Search results for: modeling and simulation
274 DTC-SVM Scheme for Induction Motors Fedwith a Three-level Inverter
Authors: Ehsan Hassankhan, Davood A. Khaburi
Abstract:
Direct Torque Control is a control technique in AC drive systems to obtain high performance torque control. The conventional DTC drive contains a pair of hysteresis comparators. DTC drives utilizing hysteresis comparators suffer from high torque ripple and variable switching frequency. The most common solution to those problems is to use the space vector depends on the reference torque and flux. In this Paper The space vector modulation technique (SVPWM) is applied to 2 level inverter control in the proposed DTC-based induction motor drive system, thereby dramatically reducing the torque ripple. Then the controller based on space vector modulation is designed to be applied in the control of Induction Motor (IM) with a three-level Inverter. This type of Inverter has several advantages over the standard two-level VSI, such as a greater number of levels in the output voltage waveforms, Lower dV/dt, less harmonic distortion in voltage and current waveforms and lower switching frequencies. This paper proposes a general SVPWM algorithm for three-level based on standard two-level SVPWM. The proposed scheme is described clearly and simulation results are reported to demonstrate its effectiveness. The entire control scheme is implemented with Matlab/Simulink.Keywords: Direct torque control, space vector Pulsewidthmodulation(SVPWM), neutral point clamped(NPC), two-levelinverter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4387273 Application of Neural Network in User Authentication for Smart Home System
Authors: A. Joseph, D.B.L. Bong, D.A.A. Mat
Abstract:
Security has been an important issue and concern in the smart home systems. Smart home networks consist of a wide range of wired or wireless devices, there is possibility that illegal access to some restricted data or devices may happen. Password-based authentication is widely used to identify authorize users, because this method is cheap, easy and quite accurate. In this paper, a neural network is trained to store the passwords instead of using verification table. This method is useful in solving security problems that happened in some authentication system. The conventional way to train the network using Backpropagation (BPN) requires a long training time. Hence, a faster training algorithm, Resilient Backpropagation (RPROP) is embedded to the MLPs Neural Network to accelerate the training process. For the Data Part, 200 sets of UserID and Passwords were created and encoded into binary as the input. The simulation had been carried out to evaluate the performance for different number of hidden neurons and combination of transfer functions. Mean Square Error (MSE), training time and number of epochs are used to determine the network performance. From the results obtained, using Tansig and Purelin in hidden and output layer and 250 hidden neurons gave the better performance. As a result, a password-based user authentication system for smart home by using neural network had been developed successfully.Keywords: Neural Network, User Authentication, Smart Home, Security
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2030272 Using Ferry Access Points to Improve the Performance of Message Ferrying in Delay-Tolerant Networks
Authors: Farzana Yasmeen, Md. Nurul Huda, Md. Enamul Haque, Michihiro Aoki, Shigeki Yamada
Abstract:
Delay-Tolerant Networks (DTNs) are sparse, wireless networks where disconnections are common due to host mobility and low node density. The Message Ferrying (MF) scheme is a mobilityassisted paradigm to improve connectivity in DTN-like networks. A ferry or message ferry is a special node in the network which has a per-determined route in the deployed area and relays messages between mobile hosts (MHs) which are intermittently connected. Increased contact opportunities among mobile hosts and the ferry improve the performance of the network, both in terms of message delivery ratio and average end-end delay. However, due to the inherent mobility of mobile hosts and pre-determined periodicity of the message ferry, mobile hosts may often -miss- contact opportunities with a ferry. In this paper, we propose the combination of stationary ferry access points (FAPs) with MF routing to increase contact opportunities between mobile hosts and the MF and consequently improve the performance of the DTN. We also propose several placement models for deploying FAPs on MF routes. We evaluate the performance of the FAP placement models through comprehensive simulation. Our findings show that FAPs do improve the performance of MF-assisted DTNs and symmetric placement of FAPs outperforms other placement strategies.Keywords: Service infrastructure, delay-tolerant network, messageferry routing, placement models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1970271 Integrating Fast Karnough Map and Modular Neural Networks for Simplification and Realization of Complex Boolean Functions
Authors: Hazem M. El-Bakry
Abstract:
In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.Keywords: Boolean Functions, Simplification, KarnoughMap, Implementation of Logic Functions, Modular NeuralNetworks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1802270 Improving Air Temperature Prediction with Artificial Neural Networks
Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom
Abstract:
The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. Previous work established that the Ward-style artificial neural network (ANN) is a suitable tool for developing such models. The current research focused on developing ANN models with reduced average prediction error by increasing the number of distinct observations used in training, adding additional input terms that describe the date of an observation, increasing the duration of prior weather data included in each observation, and reexamining the number of hidden nodes used in the network. Models were created to predict air temperature at hourly intervals from one to 12 hours ahead. Each ANN model, consisting of a network architecture and set of associated parameters, was evaluated by instantiating and training 30 networks and calculating the mean absolute error (MAE) of the resulting networks for some set of input patterns. The inclusion of seasonal input terms, up to 24 hours of prior weather information, and a larger number of processing nodes were some of the improvements that reduced average prediction error compared to previous research across all horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or 12.5%, less than the previous model. Prediction MAEs eight and 12 hours ahead improved by 0.17°C and 0.16°C, respectively, improvements of 7.4% and 5.9% over the existing model at these horizons. Networks instantiating the same model but with different initial random weights often led to different prediction errors. These results strongly suggest that ANN model developers should consider instantiating and training multiple networks with different initial weights to establish preferred model parameters.Keywords: Decision support systems, frost protection, fruit, time-series prediction, weather modeling
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2706269 Nine-Level Shunt Active Power Filter Associated with a Photovoltaic Array Coupled to the Electrical Distribution Network
Authors: Zahzouh Zoubir, Bouzaouit Azzeddine, Gahgah Mounir
Abstract:
The use of more and more electronic power switches with a nonlinear behavior generates non-sinusoidal currents in distribution networks, which causes damage to domestic and industrial equipment. The multi-level shunt power active filter is subsequently shown to be an adequate solution to the problem raised. Nevertheless, the difficulty of adjusting the active filter DC supply voltage requires another technology to ensure it. In this article, a photovoltaic generator is associated with the DC bus power terminals of the active filter. The proposed system consists of a field of solar panels, three multi-level voltage inverters connected to the power grid and a non-linear load consisting of a six-diode rectifier bridge supplying a resistive-inductive load. Current control techniques of active and reactive power are used to compensate for both harmonic currents and reactive power as well as to inject active solar power into the distribution network. An algorithm of the search method of the maximum power point of type Perturb and observe is applied. Simulation results of the system proposed under the MATLAB/Simulink environment shows that the performance of control commands that reassure the solar power injection in the network, harmonic current compensation and power factor correction.Keywords: MPPT, active power filter, PV array, perturb and observe algorithm, PWM-control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 745268 Integrating Fast Karnough Map and Modular Neural Networks for Simplification and Realization of Complex Boolean Functions
Authors: Hazem M. El-Bakry
Abstract:
In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.
Keywords: Boolean functions, simplification, Karnough map, implementation of logic functions, modular neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2062267 A CFD Study of Sensitive Parameters Effect on the Combustion in a High Velocity Oxygen-Fuel Thermal Spray Gun
Authors: S. Hossainpour, A. R. Binesh
Abstract:
High-velocity oxygen fuel (HVOF) thermal spraying uses a combustion process to heat the gas flow and coating material. A computational fluid dynamics (CFD) model has been developed to predict gas dynamic behavior in a HVOF thermal spray gun in which premixed oxygen and propane are burnt in a combustion chamber linked to a parallel-sided nozzle. The CFD analysis is applied to investigate axisymmetric, steady-state, turbulent, compressible, chemically reacting, subsonic and supersonic flow inside and outside the gun. The gas velocity, temperature, pressure and Mach number distributions are presented for various locations inside and outside the gun. The calculated results show that the most sensitive parameters affecting the process are fuel-to-oxygen gas ratio and total gas flow rate. Gas dynamic behavior along the centerline of the gun depends on both total gas flow rate and fuel-to-oxygen gas ratio. The numerical simulations show that the axial gas velocity and Mach number distribution depend on both flow rate and ratio; the highest velocity is achieved at the higher flow rate and most fuel-rich ratio. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the HVOF system design, optimization and performance analysis.Keywords: HVOF, CFD, gas dynamics, thermal spray, combustion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2147266 Structural Performance Evaluation of Electronic Road Sign Panels Reflecting Damage Scenarios
Authors: Junwon Seo, Bipin Adhikari, Euiseok Jeong
Abstract:
This paper is intended to evaluate the structural performance of welded electronic road signs under various damage scenarios (DSs) using a finite element (FE) model calibrated with full-scale ultimate load testing results. The tested electronic road sign specimen was built with a back skin made of 5052 aluminum and two channels and a frame made of 6061 aluminum, where the back skin was connected to the frame by welding. The size of the tested specimen was 1.52 m long, 1.43 m wide, and 0.28 m deep. An actuator applied vertical loads at the center of the back skin of the specimen, resulting in a displacement of 158.7 mm and an ultimate load of 153.46 kN. Using these testing data, generation and calibration of a FE model of the tested specimen were executed in ABAQUS, indicating that the difference in the ultimate load between the calibrated model simulation and full-scale testing was only 3.32%. Then, six different DSs were simulated where the areas of the welded connection in the calibrated model were diminished for the DSs. It was found that the corners at the back skin-frame joint were prone to connection failure for all the DSs, and failure of the back skin-frame connection occurred remarkably from the distant edges.
