Search results for: Shape Optimization of Chevron Nozzles
2115 Investigation on Choosing the Suitable Geometry of the Solar Air Heater to Certain Conditions
Authors: Abdulrahman M. Homadi
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This study focuses on how to control the outlet temperature of a solar air heater in a way simpler than the existing methods. In this work, five cases have been studied by using ANSYS Fluent based on a CFD numerical method. All the cases have been simulated by utilizing the same criteria and conditions like the temperature, materials, areas except the geometry. The case studies are conducted in Little Rock (LR), AR, USA during the winter time supposedly on 15th of December. A fresh air that is flowing with a velocity of 0.5 m/s and a flow rate of 0.009 m3/s. The results prove the possibility of achieving a controlled temperature just by changing the geometric shape of the heater. This geometry guarantees that the absorber plate always has a normal component of the solar radiation at any time during the day. The heater has a sectarian shape with a radius of 150 mm where the outlet temperature remains almost constant for six hours.Keywords: Solar energy, air heater, control of temperature, CFD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11362114 Application of Pattern Search Method to Power System Security Constrained Economic Dispatch
Authors: A. K. Al-Othman, K. M. EL-Nagger
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Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).
Keywords: Security Constrained Economic Dispatch, Direct Search method, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22072113 Model-Based Control for Piezoelectric-Actuated Systems Using Inverse Prandtl-Ishlinskii Model and Particle Swarm Optimization
Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin
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In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.
Keywords: The Bouc-Wen hysteresis model, Particle swarm optimization, Prandtl-Ishlinskii model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24072112 Testing Visual Abilities of Machines - Visual Intelligence Tests
Authors: Zbigniew Les, Magdalena Les
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Intelligence tests are series of tasks designed to measure the capacity to make abstractions, to learn, and to deal with novel situations. Testing of the visual abilities of the shape understanding system (SUS) is performed based on the visual intelligence tests. In this paper the progressive matrices tests are formulated as tasks given to SUS. These tests require good visual problem solving abilities of the human subject. SUS solves these tests by performing complex visual reasoning transforming the visual forms (tests) into the string forms. The experiment proved that the proposed method, which is part of the SUS visual understanding abilities, can solve a test that is very difficult for human subject.
Keywords: Shape understanding, intelligence test, visual concept, visual reasoning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14102111 Optimal Trailing Edge Flap Positions of Helicopter Rotor for Various Thrust Coefficients to Solidity (Ct/σ) Ratios
Authors: Saijal K. K., K. Prabhakaran Nair
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This study aims to determine change in optimal locations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multiobjective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization result shows that the inboard flap location at low Ct /σ ratio move farther from the baseline value and at high Ct /σ ratio move towards the root of the blade for minimizing hub vibration.
Keywords: Helicopter rotor, Trailing-edge flap, Thrust coefficient to solidity (Ct /σ) ratio, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46362110 Optimal Design of Reference Node Placement for Wireless Indoor Positioning Systems in Multi-Floor Building
Authors: Kittipob Kondee, Chutima Prommak
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In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.
Keywords: Indoor positioning System, Optimization System design, Multi-Floor Building, Wireless Sensor Networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19832109 A Genetic and Simulated Annealing Based Algorithms for Solving the Flow Assignment Problem in Computer Networks
Authors: Tarek M. Mahmoud
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Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.Keywords: Genetic Algorithms, Flow Assignment, Routing, Computer network, Simulated Annealing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22562108 Optimal Manufacturing Scheduling for Dependent Details Processing
Authors: Ivan C. Mustakerov, Daniela I. Borissova
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The increasing competitiveness in manufacturing industry is forcing manufacturers to seek effective processing schedules. The paper presents an optimization manufacture scheduling approach for dependent details processing with given processing sequences and times on multiple machines. By defining decision variables as start and end moments of details processing it is possible to use straightforward variables restrictions to satisfy different technological requirements and to formulate easy to understand and solve optimization tasks for multiple numbers of details and machines. A case study example is solved for seven base moldings for CNC metalworking machines processed on five different machines with given processing order among details and machines and known processing time-s duration. As a result of linear optimization task solution the optimal manufacturing schedule minimizing the overall processing time is obtained. The manufacturing schedule defines the moments of moldings delivery thus minimizing storage costs and provides mounting due-time satisfaction. The proposed optimization approach is based on real manufacturing plant problem. Different processing schedules variants for different technological restrictions were defined and implemented in the practice of Bulgarian company RAIS Ltd. The proposed approach could be generalized for other job shop scheduling problems for different applications.Keywords: Optimal manufacturing scheduling, linear programming, metalworking machines production, dependant details processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14872107 Efficiency of Robust Heuristic Gradient Based Enumerative and Tunneling Algorithms for Constrained Integer Programming Problems
Authors: Vijaya K. Srivastava, Davide Spinello
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This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3n enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3n integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.
