads 31310818 Training AI to Be Empathetic and Determining the Psychotype of a Person During a Conversation with a Chatbot
Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin
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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a userKeywords: AI, empathetic, chatbot, AI models
Procedia PDF Downloads 9610817 Machine Learning Approach for Anomaly Detection in the Simulated Iec-60870-5-104 Traffic
Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato
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Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security
Procedia PDF Downloads 37510816 Exploring Wheel-Motion Energy Sources for Energy Harvesting Based on Electromagnetic Effect: Experimental and Numerical Investigation
Authors: Mohammed Alaa Alwafaie, Bela Kovacs
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With the rapid emergence and evolution of renewable energy sources like wind and solar power, there is an increasing demand for effective energy harvester architectures. This paper focuses on investigating the concept of energy harvesting using a wheel-motion energy source. The proposed method involves the placement of magnets and copper coils inside the hubcap rod of a wheel. When the wheel is set in motion, following Faraday's Law, the movement of the magnet within the coil induces an electric current. The paper includes an experiment to measure the output voltage of electromagnetics, as well as a numerical simulation to further explore the potential of this energy harvesting approach. By harnessing the rotational motion of wheels, this research aims to contribute to the development of innovative techniques for generating electrical power in a sustainable and efficient manner.Keywords: harvesting energy, electromagnetic, hubcap rod wheel, magnet movement inside coil, faraday law
Procedia PDF Downloads 8410815 Application of Adaptive Neuro Fuzzy Inference Systems Technique for Modeling of Postweld Heat Treatment Process of Pressure Vessel Steel AASTM A516 Grade 70
Authors: Omar Al Denali, Abdelaziz Badi
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The ASTM A516 Grade 70 steel is a suitable material used for the fabrication of boiler pressure vessels working in moderate and lower temperature services, and it has good weldability and excellent notch toughness. The post-weld heat treatment (PWHT) or stress-relieving heat treatment has significant effects on avoiding the martensite transformation and resulting in high hardness, which can lead to cracking in the heat-affected zone (HAZ). An adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the material tensile strength of post-weld heat treatment (PWHT) experiments. The ANFIS models presented excellent predictions, and the comparison was carried out based on the mean absolute percentage error between the predicted values and the experimental values. The ANFIS model gave a Mean Absolute Percentage Error of 0.556 %, which confirms the high accuracy of the model.Keywords: prediction, post-weld heat treatment, adaptive neuro-fuzzy inference system, mean absolute percentage error
Procedia PDF Downloads 16010814 Positive Psychology and the Social Emotional Ability Instrument (SEAI)
Authors: Victor William Harris
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This research is a validation study of the Social Emotional Ability Inventory (SEAI), a multi-dimensional self-report instrument informed by positive psychology, emotional intelligence, social intelligence, and sociocultural learning theory. Designed for use in tandem with the Social Emotional Development (SEAD) theoretical model, the SEAI provides diagnostic-level guidance for professionals and individuals interested in investigating, identifying, and understanding social, emotional strengths, as well as remediating specific social competency deficiencies. The SEAI was shown to be psychometrically sound, exhibited strong internal reliability, and supported the a priori hypotheses of the SEAD. Additionally, confirmatory factor analysis provided evidence of goodness of fit, convergent and divergent validity, and supported a theoretical model that reflected SEAD expectations. The SEAI and SEAD hold potentially far-reaching and important practical implications for theoretical guidance and diagnostic-level measurement of social, emotional competency across a wide range of domains. Strategies researchers, practitioners, educators, and individuals might use to deploy SEAI in order to improve quality of life outcomes are discussed.Keywords: emotion, emotional ability, positive psychology-social emotional ability, social emotional ability, social emotional ability instrument
Procedia PDF Downloads 26510813 Small Wind Turbine Hybrid System for Remote Application: Egyptian Case Study
Authors: M. A. Badr, A. N. Mohib, M. M. Ibrahim
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The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) system supplying a remote small gathering of six families using HOMER software package. The electrical energy is to cater for the basic needs for which the daily load pattern is estimated. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites as the price of generated electricity is about 0.308 $/kWh, without taking external benefits into considerations. W/D/B systems are more economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.Keywords: optimum energy systems, remote electrification, renewable energy, wind turbine systems
