Search results for: weight improved particle swarm optimization (WIPSO)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11828

Search results for: weight improved particle swarm optimization (WIPSO)

11678 Optimization of Structures Subjected to Earthquake

Authors: Alireza Lavaei, Alireza Lohrasbi, Mohammadali M. Shahlaei

Abstract:

To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct RBF neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A 72-bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method.

Keywords: optimization, genetic algorithm, neural networks, self-organizing map

Procedia PDF Downloads 273
11677 An Algorithm for Herding Cows by a Swarm of Quadcopters

Authors: Jeryes Danial, Yosi Ben Asher

Abstract:

Algorithms for controlling a swarm of robots is an active research field, out of which cattle herding is one of the most complex problems to solve. In this paper, we derive an independent herding algorithm that is specifically designed for a swarm of quadcopters. The algorithm works by devising flight trajectories that cause the cows to run-away in the desired direction and hence herd cows that are distributed in a given field towards a common gathering point. Unlike previously proposed swarm herding algorithms, this algorithm does not use a flocking model but rather stars each cow separately. The effectiveness of this algorithm is verified experimentally using a simulator. We use a special set of experiments attempting to demonstrate that the herding times of this algorithm correspond to field diameter small constant regardless of the number of cows in the field. This is an optimal result indicating that the algorithm groups the cows into intermediate groups and herd them as one forming ever closing bigger groups.

Keywords: swarm, independent, distributed, algorithm

Procedia PDF Downloads 148
11676 Tree Species Classification Using Effective Features of Polarimetric SAR and Hyperspectral Images

Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

Abstract:

Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

Procedia PDF Downloads 387
11675 Radial Distribution Network Reliability Improvement by Using Imperialist Competitive Algorithm

Authors: Azim Khodadadi, Sahar Sadaat Vakili, Ebrahim Babaei

Abstract:

This study presents a numerical method to optimize the failure rate and repair time of a typical radial distribution system. Failure rate and repair time are effective parameters in customer and energy based indices of reliability. Decrease of these parameters improves reliability indices. Thus, system stability will be boost. The penalty functions indirectly reflect the cost of investment which spent to improve these indices. Constraints on customer and energy based indices, i.e. SAIFI, SAIDI, CAIDI and AENS have been considered by using a new method which reduces optimization algorithm controlling parameters. Imperialist Competitive Algorithm (ICA) used as main optimization technique and particle swarm optimization (PSO), simulated annealing (SA) and differential evolution (DE) has been applied for further investigation. These algorithms have been implemented on a test system by MATLAB. Obtained results have been compared with each other. The optimized values of repair time and failure rate are much lower than current values which this achievement reduced investment cost and also ICA gives better answer than the other used algorithms.

Keywords: imperialist competitive algorithm, failure rate, repair time, radial distribution network

Procedia PDF Downloads 628
11674 Half-Circle Fuzzy Number Threshold Determination via Swarm Intelligence Method

Authors: P. W. Tsai, J. W. Chen, C. W. Chen, C. Y. Chen

Abstract:

In recent years, many researchers are involved in the field of fuzzy theory. However, there are still a lot of issues to be resolved. Especially on topics related to controller design such as the field of robot, artificial intelligence, and nonlinear systems etc. Besides fuzzy theory, algorithms in swarm intelligence are also a popular field for the researchers. In this paper, a concept of utilizing one of the swarm intelligence method, which is called Bacterial-GA Foraging, to find the stabilized common P matrix for the fuzzy controller system is proposed. An example is given in in the paper, as well.

Keywords: half-circle fuzzy numbers, predictions, swarm intelligence, Lyapunov method

Procedia PDF Downloads 641
11673 Krill-Herd Step-Up Approach Based Energy Efficiency Enhancement Opportunities in the Offshore Mixed Refrigerant Natural Gas Liquefaction Process

Authors: Kinza Qadeer, Muhammad Abdul Qyyum, Moonyong Lee

Abstract:

Natural gas has become an attractive energy source in comparison with other fossil fuels because of its lower CO₂ and other air pollutant emissions. Therefore, compared to the demand for coal and oil, that for natural gas is increasing rapidly world-wide. The transportation of natural gas over long distances as a liquid (LNG) preferable for several reasons, including economic, technical, political, and safety factors. However, LNG production is an energy-intensive process due to the tremendous amount of power requirements for compression of refrigerants, which provide sufficient cold energy to liquefy natural gas. Therefore, one of the major issues in the LNG industry is to improve the energy efficiency of existing LNG processes through a cost-effective approach that is 'optimization'. In this context, a bio-inspired Krill-herd (KH) step-up approach was examined to enhance the energy efficiency of a single mixed refrigerant (SMR) natural gas liquefaction (LNG) process, which is considered as a most promising candidate for offshore LNG production (FPSO). The optimal design of a natural gas liquefaction processes involves multivariable non-linear thermodynamic interactions, which lead to exergy destruction and contribute to process irreversibility. As key decision variables, the optimal values of mixed refrigerant flow rates and process operating pressures were determined based on the herding behavior of krill individuals corresponding to the minimum energy consumption for LNG production. To perform the rigorous process analysis, the SMR process was simulated in Aspen Hysys® software and the resulting model was connected with the Krill-herd approach coded in MATLAB. The optimal operating conditions found by the proposed approach significantly reduced the overall energy consumption of the SMR process by ≤ 22.5% and also improved the coefficient of performance in comparison with the base case. The proposed approach was also compared with other well-proven optimization algorithms, such as genetic and particle swarm optimization algorithms, and was found to exhibit a superior performance over these existing approaches.

Keywords: energy efficiency, Krill-herd, LNG, optimization, single mixed refrigerant

Procedia PDF Downloads 123
11672 Particle Size Dependent Enhancement of Compressive Strength and Carbonation Efficiency in Steel Slag Cementitious Composites

Authors: Jason Ting Jing Cheng, Lee Foo Wei, Yew Ming Kun, Chin Ren Jie, Yip Chun Chieh

Abstract:

The utilization of industrial by-products, such as steel slag in cementitious materials, not only mitigates environmental impact but also enhances material properties. This study investigates the dual influence of steel slag particle size on the compressive strength and carbonation efficiency of cementitious composites. Through a systematic experimental approach, steel slag particles were incorporated into cement at varying sizes, and the resulting composites were subjected to mechanical and carbonation tests. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) are conducted in this paper. The findings reveal a positive correlation between increased particle size and compressive strength, attributed to the improved interfacial transition zone and packing density. Conversely, smaller particle sizes exhibited enhanced carbonation efficiency, likely due to the increased surface area facilitating the carbonation reaction. The presence of higher silica and calcium content in finer particles was confirmed by EDX, which contributed to the accelerated carbonation process. This study underscores the importance of particle size optimization in designing sustainable cementitious materials with balanced mechanical performance and carbon sequestration potential. The insights gained from the advanced analytical techniques offer a comprehensive understanding of the mechanisms at play, paving the way for the strategic use of steel slag in eco-friendly construction practices.

Keywords: steel slag, carbonation efficiency, particle size enhancement, compressive strength

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11671 Weight Comparison of Oil and Dry Type Distribution Transformers

Authors: Murat Toren, Mehmet Çelebi

Abstract:

Reducing the weight of transformers while providing good performance, cost reduction and increased efficiency is important. Weight is one of the most significant factors in all electrical machines, and as such, many transformer design parameters are related to weight calculations. This study presents a comparison of the weight of oil type transformers and dry type transformer weight. Oil type transformers are mainly used in industry; however, dry type transformers are becoming more widespread in recent years. MATLAB is typically used for designing transformers and design parameters (rated voltages, core loss, etc.) along with design in ANSYS Maxwell. Similar to other studies, this study presented that the dry type transformer option is limited. Moreover, the commonly-used 50 kVA distribution transformers in the industry are oil type and dry type transformers are designed and considered in terms of weight. Currently, the preference for low-cost oil-type transformers would change if costs for dry-type transformer were more competitive. The aim of this study was to compare the weight of transformers, which is a substantial cost factor, and to provide an evaluation about increasing the use of dry type transformers.

