Search results for: morphology optimization
4259 3D Carbon Structures (Globugraphite) with Hierarchical Pore Morphology for the Application in Energy Storage Systems
Authors: Hubert Beisch, Janik Marx, Svenja Garlof, Roman Shvets, Ivan Grygorchak, Andriy Kityk, Bodo Fiedler
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Three-dimensional carbon materials can be used as electrode materials for energy storage systems such as batteries and supercapacitors. Fast charging and discharging times are realizable without reducing the performance due to aging processes. Furthermore high specific surface area (SSA) of three-dimensional carbon structures leads to high specific capacities. One newly developed carbon foam is Globugraphite. This interconnected globular carbon morphology with statistically distributed hierarchical pores is manufactured by a chemical vapor deposition (CVD) process from ceramic templates resulting from a sintering process. Via scanning electron (SEM) and transmission electron microscopy (TEM), the morphology is characterized. Moreover, the SSA was measured by the Brunauer–Emmett–Teller (BET) theory. Measurements of Globugraphite in an organic and inorganic electrolyte show high energy densities and power densities resulting from ion absorption by forming an electrochemical double layer. A comparison of the specific values is summarized in a Ragone diagram. Energy densities up to 48 Wh/kg and power densities to 833 W/kg could be achieved for an SSA from 376 m²/g to 859 m²/g. For organic electrolyte, a specific capacity of 100 F/g at a density of 20 mg/cm³ was achieved.Keywords: BET, carbon foam, CVD process, electrochemical cell, Ragone diagram, SEM, TEM
Procedia PDF Downloads 2304258 An Application of Integrated Multi-Objective Particles Swarm Optimization and Genetic Algorithm Metaheuristic through Fuzzy Logic for Optimization of Vehicle Routing Problems in Sugar Industry
Authors: Mukhtiar Singh, Sumeet Nagar
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Vehicle routing problem (VRP) is a combinatorial optimization and nonlinear programming problem aiming to optimize decisions regarding given set of routes for a fleet of vehicles in order to provide cost-effective and efficient delivery of both services and goods to the intended customers. This paper proposes the application of integrated particle swarm optimization (PSO) and genetic optimization algorithm (GA) to address the Vehicle routing problem in sugarcane industry in India. Suger industry is very prominent agro-based industry in India due to its impacts on rural livelihood and estimated to be employing around 5 lakhs workers directly in sugar mills. Due to various inadequacies, inefficiencies and inappropriateness associated with the current vehicle routing model it costs huge money loss to the industry which needs to be addressed in proper context. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to improve its flexibility and manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the hybrid approach to an example of VRP and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of hybrid algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.Keywords: fuzzy logic, genetic algorithm, particle swarm optimization, vehicle routing problem
Procedia PDF Downloads 3904257 A Study on Computational Fluid Dynamics (CFD)-Based Design Optimization Techniques Using Multi-Objective Evolutionary Algorithms (MOEA)
Authors: Ahmed E. Hodaib, Mohamed A. Hashem
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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization
Procedia PDF Downloads 2514256 Optimization of the Dam Management to Satisfy the Irrigation Demand: A Case Study in Algeria
Authors: Merouane Boudjerda, Bénina Touaibia, Mustapha K Mihoubi
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In Algeria, water resources play a crucial role in economic development. But over the last decades, they are relatively limited and gradually decreasing to the detriment of agriculture. The agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Boukerdane dam’s reservoir system in North of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 34% to 60%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.Keywords: water management, agricultural demand, Boukerdane dam, dynamic programming, artificial neural network
Procedia PDF Downloads 1254255 Aerodynamic Design an UAV and Stability Analysis with Method of Genetic Algorithm Optimization
Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.
