Search results for: optimization limit
3901 The Impact of Transaction Costs on Rebalancing an Investment Portfolio in Portfolio Optimization
Authors: B. Marasović, S. Pivac, S. V. Vukasović
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Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.Keywords: Croatian capital market, Markowitz model, fractional quadratic programming, portfolio optimization, transaction costs
Procedia PDF Downloads 3853900 Process Optimization for Albanian Crude Oil Characterization
Authors: Xhaklina Cani, Ilirjan Malollari, Ismet Beqiraj, Lorina Lici
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Oil characterization is an essential step in the design, simulation, and optimization of refining facilities. To achieve optimal crude selection and processing decisions, a refiner must have exact information refer to crude oil quality. This includes crude oil TBP-curve as the main data for correct operation of refinery crude oil atmospheric distillation plants. Crude oil is typically characterized based on a distillation assay. This procedure is reasonably well-defined and is based on the representation of the mixture of actual components that boil within a boiling point interval by hypothetical components that boil at the average boiling temperature of the interval. The crude oil assay typically includes TBP distillation according to ASTM D-2892, which can characterize this part of oil that boils up to 400 C atmospheric equivalent boiling point. To model the yield curves obtained by physical distillation is necessary to compare the differences between the modelling and the experimental data. Most commercial use a different number of components and pseudo-components to represent crude oil. Laboratory tests include distillations, vapor pressures, flash points, pour points, cetane numbers, octane numbers, densities, and viscosities. The aim of the study is the drawing of true boiling curves for different crude oil resources in Albania and to compare the differences between the modeling and the experimental data for optimal characterization of crude oil.Keywords: TBP distillation curves, crude oil, optimization, simulation
Procedia PDF Downloads 3023899 Multi-Objective Optimization of an Aerodynamic Feeding System Using Genetic Algorithm
Authors: Jan Busch, Peter Nyhuis
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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation
Procedia PDF Downloads 5733898 Optimization of Technical and Technological Solutions for the Development of Offshore Hydrocarbon Fields in the Kaliningrad Region
Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov
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Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».Keywords: offshore fields of hydrocarbons of the Baltic Sea, development of offshore oil and gas fields, optimization of the field development scheme, solution of multicriteria tasks in oil and gas complex, quality management in oil and gas complex
Procedia PDF Downloads 1983897 An Evolutionary Approach for QAOA for Max-Cut
Authors: Francesca Schiavello
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This work aims to create a hybrid algorithm, combining Quantum Approximate Optimization Algorithm (QAOA) with an Evolutionary Algorithm (EA) in the place of traditional gradient based optimization processes. QAOA’s were first introduced in 2014, where, at the time, their algorithm performed better than the traditional best known classical algorithm for Max-cut graphs. Whilst classical algorithms have improved since then and have returned to being faster and more efficient, this was a huge milestone for quantum computing, and their work is often used as a benchmarking tool and a foundational tool to explore variants of QAOA’s. This, alongside with other famous algorithms like Grover’s or Shor’s, highlights to the world the potential that quantum computing holds. It also presents the reality of a real quantum advantage where, if the hardware continues to improve, this could constitute a revolutionary era. Given that the hardware is not there yet, many scientists are working on the software side of things in the hopes of future progress. Some of the major limitations holding back quantum computing are the quality of qubits and the noisy interference they generate in creating solutions, the barren plateaus that effectively hinder the optimization search in the latent space, and the availability of number of qubits limiting the scale of the problem that can be solved. These three issues are intertwined and are part of the motivation for using EAs in this work. Firstly, EAs are not based on gradient or linear optimization methods for the search in the latent space, and because of their freedom from gradients, they should suffer less from barren plateaus. Secondly, given that this algorithm performs a search in the solution space through a population of solutions, it