Keywords: weight, optimization, oil-type transformers, dry-type transformers

Procedia PDF Downloads 315
11670 An Efficient Process Analysis and Control Method for Tire Mixing Operation

Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

Abstract:

Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

Procedia PDF Downloads 235
11669 Sepiolite as a Processing Aid in Fibre Reinforced Cement Produced in Hatschek Machine

Authors: R. Pérez Castells, J. M. Carbajo

Abstract:

Sepiolite is used as a processing aid in the manufacture of fibre cement from the start of the replacement of asbestos in the 80s. Sepiolite increases the inter-laminar bond between cement layers and improves homogeneity of the slurries. A new type of sepiolite processed product, Wollatrop TF/C, has been checked as a retention agent for fine particles in the production of fibre cement in a Hatschek machine. The effect of Wollatrop T/FC on filtering and fine particle losses was studied as well as the interaction with anionic polyacrylamide and microsilica. The design of the experiments were factorial and the VDT equipment used for measuring retention and drainage was modified Rapid Köethen laboratory sheet former. Wollatrop TF/C increased the fine particle retention improving the economy of the process and reducing the accumulation of solids in recycled process water. At the same time, drainage time increased sharply at high concentration, however drainage time can be improved by adjusting APAM concentration. Wollatrop TF/C and microsilica are having very small interactions among them. Microsilica does not control fine particle losses while Wollatrop TF/C does efficiently. Further research on APAM type (molecular weight and anionic character) is advisable to improve drainage.

Keywords: drainage, fibre-reinforced cement, fine particle losses, flocculation, microsilica, sepiolite

Procedia PDF Downloads 304
11668 An Improved Cuckoo Search Algorithm for Voltage Stability Enhancement in Power Transmission Networks

Authors: Reza Sirjani, Nobosse Tafem Bolan

Abstract:

Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

Procedia PDF Downloads 522
11667 Water Quality Trading with Equitable Total Maximum Daily Loads

Authors: S. Jamshidi, E. Feizi Ashtiani, M. Ardestani, A. Feizi Ashtiani

Abstract:

Waste load allocation (WLA) strategies usually intend to find economical policies for water resource management. Water quality trading (WQT) is an approach that uses discharge permit market to reduce total environmental protection costs. This primarily requires assigning discharge limits known as total maximum daily loads (TMDLs). These are determined by monitoring organizations with respect to the receiving water quality and remediation capabilities. The purpose of this study is to compare two approaches of TMDL assignment for WQT policy in small catchment area of Haraz River, in north of Iran. At first, TMDLs are assigned uniformly for the whole point sources to keep the concentrations of BOD and dissolved oxygen (DO) at the standard level at checkpoint (terminus point). This was simply simulated and controlled by Qual2kw software. In the second scenario, TMDLs are assigned using multi objective particle swarm optimization (MOPSO) method in which the environmental violation at river basin and total treatment costs are minimized simultaneously. In both scenarios, the equity index and the WLA based on trading discharge permits (TDP) are calculated. The comparative results showed that using economically optimized TMDLs (2nd scenario) has slightly more cost savings rather than uniform TMDL approach (1st scenario). The former annually costs about 1 M$ while the latter is 1.15 M$. WQT can decrease these annual costs to 0.9 and 1.1 M$, respectively. In other word, these approaches may save 35 and 45% economically in comparison with command and control policy. It means that using multi objective decision support systems (DSS) may find more economical WLA, however its outcome is not necessarily significant in comparison with uniform TMDLs. This may be due to the similar impact factors of dischargers in small catchments. Conversely, using uniform TMDLs for WQT brings more equity that makes stakeholders not feel that much envious of difference between TMDL and WQT allocation. In addition, for this case, determination of TMDLs uniformly would be much easier for monitoring. Consequently, uniform TMDL for TDP market is recommended as a sustainable approach. However, economical TMDLs can be used for larger watersheds.

Keywords: waste load allocation (WLA), water quality trading (WQT), total maximum daily loads (TMDLs), Haraz River, multi objective particle swarm optimization (MOPSO), equity

Procedia PDF Downloads 373
11666 Design and Optimization of Composite Canopy Structure

Authors: Prakash Kattire, Rahul Pathare, Nilesh Tawde

Abstract:

A canopy is an overhead roof structure generally used at the entrance of a building to provide shelter from rain and sun and may also be used for decorative purposes. In this paper, the canopy structure to cover the conveyor line has been studied. Existing most of the canopy structures are made of steel and glass, which makes a heavier structure, so the purpose of this study is to weight and cost optimization of the canopy. To achieve this goal, the materials of construction considered are Polyvinyl chloride (PVC) natural composite, Fiber Reinforced Plastic (FRP), and Structural steel Fe250. Designing and modeling were done in Solid works, whereas Altair Inspire software was used for the optimization of the structure. Through this study, it was found that there is a total 10% weight reduction in the structure with sufficient reserve for structural strength.