Keywords: Computational analysis, damage scenarios, electronic road signs, finite element, welded connections.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 366265 Digital Twin of Real Electrical Distribution System with Real Time Recursive Load Flow Calculation and State Estimation
Authors: Anosh Arshad Sundhu, Francesco Giordano, Giacomo Della Croce, Maurizio Arnone
Abstract:
Digital Twin (DT) is a technology that generates a virtual representation of a physical system or process, enabling real-time monitoring, analysis, and simulation. DT of an Electrical Distribution System (EDS) can perform online analysis by integrating the static and real-time data in order to show the current grid status and predictions about the future status to the Distribution System Operator (DSO), producers and consumers. DT technology for EDS also offers the opportunity to DSO to test hypothetical scenarios. This paper discusses the development of a DT of an EDS by Smart Grid Controller (SGC) application, which is developed using open-source libraries and languages. The developed application can be integrated with Supervisory Control and Data Acquisition System (SCADA) of any EDS for creating the DT. The paper shows the performance of developed tools inside the application, tested on real EDS for grid observability, Smart Recursive Load Flow (SRLF) calculation and state estimation of loads in MV feeders.
Keywords: Digital Twin, Distribution System Operator, Electrical Distribution System, Smart Grid Controller, Supervisory Control and Data Acquisition System, Smart Recursive Load Flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 221264 Estimating Spatial Disaggregation of Urban Thermal Responsiveness on Summer Diurnal Range with a Numerical Modeling Approach in Bangkok, Thailand
Authors: Manat Srivanit, Hokao Kazunori
Abstract:
Facing the concern of the population to its environment and to climatic change, city planners are now considering the urban climate in their choices of planning. The urban climate, representing different urban morphologies across central Bangkok metropolitan area (BMA), are used to investigates the effects of both the composition and configuration of variables of urban morphology indicators on the summer diurnal range of urban climate, using correlation analyses and multiple linear regressions. Results show first indicate that approximately 92.6% of the variation in the average maximum daytime near-surface air temperature (Ta) was explained jointly by the two composition variables of urban morphology indicators including open space ratio (OSR) and floor area ratio (FAR). It has been possible to determine the membership of sample areas to the local climate zones (LCZs) using these urban morphology descriptors automatically computed with GIS and remote sensed data. Finally result found the temperature differences among zones of large separation, such as the city center could be respectively from 35.48±1.04ºC (Mean±S.D.) warmer than the outskirt of Bangkok on average for maximum daytime near surface temperature to 28.27±0.21ºC for extreme event and, can exceed as 8ºC. A spatially disaggregation of urban thermal responsiveness map would be helpful for several reasons. First, it would localize urban areas concerned by different climate behavior over summer daytime and be a good indicator of urban climate variability. Second, when overlaid with a land cover map, this map may contribute to identify possible urban management strategies to reduce heat wave effects in BMA.
