Search results for: Optimized output.
834 Turbine Speed Variation Study in Gas Power Plant for an Active Generator
Authors: R. Kazemzadeh, J. M. Kauffmann
Abstract:
This research deals with investigations on the “Active Generator" under rotor speed variations and output frequency control. It runs at turbine speed and it is connected to a three phase electrical power grid which has its own frequency different from turbine frequency. In this regard the set composed of a four phase synchronous generator and a natural commutated matrix converter (NCMC) made with thyristors, is called active generator. It replaces a classical mechanical gearbox which introduces many drawbacks. The main idea in this article is the presentation of frequency control at grid side when turbine runs at variable speed. Frequency control has been done by linear and step variations of the turbine speed. Relation between turbine speed (frequency) and main grid zero sequence voltage frequency is presented.Keywords: Power Generation, Energy Conversion, FrequencyControl, Matrix Converter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1895833 Mathematical Modeling of Asphaltene Precipitation: A Review
Authors: Josefina Barnachea Janier, Radzuan B. Razali, Afza Shafie, Brahim Belhaouari Samir
Abstract:
In the Enhanced Oil Recovery (EOR) method, use of Carbon dioxide flooding whereby CO2 is injected into an oil reservoir to increase output when extracting oil resulted significant recovery worldwide. The carbon dioxide function as a pressurizing agent when mixed into the underground crude oil will reduce its viscosity and will enable a rapid oil flow. Despite the CO2’s advantage in the oil recovery, it may result to asphaltene precipitation a problem that will cause the reduction of oil produced from oil wells. In severe cases, asphaltene precipitation can cause costly blockages in oil pipes and machinery. This paper presents reviews of several studies done on mathematical modeling of asphaltene precipitation. The synthesized result from several researches done on this topic can be used as guide in order to better understand asphaltene precipitation. Likewise, this can be used as initial reference for students, and new researchers doing study on asphaltene precipitation.
Keywords: Asphaltene precipitation, crude oil, carbon dioxide flooding, enhanced oil recovery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3995832 A New Controlling Parameter in Design of Above Knee Prosthesis
Abstract:
In this paper after reviewing some previous studies, in order to optimize the above knee prosthesis, beside the inertial properties a new controlling parameter is informed. This controlling parameter makes the prosthesis able to act as a multi behavior system when the amputee is opposing to different environments. This active prosthesis with the new controlling parameter can simplify the control of prosthesis and reduce the rate of energy consumption in comparison to recently presented similar prosthesis “Agonistantagonist active knee prosthesis". In this paper three models are generated, a passive, an active, and an optimized active prosthesis. Second order Taylor series is the numerical method in solution of the models equations and the optimization procedure is genetic algorithm. Modeling the prosthesis which comprises this new controlling parameter (SEP) during the swing phase represents acceptable results in comparison to natural behavior of shank. Reported results in this paper represent 3.3 degrees as the maximum deviation of models shank angle from the natural pattern. The natural gait pattern belongs to walking at the speed of 81 m/min.Keywords: Above knee prosthesis, active controlling parameter, ballistic motion, swing phase.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1871831 A Hybrid Model of ARIMA and Multiple Polynomial Regression for Uncertainties Modeling of a Serial Production Line
Authors: Amir Azizi, Amir Yazid b. Ali, Loh Wei Ping, Mohsen Mohammadzadeh
Abstract:
Uncertainties of a serial production line affect on the production throughput. The uncertainties cannot be prevented in a real production line. However the uncertain conditions can be controlled by a robust prediction model. Thus, a hybrid model including autoregressive integrated moving average (ARIMA) and multiple polynomial regression, is proposed to model the nonlinear relationship of production uncertainties with throughput. The uncertainties under consideration of this study are demand, breaktime, scrap, and lead-time. The nonlinear relationship of production uncertainties with throughput are examined in the form of quadratic and cubic regression models, where the adjusted R-squared for quadratic and cubic regressions was 98.3% and 98.2%. We optimized the multiple quadratic regression (MQR) by considering the time series trend of the uncertainties using ARIMA model. Finally the hybrid model of ARIMA and MQR is formulated by better adjusted R-squared, which is 98.9%.Keywords: ARIMA, multiple polynomial regression, production throughput, uncertainties
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2198830 Mode-Locked Fiber Laser Using Charcoal and Graphene Saturable Absorbers to Generate 20-GHz and 50-GHz Pulse Trains, Respectively
Authors: Ashiq Rahman, Sunil Thapa, Shunyao Fan, Niloy K. Dutta
Abstract:
A 20-GHz and a 50-GHz pulse train are generated using a fiber ring laser setup that incorporates rational harmonic mode-locking (RHML). Two separate experiments were carried out using charcoal nanoparticles and graphene nanoparticles acting as saturable absorbers to reduce the pulse width generated from RHML. Autocorrelator trace shows that the pulse width is reduced from 5.6 ps to 3.2 ps using charcoal at 20 GHz, and to 2.7 ps using graphene at 50-GHz repetition rates, which agrees with the simulation findings. Numerical simulations have been carried out to study the effect of varying the linear and nonlinear absorbance parameters of both absorbers on output pulse widths. Experiments closely agree with the simulations.