Keywords: canopy, composite, FRP, PVC

Procedia PDF Downloads 114
11665 A Parallel Implementation of Artificial Bee Colony Algorithm within CUDA Architecture

Authors: Selcuk Aslan, Dervis Karaboga, Celal Ozturk

Abstract:

Artificial Bee Colony (ABC) algorithm is one of the most successful swarm intelligence based metaheuristics. It has been applied to a number of constrained or unconstrained numerical and combinatorial optimization problems. In this paper, we presented a parallelized version of ABC algorithm by adapting employed and onlooker bee phases to the Compute Unified Device Architecture (CUDA) platform which is a graphical processing unit (GPU) programming environment by NVIDIA. The execution speed and obtained results of the proposed approach and sequential version of ABC algorithm are compared on functions that are typically used as benchmarks for optimization algorithms. Tests on standard benchmark functions with different colony size and number of parameters showed that proposed parallelization approach for ABC algorithm decreases the execution time consumed by the employed and onlooker bee phases in total and achieved similar or better quality of the results compared to the standard sequential implementation of the ABC algorithm.

Keywords: Artificial Bee Colony algorithm, GPU computing, swarm intelligence, parallelization

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11664 Topology and Shape Optimization of Macpherson Control Arm under Fatigue Loading

Authors: Abolfazl Hosseinpour, Javad Marzbanrad

Abstract:

In this research, the topology and shape optimization of a Macpherson control arm has been accomplished to achieve lighter weight. Present automotive market demands low cost and light weight component to meet the need of fuel efficient and cost effective vehicle. This in turn gives the rise to more effective use of materials for automotive parts which can reduce the mass of vehicle. Since automotive components are under dynamic loads which cause fatigue damage, considering fatigue criteria seems to be essential in designing automotive components. At first, in order to create severe loading condition for control arm, some rough roads are generated through power spectral density. Then, the most critical loading conditions are obtained through multibody dynamics analysis of a full vehicle model. Then, the topology optimization is performed based on fatigue life criterion using HyperMesh software, which resulted to 50 percent mass reduction. In the next step a CAD model is created using CATIA software and shape optimization is performed to achieve accurate dimensions with less mass.

Keywords: topology optimization, shape optimization, fatigue life, MacPherson control arm

Procedia PDF Downloads 289
11663 Reactive Power Cost Evaluation with FACTS Devices in Restructured Power System

Authors: A. S. Walkey, N. P. Patidar

Abstract:

It is not always economical to provide reactive power using synchronous alternators. The cost of reactive power can be minimized by optimal placing of FACTS devices in power systems. In this paper a Particle Swarm Optimization- Sequential Quadratic Programming (PSO-SQP) algorithm is applied to minimize the cost of reactive power generation along with real power generation to alleviate the bus voltage violations. The effectiveness of proposed approach tested on IEEE-14 bus systems. In this paper in addition to synchronous generators, an opportunity of FACTS devices are also proposed to procure the reactive power demands in the power system.

Keywords: reactive power, reactive power cost, voltage security margins, capability curve, FACTS devices

Procedia PDF Downloads 474
11662 Solving the Economic Load Dispatch Problem Using Differential Evolution

Authors: Alaa Sheta

Abstract:

Economic Load Dispatch (ELD) is one of the vital optimization problems in power system planning. Solving the ELD problems mean finding the best mixture of power unit outputs of all members of the power system network such that the total fuel cost is minimized while sustaining operation requirements limits satisfied across the entire dispatch phases. Many optimization techniques were proposed to solve this problem. A famous one is the Quadratic Programming (QP). QP is a very simple and fast method but it still suffer many problem as gradient methods that might trapped at local minimum solutions and cannot handle complex nonlinear functions. Numbers of metaheuristic algorithms were used to solve this problem such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). In this paper, another meta-heuristic search algorithm named Differential Evolution (DE) is used to solve the ELD problem in power systems planning. The practicality of the proposed DE based algorithm is verified for three and six power generator system test cases. The gained results are compared to existing results based on QP, GAs and PSO. The developed results show that differential evolution is superior in obtaining a combination of power loads that fulfill the problem constraints and minimize the total fuel cost. DE found to be fast in converging to the optimal power generation loads and capable of handling the non-linearity of ELD problem. The proposed DE solution is able to minimize the cost of generated power, minimize the total power loss in the transmission and maximize the reliability of the power provided to the customers.