can also be parallelized to speed up the search and optimization problem. The evaluation of the cost function, like in many other algorithms, is notoriously slow, and the ability to parallelize it can drastically improve the competitiveness of QAOA’s with respect to purely classical algorithms. Thirdly, because of the nature and structure of EA’s, solutions can be carried forward in time, making them more robust to noise and uncertainty. Preliminary results show that the EA algorithm attached to QAOA can perform on par with the traditional QAOA with a Cobyla optimizer, which is a linear based method, and in some instances, it can even create a better Max-Cut. Whilst the final objective of the work is to create an algorithm that can consistently beat the original QAOA, or its variants, due to either speedups or quality of the solution, this initial result is promising and show the potential of EAs in this field. Further tests need to be performed on an array of different graphs with the parallelization aspect of the work commencing in October 2023 and tests on real hardware scheduled for early 2024.Keywords: evolutionary algorithm, max cut, parallel simulation, quantum optimization
Procedia PDF Downloads 583896 An Optimization Algorithm for Reducing the Liquid Oscillation in the Moving Containers
Authors: Reza Babajanivalashedi, Stefania Lo Feudo, Jean-Luc Dion
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Liquid sloshing is a crucial problem for the dynamic of moving containers in the packaging industries. Sloshing issues have been so far mainly modeled within the framework of fluid dynamics or by using equivalent mechanical models with different kinds of movements and shapes of containers. Nevertheless, these approaches do not allow to determinate the shape of the free surface of the liquid in case of the irregular shape of the moving containers, so that experimental measurements may be required. If there is too much slosh in the moving tank, the liquid can be splashed out on the packages. So, the free surface oscillation must be controlled/reduced to eliminate the splashing. The purpose of this research is to propose an optimization algorithm for finding an optimum command law to reduce surface elevation. In the first step, the free surface of the liquid is simulated based on the separation variable and weak formulation models. Then Genetic and Gradient algorithms are developed for finding the optimum command law. The optimum command law is compared with existing command laws, and the results show that there is a significant difference in surface oscillation between optimum and existing command laws. This algorithm is applicable for different varieties of bottles in case of using the camera for detecting the liquid elevation, and it can produce new command laws for different kinds of tanks to reduce the surface oscillation and remove the splashing phenomenon.Keywords: sloshing phenomenon, separation variables, weak formulation, optimization algorithm, command law
Procedia PDF Downloads 1483895 Evolution of Deformation in the Southern Central Tunisian Atlas: Parameters and Modelling
Authors: Mohamed Sadok Bensalem, Soulef Amamria, Khaled Lazzez, Mohamed Ghanmi
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The southern-central Tunisian Atlas presents a typical example of an external zone. It occupies a particular position in the North African chains: firstly, it is the eastern limit of atlassic structures; secondly, it is the edges between the belts structures to the north and the stable Saharan platform in the south. The evolution of deformation study is based on several methods, such as classical or numerical methods. The principals parameters controlling the genesis of folds in the southern central Tunisian Atlas are; the reactivation of pre-existing faults during the later compressive phase, the evolution of decollement level, and the relation between thin and thick-skinned. One of the more principal characters of the southern-central Tunisian Atlas is the variation of belts structures directions determined by: NE-SW direction, named the attlassic direction in Tunisia, the NW-SE direction carried along the Gafsa fault (the oriental limit of southern atlassic accident), and the E-W direction defined in the southern Tunisian Atlas. This variation of direction is the result of important variation of deformation during different tectonics phases. A classical modelling of the Jebel ElKebar anticline, based on faults throw of the pre-existing faults and its reactivation during compressive phases, shows the importance of extensional deformation, particular during Aptian-Albian period, comparing with that of later compression (Alpine phases). A numerical modelling, based on the software Rampe E.M. 1.5.0, applied on the anticline of Jebel Orbata confirms the interpretation of “fault related fold” with decollement level within the Triassic successions. The other important parameter of evolution of deformation is the vertical migration of decollement level; indeed, more than the decollement level is in the recent series, most that the deformation is accentuated. The evolution of deformation is marked the development of duplex structure in Jebel At Taghli (eastern limit of Jebel Orbata). Consequently, the evolution of deformation is proportional to the depth of the decollement level, the most important deformation is in the higher successions; thus, is associated to the thin-skinned deformation; the decollement level permit the passive transfer of deformation in the cover.Keywords: evolution of deformation, pre-existing faults, decollement level, thin-skinned