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We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB", "ANSYS FLUENT", "XFoil" package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi-objective problems can be helpful for future developments. Also we developed method for Stability Analysis (Lateral-Directional and Longitudinal).Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, longitudinal stability, lateral-directional stability
Procedia PDF Downloads 5824254 Parallel Particle Swarm Optimization Optimized LDI Controller with Lyapunov Stability Criterion for Nonlinear Structural Systems
Authors: P. W. Tsai, W. L. Hong, C. W. Chen, C. Y. Chen
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In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.Keywords: Lyapunov stability, parallel particle swarm optimization, linear differential inclusion, artificial intelligence
Procedia PDF Downloads 6484253 Design Optimization of a Compact Quadrupole Electromagnet for CLS 2.0
Authors: Md. Armin Islam, Les Dallin, Mark Boland, W. J. Zhang
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This paper reports a study on the optimal magnetic design of a compact quadrupole electromagnet for the Canadian Light Source (CLS 2.0). The nature of the design is to determine a quadrupole with low relative higher order harmonics and better field quality. The design problem was formulated as an optimization model, in which the objective function is the higher order harmonics (multipole errors) and the variable to be optimized is the material distribution on the pole. The higher order harmonics arose in the quadrupole due to truncating the ideal hyperbola at a certain point to make the pole. In this project, the arisen harmonics have been optimized both transversely and longitudinally by adjusting material on the poles in a controlled way. For optimization, finite element analysis (FEA) has been conducted. A better higher order harmonics amplitudes and field quality have been achieved through the optimization. On the basis of the optimized magnetic design, electrical and cooling calculation has been performed for the magnet.Keywords: drift, electrical, and cooling calculation, integrated field, magnetic field gradient, multipole errors, quadrupole
Procedia PDF Downloads 1394252 Direct Torque Control of Induction Motor Employing Teaching Learning Based Optimization
Authors: Anam Gopi
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The undesired torque and flux ripple may occur in conventional direct torque control (DTC) induction motor drive. DTC can improve the system performance at low speeds by continuously tuning the regulator by adjusting the Kp, Ki values. In this Teaching Learning Based Optimization (TLBO) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion. The TLBO based PI controller has resulted is maintaining a constant speed of the motor irrespective of the load torque fluctuations.Keywords: teaching learning based optimization, direct torque control, PI controller
Procedia PDF Downloads 5814251 Parallel Gripper Modelling and Design Optimization Using Multi-Objective Grey Wolf Optimizer
Authors: Golak Bihari Mahanta, Bibhuti Bhusan Biswal, B. B. V. L. Deepak, Amruta Rout, Gunji Balamurali
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Robots are widely used in the manufacturing industry for rapid production with higher accuracy and precision. With the help of End-of-Arm Tools (EOATs), robots are interacting with the environment. Robotic grippers are such EOATs which help to grasp the object in an automation system for improving the efficiency. As the robotic gripper directly influence the quality of the product due to the contact between the gripper surface and the object to be grasped, it is necessary to design and optimize the gripper mechanism configuration. In this study, geometric and kinematic modeling of the parallel gripper is proposed. Grey wolf optimizer algorithm is introduced for solving the proposed multiobjective gripper optimization problem. Two objective functions developed from the geometric and kinematic modeling along with several nonlinear constraints of the proposed gripper mechanism is used to optimize the design variables of the systems. Finally, the proposed methodology compared with a previously proposed method such as Teaching Learning Based Optimization (TLBO) algorithm, NSGA II, MODE and it was seen that the proposed method is more efficient compared to the earlier proposed methodology.Keywords: gripper optimization, metaheuristics, , teaching learning based algorithm, multi-objective optimization, optimal gripper design
Procedia PDF Downloads 1854250 Optimization of Solar Rankine Cycle by Exergy Analysis and Genetic Algorithm
Authors: R. Akbari, M. A. Ehyaei, R. Shahi Shavvon
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Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.Keywords: exergy analysis, genetic algorithm, rankine cycle, single and multi-objective function
Procedia PDF Downloads 1424249 Characterization of Zn-Ni Alloy Elaborated Under Low and High Magnetic Field Immersed in Corrosive Medium
Authors: Sabiha Chouchane, Azzedine Hani, Jean-Paul Chopart, Alexandra Levesque
