Search results for: optimization process
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17358

Search results for: optimization process

16518 Budget Optimization for Maintenance of Bridges in Egypt

Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

Abstract:

Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

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16517 Optimal Performance of Plastic Extrusion Process Using Fuzzy Goal Programming

Authors: Abbas Al-Refaie

Abstract:

This study optimized the performance of plastic extrusion process of drip irrigation pipes using fuzzy goal programming. Two main responses were of main interest; roll thickness and hardness. Four main process factors were studied. The L18 array was then used for experimental design. The individual-moving range control charts were used to assess the stability of the process, while the process capability index was used to assess process performance. Confirmation experiments were conducted at the obtained combination of optimal factor setting by fuzzy goal programming. The results revealed that process capability was improved significantly from -1.129 to 0.8148 for roll thickness and from 0.0965 to 0.714 and hardness. Such improvement results in considerable savings in production and quality costs.

Keywords: fuzzy goal programming, extrusion process, process capability, irrigation plastic pipes

Procedia PDF Downloads 264
16516 Optimization of the Aerodynamic Performances of an Unmanned Aerial Vehicle

Authors: Fares Senouci, Bachir Imine

Abstract:

This document provides numerical and experimental optimization of the aerodynamic performance of a drone equipped with three types of horizontal stabilizer. To build this optimal configuration, an experimental and numerical study was conducted on three parameters: the geometry of the stabilizer (horizontal form or reverse V form), the position of the horizontal stabilizer (up or down), and the landing gear position (closed or open). The results show that up-stabilizer position with respect to the horizontal plane of the fuselage provides better aerodynamic performance, and that the landing gear increases the lift in the zone of stability, that is to say where the flow is not separated.

Keywords: aerodynamics, drag, lift, turbulence model, wind tunnel

Procedia PDF Downloads 248
16515 Embedding Knowledge Management in Business Process

Authors: Paul Ihuoma Oluikpe

Abstract:

The purpose of this paper is to explore and highlight the process of creating value for strategy management by embedding knowledge management in the business process. Knowledge management can be seen from a three-dimensional perspective of content, connections and competencies. These dimensions can be embedded in the knowledge processes (create, capture, share, and apply) and operationalized within a business process to effectively create a scenario where knowledge can be focused on enabling a process and the process in turn generates outcomes. The application of knowledge management on business processes of organizations is rare and underreported. Few researches have explored this paradigm although researches have tended to reinforce the notion that competitive advantage sits within the internal aspects of the firm. Given this notion, it is surprising that knowledge management research and practice have not focused sufficiently on the business process which is the basic unit of organizational decision implementation. This research serves to generate understanding on applying KM in business process using a large multinational in Sub-Saharan Africa.

Keywords: knowledge management, business process, strategy, multinational

Procedia PDF Downloads 686
16514 Optimization of Alkali Assisted Microwave Pretreatments of Sorghum Straw for Efficient Bioethanol Production

Authors: Bahiru Tsegaye, Chandrajit Balomajumder, Partha Roy

Abstract:

The limited supply and related negative environmental consequence of fossil fuels are driving researcher for finding sustainable sources of energy. Lignocellulose biomass like sorghum straw is considered as among cheap, renewable and abundantly available sources of energy. However, lignocellulose biomass conversion to bioenergy like bioethanol is hindered due to the reluctant nature of lignin in the biomass. Therefore, removal of lignin is a vital step for lignocellulose conversion to renewable energy. The aim of this study is to optimize microwave pretreatment conditions using design expert software to remove lignin and to release maximum possible polysaccharides from sorghum straw for efficient hydrolysis and fermentation process. Sodium hydroxide concentration between 0.5-1.5%, v/v, pretreatment time from 5-25 minutes and pretreatment temperature from 120-2000C were considered to depolymerize sorghum straw. The effect of pretreatment was studied by analyzing the compositional changes before and after pretreatments following renewable energy laboratory procedure. Analysis of variance (ANOVA) was used to test the significance of the model used for optimization. About 32.8%-48.27% of hemicellulose solubilization, 53% -82.62% of cellulose release, and 49.25% to 78.29% lignin solubilization were observed during microwave pretreatment. Pretreatment for 10 minutes with alkali concentration of 1.5% and temperature of 1400C released maximum cellulose and lignin. At this optimal condition, maximum of 82.62% of cellulose release and 78.29% of lignin removal was achieved. Sorghum straw at optimal pretreatment condition was subjected to enzymatic hydrolysis and fermentation. The efficiency of hydrolysis was measured by analyzing reducing sugars by 3, 5 dinitrisylicylic acid method. Reducing sugars of about 619 mg/g of sorghum straw were obtained after enzymatic hydrolysis. This study showed a significant amount of lignin removal and cellulose release at optimal condition. This enhances the yield of reducing sugars as well as ethanol yield. The study demonstrates the potential of microwave pretreatments for enhancing bioethanol yield from sorghum straw.

