Search results for: efficiency optimization
3186 Optimum Working Fluid Selection for Automotive Cogeneration System
Authors: Wonsim Cha, Kibum Kim, Kyungwook Choi, Kihyung Lee
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A co-generation system in automobile can improve thermal efficiency of vehicle in some degree. The waste heat from the engine exhaust and coolant is still attractive energy source that reaches around 60% of the total energy converted from fuel. To maximize the effectiveness of heat exchangers for recovering the waste heat, it is vital to select the most suitable working fluid for the system, not to mention that it is important to find the optimum design for the heat exchangers. The design of heat exchanger is out of scoop of this study; rather, the main focus has been on the right selection of working fluid for the co-generation system. Simulation study was carried out to find the most suitable working fluid that can allow the system to achieve the optimum efficiency in terms of the heat recovery rate and thermal efficiency.Keywords: Cycle Analysis, Heat Recovery, Rankine Cycle, Waste Heat Recovery, Working Fluid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22243185 Data Envelopment Analysis under Uncertainty and Risk
Authors: P. Beraldi, M. E. Bruni
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Data Envelopment Analysis (DEA) is one of the most widely used technique for evaluating the relative efficiency of a set of homogeneous decision making units. Traditionally, it assumes that input and output variables are known in advance, ignoring the critical issue of data uncertainty. In this paper, we deal with the problem of efficiency evaluation under uncertain conditions by adopting the general framework of the stochastic programming. We assume that output parameters are represented by discretely distributed random variables and we propose two different models defined according to a neutral and risk-averse perspective. The models have been validated by considering a real case study concerning the evaluation of the technical efficiency of a sample of individual firms operating in the Italian leather manufacturing industry. Our findings show the validity of the proposed approach as ex-ante evaluation technique by providing the decision maker with useful insights depending on his risk aversion degree.Keywords: DEA, Stochastic Programming, Ex-ante evaluation technique, Conditional Value at Risk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19683184 Enhancing Power Conversion Efficiency of P3HT/PCBM Polymer Solar Cells
Authors: Nidal H. Abu-Zahra, Mahmoud Algazzar
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In this research, n-dodecylthiol was added to P3HT/ PC70BM polymer solar cells to improve the crystallinity of P3HT and enhance the phase separation of P3HT/PC70BM. The improved crystallinity of P3HT:PC70BM doped with 0-5% by volume of n-dodecylthiol resulted in improving the power conversion efficiency of polymer solar cells by 33%. In addition, thermal annealing of the P3HT/PC70MB/n-dodecylthiolcompound showed further improvement in crystallinity with n-dodecylthiol concentration up to 2%. The highest power conversion efficiency of 3.21% was achieved with polymer crystallites size L of 11.2nm, after annealing at 150°C for 30 minutes under a vacuum atmosphere. The smaller crystallite size suggests a shorter path of the charge carriers between P3HT backbones, which could be beneficial to getting a higher short circuit current in the devices made with the additive.
Keywords: n-dodecylthiol, Congugated PSC, P3HT/PCBM, Polymer Solar Cells.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35573183 A Location-Allocation-Routing Model for a Home Health Care Supply Chain Problem
Authors: Amir Mohammad Fathollahi Fard, Mostafa Hajiaghaei-Keshteli, Mohammad Mahdi Paydar
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With increasing life expectancy in developed countries, the role of home care services is highlighted by both academia and industrial contributors in Home Health Care Supply Chain (HHCSC) companies. The main decisions in such supply chain systems are the location of pharmacies, the allocation of patients to these pharmacies and also the routing and scheduling decisions of nurses to visit their patients. In this study, for the first time, an integrated model is proposed to consist of all preliminary and necessary decisions in these companies, namely, location-allocation-routing model. This model is a type of NP-hard one. Therefore, an Imperialist Competitive Algorithm (ICA) is utilized to solve the model, especially in large sizes. Results confirm the efficiency of the developed model for HHCSC companies as well as the performance of employed ICA.