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The electrodeposition of Zn-Ni alloy is mostly studied for its high degree of corrosion and mechanical properties. In this work, the zinc–nickel alloy coatings elaborated from sulfate bath have been carried out under low and high applied magnetic field. The effect of alloy stuctural parameters upon corrosion behavior is studied. It has been found that the magnetically induced convection changes the phase composition, promoting the zinc phase in spite of the γ-Ni₅Zn₂₁. Low magnetic field acts also on the morphology of the deposits as a levelling agent and a refiner by lowering the deposit roughness Ra and the spot size. For alloy obtained with low magnetic field (up to 1T) superimposition, surface morphology modification has no significant influence on corrosion behavior whereas for low nickel content alloy, the modification of phase composition, induced by applied magnetic field, favours higher polarization resistance. When high magnetic field amplitude is involved (up to12T), the phase composition modifications are the same that for low applied B and the morphology is not largely modified. In this case, the hydrogen reduction current dramatically decreases that leads to a large shift of the corrosion potential. It is suggested that the surface reactivity of electrodeposited alloys depends on the magnetically induced convection that is efficient during the codeposition process.Keywords: magnetic field, Zn-Ni alloy, corrosion, corrosive medium
Procedia PDF Downloads 434248 Investigation of Structural and Optical Properties of Coal Fly Ash Thin Film Doped with T𝒊O₂ Nanoparticles
Authors: Rawan Aljabbari, Thamer Alomayri, Faisal G. Al-Maqate, Abeer Al Suwat
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For environmentally friendly innovative technologies and a sustainable future, fly ash/TiO₂ thin film nanocomposites are essential. Fly ash will be doped with titanium dioxide in this work in order to better understand its optical characteristics and employ it in semiconductor electrical devices. This study focused on the structure, morphology, and optical properties of fly ash/TiO₂ thin films. The spin-coating technique was used to create thin coatings of fly ash/TiO₂. For the first time, the doping of TiO₂ in the fly ash host at ratios of 1, 2, and 3 wt% was investigated with the thickness of all samples fixed. When compared to undoped thin films, the surface morphology of the doped thin films was improved. The weakly crystalline structure of the doped fly ash films was verified by XRD. The optical bandgap energy of these films was successfully reduced by the TiO₂ doping, going from 3.9 to 3.5 eV. With increasing dopant concentration, the value of Urbach energy is increasing. The optical band gap is clearly in opposition to the disorder. While it considerably improved the optical conductivity to a value of 4.1 x 10^9 s^(-1), it also raised the refractive index and extinction coefficient. Depending on the TiO₂ doping ratio, the transmittance decreased, and the reflection increased. As the TiO₂ concentration rises, the absorption of photon energy rises, and the absorption coefficient of photon energy is reduced. results in their possible use as solar energy and semiconductor materials.Keywords: fly ash, structural analysis, optical properties, morphology
Procedia PDF Downloads 764247 Cooking Attributes of Rice Stored under Varying Temperature and Moisture Regimes
Authors: Lakshmi E. Jayachandran, Manepally Rajkumar, Pavuluri Srinivasa Rao
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The objective of this research was to study the changes in eating quality of rice during storage under varying temperature and moisture regimes. Paddy (IR-36) with high amylose content (27%) was stored at a temperature range between 10 to 40°C and moisture content from 9 to 18% (d.b.) for 6 months. Drastic changes in color and parameters representing cooking qualities, cooked rice texture, and surface morphology occurred after 4 months of storage, especially at elevated temperature conditions. Head rice yield was stable throughout the storage except at extreme conditions of temperature and moisture content. Yellowing of rice was prominent at combinations of high temperature and moisture content, both of which had a synergistic effect on the b* values of rice. The cooking time, length expansion ratio and volume expansion ratio of all the rice samples increased with prolonged storage. The texture parameter, primarily, the hardness, cohesiveness, and adhesiveness of cooked rice samples were higher following storage at elevated temperature. Surface morphology was also significantly affected in stored rice as compared to fresh rice. Storage of rice at 10°C with a grain moisture content of 10% for 2 months gave cooked rice samples with good palatability and minimal cooking time. The temperature was found to be the most prominent storage parameter for rough rice, followed by moisture content and storage duration, influencing the quality of rice.Keywords: rice, cooking quality, storage, surface morphology
Procedia PDF Downloads 1694246 Characterization of Thixoformed AlSi12 Alloy with the Addition of Trace Amounts of Silver