Keywords: Urban climate, Urban morphology, Local climate zone, Urban planning, GIS and remote sensing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2451263 Lateral Torsional Buckling Resistance of Trapezoidally Corrugated Web Girders
Authors: Annamária Käferné Rácz, Bence Jáger, Balázs Kövesdi, László Dunai
Abstract:
Due to the numerous advantages of steel corrugated web girders, its application field is growing for bridges as well as for buildings. The global stability behavior of such girders is significantly larger than those of conventional I-girders with flat web, thus the application of the structural steel material can be significantly reduced. Design codes and specifications do not provide clear and complete rules or recommendations for the determination of the lateral torsional buckling (LTB) resistance of corrugated web girders. Therefore, the authors made a thorough investigation regarding the LTB resistance of the corrugated web girders. Finite element (FE) simulations have been performed to develop new design formulas for the determination of the LTB resistance of trapezoidally corrugated web girders. FE model is developed considering geometrical and material nonlinear analysis using equivalent geometric imperfections (GMNI analysis). The equivalent geometric imperfections involve the initial geometric imperfections and residual stresses coming from rolling, welding and flame cutting. Imperfection sensitivity analysis was performed to determine the necessary magnitudes regarding only the first eigenmodes shape imperfections. By the help of the validated FE model, an extended parametric study is carried out to investigate the LTB resistance for different trapezoidal corrugation profiles. First, the critical moment of a specific girder was calculated by FE model. The critical moments from the FE calculations are compared to the previous analytical calculation proposals. Then, nonlinear analysis was carried out to determine the ultimate resistance. Due to the numerical investigations, new proposals are developed for the determination of the LTB resistance of trapezoidally corrugated web girders through a modification factor on the design method related to the conventional flat web girders.Keywords: Critical moment, FE modeling, lateral torsional buckling, trapezoidally corrugated web girders.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1189262 Performance Comparison of Situation-Aware Models for Activating Robot Vacuum Cleaner in a Smart Home
Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu
Abstract:
We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.Keywords: Situation-awareness, Smart home, IoT, Machine learning, Classifier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1845261 Competitors’ Influence Analysis of a Retailer by Using Customer Value and Huff’s Gravity Model
Authors: Yepeng Cheng, Yasuhiko Morimoto
Abstract:
Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.Keywords: Customer value, Huff's Gravity Model, POS, retailer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 597260 Conformation Prediction of Human Plasmin and Docking on Gold Nanoparticle
Authors: Wen-Shyong Tzou, Chih-Ching Huang, Chin-Hwa Hu, Ying-Tsang Lo, Tun-Wen Pai, Chia-Yin Chiang, Chung-Hao Li, Hong-Jyuan Jian
Abstract:
Plasmin plays an important role in the human circulatory system owing to its catalytic ability of fibrinolysis. The immediate injection of plasmin in patients of strokes has intrigued many scientists to design vectors that can transport plasmin to the desired location in human body. Here we predict the structure of human plasmin and investigate the interaction of plasmin with the gold-nanoparticle. Because the crystal structure of plasminogen has been solved, we deleted N-terminal domain (Pan-apple domain) of plasminogen and generate a mimic of the active form of this enzyme (plasmin). We conducted a simulated annealing process on plasmin and discovered a very large conformation occurs. Kringle domains 1, 4 and 5 had been observed to leave its original location relative to the main body of the enzyme and the original doughnut shape of this enzyme has been transformed to a V-shaped by opening its two arms. This observation of conformational change is consistent with the experimental results of neutron scattering and centrifugation. We subsequently docked the plasmin on the simulated gold surface to predict their interaction. The V-shaped plasmin could utilize its Kringle domain and catalytic domain to contact the gold surface. Our findings not only reveal the flexibility of plasmin structure but also provide a guide for the design of a plasmin-gold nanoparticle.Keywords: Docking, gold nanoparticle, molecular simulation, plasmin.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2423259 A Novel Application of Network Equivalencing Method in Time Domain to Precise Calculation of Dead Time in Power Transmission Title
Authors: J. Moshtagh, L. Eslami
Abstract:
Various studies have showed that about 90% of single line to ground faults occurred on High voltage transmission lines have transient nature. This type of faults is cleared by temporary outage (by the single phase auto-reclosure). The interval between opening and reclosing of the faulted phase circuit breakers is named “Dead Time” that is varying about several hundred milliseconds. For adjustment of traditional single phase auto-reclosures that usually are not intelligent, it is necessary to calculate the dead time in the off-line condition precisely. If the dead time used in adjustment of single phase auto-reclosure is less than the real dead time, the reclosing of circuit breakers threats the power systems seriously. So in this paper a novel approach for precise calculation of dead time in power transmission lines based on the network equivalencing in time domain is presented. This approach has extremely higher precision in comparison with the traditional method based on Thevenin equivalent circuit. For comparison between the proposed approach in this paper and the traditional method, a comprehensive simulation by EMTP-ATP is performed on an extensive power network.