Keywords: Home health care supply chain, location-allocation-routing problem, imperialist competitive algorithm, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10553182 Process Optimization Regarding Geometrical Variation and Sensitivity Involving Dental Drill- and Implant-Guided Surgeries
Authors: T. Kero, R. Söderberg, M. Andersson, L. Lindkvist
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Within dental-guided surgery, there has been a lack of analytical methods for optimizing the treatment of the rehabilitation concepts regarding geometrical variation. The purpose of this study is to find the source of the greatest geometrical variation contributor and sensitivity contributor with the help of virtual variation simulation of a dental drill- and implant-guided surgery process using a methodical approach. It is believed that lower geometrical variation will lead to better patient security and higher quality of dental drill- and implant-guided surgeries. It was found that the origin of the greatest contributor to the most variation, and hence where the foci should be set, in order to minimize geometrical variation was in the assembly category (surgery). This was also the category that was the most sensitive for geometrical variation.Keywords: Variation Simulation, Process Optimization, Guided Surgeries, Dental Prosthesis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12853181 Optimization of Air Pollution Control Model for Mining
Authors: Zunaira Asif, Zhi Chen
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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM2.5, PM10, NOx, and SO2. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NOx and SO2 reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.
Keywords: Air pollution, linear programming, mining, optimization, treatment technologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16073180 School Design and Energy Efficiency
Authors: B. Su
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Auckland has a temperate climate with comfortable warm, dry summers and mild, wet winters. An Auckland school normally does not need air conditioning for cooling during the summer and only need heating during the winter. The space hating energy is the major portion of winter school energy consumption and the winter energy consumption is major portion of annual school energy consumption. School building thermal design should focus on the winter thermal performance for reducing the space heating energy. A number of Auckland schools- design data and energy consumption data are used for this study. This pilot study investigates the relationships between their energy consumption data and school building design data to improve future school design for energy efficiency.Keywords: Building energy efficiency, building thermal performance, school building design, school energy consumption
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18833179 Optimization of Flexible Job Shop Scheduling Problem with Sequence Dependent Setup Times Using Genetic Algorithm Approach
Authors: Sanjay Kumar Parjapati, Ajai Jain
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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.
Keywords: Flexible Job Shop, Genetic Algorithm, Makespan, Sequence Dependent Setup Times.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32943178 Multi-Objective Optimization in End Milling of Al-6061 Using Taguchi Based G-PCA
Authors: M. K. Pradhan, Mayank Meena, Shubham Sen, Arvind Singh
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In this study, a multi objective optimization for end milling of Al 6061 alloy has been presented to provide better surface quality and higher Material Removal Rate (MRR). The input parameters considered for the analysis are spindle speed, depth of cut and feed. The experiments were planned as per Taguchis design of experiment, with L27 orthogonal array. The Grey Relational Analysis (GRA) has been used for transforming multiple quality responses into a single response and the weights of the each performance characteristics are determined by employing the Principal Component Analysis (PCA), so that their relative importance can be properly and objectively described. The results reveal that Taguchi based G-PCA can effectively acquire the optimal combination of cutting parameters.Keywords: Material Removal Rate, Surface Roughness, Taguchi Method, Grey Relational Analysis, Principal Component Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22273177 Stability Optimization of Functionally Graded Pipes Conveying Fluid
Authors: Karam Y. Maalawi, Hanan E.M EL-Sayed
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This paper presents an exact analytical model for optimizing stability of thin-walled, composite, functionally graded pipes conveying fluid. The critical flow velocity at which divergence occurs is maximized for a specified total structural mass in order to ensure the economic feasibility of the attained optimum designs. The composition of the material of construction is optimized by defining the spatial distribution of volume fractions of the material constituents using piecewise variations along the pipe length. The major aim is to tailor the material distribution in the axial direction so as to avoid the occurrence of divergence instability without the penalty of increasing structural mass. Three types of boundary conditions have been examined; namely, Hinged-Hinged, Clamped- Hinged and Clamped-Clamped pipelines. The resulting optimization problem has been formulated as a nonlinear mathematical programming problem solved by invoking the MatLab optimization toolbox routines, which implement constrained function minimization routine named “fmincon" interacting with the associated eigenvalue problem routines. In fact, the proposed mathematical models have succeeded in maximizing the critical flow velocity without mass penalty and producing efficient and economic designs having enhanced stability characteristics as compared with the baseline designs.Keywords: Functionally graded materials, pipe flow, optimumdesign, fluid- structure interaction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22083176 Optimization of Three-dimensional Electrical Performance in a Solid Oxide Fuel Cell Stack by a Neural Network