Keywords: cellulose, hydrolysis, lignocellulose, optimization

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16513 Physical Parameters Influencing the Yield of Nigella Sativa Oil Extracted by Hydraulic Pressing

Authors: Hadjadj Naima, K. Mahdi, D. Belhachat, F. S. Ait Chaouche, A. Ferradji

Abstract:

The Nigella Sativa oil yield extracted by hydraulic pressing is influenced by the pressure temperature and size particles. The optimization of oil extraction is investigated. The rate of extraction of the whole seeds is very weak, a crushing of seeds is necessary to facilitate the extraction. This rate augments with the rise of the temperature and the pressure, and decrease of size particles. The best output (66%) is obtained for a granulometry lower than 1mm, a temperature of 50°C and a pressure of 120 bars.

Keywords: oil, Nigella sativa, extraction, optimization, temperature, pressure

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16512 Optimized Renewable Energy Mix for Energy Saving in Waste Water Treatment Plants

Authors: J. D. García Espinel, Paula Pérez Sánchez, Carlos Egea Ruiz, Carlos Lardín Mifsut, Andrés López-Aranguren Oliver

Abstract:

This paper shortly describes three main actuations over a Waste Water Treatment Plant (WWTP) for reducing its energy consumption: Optimization of the biological reactor in the aeration stage by including new control algorithms and introducing new efficient equipment, the installation of an innovative hybrid system with zero Grid injection (formed by 100kW of PV energy and 5 kW of mini-wind energy generation) and an intelligent management system for load consumption and energy generation control in the most optimum way. This project called RENEWAT, involved in the European Commission call LIFE 2013, has the main objective of reducing the energy consumptions through different actions on the processes which take place in a WWTP and introducing renewable energies on these treatment plants, with the purpose of promoting the usage of treated waste water for irrigation and decreasing the C02 gas emissions. WWTP is always required before waste water can be reused for irrigation or discharged in water bodies. However, the energetic demand of the treatment process is high enough for making the price of treated water to exceed the one for drinkable water. This makes any policy very difficult to encourage the re-use of treated water, with a great impact on the water cycle, particularly in those areas suffering hydric stress or deficiency. The cost of treating waste water involves another climate-change related burden: the energy necessary for the process is obtained mainly from the electric network, which is, in most of the cases in Europe, energy obtained from the burning of fossil fuels. The innovative part of this project is based on the implementation, adaptation and integration of solutions for this problem, together with a new concept of the integration of energy input and operative energy demand. Moreover, there is an important qualitative jump between the technologies used and the alleged technologies to use in the project which give it an innovative character, due to the fact that there are no similar previous experiences of a WWTP including an intelligent discrimination of energy sources, integrating renewable ones (PV and Wind) and the grid.

Keywords: aeration system, biological reactor, CO2 emissions, energy efficiency, hybrid systems, LIFE 2013 call, process optimization, renewable energy sources, wasted water treatment plants

Procedia PDF Downloads 350
16511 A Review on Artificial Neural Networks in Image Processing

Authors: B. Afsharipoor, E. Nazemi

Abstract:

Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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16510 Degradation of Emerging Pharmaceuticals by Gamma Irradiation Process

Authors: W. Jahouach-Rabai, J. Aribi, Z. Azzouz-Berriche, R. Lahsni, F. Hosni

Abstract:

Gamma irradiation applied in removing pharmaceutical contaminants from wastewater is an effective advanced oxidation process (AOP), considered as an alternative to conventional water treatment technologies. In this purpose, the degradation efficiency of several detected contaminants under gamma irradiation was evaluated. In fact, radiolysis of organic pollutants in aqueous solutions produces powerful reactive species, essentially hydroxyl radical ( ·OH), able to destroy recalcitrant pollutants in water. Pharmaceuticals considered in this study are aqueous solutions of paracetamol, ibuprofen, and diclofenac at different concentrations 0.1-1 mmol/L, which were treated with irradiation doses from 3 to 15 kGy. The catalytic oxidation of these compounds by gamma irradiation was investigated using hydrogen peroxide (H₂O₂) as a convenient oxidant. Optimization of the main parameters influencing irradiation process, namely irradiation doses, initial concentration and oxidant volume (H₂O₂) were investigated, in the aim to release high degradation efficiency of considered pharmaceuticals. Significant modifications attributed to these parameters appeared in the variation of degradation efficiency, chemical oxygen demand removal (COD) and concentration of radio-induced radicals, confirming them synergistic effect to attempt total mineralization. Pseudo-first-order reaction kinetics could be used to depict the degradation process of these compounds. A sophisticated analytical study was released to quantify the detected radio-induced radicals (electron paramagnetic resonance spectroscopy (EPR) and high performance liquid chromatography (HPLC)). All results showed that this process is effective for the degradation of many pharmaceutical products in aqueous solutions due to strong oxidative properties of generated radicals mainly hydroxyl radical. Furthermore, the addition of an optimal amount of H₂O₂ was efficient to improve the oxidative degradation and contribute to the high performance of this process at very low doses (0.5 and 1 kGy).

Keywords: AOP, COD, hydroxyl radical, EPR, gamma irradiation, HPLC, pharmaceuticals

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16509 Taguchi Approach for the Optimization of the Stitching Defects of Knitted Garments

Authors: Adel El-Hadidy

Abstract:

For any industry, the production and quality management or wastages reductions have major impingement on overall factory economy. This work discusses the quality improvement of garment industry by applying Pareto analysis, cause and effect diagram and Taguchi experimental design. The main purpose of the work is to reduce the stitching defects, which will also minimize the rejection and reworks rate. Application of Pareto chart, fish bone diagram and Process Sigma Level/and or Performance Level tools helps solving those problems on priority basis. Among all, only sewing, defects are responsible form 69.3% to 97.3 % of total defects. Process Sigma level has been improved from 0.79 to 1.3 and performance rate improved, from F to D level. The results showed that the new set of sewing parameters was superior to the original one. It can be seen that fabric size has the largest effect on the sewing defects and that needle size has the smallest effect on the stitching defects.

Keywords: garment, sewing defects, cost of rework, DMAIC, sigma level, cause and effect diagram, Pareto analysis

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16508 Obtaining Constants of Johnson-Cook Material Model Using a Combined Experimental, Numerical Simulation and Optimization Method

Authors: F. Rahimi Dehgolan, M. Behzadi, J. Fathi Sola

Abstract:

In this article, the Johnson-Cook material model’s constants for structural steel ST.37 have been determined by a method which integrates experimental tests, numerical simulation, and optimization. In the first step, a quasi-static test was carried out on a plain specimen. Next, the constants were calculated for it by minimizing the difference between the results acquired from the experiment and numerical simulation. Then, a quasi-static tension test was performed on three notched specimens with different notch radii. At last, in order to verify the results, they were used in numerical simulation of notched specimens and it was observed that experimental and simulation results are in good agreement. Changing the diameter size of the plain specimen in the necking area was set as the objective function in the optimization step. For final validation of the proposed method, diameter variation was considered as a parameter and its sensitivity to a change in any of the model constants was examined and the results were completely corroborating.