Keywords: Dead Time, Network Equivalencing, High Voltage Transmission Lines, Single Phase Auto-Reclosure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1571258 Forecast of the Small Wind Turbines Sales with Replacement Purchases and with or without Account of Price Changes
Authors: V. Churkin, M. Lopatin
Abstract:
The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1873257 Investigations on the Influence of Optimized Charge Air Cooling for a Diesel Passenger Car
Authors: Christian Doppler, Gernot Hirschl, Gerhard Zsiga
Abstract:
Starting in 2020, an EU-wide CO2-limitation of 95 g/km is scheduled for the average of an OEMs passenger car fleet. Taking that into consideration additional improvement measures of the Diesel cycle are necessary in order to reduce fuel consumption and emissions while boosting, or at the least, keeping performance values at the same time. The present article deals with the possibilities of an optimized air/water charge air cooler, also called iCAC (indirect Charge Air Cooler) for a Diesel passenger car amongst extreme-boundary conditions. In this context, the precise objective was to show the impact of improved intercooling with reference to the engine working process (fuel consumption and NOx-emissions). Several extremeboundaries - e.g. varying ambient temperatures or mountainous routes - that will become very important in the near future regarding RDE (Real Driving emissions) were subject of the investigation. With the introduction of RDE in 2017 (EU6c measure), the controversial NEDC (New European Driving Cycle) will belong to the past and the OEMs will have to avoid harmful emissions in any conceivable real life situation. This is certainly going to lead to optimization-measurements at the powertrain, which again is going to make the implementation of iCACs, presently solely used for the premium class, more and more attractive for compact class cars. The investigations showed a benefit in FC between 1 and 3% for the iCAC in real world conditions.
Keywords: Air/Water-Charge Air Cooler, Co-Simulation, Diesel Working Process, EURO VI Fuel Consumption.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2898256 Exploring Additional Intention Predictors within Dietary Behavior among Type 2 Diabetes
Authors: D. O. Omondi, M. K. Walingo, G. M. Mbagaya
Abstract:
Objective: This study explored the possibility of integrating Health Belief Concepts as additional predictors of intention to adopt a recommended diet-category within the Theory of Planned Behavior (TPB). Methods: The study adopted a Sequential Exploratory Mixed Methods approach. Qualitative data were generated on attitude, subjective norm, perceived behavioral control and perceptions on predetermined diet-categories including perceived susceptibility, perceived benefits, perceived severity and cues to action. Synthesis of qualitative data was done using constant comparative approach during phase 1. A survey tool developed from qualitative results was used to collect information on the same concepts across 237 legible Type 2 diabetics. Data analysis included use of Structural Equation Modeling in Analysis of Moment Structures to explore the possibility of including perceived susceptibility, perceived benefits, perceived severity and cues to action as additional intention predictors in a single nested model. Results: Two models-one nested based on the traditional TPB model {χ2=223.3, df = 77, p = .02, χ2/df = 2.9; TLI = .93; CFI =.91; RMSEA (90CI) = .090(.039, .146)} and the newly proposed Planned Behavior Health Belief Model (PBHB) {χ2 = 743.47, df = 301, p = .019; TLI = .90; CFI=.91; RMSEA (90CI) = .079(.031, .14)} passed the goodness of fit tests based on common fit indicators used. Conclusion: The newly developed PBHB Model ranked higher than the traditional TPB model with reference made to chi-square ratios (PBHB: χ2/df = 2.47; p=0.19 against TPB: χ2/df = 2.9, p=0.02). The integrated model can be used to motivate Type 2 diabetics towards healthy eating.
Keywords: Theory, intention, predictors, mixed methods design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1403255 Comparing Field Displacement History with Numerical Results to Estimate Geotechnical Parameters: Case Study of Arash-Esfandiar-Niayesh under Passing Tunnel, 2.5 Traffic Lane Tunnel, Tehran, Iran
Authors: A. Golshani, M. Gharizade Varnusefaderani, S. Majidian
Abstract:
Underground structures are of those structures that have uncertainty in design procedures. That is due to the complexity of soil condition around. Under passing tunnels are also such affected structures. Despite geotechnical site investigations, lots of uncertainties exist in soil properties due to unknown events. As results, it possibly causes conflicting settlements in numerical analysis with recorded values in the project. This paper aims to report a case study on a specific under passing tunnel constructed by New Austrian Tunnelling Method in Iran. The intended tunnel has an overburden of about 11.3m, the height of 12.2m and, the width of 14.4m with 2.5 traffic lane. The numerical modeling was developed by a 2D finite element program (PLAXIS Version 8). Comparing displacement histories at the ground surface during the entire installation of initial lining, the estimated surface settlement was about four times the field recorded one, which indicates that some local unknown events affect that value. Also, the displacement ratios were in a big difference between the numerical and field data. Consequently, running several numerical back analyses using laboratory and field tests data, the geotechnical parameters were accurately revised to match with the obtained monitoring data. Finally, it was found that usually the values of soil parameters are conservatively low-estimated up to 40 percent by typical engineering judgment. Additionally, it could be attributed to inappropriate constitutive models applied for the specific soil condition.