Authors: Shih-Bin Wang, Ping Yuan, Syu-Fang Liu, Ming-Jun Kuo
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By the application of an improved back-propagation neural network (BPNN), a model of current densities for a solid oxide fuel cell (SOFC) with 10 layers is established in this study. To build the learning data of BPNN, Taguchi orthogonal array is applied to arrange the conditions of operating parameters, which totally 7 factors act as the inputs of BPNN. Also, the average current densities achieved by numerical method acts as the outputs of BPNN. Comparing with the direct solution, the learning errors for all learning data are smaller than 0.117%, and the predicting errors for 27 forecasting cases are less than 0.231%. The results show that the presented model effectively builds a mathematical algorithm to predict performance of a SOFC stack immediately in real time. Also, the calculating algorithms are applied to proceed with the optimization of the average current density for a SOFC stack. The operating performance window of a SOFC stack is found to be between 41137.11 and 53907.89. Furthermore, an inverse predicting model of operating parameters of a SOFC stack is developed here by the calculating algorithms of the improved BPNN, which is proved to effectively predict operating parameters to achieve a desired performance output of a SOFC stack.Keywords: a SOFC stack, BPNN, inverse predicting model of operating parameters, optimization of the average current density
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13643175 Electricity Power Planning: the Role of Wind Energy
Authors: Paula Ferreira, Madalena Araújo, M.E.J. O’Kelly
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Combining energy efficiency with renewable energy sources constitutes a key strategy for a sustainable future. The wind power sector stands out as a fundamental element for the achievement of the European renewable objectives and Portugal is no exception to the increase of the wind energy for the electricity generation. This work proposes an optimization model for the long range electricity power planning in a system similar to the Portuguese one, where the expected impacts of the increasing installed wind power on the operating performance of thermal power plants are taken into account. The main results indicate that the increasing penetration of wind power in the electricity system will have significant effects on the combined cycle gas power plants operation and on the theoretically expected cost reduction and environmental gains. This research demonstrated the need to address the impact that energy sources with variable output may have, not only on the short-term operational planning, but especially on the medium to long range planning activities, in order to meet the strategic objectives for the energy sector.Keywords: Wind power, electricity planning model, cost, emissions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16083174 A New Method for Identifying Broken Rotor Bars in Squirrel Cage Induction Motor Based on Particle Swarm Optimization Method
Authors: V. Rashtchi, R. Aghmasheh
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Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteristic frequency components of faylted rotor will be detected by minimizing a fitness function using pso. Supply frequency and side band frequencies and their amplitudes can be estimated by the proposed method. The proposed method is applied to a faulty motor with one and two broken bars in different loading condition. Experimental results prove that the proposed method is effective and applicable.
Keywords: broken bar, PSO, fault detection, SCIM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17173173 Statistical Optimization of the Enzymatic Saccharification of the Oil Palm Empty Fruit Bunches
Authors: Rashid S. S., Alam M. Z.
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A statistical optimization of the saccharification process of EFB was studied. The statistical analysis was done by applying faced centered central composite design (FCCCD) under response surface methodology (RSM). In this investigation, EFB dose, enzyme dose and saccharification period was examined, and the maximum 53.45% (w/w) yield of reducing sugar was found with 4% (w/v) of EFB, 10% (v/v) of enzyme after 120 hours of incubation. It can be calculated that the conversion rate of cellulose content of the substrate is more than 75% (w/w) which can be considered as a remarkable achievement. All the variables, linear, quadratic and interaction coefficient, were found to be highly significant, other than two coefficients, one quadratic and another interaction coefficient. The coefficient of determination (R2) is 0.9898 that confirms a satisfactory data and indicated that approximately 98.98% of the variability in the dependent variable, saccharification of EFB, could be explained by this model.Keywords: Face centered central composite design (FCCCD), Liquid state bioconversion (LSB), Palm oil mill effluent, Trichoderma reesei RUT C-30.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22513172 EML-Estimation of Multivariate t Copulas with Heuristic Optimization
Authors: Jin Zhang, Wing Lon Ng