Keywords: Fiber optics, fiber lasers, mode locking, saturable absorbers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 261829 Performance Enhancement of Cellular OFDM Based Wireless LANs by Exploiting Spatial Diversity Techniques
Authors: S. Ali. Tajer, Babak H. Khalaj
Abstract:
This paper represents an investigation on how exploiting multiple transmit antennas by OFDM based wireless LAN subscribers can mitigate physical layer error rate. Then by comparing the Wireless LANs that utilize spatial diversity techniques with the conventional ones it will reveal how PHY and TCP throughputs behaviors are ameliorated. In the next step it will assess the same issues based on a cellular context operation which is mainly introduced as an innovated solution that beside a multi cell operation scenario benefits spatio-temporal signaling schemes as well. Presented simulations will shed light on the improved performance of the wide range and high quality wireless LAN services provided by the proposed approach.
Keywords: Multiple Input Multiple Output (MIMO), Orthogonal Frequency Division Multiplexing (OFDM), and WirelessLocal Area Network (WLAN).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1401828 Design Optimization of Cutting Parameters when Turning Inconel 718 with Cermet Inserts
Authors: M. Aruna, V. Dhanalaksmi
Abstract:
Inconel 718, a nickel based super-alloy is an extensively used alloy, accounting for about 50% by weight of materials used in an aerospace engine, mainly in the gas turbine compartment. This is owing to their outstanding strength and oxidation resistance at elevated temperatures in excess of 5500 C. Machining is a requisite operation in the aircraft industries for the manufacture of the components especially for gas turbines. This paper is concerned with optimization of the surface roughness when turning Inconel 718 with cermet inserts. Optimization of turning operation is very useful to reduce cost and time for machining. The approach is based on Response Surface Method (RSM). In this work, second-order quadratic models are developed for surface roughness, considering the cutting speed, feed rate and depth of cut as the cutting parameters, using central composite design. The developed models are used to determine the optimum machining parameters. These optimized machining parameters are validated experimentally, and it is observed that the response values are in reasonable agreement with the predicted values.Keywords: Inconel 718, Optimization, Response Surface Methodology (RSM), Surface roughness
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2837827 Non-Sensitive Solutions in Multi-Objective Optimization of a Solar Photovoltaic/Thermal(PV/T) Air Collector
Authors: F. Sarhaddi, S. Farahat, M .A. Alavi, F. Sobhnamayan
Abstract:
In this paper, an attempt has been made to obtain nonsensitive solutions in the multi-objective optimization of a photovoltaic/thermal (PV/T) air collector. The selected objective functions are overall energy efficiency and exergy efficiency. Improved thermal, electrical and exergy models are used to calculate the thermal and electrical parameters, overall energy efficiency, exergy components and exergy efficiency of a typical PV/T air collector. A computer simulation program is also developed. The results of numerical simulation are in good agreement with the experimental measurements noted in the previous literature. Finally, multi-objective optimization has been carried out under given climatic, operating and design parameters. The optimized ranges of inlet air velocity, duct depth and the objective functions in optimal Pareto front have been obtained. Furthermore, non-sensitive solutions from energy or exergy point of view in the results of multi-objective optimization have been shown.Keywords: Solar photovoltaic thermal (PV/T) air collector, Overall energy efficiency, Exergy efficiency, Multi-objectiveoptimization, Sensitivity analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2156826 Frequency-Dependent and Full Range Tunable Phase Shifter
Authors: Yufu Yin, Tao Lin, Shanghong Zhao, Zihang Zhu, Xuan Li, Wei Jiang, Qiurong Zheng, Hui Wang
Abstract:
In this paper, a frequency-dependent and tunable phase shifter is proposed and numerically analyzed. The key devices are the dual-polarization binary phase shift keying modulator (DP-BPSK) and the fiber Bragg grating (FBG). The phase-frequency response of the FBG is employed to determine the frequency-dependent phase shift. The simulation results show that a linear phase shift of the recovered output microwave signal which depends on the frequency of the input RF signal is achieved. In addition, by adjusting the power of the RF signal, the full range phase shift from 0° to 360° can be realized. This structure shows the spurious free dynamic range (SFDR) of 70.90 dB·Hz2/3 and 72.11 dB·Hz2/3 under different RF powers.
Keywords: Microwave photonics, phase shifter, spurious free dynamic range, frequency-dependent.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1068825 Nonlinear Adaptive PID Control for a Semi-Batch Reactor Based On an RBF Network
Authors: Magdi M. Nabi, Ding-Li Yu
Abstract:
Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.
Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward and feedback control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2675824 Low Cost Chip Set Selection Algorithm for Multi-way Partitioning of Digital System
Authors: Jae Young Park, Soongyu Kwon, Kyu Han Kim, Hyeong Geon Lee, Jong Tae Kim
Abstract:
This paper considers the problem of finding low cost chip set for a minimum cost partitioning of a large logic circuits. Chip sets are selected from a given library. Each chip in the library has a different price, area, and I/O pin. We propose a low cost chip set selection algorithm. Inputs to the algorithm are a netlist and a chip information in the library. Output is a list of chip sets satisfied with area and maximum partitioning number and it is sorted by cost. The algorithm finds the sorted list of chip sets from minimum cost to maximum cost. We used MCNC benchmark circuits for experiments. The experimental results show that all of chip sets found satisfy the multiple partitioning constraints.Keywords: lowest cost chip set, MCNC benchmark, multi-way partitioning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1502823 A New Floating Point Implementation of Base 2 Logarithm
Authors: Ahmed M. Mansour, Ali M. El-Sawy, Ahmed T Sayed
Abstract:
Logarithms reduce products to sums and powers to products; they play an important role in signal processing, communication and information theory. They are primarily used for hardware calculations, handling multiplications, divisions, powers, and roots effectively. There are three commonly used bases for logarithms; the logarithm with base-10 is called the common logarithm, the natural logarithm with base-e and the binary logarithm with base-2. This paper demonstrates different methods of calculation for log2 showing the complexity of each and finds out the most accurate and efficient besides giving insights to their hardware design. We present a new method called Floor Shift for fast calculation of log2, and then we combine this algorithm with Taylor series to improve the accuracy of the output, we illustrate that by using two examples. We finally compare the algorithms and conclude with our remarks.
Keywords: Logarithms, log2, floor, iterative, CORDIC, Taylor series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3821822 Optimization of Carbon Nanotube Content of Asphalt Nanocomposites with Regard to Resistance to Permanent Deformation
Authors: João V. Staub de Melo, Glicério Trichês, Liseane P. Thives
Abstract:
This paper presents the results of the development of asphalt nanocomposites containing carbon nanotubes (CNTs) with high resistance to permanent deformation, aiming to increase the performance of asphalt surfaces in relation to the rutting problem. Asphalt nanocomposites were prepared with the addition of different proportions of CNTs (1%, 2% and 3%) in relation to the weight of asphalt binder. The base binder used was a conventional binder (50-70 penetration) classified as PG 58-22. The optimum percentage of CNT addition in the asphalt binder (base) was determined through the evaluation of the rheological and empirical characteristics of the nanocomposites produced. In order to evaluate the contribution and the effects of the nanocomposite (optimized) in relation to the rutting, the conventional and nanomodified asphalt mixtures were tested in a French traffic simulator (Orniéreur). The results obtained demonstrate the efficient contribution of the asphalt nanocomposite containing CNTs to the resistance to permanent deformation of the asphalt mixture.