Keywords: NATM, surface displacement history, soil tests, monitoring data, numerical back-analysis, geotechnical parameters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 782254 Development of EPID-based Real time Dose Verification for Dynamic IMRT
Authors: Todsaporn Fuangrod, Daryl J. O'Connor, Boyd MC McCurdy, Peter B. Greer
Abstract:
An electronic portal image device (EPID) has become a method of patient-specific IMRT dose verification for radiotherapy. Research studies have focused on pre and post-treatment verification, however, there are currently no interventional procedures using EPID dosimetry that measure the dose in real time as a mechanism to ensure that overdoses do not occur and underdoses are detected as soon as is practically possible. As a result, an EPID-based real time dose verification system for dynamic IMRT was developed and was implemented with MATLAB/Simulink. The EPID image acquisition was set to continuous acquisition mode at 1.4 images per second. The system defined the time constraint gap, or execution gap at the image acquisition time, so that every calculation must be completed before the next image capture is completed. In addition, the <=-evaluation method was used for dose comparison, with two types of comparison processes; individual image and cumulative dose comparison monitored. The outputs of the system are the <=-map, the percent of <=<1, and mean-<= versus time, all in real time. Two strategies were used to test the system, including an error detection test and a clinical data test. The system can monitor the actual dose delivery compared with the treatment plan data or previous treatment dose delivery that means a radiation therapist is able to switch off the machine when the error is detected.Keywords: real-time dose verification, EPID dosimetry, simulation, dynamic IMRT
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2175253 The Application of Real Options to Capital Budgeting
Authors: George Yungchih Wang
Abstract:
Real options theory suggests that managerial flexibility embedded within irreversible investments can account for a significant value in project valuation. Although the argument has become the dominant focus of capital investment theory over decades, yet recent survey literature in capital budgeting indicates that corporate practitioners still do not explicitly apply real options in investment decisions. In this paper, we explore how real options decision criteria can be transformed into equivalent capital budgeting criteria under the consideration of uncertainty, assuming that underlying stochastic process follows a geometric Brownian motion (GBM), a mixed diffusion-jump (MX), or a mean-reverting process (MR). These equivalent valuation techniques can be readily decomposed into conventional investment rules and “option impacts", the latter of which describe the impacts on optimal investment rules with the option value considered. Based on numerical analysis and Monte Carlo simulation, three major findings are derived. First, it is shown that real options could be successfully integrated into the mindset of conventional capital budgeting. Second, the inclusion of option impacts tends to delay investment. It is indicated that the delay effect is the most significant under a GBM process and the least significant under a MR process. Third, it is optimal to adopt the new capital budgeting criteria in investment decision-making and adopting a suboptimal investment rule without considering real options could lead to a substantial loss in value.
Keywords: real options, capital budgeting, geometric Brownianmotion, mixed diffusion-jump, mean-reverting process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2754252 Dicotyledon Weed Quantification Algorithm for Selective Herbicide Application in Maize Crops: Statistical Evaluation of the Potential Herbicide Savings
Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Henrik Skov Midtiby, Anders Krogh Mortensen, Sanmohan Baby
Abstract:
This work contributes a statistical model and simulation framework yielding the best estimate possible for the potential herbicide reduction when using the MoDiCoVi algorithm all the while requiring a efficacy comparable to conventional spraying. In June 2013 a maize field located in Denmark were seeded. The field was divided into parcels which was assigned to one of two main groups: 1) Control, consisting of subgroups of no spray and full dose spraty; 2) MoDiCoVi algorithm subdivided into five different leaf cover thresholds for spray activation. In addition approximately 25% of the parcels were seeded with additional weeds perpendicular to the maize rows. In total 299 parcels were randomly assigned with the 28 different treatment combinations. In the statistical analysis, bootstrapping was used for balancing the number of replicates. The achieved potential herbicide savings was found to be 70% to 95% depending on the initial weed coverage. However additional field trials covering more seasons and locations are needed to verify the generalisation of these results. There is a potential for further herbicide savings as the time interval between the first and second spraying session was not long enough for the weeds to turn yellow, instead they only stagnated in growth.Keywords: Weed crop discrimination, macrosprayer, herbicide reduction, site-specific, sprayer-boom.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1037251 A Concept to Assess the Economic Importance of the On-Site Activities of ETICS
Authors: V. Sulakatko, F. U. Vogdt, I. Lill
Abstract:
Construction technology and on-site construction activities have a direct influence on the life cycle costs of energy efficiently renovated apartment buildings. The systematic inadequacies of the External Thermal Insulation Composite System (ETICS) which occur during the construction phase increase the risk for all stakeholders, reduce mechanical durability and increase the life cycle costs of the building. The economic effect of these shortcomings can be minimised if the risk of the most significant on-site activities is recognised. The objective of the presented ETICS economic assessment concept is to evaluate the economic influence of on-site shortcomings and reveal their significance to the foreseeable future repair costs. The model assembles repair techniques, discusses their direct cost calculation methods, argues over the proper usage of net present value over the life cycle of the building, and proposes a simulation tool to evaluate the risk of on-site activities. As the technique is dependent on the selected real interest rate, a sensitivity analysis is anticipated to determine the validity of the recommendations. After the verification of the model on the sample buildings by the industry, it is expected to increase economic rationality of resource allocation and reduce high-risk systematic shortcomings during the construction process of ETICS.