Authors: Nursen Saklakoglu, Adnan Turker
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The main objective of this study is to reveal the effect of the Thixoforming process on the microstructure and mechanical properties of the AlSi12 alloy with trace amounts of silver. It is concluded that Thixoforming has an important effect on the morphology of intermetallics and Si formation, as well as globular α-Al morphology. The intermetallics have been fractured during thixoforming. It is believed that the fine distribution of the intermetallics is one mechanism for the improved mechanical properties of Thixoformed alloys. The discrete Si particles have been observed during both isothermal heating to the semi-solid range and Thixoforming, also have an important effect on mechanical properties. The Thixoforming process has a greater effect on hardness than the addition of Ag does.Keywords: AlSi alloys, intermetallic phases, mechanical properties trace element, silver, thixoforming
Procedia PDF Downloads 3214245 Multi-Objective Random Drift Particle Swarm Optimization Algorithm Based on RDPSO and Crowding Distance Sorting
Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun
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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distributionKeywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution
Procedia PDF Downloads 2514244 Developing Model for Fuel Consumption Optimization in Aviation Industry
Authors: Somesh Kumar Sharma, Sunanad Gupta
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The contribution of aviation to society and economy is undisputedly significant. The aviation industry drives economic and social progress by contributing prominently to tourism, commerce and improved quality of life. Identifying the amount of fuel consumed by an aircraft while moving in both airspace and ground networks is critical to air transport economics. Aviation fuel is a major operating cost parameter of the aviation industry and at the same time it is prone to various constraints. This article aims to develop a model for fuel consumption of aviation product. The paper tailors the information for the fuel consumption optimization in terms of information development, information evaluation and information refinement. The information is evaluated and refined using statistical package R and Factor Analysis which is further validated with neural networking. The study explores three primary dimensions which are finally summarized into 23 influencing variables in contrast to 96 variables available in literature. The 23 variables explored in this study should be considered as highly influencing variables for fuel consumption which will contribute significantly towards fuel optimization.Keywords: fuel consumption, civil aviation industry, neural networking, optimization
Procedia PDF Downloads 3314243 Morphology and Permeability of Biomimetic Cellulose Triacetate-Impregnated Membranes: in situ Synchrotron Imaging and Experimental Studies
Authors: Amira Abdelrasoul
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This study aimed to ascertain the controlled permeability of biomimetic cellulose triacetate (CTA) membranes by investigating the electrical oscillatory behavior across impregnated membranes (IM). The biomimetic CTA membranes were infused with a fatty acid to induce electrical oscillatory behavior and, hence, to ensure controlled permeability. In situ synchrotron radiation micro-computed tomography (SR-μCT) at the BioMedical Imaging and Therapy (BMIT) Beamline at the Canadian Light Source (CLS) was used to evaluate the main morphology of IMs compared to neat CTA membranes to ensure fatty acid impregnation inside the pores of the membrane matrices. A monochromatic beam at 20 keV was used for the visualization of the morphology of the membrane. The X-ray radiographs were recorded by means of a beam monitor AA-40 (500 μm LuAG scintillator, Hamamatsu, Japan) coupled with a high-resolution camera, providing a pixel size of 5.5 μm and a field of view (FOV) of 4.4 mm × 2.2 mm. Changes were evident in the phase transition temperatures of the impregnated CTA membrane at the melting temperature of the fatty acid. The pulsations of measured voltages were related to changes in the salt concentration of KCl in the vicinity of the electrode. Amplitudes and frequencies of voltage pulsations were dependent on the temperature and concentration of the KCl solution, which controlled the permeability of the biomimetic membranes. The presented smart biomimetic membrane successfully combined porous polymer support and impregnating liquid not only imitate the main barrier properties of the biological membranes but could be easily modified to achieve some new properties, such as facilitated and active transport, regulation by chemical, physical and pharmaceutical factors. These results open new frontiers for the facilitation and regulation of active transport and permeability through biomimetic smart membranes for a variety of biomedical and drug delivery applications.Keywords: biomimetic, membrane, synchrotron, permeability, morphology
Procedia PDF Downloads 934242 Multiparametric Optimization of Water Treatment Process for Thermal Power Plants