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In recent years, copulas have become very popular in financial research and actuarial science as they are more flexible in modelling the co-movements and relationships of risk factors as compared to the conventional linear correlation coefficient by Pearson. However, a precise estimation of the copula parameters is vital in order to correctly capture the (possibly nonlinear) dependence structure and joint tail events. In this study, we employ two optimization heuristics, namely Differential Evolution and Threshold Accepting to tackle the parameter estimation of multivariate t distribution models in the EML approach. Since the evolutionary optimizer does not rely on gradient search, the EML approach can be applied to estimation of more complicated copula models such as high-dimensional copulas. Our experimental study shows that the proposed method provides more robust and more accurate estimates as compared to the IFM approach.Keywords: Copula Models, Student t Copula, Parameter Inference, Differential Evolution, Threshold Accepting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15603171 Optimization of CO2 Emissions and Cost for Composite Building Design with NSGA-II
Authors: Ji Hyeong Park, Ji Hye Jeon, Hyo Seon Park
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Environmental pollution problems have been globally main concern in all fields including economy, society and culture into the 21st century. Beginning with the Kyoto Protocol, the reduction on the emissions of greenhouse gas such as CO2 and SOX has been a principal challenge of our day. As most buildings unlike durable goods in other industries have a characteristic and long life cycle, they consume energy in quantity and emit much CO2. Thus, for green building construction, more research is needed to reduce the CO2 emissions at each stage in the life cycle. However, recent studies are focused on the use and maintenance phase. Also, there is a lack of research on the initial design stage, especially the structure design. Therefore, in this study, we propose an optimal design plan considering CO2 emissions and cost in composite buildings simultaneously by applying to the structural design of actual building.Keywords: Multi-objective optimization, CO2 emissions, structural cost, encased composite structure
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21653170 Strength Optimization of Induction Hardened Splined Shaft – Material and Geometric Aspects
Authors: I. Barsoum, F. Khan
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the current study presents a modeling framework to determine the torsion strength of an induction hardened splined shaft by considering geometry and material aspects with the aim to optimize the static torsion strength by selection of spline geometry and hardness depth. Six different spline geometries and seven different hardness profiles including non-hardened and throughhardened shafts have been considered. The results reveal that the torque that causes initial yielding of the induction hardened splined shaft is strongly dependent on the hardness depth and the geometry of the spline teeth. Guidelines for selection of the appropriate hardness depth and spline geometry are given such that an optimum static torsion strength of the component can be achieved.
Keywords: Static strength, splined shaft, torsion, induction hardening, hardness profile, finite element, optimization, design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 49703169 An Optimal Feature Subset Selection for Leaf Analysis
Authors: N. Valliammal, S.N. Geethalakshmi
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This paper describes an optimal approach for feature subset selection to classify the leaves based on Genetic Algorithm (GA) and Kernel Based Principle Component Analysis (KPCA). Due to high complexity in the selection of the optimal features, the classification has become a critical task to analyse the leaf image data. Initially the shape, texture and colour features are extracted from the leaf images. These extracted features are optimized through the separate functioning of GA and KPCA. This approach performs an intersection operation over the subsets obtained from the optimization process. Finally, the most common matching subset is forwarded to train the Support Vector Machine (SVM). Our experimental results successfully prove that the application of GA and KPCA for feature subset selection using SVM as a classifier is computationally effective and improves the accuracy of the classifier.Keywords: Optimization, Feature extraction, Feature subset, Classification, GA, KPCA, SVM and Computation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22423168 A Shape Optimization Method in Viscous Flow Using Acoustic Velocity and Four-step Explicit Scheme
Authors: Yoichi Hikino, Mutsuto Kawahara
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The purpose of this study is to derive optimal shapes of a body located in viscous flows by the finite element method using the acoustic velocity and the four-step explicit scheme. The formulation is based on an optimal control theory in which a performance function of the fluid force is introduced. The performance function should be minimized satisfying the state equation. This problem can be transformed into the minimization problem without constraint conditions by using the adjoint equation with adjoint variables corresponding to the state equation. The performance function is defined by the drag and lift forces acting on the body. The weighted gradient method is applied as a minimization technique, the Galerkin finite element method is used as a spatial discretization and the four-step explicit scheme is used as a temporal discretization to solve the state equation and the adjoint equation. As the interpolation, the orthogonal basis bubble function for velocity and the linear function for pressure are employed. In case that the orthogonal basis bubble function is used, the mass matrix can be diagonalized without any artificial centralization. The shape optimization is performed by the presented method.Keywords: Shape Optimization, Optimal Control Theory, Finite Element Method, Weighted Gradient Method, Fluid Force, Orthogonal Basis Bubble Function, Four-step Explicit Scheme, Acoustic Velocity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14653167 An Efficient Approach for Optimal Placement of TCSC in Double Auction Power Market