Procedia PDF Downloads 1243894 Machine Learning and Metaheuristic Algorithms in Short Femoral Stem Custom Design to Reduce Stress Shielding
Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez
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Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement
Procedia PDF Downloads 1943893 Optimization Techniques of Doubly-Fed Induction Generator Controller Design for Reliability Enhancement of Wind Energy Conversion Systems
Authors: Om Prakash Bharti, Aanchal Verma, R. K. Saket
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The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.Keywords: doubly-fed induction generator, wind turbine, wind energy conversion system, induction generator, transfer function, proportional, integral, derivatives
Procedia PDF Downloads 923892 Wind Turbines Optimization: Shield Structure for a High Wind Speed Conditions
Authors: Daniyar Seitenov, Nazim Mir-Nasiri
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Optimization of horizontal axis semi-exposed wind turbine has been performed using a shield protection that automatically protects the generator shaft at extreme wind speeds from over speeding, mechanical damage and continues generating electricity during the high wind speed conditions. A semi-exposed to wind generator has been designed and its structure has been described in this paper. The simplified point-force dynamic load model on the blades has been derived for normal and extreme wind conditions with and without shield involvement. Numerical simulation has been conducted at different values of wind speed to study the efficiency of shield application. The obtained results show that the maximum power generated by the wind turbine with shield does not exceed approximately the rated value of the generator, where shield serves as an automatic break for extreme wind speed values of 15 m/sec and above. Meantime the wind turbine without shield produced a power that is much larger than the rated value. The optimized horizontal axis semi-exposed wind turbine with shield protection is suitable for low and medium power generation when installed on the roofs of high rise buildings for harvesting wind energy. Wind shield works automatically with no power consumption. The structure of the generator with the protection, math simulation of kinematics and dynamics of power generation has been described in details in this paper.Keywords: renewable energy, wind turbine, wind turbine optimization, high wind speed
Procedia PDF Downloads 1773891 Optimization of End Milling Process Parameters for Minimization of Surface Roughness of AISI D2 Steel
Authors: Pankaj Chandna, Dinesh Kumar
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The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.Keywords: D2 steel, orthogonal array, optimization, surface roughness, Taguchi methodology
Procedia PDF Downloads 5433890 Design and Optimization of Soil Nailing Construction
Authors: Fereshteh Akbari, Farrokh Jalali Mosalam, Ali Hedayatifar, Amirreza Aminjavaheri
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The soil nailing is an effective method to stabilize slopes and retaining structures. Consequently, the lateral and vertical displacement of retaining walls are important criteria to evaluate the safety risks of adjacent structures. This paper is devoted to the optimization problems of retaining walls based on ABAQOUS Software. The various parameters such as nail length, orientation, arrangement, horizontal spacing, and bond skin friction, on lateral and vertical displacement of retaining walls are investigated. In order to ensure accuracy, the mobilized shear stress acting around the perimeter of the nail-soil interface is also modeled in ABAQOUS software. The observed trend of results is compared to the previous researches.Keywords: retaining walls, soil nailing, ABAQOUS software, lateral displacement, vertical displacement
Procedia PDF Downloads 1283889 Functional and Efficient Query Interpreters: Principle, Application and Performances’ Comparison
Authors: Laurent Thiry, Michel Hassenforder