Authors: Balgaisha Mukanova, Natalya Glazyrina, Sergey Glazyrin
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The formulated problem of optimization of the technological process of water treatment for thermal power plants is considered in this article. The problem is of multiparametric nature. To optimize the process, namely, reduce the amount of waste water, a new technology was developed to reuse such water. A mathematical model of the technology of wastewater reuse was developed. Optimization parameters were determined. The model consists of a material balance equation, an equation describing the kinetics of ion exchange for the non-equilibrium case and an equation for the ion exchange isotherm. The material balance equation includes a nonlinear term that depends on the kinetics of ion exchange. A direct problem of calculating the impurity concentration at the outlet of the water treatment plant was numerically solved. The direct problem was approximated by an implicit point-to-point computation difference scheme. The inverse problem was formulated as relates to determination of the parameters of the mathematical model of the water treatment plant operating in non-equilibrium conditions. The formulated inverse problem was solved. Following the results of calculation the time of start of the filter regeneration process was determined, as well as the period of regeneration process and the amount of regeneration and wash water. Multi-parameter optimization of water treatment process for thermal power plants allowed decreasing the amount of wastewater by 15%.Keywords: direct problem, multiparametric optimization, optimization parameters, water treatment
Procedia PDF Downloads 3834241 Crashworthiness Optimization of an Automotive Front Bumper in Composite Material
Authors: S. Boria
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In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.Keywords: composite material, crashworthiness, finite element analysis, optimization
Procedia PDF Downloads 2504240 Uncertain Time-Cost Trade off Problems of Construction Projects Using Fuzzy Set Theory
Authors: V. S. S. Kumar, B. Vikram
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The development of effective decision support tools that adopted in the construction industry is vital in the world we live in today, since it can lead to substantial cost reduction and efficient resource consumption. Solving the time-cost trade off problems and its related variants is at the heart of scientific research for optimizing construction planning problems. In general, the classical optimization techniques have difficulties in dealing with TCT problems. One of the main reasons of their failure is that they can easily be entrapped in local minima. This paper presents an investigation on the application of meta-heuristic techniques to two particular variants of the time-cost trade of analysis, the time-cost trade off problem (TCT), and time-cost trade off optimization problem (TCO). In first problem, the total project cost should be minimized, and in the second problem, the total project cost and total project duration should be minimized simultaneously. Finally it is expected that, the optimization models developed in this paper will contribute significantly for efficient planning and management of construction project.Keywords: fuzzy sets, uncertainty, optimization, time cost trade off problems
Procedia PDF Downloads 3504239 Optimization of Electric Vehicle (EV) Charging Station Allocation Based on Multiple Data - Taking Nanjing (China) as an Example
Authors: Yue Huang, Yiheng Feng
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Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing
Procedia PDF Downloads 874238 Route Planning for Optimization Approach PSO_GA Sharing System (Scooter Sharing-Public Transportation) with Hybrid Optimization Approach PSO_GA
Authors: Mohammad Ali Farrokhpour
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In the current decade and sustainable transportation systems, scooter sharing has attracted widespread attention as an environmentally-friendly means of public transportation which can help develop public transportation. The combination of scooters and subway in the area of sustainable transportation systems can provide a great many opportunities for developing access to public transportation. Of the challenges which have arisen and initiated discussions of interest about the implementation of a scooter-subway system to replace personal vehicles is the issue of routing in the aforementioned system. This has been chosen as the main subject of the present paper. Thus, the present paper provides an account for routing in this system. Because the issue of routing includes multiple factors such as time, costs, traffic, green spaces, etc., the above-mentioned problem is considered to be a multi-objective NP-hard optimization problem. For this purpose, the hybrid optimization approach of PSO-GA has been put forward in the present paper for the provided answers to be of higher accuracy and validity than those of normal optimization methods. The results obtained from modeling and problem solving for the case study in the MATLAB software are indicative of the efficiency and desirability of the model and the proposed approach for solving the modelKeywords: route planning, scooter sharing, public transportation, sharing system