Authors: Prashant Kumar Tiwari, Yog Raj Sood
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This paper proposes an investment cost recovery based efficient and fast sequential optimization approach to optimal allocation of thyristor controlled series compensator (TCSC) in competitive power market. The optimization technique has been used with an objective to maximizing the social welfare and minimizing the device installation cost by suitable location and rating of TCSC in the system. The effectiveness of proposed approach for location of TCSC has been compared with some existing methods of TCSC placement, in terms of its impact on social welfare, TCSC investment recovery and optimal generation as well as load patterns. The results have been obtained on modified IEEE 14-bus system.Keywords: Double auction market, Investment cost recovery, Optimal location, Social welfare, TCSC
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22543166 Hot Workability of High Strength Low Alloy Steels
Authors: Seok Hong Min, Jung Ho Moon, Woo Young Jung, Tae Kwon Ha
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The hot deformation behavior of high strength low alloy (HSLA) steels with different chemical compositions under hot working conditions in the temperature range of 900 to 1100℃ and strain rate range from 0.1 to 10 s-1 has been studied by performing a series of hot compression tests. The dynamic materials model has been employed for developing the processing maps, which show variation of the efficiency of power dissipation with temperature and strain rate. Also the Kumar-s model has been used for developing the instability map, which shows variation of the instability for plastic deformation with temperature and strain rate. The efficiency of power dissipation increased with decreasing strain rate and increasing temperature in the steel with higher Cr and Ti content. High efficiency of power dissipation over 20 % was obtained at a finite strain level of 0.1 under the conditions of strain rate lower than 1 s-1 and temperature higher than 1050 ℃ . Plastic instability was expected in the regime of temperatures lower than 1000 ℃ and strain rate lower than 0.3 s-1. Steel with lower Cr and Ti contents showed high efficiency of power dissipation at higher strain rate and lower temperature conditions.Keywords: High strength low alloys steels, hot workability, Dynamic materials model, Processing maps.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20193165 A Case Study on Optimization of Contractor’s Financing through Allocation of Subcontractors
Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin
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In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.
Keywords: Cash flow optimization, payment plan, procurement management, subcontracting plan.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2093164 Multi-Objective Optimization of Run-of-River Small-Hydropower Plants Considering Both Investment Cost and Annual Energy Generation
Authors: Amèdédjihundé H. J. Hounnou, Frédéric Dubas, François-Xavier Fifatin, Didier Chamagne, Antoine Vianou
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This paper presents the techno-economic evaluation of run-of-river small-hydropower plants. In this regard, a multi-objective optimization procedure is proposed for the optimal sizing of the hydropower plants, and NSGAII is employed as the optimization algorithm. Annual generated energy and investment cost are considered as the objective functions, and number of generator units (n) and nominal turbine flow rate (QT) constitute the decision variables. Site of Yeripao in Benin is considered as the case study. We have categorized the river of this site using its environmental characteristics: gross head, and first quartile, median, third quartile and mean of flow. Effects of each decision variable on the objective functions are analysed. The results gave Pareto Front which represents the trade-offs between annual energy generation and the investment cost of hydropower plants, as well as the recommended optimal solutions. We noted that with the increase of the annual energy generation, the investment cost rises. Thus, maximizing energy generation is contradictory with minimizing the investment cost. Moreover, we have noted that the solutions of Pareto Front are grouped according to the number of generator units (n). The results also illustrate that the costs per kWh are grouped according to the n and rise with the increase of the nominal turbine flow rate. The lowest investment costs per kWh are obtained for n equal to one and are between 0.065 and 0.180 €/kWh. Following the values of n (equal to 1, 2, 3 or 4), the investment cost and investment cost per kWh increase almost linearly with increasing the nominal turbine flowrate while annual generated. Energy increases logarithmically with increasing of the nominal turbine flowrate. This study made for the Yeripao river can be applied to other rivers with their own characteristics.