Keywords: economic load dispatch, power systems, optimization, differential evolution

Procedia PDF Downloads 259
11661 Design of a Graphical User Interface for Data Preprocessing and Image Segmentation Process in 2D MRI Images

Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

Abstract:

The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

Procedia PDF Downloads 348
11660 Development of Methods for Plastic Injection Mold Weight Reduction

Authors: Bita Mohajernia, R. J. Urbanic

Abstract:

Mold making techniques have focused on meeting the customers’ functional and process requirements; however, today, molds are increasing in size and sophistication, and are difficult to manufacture, transport, and set up due to their size and mass. Presently, mold weight saving techniques focus on pockets to reduce the mass of the mold, but the overall size is still large, which introduces costs related to the stock material purchase, processing time for process planning, machining and validation, and excess waste materials. Reducing the overall size of the mold is desirable for many reasons, but the functional requirements, tool life, and durability cannot be compromised in the process. It is proposed to use Finite Element Analysis simulation tools to model the forces, and pressures to determine where the material can be removed. The potential results of this project will reduce manufacturing costs. In this study, a light weight structure is defined by an optimal distribution of material to carry external loads. The optimization objective of this research is to determine methods to provide the optimum layout for the mold structure. The topology optimization method is utilized to improve structural stiffness while decreasing the weight using the OptiStruct software. The optimized CAD model is compared with the primary geometry of the mold from the NX software. Results of optimization show an 8% weight reduction while the actual performance of the optimized structure, validated by physical testing, is similar to the original structure.

Keywords: finite element analysis, plastic injection molding, topology optimization, weight reduction

Procedia PDF Downloads 264
11659 Topology Optimization of Heat Exchanger Manifolds for Aircraft

Authors: Hanjong Kim, Changwan Han, Seonghun Park

Abstract:

Heat exchanger manifolds in aircraft play an important role in evenly distributing the fluid entering through the inlet to the heat transfer unit. In order to achieve this requirement, the manifold should be designed to have a light weight by withstanding high internal pressure. Therefore, this study aims at minimizing the weight of the heat exchanger manifold through topology optimization. For topology optimization, the initial design space was created with the inner surface extracted from the currently used manifold model and with the outer surface having a dimension of 243.42 mm of X 74.09 mm X 65 mm. This design space solid model was transformed into a finite element model with a maximum tetrahedron mesh size of 2 mm using ANSYS Workbench. Then, topology optimization was performed under the boundary conditions of an internal pressure of 5.5 MPa and the fixed support for rectangular inlet boundaries by SIMULIA TOSCA. This topology optimization produced the minimized finial volume of the manifold (i.e., 7.3% of the initial volume) based on the given constraints (i.e., 6% of the initial volume) and the objective function (i.e., maximizing manifold stiffness). Weight of the optimized model was 6.7% lighter than the currently used manifold, but after smoothing the topology optimized model, this difference would be bigger. The current optimized model has uneven thickness and skeleton-shaped outer surface to reduce stress concentration. We are currently simplifying the optimized model shape with spline interpolations by reflecting the design characteristics in thickness and skeletal structures from the optimized model. This simplified model will be validated again by calculating both stress distributions and weight reduction and then the validated model will be manufactured using 3D printing processes.

Keywords: topology optimization, manifold, heat exchanger, 3D printing

Procedia PDF Downloads 216
11658 Application of Imperialist Competitive Algorithm for Optimal Location and Sizing of Static Compensator Considering Voltage Profile

Authors: Vahid Rashtchi, Ashkan Pirooz

Abstract:

This paper applies the Imperialist Competitive Algorithm (ICA) to find the optimal place and size of Static Compensator (STATCOM) in power systems. The output of the algorithm is a two dimensional array which indicates the best bus number and STATCOM's optimal size that minimizes all bus voltage deviations from their nominal value. Simulations are performed on IEEE 5, 14, and 30 bus test systems. Also some comparisons have been done between ICA and the famous Particle Swarm Optimization (PSO) algorithm. Results show that how this method can be considered as one of the most precise evolutionary methods for the use of optimum compensator placement in electrical grids.