Keywords: Asphalt nanocomposites, asphalt mixtures, carbon nanotubes, nanotechnology, permanent deformation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1488821 Piezoelectric Approach on Harvesting Acoustic Energy
Authors: Khin Fai Chen, Jee-Hou Ho, Eng Hwa Yap
Abstract:
An Acoustic Micro-Energy Harvester (AMEH) is developed to convert wasted acoustical energy into useful electrical energy. AMEH is mathematically modeled using Lumped Element Modelling (LEM) and Euler-Bernoulli beam (EBB) modelling. An experiment is designed to validate the mathematical model and assess the feasibility of AMEH. Comparison of theoretical and experimental data on critical parameter value such as Mm, Cms, dm and Ceb showed the variances are within 1% to 6%, which is reasonably acceptable. Then, AMEH undergoes bandwidth tuning for performance optimization. The AMEH successfully produces 0.9V/(m/s^2) and 1.79μW/(m^2/s^4) at 60Hz and 400kΩ resistive load which only show variances about 7% compared to theoretical data. At 1g and 60Hz resonance frequency, the averaged power output is about 2.2mW which fulfilled a range of wireless sensors and communication peripherals power requirements. Finally, the design for AMEH is assessed, validated and deemed as a feasible design.Keywords: Piezoelectric, acoustic, energy harvester, thermoacoustic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3271820 Analysis and Measuring Surface Roughness of Nonwovens Using Machine Vision Method
Authors: Dariush Semnani, Javad Yekrang, Hossein Ghayoor
Abstract:
Concerning the measurement of friction properties of textiles and fabrics using Kawabata Evaluation System (KES), whose output is constrained to the surface friction factor of fabric, and no other data would be generated; this research has been conducted to gain information about surface roughness regarding its surface friction factor. To assess roughness properties of light nonwovens, a 3-dimensional model of a surface has been simulated with regular sinuous waves through it as an ideal surface. A new factor was defined, namely Surface Roughness Factor, through comparing roughness properties of simulated surface and real specimens. The relation between the proposed factor and friction factor of specimens has been analyzed by regression, and results showed a meaningful correlation between them. It can be inferred that the new presented factor can be used as an acceptable criterion for evaluating the roughness properties of light nonwoven fabrics.Keywords: Surface roughness, Nonwoven, Machine vision, Image processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3090819 A Double Differential Chaos Shift Keying Scheme for Ultra-Wideband Chaotic Communication Technology Applied in Low-Rate Wireless Personal Area Network
Authors: Ghobad Gorji, Hasan Golabi
Abstract:
The goal of this paper is to describe the design of an ultra-wideband (UWB) system that is optimized for the low-rate wireless personal area network application. To this aim, we propose a system based on direct chaotic communication (DCC) technology. Based on this system, a 2-GHz wide chaotic signal is produced into the UWB spectrum lower band, i.e., 3.1–5.1 GHz. For this system, two simple modulation schemes, namely chaotic on-off keying (COOK) and differential chaos shift keying (DCSK) are evaluated first. We propose a modulation scheme, namely Double DCSK, to improve the performance of UWB DCC. Different characteristics of these systems, with Monte Carlo simulations based on the Additive White Gaussian Noise (AWGN) and the IEEE 802.15.4a standard channel models, are compared.