Keywords: Constrained integer problems, enumerative search algorithm, Heuristic algorithm, tunneling algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8002106 Optimization Modeling of the Hybrid Antenna Array for the DoA Estimation
Authors: Somayeh Komeylian
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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).
Keywords: DoA estimation, adaptive antenna array, Deep Neural Network, LS-SVM optimization model, radial basis function, MSE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5392105 Estimation of Structural Parameters in Time Domain Using One Dimensional Piezo Zirconium Titanium Patch Model
Authors: N. Jinesh, K. Shankar
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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.
Keywords: Structural identification, PZT patches, inverse problem, particle swarm optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9312104 Modeling and Optimization of Abrasive Waterjet Parameters using Regression Analysis
Authors: Farhad Kolahan, A. Hamid Khajavi
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Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.
Keywords: AWJ cutting, Mathematical modeling, Simulated Annealing, Optimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21542103 Model Updating-Based Approach for Damage Prognosis in Frames via Modal Residual Force
Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh
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This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.Keywords: Frame, grey wolf optimization algorithm, modal residual force, structural damage detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14952102 Networked Implementation of Milling Stability Optimization with Bayesian Learning
Authors: C. Ramsauer, J. Karandikar, D. Leitner, T. Schmitz, F. Bleicher
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Machining instability, or chatter, can impose an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the TU Wien, Vienna, Austria. The recorded data from a milling test cut were used to classify the cut as stable or unstable based on a frequency analysis. The test cut result was used in a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculated the probability of stability as a function of axial depth of cut and spindle speed based on the test result and recommended parameters for the next test cut. The iterative process between two transatlantic locations was repeated until convergence to a stable optimal process parameter set was achieved.
Keywords: Bayesian learning, instrumented tool holder, machining stability, optimization strategy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5392101 Soft Computing Based Cluster Head Selection in Wireless Sensor Network Using Bacterial Foraging Optimization Algorithm
Authors: A. Rajagopal, S. Somasundaram, B. Sowmya, T. Suguna
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Wireless Sensor Networks (WSNs) enable new applications and need non-conventional paradigms for the protocol because of energy and bandwidth constraints, In WSN, sensor node’s life is a critical parameter. Research on life extension is based on Low-Energy Adaptive Clustering Hierarchy (LEACH) scheme, which rotates Cluster Head (CH) among sensor nodes to distribute energy consumption over all network nodes. CH selection in WSN affects network energy efficiency greatly. This study proposes an improved CH selection for efficient data aggregation in sensor networks. This new algorithm is based on Bacterial Foraging Optimization (BFO) incorporated in LEACH.Keywords: Bacterial Foraging Optimization (BFO), Cluster Head (CH), Data-aggregation protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34792100 A Study on Applying 3D Reconstruction to 3D Last Morphing
Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin
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When it comes to last, it is regarded as the critical foundation of shoe design and development. A computer aided methodology for various last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then with the minimum energy for revision of surface continuity, the surface reconstruction of last is rebuilt by the feature curves of the scanned last. When the surface reconstruction of last is completed, the weighted arithmetic mean method is applied to the computation on the shape morphing for the control mesh of last, thus 3D last form of different sizes is generated from its original form feature with functions remained. In the end, the result of this study is applied to an application for 3D last reconstruction system. The practicability of the proposed methodology is verified through later case studies.
Keywords: Reverse engineering, Surface reconstruction, Surface continuity, Shape morphing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17492099 Investments Attractiveness via Combinatorial Optimization Ranking
Authors: Ivan C. Mustakerov, Daniela I. Borissova
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The paper proposes an approach to ranking a set of potential countries to invest taking into account the investor point of view about importance of different economic indicators. For the goal, a ranking algorithm that contributes to rational decision making is proposed. The described algorithm is based on combinatorial optimization modeling and repeated multi-criteria tasks solution. The final result is list of countries ranked in respect of investor preferences about importance of economic indicators for investment attractiveness. Different scenarios are simulated conforming to different investors preferences. A numerical example with real dataset of indicators is solved. The numerical testing shows the applicability of the described algorithm. The proposed approach can be used with any sets of indicators as ranking criteria reflecting different points of view of investors.