Keywords: Activity-based cost estimating, Cost estimation, ETICS, Life cycle costing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 814250 Fast Painting with Different Colors Using Cross Correlation in the Frequency Domain
Authors: Hazem M. El-Bakry
Abstract:
In this paper, a new technique for fast painting with different colors is presented. The idea of painting relies on applying masks with different colors to the background. Fast painting is achieved by applying these masks in the frequency domain instead of spatial (time) domain. New colors can be generated automatically as a result from the cross correlation operation. This idea was applied successfully for faster specific data (face, object, pattern, and code) detection using neural algorithms. Here, instead of performing cross correlation between the input input data (e.g., image, or a stream of sequential data) and the weights of neural networks, the cross correlation is performed between the colored masks and the background. Furthermore, this approach is developed to reduce the computation steps required by the painting operation. The principle of divide and conquer strategy is applied through background decomposition. Each background is divided into small in size subbackgrounds and then each sub-background is processed separately by using a single faster painting algorithm. Moreover, the fastest painting is achieved by using parallel processing techniques to paint the resulting sub-backgrounds using the same number of faster painting algorithms. In contrast to using only faster painting algorithm, the speed up ratio is increased with the size of the background when using faster painting algorithm and background decomposition. Simulation results show that painting in the frequency domain is faster than that in the spatial domain.Keywords: Fast Painting, Cross Correlation, Frequency Domain, Parallel Processing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1783249 An ACO Based Algorithm for Distribution Networks Including Dispersed Generations
Authors: B. Bahmani Firouzi, T. Niknam, M. Nayeripour
Abstract:
With Power system movement toward restructuring along with factors such as life environment pollution, problems of transmission expansion and with advancement in construction technology of small generation units, it is expected that small units like wind turbines, fuel cells, photovoltaic, ... that most of the time connect to the distribution networks play a very essential role in electric power industry. With increase in developing usage of small generation units, management of distribution networks should be reviewed. The target of this paper is to present a new method for optimal management of active and reactive power in distribution networks with regard to costs pertaining to various types of dispersed generations, capacitors and cost of electric energy achieved from network. In other words, in this method it-s endeavored to select optimal sources of active and reactive power generation and controlling equipments such as dispersed generations, capacitors, under load tapchanger transformers and substations in a way that firstly costs in relation to them are minimized and secondly technical and physical constraints are regarded. Because the optimal management of distribution networks is an optimization problem with continuous and discrete variables, the new evolutionary method based on Ant Colony Algorithm has been applied. The simulation results of the method tested on two cases containing 23 and 34 buses exist and will be shown at later sections.
Keywords: Distributed Generation, Optimal Operation Management of distribution networks, Ant Colony Optimization(ACO).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1694248 DC Bus Voltage Regulator for Renewable Energy Based Microgrid Application
Authors: Bakari M. M. Mwinyiwiwa
Abstract:
Renewable Energy based microgrids are being considered to provide electricity for the expanding energy demand in the grid distribution network and grid isolated areas. The technical challenges associated with the operation and controls are immense. Electricity generation by Renewable Energy Sources is of stochastic nature such that there is a demand for regulation of voltage output in order to satisfy the standard loads’ requirements. In a renewable energy based microgrid, the energy sources give stochastically variable magnitude AC or DC voltages. AC voltage regulation of micro and mini sources pose practical challenges as well as unbearable costs. It is therefore practically and economically viable to convert the voltage outputs from stochastic AC and DC voltage sources to constant DC voltage to satisfy various DC loads including inverters which ultimately feed AC loads. This paper presents results obtained from SEPIC converter based DC bus voltage regulator as a case study for renewable energy microgrid application. Real-Time Simulation results show that upon appropriate choice of controller parameters for control of the SEPIC converter, the output DC bus voltage can be kept constant regardless of wide range of voltage variations of the source. This feature is particularly important in the situation that multiple renewable sources are to be integrated to supply a microgrid under main grid integration or isolated modes of operation.