Keywords: constants, Johnson-Cook material model, notched specimens, quasi-static test, sensitivity

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16507 Practical Software for Optimum Bore Hole Cleaning Using Drilling Hydraulics Techniques

Authors: Abdulaziz F. Ettir, Ghait Bashir, Tarek S. Duzan

Abstract:

A proper well planning is very vital to achieve any successful drilling program on the basis of preventing, overcome all drilling problems and minimize cost operations. Since the hydraulic system plays an active role during the drilling operations, that will lead to accelerate the drilling effort and lower the overall well cost. Likewise, an improperly designed hydraulic system can slow drill rate, fail to clean the hole of cuttings, and cause kicks. In most cases, common sense and commercially available computer programs are the only elements required to design the hydraulic system. Drilling optimization is the logical process of analyzing effects and interactions of drilling variables through applied drilling and hydraulic equations and mathematical modeling to achieve maximum drilling efficiency with minimize drilling cost. In this paper, practical software adopted in this paper to define drilling optimization models including four different optimum keys, namely Opti-flow, Opti-clean, Opti-slip and Opti-nozzle that can help to achieve high drilling efficiency with lower cost. The used data in this research from vertical and horizontal wells were recently drilled in Waha Oil Company fields. The input data are: Formation type, Geopressures, Hole Geometry, Bottom hole assembly and Mud reghology. Upon data analysis, all the results from wells show that the proposed program provides a high accuracy than that proposed from the company in terms of hole cleaning efficiency, and cost break down if we consider that the actual data as a reference base for all wells. Finally, it is recommended to use the established Optimization calculations software at drilling design to achieve correct drilling parameters that can provide high drilling efficiency, borehole cleaning and all other hydraulic parameters which assist to minimize hole problems and control drilling operation costs.

Keywords: optimum keys, namely opti-flow, opti-clean, opti-slip and opti-nozzle

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16506 Multi-Objective Optimization of Assembly Manufacturing Factory Setups

Authors: Andreas Lind, Aitor Iriondo Pascual, Dan Hogberg, Lars Hanson

Abstract:

Factory setup lifecycles are most often described and prepared in CAD environments; the preparation is based on experience and inputs from several cross-disciplinary processes. Early in the factory setup preparation, a so-called block layout is created. The intention is to describe a high-level view of the intended factory setup and to claim area reservations and allocations. Factory areas are then blocked, i.e., targeted to be used for specific intended resources and processes, later redefined with detailed factory setup layouts. Each detailed layout is based on the block layout and inputs from cross-disciplinary preparation processes, such as manufacturing sequence, productivity, workers’ workplace requirements, and resource setup preparation. However, this activity is often not carried out with all variables considered simultaneously, which might entail a risk of sub-optimizing the detailed layout based on manual decisions. Therefore, this work aims to realize a digital method for assembly manufacturing layout planning where productivity, area utilization, and ergonomics can be considered simultaneously in a cross-disciplinary manner. The purpose of the digital method is to support engineers in finding optimized designs of detailed layouts for assembly manufacturing factories, thereby facilitating better decisions regarding setups of future factories. Input datasets are company-specific descriptions of required dimensions for specific area reservations, such as defined dimensions of a worker’s workplace, material façades, aisles, and the sequence to realize the product assembly manufacturing process. To test and iteratively develop the digital method, a demonstrator has been developed with an adaptation of existing software that simulates and proposes optimized designs of detailed layouts. Since the method is to consider productivity, ergonomics, area utilization, and constraints from the automatically generated block layout, a multi-objective optimization approach is utilized. In the demonstrator, the input data are sent to the simulation software industrial path solutions (IPS). Based on the input and Lua scripts, the IPS software generates a block layout in compliance with the company’s defined dimensions of area reservations. Communication is then established between the IPS and the software EPP (Ergonomics in Productivity Platform), including intended resource descriptions, assembly manufacturing process, and manikin (digital human) resources. Using multi-objective optimization approaches, the EPP software then calculates layout proposals that are sent iteratively and simulated and rendered in IPS, following the rules and regulations defined in the block layout as well as productivity and ergonomics constraints and objectives. The software demonstrator is promising. The software can handle several parameters to optimize the detailed layout simultaneously and can put forward several proposals. It can optimize multiple parameters or weight the parameters to fine-tune the optimal result of the detailed layout. The intention of the demonstrator is to make the preparation between cross-disciplinary silos transparent and achieve a common preparation of the assembly manufacturing factory setup, thereby facilitating better decisions.