Keywords: Combinatorial optimization modeling, economics investment attractiveness, economics ranking algorithm, multi-criteria problems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21072098 Cellular Components of the Hemal Node of Egyptian Cattle
Authors: Amira E. Derbalah, Doaa M. Zaghloul
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10 clinically healthy hemal nodes were collected from male bulls aged 2-3 years. Light microscopy revealed a capsule of connective tissue consisted mainly of collagen fiber surrounding hemal node, numerous erythrocytes were found in wide subcapsular sinus under the capsule. The parenchyma of the hemal node was divided into cortex and medulla. Diffused lymphocytes, and lymphoid follicles, having germinal centers were the main components of the cortex, while in the medulla there was wide medullary sinus, diffused lymphocytes and few lymphoid nodules. The area occupied with lymph nodules was larger than that occupied with non-nodular structure of lymphoid cords and blood sinusoids. Electron microscopy revealed the cellular components of hemal node including elements of circulating erythrocytes intermingled with lymphocytes, plasma cells, mast cells, reticular cells, macrophages, megakaryocytes and endothelial cells lining the blood sinuses. The lymphocytes were somewhat triangular in shape with cytoplasmic processes extending between adjacent erythrocytes. Nuclei were triangular to oval in shape, lightly stained with clear nuclear membrane indentation and clear nucleoli. The reticular cells were elongated in shape with cytoplasmic processes extending between adjacent lymphocytes, rough endoplasmic reticulum, ribosomes and few lysosomes were seen in their cytoplasm. Nucleus was elongated in shape with less condensed chromatin. Plasma cells were oval to irregular in shape with numerous dilated rough endoplasmic reticulum containing electron lucent material occupying the whole cytoplasm and few mitochondria were found. Nuclei were centrally located and oval in shape with heterochromatin emarginated and often clumped near the nuclear membrane. Occasionally megakaryocytes and mast cells were seen among lymphocytes. Megakaryocytes had multilobulated nucleus and free ribosomes often appearing as small aggregates in their cytoplasm, while mast cell had their characteristic electron dense granule in the cytoplasm, few electron lucent granules were found also, we conclude that, the main function of the hemal node of cattle is proliferation of lymphocytes. No role for plasma cell in erythrophagocytosis could be suggested.Keywords: Cattle, Electron microscopy, Hemal node, Histology, Immune system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19872097 Fuzzy Based Particle Swarm Optimization Routing Technique for Load Balancing in Wireless Sensor Networks
Authors: S. Balaji, E. Golden Julie, M. Rajaram, Y. Harold Robinson
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Network lifetime improvement and uncertainty in multiple systems are the issues of wireless sensor network routing. This paper presents fuzzy based particle swarm optimization routing technique to improve the network scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve the uncertainty and network balancing. Cluster heads play an important role to reduce the energy consumption using particle swarm optimization algorithm, the cluster head sends its information along data packets to the heads with link. The simulation results show that the presented routing protocol can perform load balancing effectively and reduce the energy consumption of cluster heads.
Keywords: Wireless sensor networks, fuzzy logic, PSO, LEACH.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12832096 Optimization of Inverse Kinematics of a 3R Robotic Manipulator using Genetic Algorithms
Authors: J. Ramírez A., A. Rubiano F.
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In this paper the direct kinematic model of a multiple applications three degrees of freedom industrial manipulator, was developed using the homogeneous transformation matrices and the Denavit - Hartenberg parameters, likewise the inverse kinematic model was developed using the same method, verifying that in the workload border the inverse kinematic presents considerable errors, therefore a genetic algorithm was implemented to optimize the model improving greatly the efficiency of the model.Keywords: Direct Kinematic, Genetic Algorithm, InverseKinematic, Optimization, Robot Manipulator
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33322095 A Weighted Sum Technique for the Joint Optimization of Performance and Power Consumption in Data Centers
Authors: Samee Ullah Khan, C.Ardil
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With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Compared to traditional methodologies for multi-objective optimization problems, the proposed self-adaptive weighted sum technique does not rely on a systematical change of weights during the optimization procedure. The proposed technique is compared with the greedy and LR heuristics for large-scale problems, and the optimal solution for small-scale problems implemented in LINDO. the experimental results revealed that the proposed selfadaptive weighted sum technique outperforms both of the heuristics and projects a competitive performance compared to the optimal solution.Keywords: Meta-heuristics, distributed systems, adaptive methods, resource allocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18362094 A PSO-based SSSC Controller for Improvement of Transient Stability Performance
Authors: Sidhartha Panda, N. P. Padhy
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The application of a Static Synchronous Series Compensator (SSSC) controller to improve the transient stability performance of a power system is thoroughly investigated in this paper. The design problem of SSSC controller is formulated as an optimization problem and Particle Swarm Optimization (PSO) Technique is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor angle of the generator is involved; transient stability performance of the system is improved. The proposed controller is tested on a weakly connected power system subjected to different severe disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and its ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC controller improves greatly the voltage profile of the system under severe disturbances.