Keywords: Hydropower plant, investment cost, multi-objective optimization, number of generator units.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10573163 Improvement in Performance and Emission Characteristics of a Single Cylinder S.I. Engine Operated on Blends of CNG and Hydrogen
Authors: Sarbjot Singh Sandhu
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This paper presents the experimental results of a single cylinder Enfield engine using an electronically controlled fuel injection system which was developed to carry out exhaustive tests using neat CNG, and mixtures of hydrogen in compressed natural gas (HCNG) as 0, 5, 10, 15 and 20% by energy. Experiments were performed at 2000 and 2400 rpm with wide open throttle and varying the equivalence ratio. Hydrogen which has fast burning rate, when added to compressed natural gas, enhances its flame propagation rate. The emissions of HC, CO, decreased with increasing percentage of hydrogen but NOx was found to increase. The results indicated a marked improvement in the brake thermal efficiency with the increase in percentage of hydrogen added. The improved thermal efficiency was clearly observed to be more in lean region as compared to rich region. This study is expected to reduce vehicular emissions along with increase in thermal efficiency and thus help in reduction of further environmental degradation.
Keywords: Hydrogen, CNG, HCNG, Emissions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27123162 Traffic Signal Coordinated Control Optimization: A Case Study
Authors: Pengdi Diao, Zhuo Wang, Zundong Zhang, Hua Cheng
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In the urban traffic network, the intersections are the “bottleneck point" of road network capacity. And the arterials are the main body in road network and the key factor which guarantees the normal operation of the city-s social and economic activities. The rapid increase in vehicles leads to seriously traffic jam and cause the increment of vehicles- delay. Most cities of our country are traditional single control system, which cannot meet the need for the city traffic any longer. In this paper, Synchro6.0 as a platform to minimize the intersection delay, optimizesingle signal cycle and split for Zhonghua Street in Handan City. Meanwhile, linear control system uses to optimize the phase for the t arterial road in this system. Comparing before and after use the control, capacities and service levels of this road and the adjacent road have improved significantly.Keywords: linear control system; delay mode; signal optimization; synchro6.0 simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21253161 Optimization of Solar Tracking Systems
Authors: A. Zaher, A. Traore, F. Thiéry, T. Talbert, B. Shaer
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In this paper, an intelligent approach is proposed to optimize the orientation of continuous solar tracking systems on cloudy days. Considering the weather case, the direct sunlight is more important than the diffuse radiation in case of clear sky. Thus, the panel is always pointed towards the sun. In case of an overcast sky, the solar beam is close to zero, and the panel is placed horizontally to receive the maximum of diffuse radiation. Under partly covered conditions, the panel must be pointed towards the source that emits the maximum of solar energy and it may be anywhere in the sky dome. Thus, the idea of our approach is to analyze the images, captured by ground-based sky camera system, in order to detect the zone in the sky dome which is considered as the optimal source of energy under cloudy conditions. The proposed approach is implemented using experimental setup developed at PROMES-CNRS laboratory in Perpignan city (France). Under overcast conditions, the results were very satisfactory, and the intelligent approach has provided efficiency gains of up to 9% relative to conventional continuous sun tracking systems.
Keywords: Clouds detection, fuzzy inference systems, images processing, sun trackers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12133160 Bee Optimized Fuzzy Geographical Routing Protocol for VANET
Authors: P. Saravanan, T. Arunkumar
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Vehicular Adhoc Network (VANET) is a new technology which aims to ensure intelligent inter-vehicle communications, seamless internet connectivity leading to improved road safety, essential alerts, and access to comfort and entertainment. VANET operations are hindered by mobile node’s (vehicles) uncertain mobility. Routing algorithms use metrics to evaluate which path is best for packets to travel. Metrics like path length (hop count), delay, reliability, bandwidth, and load determine optimal route. The proposed scheme exploits link quality, traffic density, and intersections as routing metrics to determine next hop. This study enhances Geographical Routing Protocol (GRP) using fuzzy controllers while rules are optimized with Bee Swarm Optimization (BSO). Simulations results are compared to conventional GRP.