Keywords: factory setup, multi-objective, optimization, simulation

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16505 Modelling and Optimisation of Floating Drum Biogas Reactor

Authors: L. Rakesh, T. Y. Heblekar

Abstract:

This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

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16504 Generative Design of Acoustical Diffuser and Absorber Elements Using Large-Scale Additive Manufacturing

Authors: Saqib Aziz, Brad Alexander, Christoph Gengnagel, Stefan Weinzierl

Abstract:

This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full-scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the building information modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit, the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models, which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: acoustical design, additive manufacturing, computational design, multimodal optimization

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16503 Taguchi-Based Optimization of Surface Roughness and Dimensional Accuracy in Wire EDM Process with S7 Heat Treated Steel

Authors: Joseph C. Chen, Joshua Cox

Abstract:

This research focuses on the use of the Taguchi method to reduce the surface roughness and improve dimensional accuracy of parts machined by Wire Electrical Discharge Machining (EDM) with S7 heat treated steel material. Due to its high impact toughness, the material is a candidate for a wide variety of tooling applications which require high precision in dimension and desired surface roughness. This paper demonstrates that Taguchi Parameter Design methodology is able to optimize both dimensioning and surface roughness successfully by investigating seven wire-EDM controllable parameters: pulse on time (ON), pulse off time (OFF), servo voltage (SV), voltage (V), servo feed (SF), wire tension (WT), and wire speed (WS). The temperature of the water in the Wire EDM process is investigated as the noise factor in this research. Experimental design and analysis based on L18 Taguchi orthogonal arrays are conducted. This paper demonstrates that the Taguchi-based system enables the wire EDM process to produce (1) high precision parts with an average of 0.6601 inches dimension, while the desired dimension is 0.6600 inches; and (2) surface roughness of 1.7322 microns which is significantly improved from 2.8160 microns.

Keywords: Taguchi Parameter Design, surface roughness, Wire EDM, dimensional accuracy

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16502 Optimization of Batch to Up-Scaling of Soy-Based Prepolymer Polyurethane

Authors: Flora Elvistia Firdaus

Abstract:

The chemical structure of soybean oils have to be chemically modified through its tryglyceride to attain resemblance properties with petrochemicals. Sulfur acid catalyst in peracetic acid co-reagent has good performance on modified soybean oil strucutures through its unsaturated fatty acid moiety to the desired hydroxyl functional groups. A series of screening reactions have indicated that the ratio of acetic/peroxide acid 1:7.25 (mol/mol) with temperature of 600°C for soy-epoxide synthesis are prevailed for up-scaling of bodied soybean into 10 and 20 folds from initials. A two-step process was conducted for the preparation of soy-polyol in designated temperatures.

Keywords: soybean, polyol, up-scaling, polyurethane

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16501 A Mixture Vine Copula Structures Model for Dependence Wind Speed among Wind Farms and Its Application in Reactive Power Optimization

Authors: Yibin Qiu, Yubo Ouyang, Shihan Li, Guorui Zhang, Qi Li, Weirong Chen

Abstract:

This paper aims at exploring the impacts of high dimensional dependencies of wind speed among wind farms on probabilistic optimal power flow. To obtain the reactive power optimization faster and more accurately, a mixture vine Copula structure model combining the K-means clustering, C vine copula and D vine copula is proposed in this paper, through which a more accurate correlation model can be obtained. Moreover, a Modified Backtracking Search Algorithm (MBSA), the three-point estimate method is applied to probabilistic optimal power flow. The validity of the mixture vine copula structure model and the MBSA are respectively tested in IEEE30 node system with measured data of 3 adjacent wind farms in a certain area, and the results indicate effectiveness of these methods.

Keywords: mixture vine copula structure model, three-point estimate method, the probability integral transform, modified backtracking search algorithm, reactive power optimization

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16500 An Optimization Modelling to Evaluate Flights Scheduling at Tourist Airports

Authors: Dimitrios J. Dimitriou

Abstract:

Airport’s serving a tourist destination are an essential counterpart of the tourist demand supply chain, and their productivity is related to the region’s attractiveness and is enhanced by the air transport business. In this paper, the evaluation framework of the scheduled flights between two tourist airports is taken into consideration. By adopting a systemic approach, the arrivals from an airport that its connectivity heavily depended on the departures of another major airport are reviewed. The methodology framework, based on inventory control theory and the numerical example, promotes the use of the modelling formulation. The results would be essential for comparison and exercising to other similar cases.