Keywords: Particle swarm optimization, transient stability, power system oscillations, SSSC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26902093 Split-Pipe Design of Water Distribution Network Using Simulated Annealing
Authors: J. Tospornsampan, I. Kita, M. Ishii, Y. Kitamura
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In this paper a procedure for the split-pipe design of looped water distribution network based on the use of simulated annealing is proposed. Simulated annealing is a heuristic-based search algorithm, motivated by an analogy of physical annealing in solids. It is capable for solving the combinatorial optimization problem. In contrast to the split-pipe design that is derived from a continuous diameter design that has been implemented in conventional optimization techniques, the split-pipe design proposed in this paper is derived from a discrete diameter design where a set of pipe diameters is chosen directly from a specified set of commercial pipes. The optimality and feasibility of the solutions are found to be guaranteed by using the proposed method. The performance of the proposed procedure is demonstrated through solving the three well-known problems of water distribution network taken from the literature. Simulated annealing provides very promising solutions and the lowest-cost solutions are found for all of these test problems. The results obtained from these applications show that simulated annealing is able to handle a combinatorial optimization problem of the least cost design of water distribution network. The technique can be considered as an alternative tool for similar areas of research. Further applications and improvements of the technique are expected as well.Keywords: Combinatorial problem, Heuristics, Least-cost design, Looped network, Pipe network, Optimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26782092 Multicast Optimization Techniques using Best Effort Genetic Algorithms
Authors: Dinesh Kumar, Y. S. Brar, V. K. Banga
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Multicast Network Technology has pervaded our lives-a few examples of the Networking Techniques and also for the improvement of various routing devices we use. As we know the Multicast Data is a technology offers many applications to the user such as high speed voice, high speed data services, which is presently dominated by the Normal networking and the cable system and digital subscriber line (DSL) technologies. Advantages of Multi cast Broadcast such as over other routing techniques. Usually QoS (Quality of Service) Guarantees are required in most of Multicast applications. The bandwidth-delay constrained optimization and we use a multi objective model and routing approach based on genetic algorithm that optimizes multiple QoS parameters simultaneously. The proposed approach is non-dominated routes and the performance with high efficiency of GA. Its betterment and high optimization has been verified. We have also introduced and correlate the result of multicast GA with the Broadband wireless to minimize the delay in the path.Keywords: GA (genetic Algorithms), Quality of Service, MOGA, Steiner Tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15562091 Mining Sequential Patterns Using Hybrid Evolutionary Algorithm
Authors: Mourad Ykhlef, Hebah ElGibreen
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Mining Sequential Patterns in large databases has become an important data mining task with broad applications. It is an important task in data mining field, which describes potential sequenced relationships among items in a database. There are many different algorithms introduced for this task. Conventional algorithms can find the exact optimal Sequential Pattern rule but it takes a long time, particularly when they are applied on large databases. Nowadays, some evolutionary algorithms, such as Particle Swarm Optimization and Genetic Algorithm, were proposed and have been applied to solve this problem. This paper will introduce a new kind of hybrid evolutionary algorithm that combines Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) to mine Sequential Pattern, in order to improve the speed of evolutionary algorithms convergence. This algorithm is referred to as SP-GAPSO.Keywords: Genetic Algorithm, Hybrid Evolutionary Algorithm, Particle Swarm Optimization algorithm, Sequential Pattern mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20262090 An Economical Operation Analysis Optimization Model for Heavy Equipment Selection
Authors: A. Jrade, N. Markiz, N. Albelwi
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Optimizing equipment selection in heavy earthwork operations is a critical key in the success of any construction project. The objective of this research incentive was geared towards developing a computer model to assist contractors and construction managers in estimating the cost of heavy earthwork operations. Economical operation analysis was conducted for an equipment fleet taking into consideration the owning and operating costs involved in earthwork operations. The model is being developed in a Microsoft environment and is capable of being integrated with other estimating and optimization models. In this study, Caterpillar® Performance Handbook [5] was the main resource used to obtain specifications of selected equipment. The implementation of the model shall give optimum selection of equipment fleet not only based on cost effectiveness but also in terms of versatility. To validate the model, a case study of an actual dam construction project was selected to quantify its degree of accuracy.Keywords: Operation analysis, optimization model, equipment economics, equipment selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42582089 Active Control for Reduction of Noise Passing through Enclosure and Optimization of Microphone Position