Keywords: evolutionary computation, imperialist competitive algorithm, power systems compensation, static compensators, voltage profile

Procedia PDF Downloads 579
11657 Effect of Alloying Elements on Particle Incorporation of Boron Carbide Reinforced Aluminum Matrix Composites

Authors: Steven Ploetz, Andreas Lohmueller, Robert F. Singer

Abstract:

The outstanding performance of aluminum matrix composites (AMCs) regarding stiffness/weight ratio makes AMCs attractive material for lightweight construction. Low-density boride compounds promise simultaneously an increase in stiffness and decrease in composite density. This is why boron carbide is chosen for composite manufacturing. The composites are fabricated with the stir casting process. To avoid gas entrapment during mixing and ensure nonporous composites, partial vacuum is adapted during particle feeding and stirring. Poor wettability of boron carbide with liquid aluminum hinders particle incorporation, but alloying elements such as magnesium and titanium could improve wettability and thus particle incorporation. Next to alloying elements, adapted stirring parameters and impeller geometries improve particle incorporation and enable homogenous particle distribution and high particle volume fractions of boron carbide. AMCs with up to 15 vol.% of boron carbide particles are produced via melt stirring, resulting in an increase in stiffness and strength.

Keywords: aluminum matrix composites, boron carbide, stiffness, stir casting

Procedia PDF Downloads 286
11656 An Online Priority-Configuration Algorithm for Obstacle Avoidance of the Unmanned Air Vehicles Swarm

Authors: Lihua Zhu, Jianfeng Du, Yu Wang, Zhiqiang Wu

Abstract:

Collision avoidance problems of a swarm of unmanned air vehicles (UAVs) flying in an obstacle-laden environment are investigated in this paper. Given that the UAV swarm needs to adapt to the obstacle distribution in dynamic operation, a priority configuration is designed to guide the UAVs to pass through the obstacles in turn. Based on the collision cone approach and the prediction of the collision time, a collision evaluation model is established to judge the urgency of the imminent collision of each UAV, and the evaluation result is used to assign the priority of each UAV to further instruct them going through the obstacles in descending order. At last, the simulation results provide the promising validation in terms of the efficiency and scalability of the proposed approach.

Keywords: UAV swarm, collision avoidance, complex environment, online priority design

Procedia PDF Downloads 187
11655 IACOP - Route Optimization in Wireless Networks Using Improved Ant Colony Optimization Protocol

Authors: S. Vasundra, D. Venkatesh

Abstract:

Wireless networks have gone through an extraordinary growth in the past few years, and will keep on playing a crucial role in future data communication. The present wireless networks aim to make communication possible anywhere and anytime. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Since an ad hoc network may consist of a large number of mobile hosts, this imposes a significant challenge on the design of an effective and efficient routing protocol that can work well in an environment with frequent topological changes. This paper proposes improved ant colony optimization (IACO) technique. It also maintains load balancing in wireless networks. The simulation results show that the proposed IACO performs better than existing routing techniques.

Keywords: wireless networks, ant colony optimization, load balancing, architecture

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11654 Influence of Processing Parameters on the Reliability of Sieving as a Particle Size Distribution Measurements

Authors: Eseldin Keleb

Abstract:

In the pharmaceutical industry particle size distribution is an important parameter for the characterization of pharmaceutical powders. The powder flowability, reactivity and compatibility, which have a decisive impact on the final product, are determined by particle size and size distribution. Therefore, the aim of this study was to evaluate the influence of processing parameters on the particle size distribution measurements. Different Size fractions of α-lactose monohydrate and 5% polyvinylpyrrolidone were prepared by wet granulation and were used for the preparation of samples. The influence of sieve load (50, 100, 150, 200, 250, 300, and 350 g), processing time (5, 10, and 15 min), sample size ratios (high percentage of small and large particles), type of disturbances (vibration and shaking) and process reproducibility have been investigated. Results obtained showed that a sieve load of 50 g produce the best separation, a further increase in sample weight resulted in incomplete separation even after the extension of the processing time for 15 min. Performing sieving using vibration was rapider and more efficient than shaking. Meanwhile between day reproducibility showed that particle size distribution measurements are reproducible. However, for samples containing 70% fines or 70% large particles, which processed at optimized parameters, the incomplete separation was always observed. These results indicated that sieving reliability is highly influenced by the particle size distribution of the sample and care must be taken for samples with particle size distribution skewness.