Keywords: airport connectivity, inventory control, optimization, optimum allocation

Procedia PDF Downloads 331
16499 Optimization Parameters Using Response Surface Method on Biomechanical Analysis for Malaysian Soccer Players

Authors: M. F. M. Ali, A. R. Ismail, B. M. Deros

Abstract:

Soccer is very popular and ranked as the top sports in the world as well as in Malaysia. Although soccer sport in Malaysia is currently professionalized, but it’s plunging achievements within recent years continue and are not to be proud of. After review, the Malaysian soccer players are still weak in terms of kicking techniques. The instep kick is a technique, which is often used in soccer for the purpose of short passes and making a scoring. This study presents the 3D biomechanics analysis on a soccer player during performing instep kick. This study was conducted to determine the optimization value for approach angle, distance of supporting leg from the ball and ball internal pressure respect to the knee angular velocity of the ball on the kicking leg. Six subjects from different categories using dominant right leg and free from any injury were selected to take part in this study. Subjects were asked to perform one step instep kick according to the setting for the variables with different parameter. Data analysis was performed using 3 Dimensional “Qualisys Track Manager” system and will focused on the bottom of the body from the waist to the ankle. For this purpose, the marker will be attached to the bottom of the body before the kicking is perform by the subjects. Statistical analysis was conducted by using Minitab software using Response Surface Method through Box-Behnken design. The results of this study found the optimization values for all three parameters, namely the approach angle, 53.6º, distance of supporting leg from the ball, 8.84sm and ball internal pressure, 0.9bar with knee angular velocity, 779.27 degrees/sec have been produced.

Keywords: biomechanics, instep kick, soccer, optimization

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16498 Integrated Two Stage Processing of Biomass Conversion to Hydroxymethylfurfural Esters Using Ionic Liquid as Green Solvent and Catalyst: Synthesis of Mono Esters

Authors: Komal Kumar, Sreedevi Upadhyayula

Abstract:

In this study, a two-stage process was established for the synthesis of HMF esters using ionic liquid acid catalyst. Ionic liquid catalyst with different strength of the Bronsted acidity was prepared in the laboratory and characterized using 1H NMR, FT-IR, and 13C NMR spectroscopy. Solid acid catalyst from the ionic liquid catalyst was prepared using the immobilization method. The acidity of the synthesized acid catalyst was measured using Hammett function and titration method. Catalytic performance was evaluated for the biomass conversion to 5-hydroxymethylfurfural (5-HMF) and levulinic acid (LA) in methyl isobutyl ketone (MIBK)-water biphasic system. A good yield of 5-HMF and LA was found at the different composition of MIBK: Water. In the case of MIBK: Water ratio 10:1, good yield of 5-HMF was observed at ambient temperature 150˚C. Upgrading of 5-HMF into monoesters from the reaction of 5-HMF and reactants using biomass-derived monoacid were performed. Ionic liquid catalyst with -SO₃H functional group was found to be best efficient in comparative of a solid acid catalyst for the esterification reaction and biomass conversion. A good yield of 5-HMF esters with high 5-HMF conversion was found to be at 105˚C using the best active catalyst. In this process, process A was the hydrothermal conversion of cellulose and monomer into 5-HMF and LA using acid catalyst. And the process B was the esterification followed by using similar acid catalyst. All monoesters of 5-HMF synthesized here can be used in chemical, cross linker for adhesive or coatings and pharmaceutical industry. A theoretical density functional theory (DFT) study for the optimization of the ionic liquid structure was performed using the Gaussian 09 program to find out the minimum energy configuration of ionic liquid catalyst.

Keywords: biomass conversion, 5-HMF, Ionic liquid, HMF ester

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16497 Ant Colony Optimization Control for Multilevel STATCOM

Authors: H. Tédjini, Y. Meslem, B. Guesbaoui, A. Safa

Abstract:

Flexible AC Transmission Systems (FACTS) are potentially becoming more flexible and more economical local controllers in the power system; and because of the high MVA ratings, it would be expensive to provide independent, equal, regulated DC voltage sources to power the multilevel converters which are presently proposed for STATCOMs. DC voltage sources can be derived from the DC link capacitances which are charged by the rectified ac power. In this paper a new stronger control combined of nonlinear control based Lyapunov’s theorem and Ant Colony Algorithm (ACA) to maintain stability of multilevel STATCOM and the utility.