Procedia PDF Downloads 40610812 A Model of Human Security: A Comparison of Vulnerabilities and Timespace
Authors: Anders Troedsson
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For us humans, risks are intimately linked to human vulnerabilities - where there is vulnerability, there is potentially insecurity, and risk. Reducing vulnerability through compensatory measures means increasing security and decreasing risk. The paper suggests that a meaningful way to approach the study of risks (including threats, assaults, crisis etc.), is to understand the vulnerabilities these external phenomena evoke in humans. As is argued, the basis of risk evaluation, as well as responses, is the more or less subjective perception by the individual person, or a group of persons, exposed to the external event or phenomena in question. This will be determined primarily by the vulnerability or vulnerabilities that the external factor are perceived to evoke. In this way, risk perception is primarily an inward dynamic, rather than an outward one. Therefore, a route towards an understanding of the perception of risks, is a closer scrutiny of the vulnerabilities which they can evoke, thereby approaching an understanding of what in the paper is called the essence of risk (including threat, assault etc.), or that which a certain perceived risk means to an individual or group of individuals. As a necessary basis for gauging the wide spectrum of potential risks and their meaning, the paper proposes a model of human vulnerabilities, drawing from i.a. a long tradition of needs theory. In order to account for the subjectivity factor, which mediates between the innate vulnerabilities on the one hand, and the event or phenomenon out there on the other hand, an ensuing ontological discussion about the timespace characteristics of risk/threat/assault as perceived by humans leads to the positing of two dimensions. These two dimensions are applied on the vulnerabilities, resulting in a modelling effort featuring four realms of vulnerabilities which are related to each other and together represent a dynamic whole. In approaching the problem of risk perception, the paper thus defines the relevant realms of vulnerabilities, depicting them as a dynamic whole. With reference to a substantial body of literature and a growing international policy trend since the 1990s, this model is put in the language of human security - a concept relevant not only for international security studies and policy, but also for other academic disciplines and spheres of human endeavor.Keywords: human security, timespace, vulnerabilities, risk perception
Procedia PDF Downloads 34310811 Compromising Relevance for Elegance: A Danger of Dominant Growth Models for Backward Economies
Authors: Givi Kupatadze
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Backward economies are facing a challenge of achieving sustainable high economic growth rate. Dominant growth models represent a roadmap in framing economic development strategy. This paper examines a relevance of the dominant growth models for backward economies. Cobb-Douglas production function, the Harrod-Domar model of economic growth, the Solow growth model and general formula of gross domestic product are examined to undertake a comprehensive study of the dominant growth models. Deductive research method allows to uncover major weaknesses of the dominant growth models and to come up with practical implications for economic development strategy. The key finding of the paper shows, contrary to what used to be taught by textbooks of economics, that constant returns to scale property of the dominant growth models are a mere coincidence and its generalization over space and time can be regarded as one of the most unfortunate mistakes in the whole field of political economy. The major suggestion of the paper for backward economies is that understanding and considering taxonomy of economic activities based on increasing and diminishing returns to scale represent a cornerstone of successful economic development strategy.Keywords: backward economies, constant returns to scale, dominant growth models, taxonomy of economic activities
Procedia PDF Downloads 37810810 A Collaborative Learning Model in Engineering Science Based on a Cyber-Physical Production Line
Authors: Yosr Ghozzi
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The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0
Procedia PDF Downloads 11210809 Destructive and Nondestructive Characterization of Advanced High Strength Steels DP1000/1200
Authors: Carla M. Machado, André A. Silva, Armando Bastos, Telmo G. Santos, J. Pamies Teixeira