Procedia PDF Downloads 784237 Transmit Power Optimization for Cooperative Beamforming in Reverse-Link MIMO Ad-Hoc Networks
Authors: Younghyun Jeon, Seungjoo Maeng
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In the Ad-hoc network, the great interests regarding MIMO scheme leads to their combination, which is also utilized into its applicable network. We manage the field of the problem into Reverse-link MIMO Ad-hoc Network (RMAN) and propose the methodology to maximize the data rate with its power consumption using Node-Cooperative beamforming technique. Based on the result of mathematical optimization formulation, we design the algorithm to construct optimal orthogonal weight vector according to channel feedback and control its transmission power according to QoS-pricing value level. In simulation results, we show the validity of the proposed mathematical optimization result and algorithm which mean that the sum-rate of each link is converged into some point.Keywords: ad-hoc network, MIMO, cooperative beamforming, transmit power
Procedia PDF Downloads 3914236 An Optimization Tool-Based Design Strategy Applied to Divide-by-2 Circuits with Unbalanced Loads
Authors: Agord M. Pinto Jr., Yuzo Iano, Leandro T. Manera, Raphael R. N. Souza
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This paper describes an optimization tool-based design strategy for a Current Mode Logic CML divide-by-2 circuit. Representing a building block for output frequency generation in a RFID protocol based-frequency synthesizer, the circuit was designed to minimize the power consumption for driving of multiple loads with unbalancing (at transceiver level). Implemented with XFAB XC08 180 nm technology, the circuit was optimized through MunEDA WiCkeD tool at Cadence Virtuoso Analog Design Environment ADE.Keywords: divide-by-2 circuit, CMOS technology, PLL phase locked-loop, optimization tool, CML current mode logic, RF transceiver
Procedia PDF Downloads 4584235 Development of Algorithms for the Study of the Image in Digital Form for Satellite Applications: Extraction of a Road Network and Its Nodes
Authors: Zineb Nougrara
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In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.Keywords: satellite image, road network, nodes, image analysis and processing
Procedia PDF Downloads 2694234 Parametric Analysis and Optimal Design of Functionally Graded Plates Using Particle Swarm Optimization Algorithm and a Hybrid Meshless Method
Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari
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The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.Keywords: optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization
Procedia PDF Downloads 3614233 Parametric Optimization of Wire Electric Discharge Machining (WEDM) for Aluminium Metal Matrix Composites
Authors: G. Rajyalakhmi, C. Karthik, Gerson Desouza, Rimmie Duraisamy
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In this present work, metal matrix composites with combination of aluminium with (Sic/Al2O3) were fabricated using stir casting technique. The objective of the present work is to optimize the process parameters of Wire Electric Discharge Machining (WEDM) composites. Pulse ON Time, Pulse OFF Time, wire feed and sensitivity are considered as input process parameters with responses Material Removal Rate (MRR), Surface Roughness (SR) for optimization of WEDM process. Taguchi L18 Orthogonal Array (OA) is used for experimentation. Grey Relational Analysis (GRA) is coupled with Taguchi technique for multiple process parameters optimization. ANOVA (Analysis of Variance) is used for finding the impact of process parameters individually. Finally confirmation experiments were carried out to validate the predicted results.Keywords: parametric optimization, particulate reinforced metal matrix composites, Taguchi-grey relational analysis, WEDM
Procedia PDF Downloads 5694232 An Improved Many Worlds Quantum Genetic Algorithm
Authors: Li Dan, Zhao Junsuo, Zhang Wenjun
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Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm.Keywords: quantum genetic algorithm, many worlds, quantum training operator, combinatorial optimization operator
Procedia PDF Downloads 7314231 Multi-Factor Optimization Method through Machine Learning in Building Envelope Design: Focusing on Perforated Metal Façade
Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim
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Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.Keywords: building envelope, machine learning, perforated metal, multi-factor optimization, façade
Procedia PDF Downloads 2164230 Urban Energy Demand Modelling: Spatial Analysis Approach
Authors: Hung-Chu Chen, Han Qi, Bauke de Vries
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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics
Procedia PDF Downloads 141