Keywords: DC Voltage Regulator, microgrid, multisource, Renewable Energy, SEPIC Converter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4300247 Modeling of Radiative Heat Transfer in 2D Complex Heat Recuperator of Biomass Pyrolysis Furnace: A Study of Baffles Shadow and Soot Volume Fraction Effects
Authors: Mohamed Ammar Abbassi, Kamel Guedri, Mohamed Naceur Borjini, Kamel Halouani, Belkacem Zeghmati
Abstract:
The radiative heat transfer problem is investigated numerically for 2D complex geometry biomass pyrolysis reactor composed of two pyrolysis chambers and a heat recuperator. The fumes are a mixture of carbon dioxide and water vapor charged with absorbing and scattering particles and soot. In order to increase gases residence time and heat transfer, the heat recuperator is provided with many inclined, vertical, horizontal, diffuse and grey baffles of finite thickness and has a complex geometry. The Finite Volume Method (FVM) is applied to study radiative heat transfer. The blocked-off region procedure is used to treat the geometrical irregularities. Eight cases are considered in order to demonstrate the effect of adding baffles on the walls of the heat recuperator and on the walls of the pyrolysis rooms then choose the best case giving the maximum heat flux transferred to the biomass in the pyrolysis chambers. Ray effect due to the presence of baffles is studied and demonstrated to have a crucial effect on radiative heat flux on the walls of the pyrolysis rooms. Shadow effect caused by the presence of the baffles is also studied. The non grey radiative heat transfer is studied for the real existent configuration. The Weighted Sum of The Grey Gases (WSGG) Model of Kim and Song is used as non grey model. The effect of soot volumetric fraction on the non grey radiative heat flux is investigated and discussed.
Keywords: Baffles, Blocked-off region procedure, FVM, Heat recuperation, Radiative heat transfer, Shadow effect.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2242246 On the Early Development of Dispersion in Flow through a Tube with Wall Reactions
Abstract:
This is a study on numerical simulation of the convection-diffusion transport of a chemical species in steady flow through a small-diameter tube, which is lined with a very thin layer made up of retentive and absorptive materials. The species may be subject to a first-order kinetic reversible phase exchange with the wall material and irreversible absorption into the tube wall. Owing to the velocity shear across the tube section, the chemical species may spread out axially along the tube at a rate much larger than that given by the molecular diffusion; this process is known as dispersion. While the long-time dispersion behavior, well described by the Taylor model, has been extensively studied in the literature, the early development of the dispersion process is by contrast much less investigated. By early development, that means a span of time, after the release of the chemical into the flow, that is shorter than or comparable to the diffusion time scale across the tube section. To understand the early development of the dispersion, the governing equations along with the reactive boundary conditions are solved numerically using the Flux Corrected Transport Algorithm (FCTA). The computation has enabled us to investigate the combined effects on the early development of the dispersion coefficient due to the reversible and irreversible wall reactions. One of the results is shown that the dispersion coefficient may approach its steady-state limit in a short time under the following conditions: (i) a high value of Damkohler number (say Da ≥ 10); (ii) a small but non-zero value of absorption rate (say Γ* ≤ 0.5).
Keywords: Dispersion coefficient, early development of dispersion, FCTA, wall reactions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1333245 Elastic-Plastic Contact Analysis of Single Layer Solid Rough Surface Model using FEM
Authors: A. Megalingam, M.M.Mayuram
Abstract:
Evaluation of contact pressure, surface and subsurface contact stresses are essential to know the functional response of surface coatings and the contact behavior mainly depends on surface roughness, material property, thickness of layer and the manner of loading. Contact parameter evaluation of real rough surface contacts mostly relies on statistical single asperity contact approaches. In this work, a three dimensional layered solid rough surface in contact with a rigid flat is modeled and analyzed using finite element method. The rough surface of layered solid is generated by FFT approach. The generated rough surface is exported to a finite element method based ANSYS package through which the bottom up solid modeling is employed to create a deformable solid model with a layered solid rough surface on top. The discretization and contact analysis are carried by using the same ANSYS package. The elastic, elastoplastic and plastic deformations are continuous in the present finite element method unlike many other contact models. The Young-s modulus to yield strength ratio of layer is varied in the present work to observe the contact parameters effect while keeping the surface roughness and substrate material properties as constant. The contacting asperities attain elastic, elastoplastic and plastic states with their continuity and asperity interaction phenomena is inherently included. The resultant contact parameters show that neighboring asperity interaction and the Young-s modulus to yield strength ratio of layer influence the bulk deformation consequently affect the interface strength.Keywords: Asperity interaction, finite element method, rough surface contact, single layered solid
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2724