Keywords: Bee Swarm Optimization (BSO), Geographical Routing Protocol (GRP), Vehicular Adhoc Network (VANET).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24583159 Phytoremediation of Wastewater Using Some of Aquatic Macrophytes as Biological Purifiers for Irrigation Purposes
Authors: Dilshad G.A. Ganjo, Ahmed I. Khwakaram
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An attempt was made for availability of wastewater reuse/reclamation for irrigation purposes using phytoremediation “the low cost and less technology", using six local aquatic macrophytes “e.g. T. angustifolia, B. maritimus, Ph. australis, A. donax, A. plantago-aquatica and M. longifolia (Linn)" as biological waste purifiers. Outdoor experiments/designs were conducted from May 03, 2007 till October 15, 2008, close to one of the main sewage channels of Sulaimani City/Iraq*. All processes were mainly based on conventional wastewater treatment processes, besides two further modifications were tested, the first was sand filtration pots, implanted by individual species of experimental macrophytes and the second was constructed wetlands implanted by experimental macrophytes all together. Untreated and treated wastewater samples were analyzed for their key physico-chemical properties (only heavy metals Fe, Mn, Zn and Cu with particular reference to removal efficiency by experimental macrophytes are highlighted in this paper). On the other hand, vertical contents of heavy metals were also evaluated from both pots and the cells of constructed wetland. After 135 days, macrophytes were harvested and heavy metals were analyzed in their biomass (roots/shoots) for removal efficiency assessment (i.e. uptake/ bioaccumulation rate). Results showed that; removal efficiency of all studied heavy metals was much higher in T. angustifolia followed by Ph. Australis, B. maritimus and A. donax in triple experiment sand pots. Constructed wetland experiments have revealed that; the more replicated constructed wetland cells the highest heavy metal removal efficiency was indicated.
Keywords: Aquatic Macrophytes, Heavy Metals (Fe, Mn, Zn and Cu), Phytoremediation and Removal Efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33473158 The Design Optimization for Sound Absorption Material of Multi-Layer Structure
Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Kyu Park
Abstract:
Sound absorbing material is used as automotive interior material. Sound absorption coefficient should be predicted to design it. But it is difficult to predict sound absorbing coefficient because it is comprised of several material layers. So, its targets are achieved through many experimental tunings. It causes a lot of cost and time. In this paper, we propose the process to estimate the sound absorption coefficient with multi-layer structure. In order to estimate the coefficient, physical properties of each material are used. These properties also use predicted values by Foam-X software using the sound absorption coefficient data measured by impedance tube. Since there are many physical properties and the measurement equipment is expensive, the values predicted by software are used. Through the measurement of the sound absorption coefficient of each material, its physical properties are calculated inversely. The properties of each material are used to calculate the sound absorption coefficient of the multi-layer material. Since the absorption coefficient of multi-layer can be calculated, optimization design is possible through simulation. Then, we will compare and analyze the calculated sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If this method is used when developing automotive interior materials with multi-layer structure, the development effort can be reduced because it can be optimized by simulation. So, cost and time can be saved.
Keywords: Optimization design, multi-layer nonwoven, sound absorption coefficient, scaled reverberation chamber, impedance tubes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10003157 Exploring Dimensionality, Systematic Mutations and Number of Contacts in Simple HP ab-initio Protein Folding Using a Blackboard-based Agent Platform
Authors: Hiram I. Beltrán, Arturo Rojo-Domínguez, Máximo Eduardo Sánchez Gutiérrez, Pedro Pablo González Pérez
Abstract:
A computational platform is presented in this contribution. It has been designed as a virtual laboratory to be used for exploring optimization algorithms in biological problems. This platform is built on a blackboard-based agent architecture. As a test case, the version of the platform presented here is devoted to the study of protein folding, initially with a bead-like description of the chain and with the widely used model of hydrophobic and polar residues (HP model). Some details of the platform design are presented along with its capabilities and also are revised some explorations of the protein folding problems with different types of discrete space. It is also shown the capability of the platform to incorporate specific tools for the structural analysis of the runs in order to understand and improve the optimization process. Accordingly, the results obtained demonstrate that the ensemble of computational tools into a single platform is worthwhile by itself, since experiments developed on it can be designed to fulfill different levels of information in a self-consistent fashion. By now, it is being explored how an experiment design can be useful to create a computational agent to be included within the platform. These inclusions of designed agents –or software pieces– are useful for the better accomplishment of the tasks to be developed by the platform. Clearly, while the number of agents increases the new version of the virtual laboratory thus enhances in robustness and functionality.Keywords: genetic algorithms, multi-agent systems, bioinformatics, optimization, protein folding, structural biology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1899