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Advanced high-strength steels (AHSS) are increasingly being used in automotive components. The use of AHSS sheets plays an important role in reducing weight, as well as increasing the resistance to impact in vehicle components. However, the large-scale use of these sheets becomes more difficult due to the limitations during the forming process. Such limitations are due to the elastically driven change of shape of a metal sheet during unloading and following forming, known as the springback effect. As the magnitude of the springback tends to increase with the strength of the material, it is among the most worrisome problems in the use of AHSS steels. The prediction of strain hardening, especially under non-proportional loading conditions, is very limited due to the lack of constitutive models and mainly due to very limited experimental tests. It is very clear from the literature that in experimental terms there is not much work to evaluate deformation behavior under real conditions, which implies a very limited and scarce development of mathematical models for these conditions. The Bauschinger effect is also fundamental to the difference between kinematic and isotropic hardening models used to predict springback in sheet metal forming. It is of major importance to deepen the phenomenological knowledge of the mechanical and microstructural behavior of the materials, in order to be able to reproduce with high fidelity the behavior of extension of the materials by means of computational simulation. For this, a multi phenomenological analysis and characterization are necessary to understand the various aspects involved in plastic deformation, namely the stress-strain relations and also the variations of electrical conductivity and magnetic permeability associated with the metallurgical changes due to plastic deformation. Aiming a complete mechanical-microstructural characterization, uniaxial tensile tests involving successive cycles of loading and unloading were performed, as well as biaxial tests such as the Erichsen test. Also, nondestructive evaluation comprising eddy currents to verify microstructural changes due to plastic deformation and ultrasonic tests to evaluate the local variations of thickness were made. The material parameters for the stable yield function and the monotonic strain hardening were obtained using uniaxial tension tests in different material directions and balanced biaxial tests. Both the decrease of the modulus of elasticity and Bauschinger effect were determined through the load-unload tensile tests. By means of the eddy currents tests, it was possible to verify changes in the magnetic permeability of the material according to the different plastically deformed areas. The ultrasonic tests were an important aid to quantify the local plastic extension. With these data, it is possible to parameterize the different models of kinematic hardening to better approximate the results obtained by simulation with the experimental results, which are fundamental for the springback prediction of the stamped parts.Keywords: advanced high strength steel, Bauschinger effect, sheet metal forming, springback
Procedia PDF Downloads 22910808 Investigation of the Physical Computing in Computational Thinking Practices, Computer Programming Concepts and Self-Efficacy for Crosscutting Ideas in STEM Content Environments
Authors: Sarantos Psycharis
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Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.Keywords: arduino, computational thinking, computer programming, Labview, self-efficacy, STEM
Procedia PDF Downloads 11610807 Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market
Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua
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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.Keywords: candlestick chart, deep learning, neural network, stock market prediction
Procedia PDF Downloads 45610806 A Fuzzy TOPSIS Based Model for Safety Risk Assessment of Operational Flight Data
Authors: N. Borjalilu, P. Rabiei, A. Enjoo
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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety
Procedia PDF Downloads 16910805 Optimal Design of Reference Node Placement for Wireless Indoor Positioning Systems in Multi-Floor Building
Authors: Kittipob Kondee, Chutima Prommak
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In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.Keywords: indoor positioning system, optimization system design, multi-floor building, wireless sensor networks
Procedia PDF Downloads 25110804 Inhibition of α-Glucosidase and Xanthine Oxidase by Curcumin and Its Analogs
Authors: Jung-Feng Hsieh, Chu Ze Chen
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Curcumin is the main active compound of turmeric that can inhibit the activities of α-glucosidase and xanthine oxidase (XO). α-Glucosidase and XO inhibitors are widely used to treat patients with diabetes mellitus and gout, respectively; therefore, the objective of this research was to evaluate the inhibitory activities of curcumin and its analogs against α-glucosidase and XO. Our results demonstrated that CM-F had the strongest antioxidant activity with a half-maximal effective concentration (EC50) of 9.39 ± 0.16 μM, which was superior to vitamin E (EC50=17.03 ± 0.09 μM). CM-F also exhibited potent inhibitory activity against XO with an IC50 value of 6.14 ± 0.38 μM and enzyme kinetic results revealed competitive inhibition of XO. We also found that CM-1 and CM-2 inhibited α-glucosidase with IC50 values of 21.06 ± 0.92 μM and 5.95 ± 0.09 μM, respectively, and kinetic studies indicated that both CM-1 and CM-2 are mixed competitive inhibitors of α-glucosidase. Furthermore, docking simulation identified five hydrogen bonds between XO and CM-F; however, only one and two hydrogen bonds are involved in CM-1 and CM-2 binding to α-glucosidase, respectively. Accordingly, curcumin and its analogs have the potential to be used in the treatment of patients with diabetes mellitus and gout.Keywords: curcumin, α-glucosidase, inhibitor, xanthine oxidase
Procedia PDF Downloads 209