Authors: Han-wool Lee, Chin-suk Hong, Weui-bong Jung
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In this study, noise characteristics of structure were analyzed in an effort to reduce noise passing through an opening of an enclosure surrounding the structure that generates noise. Enclosures are essential measure to protect noise propagation from operating machinery. Access openings of the enclosures are important path of noise leakage. First, noise characteristics of structure were analyzed and feed-forward noise control was performed using simulation in order to reduce noise passing through the opening of enclosure, which surrounds a structure generating noise. We then implemented a feed-forward controller to actively control the acoustic power through the opening. Finally, we conducted optimization of placement of the reference sensors for several cases of the number of sensors. Good control performances were achieved using the minimum number of microphones arranged an optimal placement.Keywords: Active Noise Control, Feed-forward Control, Noise Attenuation, Position Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16452088 Structural Cost of Optimized Reinforced Concrete Isolated Footing
Authors: Mohammed S. Al-Ansari
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This paper presents an analytical model to estimate the cost of an optimized design of reinforced concrete isolated footing base on structural safety. Flexural and optimized formulas for square and rectangular footingare derived base on ACI building code of design, material cost and optimization. The optimization constraints consist of upper and lower limits of depth and area of steel. Footing depth and area of reinforcing steel are to be minimized to yield the optimal footing dimensions. Optimized footing materials cost of concrete, reinforcing steel and formwork of the designed sections are computed. Total cost factor TCF and other cost factors are developed to generalize and simplify the calculations of footing material cost. Numerical examples are presented to illustrate the model capability of estimating the material cost of the footing for a desired axial load.Keywords: Footing, Depth, Concrete, Steel, Formwork, Optimization, Material cost, Cost Factors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47162087 Hull Separation Optimization of Catamaran Unmanned Surface Vehicle Powered with Hydrogen Fuel Cell
Authors: Seok-In Sohn, Dae-Hwan Park, Yeon-Seung Lee, Il-Kwon Oh
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This paper presents an optimization of the hull separation, i.e. transverse clearance. The main objective is to identify the feasible speed ranges and find the optimum transverse clearance considering the minimum wave-making resistance. The dimensions and the weight of hardware systems installed in the catamaran structured fuel cell powered USV (Unmanned Surface Vehicle) were considered as constraints. As the CAE (Computer Aided Engineering) platform FRIENDSHIP-Framework was used. The hull surface modeling, DoE (Design of Experiment), Tangent search optimization, tool integration and the process automation were performed by FRIENDSHIP-Framework. The hydrodynamic result was evaluated by XPAN the potential solver of SHIPFLOW.Keywords: Full parametric modeling, Hull Separation, Wave-making resistance, Design Of Experiment, Tangent search method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29602086 Shape Sensing and Damage Detection of Thin-Walled Cylinders Using an Inverse Finite Element Method
Authors: Ionel D. Craiu, Mihai Nedelcu
Abstract:
Thin-walled cylinders are often used by the offshore industry as columns of floating installations. Based on observed strains, the inverse Finite Element Method (iFEM) may rebuild the deformation of structures. Structural Health Monitoring uses this approach extensively. However, the number of in-situ strain gauges is what determines how accurate it is, and for shell structures with complicated deformation, this number can easily become too high for practical use. Any thin-walled beam member's complicated deformation can be modeled by the Generalized Beam Theory (GBT) as a linear combination of pre-specified cross-section deformation modes. GBT uses bar finite elements as opposed to shell finite elements. This paper proposes an iFEM/GBT formulation for the shape sensing of thin-walled cylinders based on these benefits. This method significantly reduces the number of strain gauges compared to using the traditional inverse-shell finite elements. Using numerical simulations, dent damage detection is achieved by comparing the strain distributions of the undamaged and damaged members. The effect of noise on strain measurements is also investigated.
Keywords: Damage detection, generalized beam theory, inverse finite element method, shape sensing.
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