Keywords: Static Compensator (STATCOM), ant colony optimization (ACO), lyapunov control theory, Decoupled power control, neutral point clamped (NPC)

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16496 Multi-Objective Optimization and Effect of Surface Conditions on Fatigue Performance of Burnished Components Made of AISI 52100 Steel

Authors: Ouahiba Taamallah, Tarek Litim

Abstract:

The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

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16495 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

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16494 Illuminating Human Identity in Theology and Islamic Philosophy

Authors: Khan Shahid, Shahid Zakia

Abstract:

The article demonstrates how Theology and Islamic Philosophy can be illuminated and enhanced through the application of the SOUL framework (Sincere act, Optimization effort, Ultimate goal, Law compliance). The study explores historical development using a phenomenological approach and integrates the SOUL framework to enrich Theology and Islamic Philosophy. The proposed framework highlights the significance of these elements, ultimately leading to a deeper understanding of Theology and Islamic Philosophy.

Keywords: SOUL framework, illuminating human identity, theology, Islamic Philosophy, sincerity act, optimization effort, ultimate goals, law compliance

Procedia PDF Downloads 86
16493 Evaluation of Forming Properties on AA 5052 Aluminium Alloy by Incremental Forming

Authors: A. Anbu Raj, V. Mugendiren

Abstract:

Sheet metal forming is a vital manufacturing process used in automobile, aerospace, agricultural industries, etc. Incremental forming is a promising process providing a short and inexpensive way of forming complex three-dimensional parts without using die. The aim of this research is to study the forming behaviour of AA 5052, Aluminium Alloy, using incremental forming and also to study the FLD of cone shape AA 5052 Aluminium Alloy at room temperature and various annealing temperature. Initially the surface roughness and wall thickness through incremental forming on AA 5052 Aluminium Alloy sheet at room temperature is optimized by controlling the effects of forming parameters. The central composite design (CCD) was utilized to plan the experiment. The step depth, feed rate, and spindle speed were considered as input parameters in this study. The surface roughness and wall thickness were used as output response. The process performances such as average thickness and surface roughness were evaluated. The optimized results are taken for minimum surface roughness and maximum wall thickness. The optimal results are determined based on response surface methodology and the analysis of variance. Formability Limit Diagram is constructed on AA 5052 Aluminium Alloy at room temperature and various annealing temperature by using optimized process parameters from the response surface methodology. The cone has higher formability than the square pyramid and higher wall thickness distribution. Finally the FLD on cone shape and square pyramid shape at room temperature and the various annealing temperature is compared experimentally and simulated with Abaqus software.

Keywords: incremental forming, response surface methodology, optimization, wall thickness, surface roughness

Procedia PDF Downloads 334
16492 Hybrid Gravity Gradient Inversion-Ant Colony Optimization Algorithm for Motion Planning of Mobile Robots

Authors: Meng Wu

Abstract:

Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.

Keywords: motion planning, gravity gradient inversion algorithm, ant colony optimization

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16491 Influence of Sodium Acetate on Electroless Ni-P Deposits and Effect of Heat Treatment on Corrosion Behavior

Authors: Y. El Kaissi, M. Allam, A. Koulou, M. Galai, M. Ebn Touhami

Abstract:

The aim of our work is to develop an industrial bath of nickel alloy deposit on mild steel. The optimization of the operating parameters made it possible to obtain a stable Ni-P alloy deposition formulation. To understand the reaction mechanism of the deposition process, a kinetic study was performed by cyclic voltammetry and by electrochemical impedance spectroscopy (EIS). The coatings obtained have a very high corrosion resistance in a very aggressive acid medium which increases with the heat treatment.

Keywords: cyclic voltammetry, EIS, electroless Ni–P coating, heat treatment, potentiodynamic polarization

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16490 A Deep Learning Approach for Optimum Shape Design

Authors: Cahit Perkgöz

Abstract:

Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

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16489 Data-Mining Approach to Analyzing Industrial Process Information for Real-Time Monitoring

Authors: Seung-Lock Seo

Abstract:

This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

Procedia PDF Downloads 394