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This paper presents a general approach to implement efficient queries’ interpreters in a functional programming language. Indeed, most of the standard tools actually available use an imperative and/or object-oriented language for the implementation (e.g. Java for Jena-Fuseki) but other paradigms are possible with, maybe, better performances. To proceed, the paper first explains how to model data structures and queries in a functional point of view. Then, it proposes a general methodology to get performances (i.e. number of computation steps to answer a query) then it explains how to integrate some optimization techniques (short-cut fusion and, more important, data transformations). It then compares the functional server proposed to a standard tool (Fuseki) demonstrating that the first one can be twice to ten times faster to answer queries.Keywords: data transformation, functional programming, information server, optimization
Procedia PDF Downloads 1563888 Conceptual Design of Panel Based Reinforced Concrete Floating Substructure for 10 MW Offshore Wind Turbine
Authors: M. Sohail Hasan, Wichuda Munbua, Chikako Fujiyama, Koichi Maekawa
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During the past few years, offshore wind energy has become the key parameter to reduce carbon emissions. In most of the previous studies, floaters in floating offshore wind turbines (FOWT) are made up of steel. However, fatigue and corrosion are always major concerns of steel marine structures. Recently, researchers are working on concrete floating substructures. In this paper, the conceptual design of pre-cast panel-based economical and durable reinforced concrete floating substructure for a 10 MW offshore wind turbine is proposed. The new geometrical shape, i.e., hexagon with inside hollow boxes, is proposed under static conditions. To design the outer panel/side walls to resist hydrostatic forces, special consideration for durability is given to limit the crack width within permissible range under service limit state. A comprehensive system is proposed for transferring the ultimate moment and shear due to strong wind at the connection between steel tower and concrete floating substructure. Moreover, a stable connection is also designed considering the fatigue of concrete and steel due to the fluctuation of stress from the mooring line. This conceptual design will be verified by subsequent dynamic analysis soon.Keywords: cracks width control, mooring line, reinforced concrete floater, steel tower
Procedia PDF Downloads 2213887 Mechanical Characterization of Porcine Skin with the Finite Element Method Based Inverse Optimization Approach
Authors: Djamel Remache, Serge Dos Santos, Michael Cliez, Michel Gratton, Patrick Chabrand, Jean-Marie Rossi, Jean-Louis Milan
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Skin tissue is an inhomogeneous and anisotropic material. Uniaxial tensile testing is one of the primary testing techniques for the mechanical characterization of skin at large scales. In order to predict the mechanical behavior of materials, the direct or inverse analytical approaches are often used. However, in case of an inhomogeneous and anisotropic material as skin tissue, analytical approaches are not able to provide solutions. The numerical simulation is thus necessary. In this work, the uniaxial tensile test and the FEM (finite element method) based inverse method were used to identify the anisotropic mechanical properties of porcine skin tissue. The uniaxial tensile experiments were performed using Instron 8800 tensile machine®. The uniaxial tensile test was simulated with FEM, and then the inverse optimization approach (or the inverse calibration) was used for the identification of mechanical properties of the samples. Experimentally results were compared to finite element solutions. The results showed that the finite element model predictions of the mechanical behavior of the tested skin samples were well correlated with experimental results.Keywords: mechanical skin tissue behavior, uniaxial tensile test, finite element analysis, inverse optimization approach
Procedia PDF Downloads 4063886 Hybrid Hierarchical Routing Protocol for WSN Lifetime Maximization
Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif
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Conceiving and developing routing protocols for wireless sensor networks requires considerations on constraints such as network lifetime and energy consumption. In this paper, we propose a hybrid hierarchical routing protocol named HHRP combining both clustering mechanism and multipath optimization taking into account residual energy and RSSI measures. HHRP consists of classifying dynamically nodes into clusters where coordinators nodes with extra privileges are able to manipulate messages, aggregate data and ensure transmission between nodes according to TDMA and CDMA schedules. The reconfiguration of the network is carried out dynamically based on a threshold value which is associated with the number of nodes belonging to the smallest cluster. To show the effectiveness of the proposed approach HHRP, a comparative study with LEACH protocol is illustrated in simulations.Keywords: routing protocol, optimization, clustering, WSN