Keywords: Ultra-wideband, UWB, Direct Chaotic Communication, DCC, IEEE 802.15.4a, COOK, DCSK.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 207818 Optimal Choice and Location of Multi Type Facts Devices in Deregulated Electricity Market Using Evolutionary Programming Method
Authors: K. Balamurugan, R. Muralisachithanandam, V. Dharmalingam, R. Srikanth
Abstract:
This paper deals with the optimal choice and allocation of multi FACTS devices in Deregulated power system using Evolutionary Programming method. The objective is to achieve the power system economic generation allocation and dispatch in deregulated electricity market. Using the proposed method, the locations of the FACTS devices, their types and ratings are optimized simultaneously. Different kinds of FACTS devices are simulated in this study such as UPFC, TCSC, TCPST, and SVC. Simulation results validate the capability of this new approach in minimizing the overall system cost function, which includes the investment costs of the FACTS devices and the bid offers of the market participants. The proposed algorithm is an effective and practical method for the choice and allocation of FACTS devices in deregulated electricity market environment. The standard data of IEEE 14 Bus systems has been taken into account and simulated with aid of MAT-lab software and results were obtained.
Keywords: FACTS devices, Optimal allocation, Deregulated electricity market, Evolutionary programming, Mat Lab.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2317817 Monitoring of Spectrum Usage and Signal Identification Using Cognitive Radio
Authors: O. S. Omorogiuwa, E. J. Omozusi
Abstract:
The monitoring of spectrum usage and signal identification, using cognitive radio, is done to identify frequencies that are vacant for reuse. It has been established that ‘internet of things’ device uses secondary frequency which is free, thereby facing the challenge of interference from other users, where some primary frequencies are not being utilised. The design was done by analysing a specific frequency spectrum, checking if all the frequency stations that range from 87.5-108 MHz are presently being used in Benin City, Edo State, Nigeria. From the results, it was noticed that by using Software Defined Radio/Simulink, we were able to identify vacant frequencies in the range of frequency under consideration. Also, we were able to use the significance of energy detection threshold to reuse this vacant frequency spectrum, when the cognitive radio displays a zero output (that is decision H0), meaning that the channel is unoccupied. Hence, the analysis was able to find the spectrum hole and identify how it can be reused.
Keywords: Spectrum, interference, telecommunication, cognitive radio, frequency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 861816 Comprehensive Nonlinearity Simulation of Different Types and Modes of HEMTs with Respect to Biasing Conditions
Authors: M. M. Karkhanehchi, A. Ammani
Abstract:
A simple analytical model has been developed to optimize biasing conditions for obtaining maximum linearity among lattice-matched, pseudomorphic and metamorphic HEMT types as well as enhancement and depletion HEMT modes. A nonlinear current-voltage model has been simulated based on extracted data to study and select the most appropriate type and mode of HEMT in terms of a given gate-source biasing voltage within the device so as to employ the circuit for the highest possible output current or voltage linear swing. Simulation results can be used as a basis for the selection of optimum gate-source biasing voltage for a given type and mode of HEMT with regard to a circuit design. The consequences can also be a criterion for choosing the optimum type or mode of HEMT for a predetermined biasing condition.Keywords: Biasing, characteristic, linearity, simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1499815 Low NOx Combustion of Pulverized Petroleum Cokes
Authors: Sewon Kim, Minjun Kwon, Changyeop Lee
Abstract:
This paper is aimed to study combustion characteristics of low NOx burner using petroleum cokes as fuel. The petroleum coke, which is produced through the oil refining process, is an attractive fuel in terms of its high heating value and low price. But petroleum coke is a challenging fuel because of its low volatile content, high sulfur and nitrogen content, which give rise to undesirable emission characteristics and low ignitability. Therefore, the research and development regarding the petroleum coke burner is needed for applying this industrial system. In this study, combustion and emission characteristics of petroleum cokes burner are experimentally investigated in an industrial steam boiler. The low NOx burner is designed to control fuel and air mixing to achieve staged combustion, which, in turn reduces both flame temperature and oxygen. Air distribution ratio of triple staged air is optimized experimentally. The result showed that NOx concentration is lowest when overfire air is used, and the burner function at a fuel rich condition. That is, the burner is operated at the equivalence ratio of 1.67 and overall equivalence ratio including overfire air is kept 0.87.Keywords: Petroleum cokes, Staged combustion, Low NOx, Equivalence ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2179814 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques
Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas
Abstract:
The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.