Keywords: sieving, reliability, particle size distribution, processing parameters

Procedia PDF Downloads 579
11653 Cylindrical Spacer Shape Optimization for Enhanced Inhalation Therapy

Authors: Shahab Azimi, Siamak Arzanpour, Anahita Sayyar

Abstract:

Asthma and Chronic obstructive pulmonary disease (COPD) are common lung diseases that have a significant global impact. Pressurized metered dose inhalers (pMDIs) are widely used for treatment, but they can have limitations such as high medication release speed resulting in drug deposition in the mouth or oral cavity and difficulty achieving proper synchronization with inhalation by users. Spacers are add-on devices that improve the efficiency of pMDIs by reducing the release speed and providing space for aerosol particle breakup to have finer and medically effective medication. The aim of this study is to optimize the size and cylindrical shape of spacers to enhance their drug delivery performance. The study was based on fluid dynamics theory and employed Ansys software for simulation and optimization. Results showed that optimization of the spacer's geometry greatly influenced its performance and improved drug delivery. This study provides a foundation for future research on enhancing the efficiency of inhalation therapy for lung diseases.

Keywords: asthma, COPD, pressurized metered dose inhalers, spacers, CFD, shape optimization

Procedia PDF Downloads 55
11652 Growth Performance and Critical Supersaturation of Heterogeneous Condensation for High Concentration of Insoluble Sub-Micron Particles

Authors: Jie Yin, Jun Zhang

Abstract:

Measuring the growth performance and critical supersaturation of particle group have a high reference value for constructing a supersaturated water vapor environment that can improve the removal efficiency of the high-concentration particle group. The critical supersaturation and the variation of the growth performance with supersaturation for high-concentration particles were measured by a flow cloud chamber. Findings suggest that the influence of particle concentration on the growth performance will reduce with the increase of supersaturation. Reducing residence time and increasing particle concentration have similar effects on the growth performance of the high-concentration particle group. Increasing particle concentration and shortening residence time will increase the critical supersaturation of the particle group. The critical supersaturation required to activate a high-concentration particle group is lower than that of the single-particle when the minimum particle size in the particle group is the same as that of a single particle.

Keywords: sub-micron particles, heterogeneous condensation, critical supersaturation, nucleation

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11651 Using Swarm Intelligence to Forecast Outcomes of English Premier League Matches

Authors: Hans Schumann, Colin Domnauer, Louis Rosenberg

Abstract:

In this study, machine learning techniques were deployed on real-time human swarm data to forecast the likelihood of outcomes for English Premier League matches in the 2020/21 season. These techniques included ensemble models in combination with neural networks and were tested against an industry standard of Vegas Oddsmakers. Predictions made from the collective intelligence of human swarm participants managed to achieve a positive return on investment over a full season on matches, empirically proving the usefulness of a new artificial intelligence valuing human instinct and intelligence.

Keywords: artificial intelligence, data science, English Premier League, human swarming, machine learning, sports betting, swarm intelligence

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11650 Effects of Particle Size Distribution on Mechanical Strength and Physical Properties in Engineered Quartz Stone

Authors: Esra Arici, Duygu Olmez, Murat Ozkan, Nurcan Topcu, Furkan Capraz, Gokhan Deniz, Arman Altinyay

Abstract:

Engineered quartz stone is a composite material comprising approximately 90 wt.% fine quartz aggregate with a variety of particle size ranges and `10 wt.% unsaturated polyester resin (UPR). In this study, the objective is to investigate the influence of particle size distribution on mechanical strength and physical properties of the engineered stone slabs. For this purpose, granular quartz with two particle size ranges of 63-200 µm and 100-300 µm were used individually and mixed with a difference in ratios of mixing. The void volume of each granular packing was measured in order to define the amount of filler; quartz powder with the size of less than 38 µm, and UPR required filling inter-particle spaces. Test slabs were prepared using vibration-compression under vacuum. The study reports that both impact strength and flexural strength of samples increased as the mix ratio of the particle size range of 63-200 µm increased. On the other hand, the values of water absorption rate, apparent density and abrasion resistance were not affected by the particle size distribution owing to vacuum compaction. It is found that increasing the mix ratio of the particle size range of 63-200 µm caused the higher porosity. This led to increasing in the amount of the binder paste needed. It is also observed that homogeneity in the slabs was improved with the particle size range of 63-200 µm.

Keywords: engineered quartz stone, fine quartz aggregate, granular packing, mechanical strength, particle size distribution, physical properties.

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11649 An Improved Many Worlds Quantum Genetic Algorithm

Authors: Li Dan, Zhao Junsuo, Zhang Wenjun

Abstract:

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

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