Procedia PDF Downloads 4683885 Identifying Autism Spectrum Disorder Using Optimization-Based Clustering
Authors: Sharifah Mousli, Sona Taheri, Jiayuan He
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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning
Procedia PDF Downloads 1153884 Pilot Scale Deproteinization Study on Fish Scale Using Response Surface Methodology
Authors: Fatima Bellali, Mariem Kharroubi
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Fish scale wastes are one of the main sources of production of value-added products such as collagen. The main aim of this study is to investigate the optimization conditions of the sardine scale deproteinization using response surface methodology (RSM) on a pilot scale. In order to look for the optimal conditions, a Box–Behnken-based design of experiment (DOE) method was carried out. The model predicted values of product coal ash content were in good agreement with the experiment values (R2 = 0.9813). Finally, model-based optimization was carried out to identify the operating parameters (reaction time=4h and the solid-liquid ratio= 1/10) and to obtain the lowest collagen content.Keywords: pilot scale, Plackett and Burman design, fish waste, deproteinization
Procedia PDF Downloads 1593883 Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System
Authors: S. Gherbi, F. Bouchareb
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This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method.Keywords: delayed systems, fuzzy immune PID, optimization, Smith predictor
Procedia PDF Downloads 4313882 FEM for Stress Reduction by Optimal Auxiliary Holes in a Uniaxially Loaded Plate
Authors: Basavaraj R. Endigeri, Shriharsh Desphande
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Optimization and reduction of stress concentration around holes in a uniaxially loaded plate is one of the important design criteria in many of the engineering applications. These stress risers will lead to failure of the component at the region of high stress concentration which has to be avoided by means of providing auxiliary holes on either side of the parent hole. By literature survey it is known that till date, there is no analytical solution documented to reduce the stress concentration by providing auxiliary holes expect for fever geometries. In the present work, plate with a hole subjected to uniaxial load is analyzed with the numerical method to determine the optimum sizes and locations for the auxillary holes for different center hole diameter to plate width ratios. The introduction of auxiliary holes at a optimum location and radii with its effect on stress concentration is also represented graphically. The finite element analysis package ANSYS 8.0 is used to carry out analysis and optimization is performed to determine the location and radii for optimum values of auxiliary holes to reduce stress concentration. All the results for different diameter to plate width ratio are presented graphically. It is found from the work that introduction of auxiliary holes on either side of central circular hole will reduce stress concentration factor by a factor of 19 to 21 percentage.Keywords: finite element method, optimization, stress concentration factor, auxiliary holes
Procedia PDF Downloads 4383881 Scheduling in a Single-Stage, Multi-Item Compatible Process Using Multiple Arc Network Model
Authors: Bokkasam Sasidhar, Ibrahim Aljasser
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The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.Keywords: scheduling, maximal flow problem, multiple arc network model, optimization
Procedia PDF Downloads 4013880 The Design, Development, and Optimization of a Capacitive Pressure Sensor Utilizing an Existing 9DOF Platform
Authors: Andrew Randles, Ilker Ocak, Cheam Daw Don, Navab Singh, Alex Gu
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Nine Degrees of Freedom (9 DOF) systems are already in development in many areas. In this paper, an integrated pressure sensor is proposed that will make use of an already existing monolithic 9 DOF inertial MEMS platform. Capacitive pressure sensors can suffer from limited sensitivity for a given size of membrane. This novel pressure sensor design increases the sensitivity by over 5 times compared to a traditional array of square diaphragms while still fitting within a 2 mm x 2 mm chip and maintaining a fixed static capacitance. The improved design uses one large diaphragm supported by pillars with fixed electrodes placed above the areas of maximum deflection. The design optimization increases the sensitivity from 0.22 fF/kPa to 1.16 fF/kPa. Temperature sensitivity was also examined through simulation.Keywords: capacitive pressure sensor, 9 DOF, 10 DOF, sensor, capacitive, inertial measurement unit, IMU, inertial navigation system, INS