Keywords: Artificial neural network, competitive dynamics, logistic regression, text classification, text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 533813 Effects of Sprint Training on Athletic Performance Related Physiological, Cardiovascular, and Neuromuscular Parameters
Authors: Asim Cengiz, Dede Basturk, Hakan Ozalp
Abstract:
Practicing recurring resistance workout such as may cause changes in human muscle. These changes may be because combination if several factors determining physical fitness. Thus, it is important to identify these changes. Several studies were reviewed to investigate these changes. As a result, the changes included positive modifications in amplified citrate synthase (CS) maximal activity, increased capacity for pyruvate oxidation, improvement on molecular signaling on human performance, amplified resting muscle glycogen and whole GLUT4 protein content, better health outcomes such as enhancement in cardiorespiratory fitness. Sprint training also have numerous long long-term changes inhuman body such as better enzyme action, changes in muscle fiber and oxidative ability. This is important because SV is the critical factor influencing maximal cardiac output and therefore oxygen delivery and maximal aerobic power.
Keywords: Sprint, training, performance, exercise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 906812 An Optimization Model for Natural Gas Supply Chain through a Cost Approach under Uncertainty
Abstract:
Natural gas, as one of the most important sources of energy for many of the industrial and domestic users all over the world, has a complex, huge supply chain which is in need of heavy investments in all the phases of exploration, extraction, production, transportation, storage and distribution. The main purpose of supply chain is to meet customers’ need efficiently and with minimum cost. In this study, with the aim of minimizing economic costs, different levels of natural gas supply chain in the form of a multi-echelon, multi-period fuzzy linear programming have been modeled. In this model, different constraints including constraints on demand satisfaction, capacity, input/output balance and presence/absence of a path have been defined. The obtained results suggest efficiency of the recommended model in optimal allocation and reduction of supply chain costs.
Keywords: Cost Approach, Fuzzy Theory, Linear Programming, Natural Gas Supply Chain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2520811 Stability of Stochastic Model Predictive Control for Schrödinger Equation with Finite Approximation
Authors: Tomoaki Hashimoto
Abstract:
Recent technological advance has prompted significant interest in developing the control theory of quantum systems. Following the increasing interest in the control of quantum dynamics, this paper examines the control problem of Schrödinger equation because quantum dynamics is basically governed by Schrödinger equation. From the practical point of view, stochastic disturbances cannot be avoided in the implementation of control method for quantum systems. Thus, we consider here the robust stabilization problem of Schrödinger equation against stochastic disturbances. In this paper, we adopt model predictive control method in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. The objective of this study is to derive the stability criterion for model predictive control of Schrödinger equation under stochastic disturbances.Keywords: Optimal control, stochastic systems, quantum systems, stabilization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2353810 Using Radial Basis Function Neural Networks to Calibrate Water Quality Model
Authors: Lihui Ma, Kunlun Xin, Suiqing Liu
Abstract:
Modern managements of water distribution system (WDS) need water quality models that are able to accurately predict the dynamics of water quality variations within the distribution system environment. Before water quality models can be applied to solve system problems, they should be calibrated. Although former researchers use GA solver to calibrate relative parameters, it is difficult to apply on the large-scale or medium-scale real system for long computational time. In this paper a new method is designed which combines both macro and detailed model to optimize the water quality parameters. This new combinational algorithm uses radial basis function (RBF) metamodeling as a surrogate to be optimized for the purpose of decreasing the times of time-consuming water quality simulation and can realize rapidly the calibration of pipe wall reaction coefficients of chlorine model of large-scaled WDS. After two cases study this method is testified to be more efficient and promising, and deserve to generalize in the future.Keywords: Metamodeling, model calibration, radial basisfunction, water distribution system, water quality model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2020809 Sparse Networks-Based Speedup Technique for Proteins Betweenness Centrality Computation
Authors: Razvan Bocu, Dr Sabin Tabirca
Abstract:
The study of proteomics reached unexpected levels of interest, as a direct consequence of its discovered influence over some complex biological phenomena, such as problematic diseases like cancer. This paper presents the latest authors- achievements regarding the analysis of the networks of proteins (interactome networks), by computing more efficiently the betweenness centrality measure. The paper introduces the concept of betweenness centrality, and then describes how betweenness computation can help the interactome net- work analysis. Current sequential implementations for the between- ness computation do not perform satisfactory in terms of execution times. The paper-s main contribution is centered towards introducing a speedup technique for the betweenness computation, based on modified shortest path algorithms for sparse graphs. Three optimized generic algorithms for betweenness computation are described and implemented, and their performance tested against real biological data, which is part of the IntAct dataset.Keywords: Betweenness centrality, interactome networks, protein-protein interactions, sub-communities, sparse networks, speedup tech-nique, IntAct.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1506808 Dissecting Big Trajectory Data to Analyse Road Network Travel Efficiency
Authors: Rania Alshikhe, Vinita Jindal
Abstract:
Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from trav-eling vehicles, such as taxis through installed global positioning sys-tem (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.
Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 508807 Thermal Characterization of Smart and Large-Scale Building Envelope System in a Subtropical Climate
Authors: Andrey A. Chernousov, Ben Y. B. Chan
Abstract:
The thermal behavior of a large-scale, phase change material (PCM) enhanced building envelope system was studied in regard to the need for pre-fabricated construction in subtropical regions. The proposed large-scale envelope consists of a reinforced aluminum skin, insulation core, phase change material and reinforced gypsum board. The PCM impact on an energy efficiency of an enveloped room was resolved by validation of the EnergyPlus numerical scheme and optimization of a smart material location in the core. The PCM location was optimized by a minimization method of a cooling energy demand. It has been shown that there is good agreement between the test and simulation results. The optimal location of the PCM layer in Hong Kong summer conditions has been then recomputed for core thicknesses of 40, 60 and 80 mm. A non-dimensional value of the optimal PCM location was obtained to be same for all the studied cases and the considered external and internal conditions.
Keywords: Thermal performance, phase change material, energy efficiency, PCM optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2227806 Prediction of Bath Temperature Using Neural Networks
Authors: H. Meradi, S. Bouhouche, M. Lahreche
Abstract:
In this work, we consider an application of neural networks in LD converter. Application of this approach assumes a reliable prediction of steel temperature and reduces a reblow ratio in steel work. It has been applied a conventional model to charge calculation, the obtained results by this technique are not always good, this is due to the process complexity. Difficulties are mainly generated by the noisy measurement and the process non linearities. Artificial Neural Networks (ANNs) have become a powerful tool for these complex applications. It is used a backpropagation algorithm to learn the neural nets. (ANNs) is used to predict the steel bath temperature in oxygen converter process for the end condition. This model has 11 inputs process variables and one output. The model was tested in steel work, the obtained results by neural approach are better than the conventional model.
Keywords: LD converter, bath temperature, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1836805 Optimization of Supersonic Ejector via Sequence-Adapted Micro-Genetic Algorithm
Authors: Kolar Jan, Dvorak Vaclav
Abstract:
In this study, an optimization of supersonic air-to-air ejector is carried out by a recently developed single-objective genetic algorithm based on adaption of sequence of individuals. Adaptation of sequence is based on Shape-based distance of individuals and embedded micro-genetic algorithm. The optimal sequence found defines the succession of CFD-aimed objective calculation within each generation of regular micro-genetic algorithm. A spring-based deformation mutates the computational grid starting the initial individualvia adapted population in the optimized sequence. Selection of a generation initial individual is knowledge-based. A direct comparison of the newly defined and standard micro-genetic algorithm is carried out for supersonic air-to-air ejector. The only objective is to minimize the loose of total stagnation pressure in the ejector. The result is that sequence-adopted micro-genetic algorithm can provide comparative results to standard algorithm but in significantly lower number of overall CFD iteration steps.
Keywords: Grid deformation, Micro-genetic algorithm, shapebased sequence, supersonic ejector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1563