Procedia PDF Downloads 5443879 Optimization of Fenton Process for the Treatment of Young Municipal Leachate
Authors: Bouchra Wassate, Younes Karhat, Khadija El Falaki
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Leachate is a source of surface water and groundwater contamination if it has not been pretreated. Indeed, due to its complex structure and its pollution load make its treatment extremely difficult to achieve the standard limits required. The objective of this work is to show the interest of advanced oxidation processes on leachate treatment of urban waste containing high concentrations of organic pollutants. The efficiency of Fenton (Fe2+ +H2O2 + H+) reagent for young leachate recovered from collection trucks household waste in the city of Casablanca, Morocco, was evaluated with the objectives of chemical oxygen demand (COD) and discoloration reductions. The optimization of certain physicochemical parameters (initial pH value, reaction time, and [Fe2+], [H2O2]/ [Fe2+] ratio) has yielded good results in terms of reduction of COD and discoloration of the leachate.Keywords: COD removal, color removal, Fenton process, oxidation process, leachate
Procedia PDF Downloads 2853878 Hybrid Approach for the Min-Interference Frequency Assignment
Authors: F. Debbat, F. T. Bendimerad
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The efficient frequency assignment for radio communications becomes more and more crucial when developing new information technologies and their applications. It is consists in defining an assignment of frequencies to radio links, to be established between base stations and mobile transmitters. Separation of the frequencies assigned is necessary to avoid interference. However, unnecessary separation causes an excess requirement for spectrum, the cost of which may be very high. This problem is NP-hard problem which cannot be solved by conventional optimization algorithms. It is therefore necessary to use metaheuristic methods to solve it. This paper proposes Hybrid approach based on simulated annealing (SA) and Tabu Search (TS) methods to solve this problem. Computational results, obtained on a number of standard problem instances, testify the effectiveness of the proposed approach.Keywords: cellular mobile communication, frequency assignment problem, optimization, tabu search, simulated annealing
Procedia PDF Downloads 3823877 Development of a General Purpose Computer Programme Based on Differential Evolution Algorithm: An Application towards Predicting Elastic Properties of Pavement
Authors: Sai Sankalp Vemavarapu
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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation
Procedia PDF Downloads 1633876 Optimization of Biomass Production and Lipid Formation from Chlorococcum sp. Cultivation on Dairy and Paper-Pulp Wastewater
Authors: Emmanuel C. Ngerem
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The ever-increasing depletion of the dominant global form of energy (fossil fuels) calls for the development of sustainable and green alternative energy sources such as bioethanol, biohydrogen, and biodiesel. The production of the major biofuels relies on biomass feedstocks that are mainly derived from edible food crops and some inedible plants. One suitable feedstock with great potential as raw material for biofuel production is microalgal biomass. Despite the tremendous attributes of microalgae as a source of biofuel, their cultivation requires huge volumes of freshwater, thus posing a serious threat to commercial-scale production and utilization of algal biomass. In this study, a multi-media wastewater mixture for microalgae growth was formulated and optimized. Moreover, the obtained microalgae biomass was pre-treated to reduce sugar recovery and was compared with previous studies on microalgae biomass pre-treatment. The formulated and optimized mixed wastewater media for biomass and lipid accumulation was established using the simplex lattice mixture design. Based on the superposition approach of the potential results, numerical optimization was conducted, followed by the analysis of biomass concentration and lipid accumulation. The coefficients of regression (R²) of 0.91 and 0.98 were obtained for biomass concentration and lipid accumulation models, respectively. The developed optimization model predicted optimal biomass concentration and lipid accumulation of 1.17 g/L and 0.39 g/g, respectively. It suggested 64.69% dairy wastewater (DWW) and 35.31% paper and pulp wastewater (PWW) mixture for biomass concentration, 34.21% DWW, and 65.79% PWW for lipid accumulation. Experimental validation generated 0.94 g/L and 0.39 g/g of biomass concentration and lipid accumulation, respectively. The obtained microalgae biomass was pre-treated, enzymatically hydrolysed, and subsequently assessed for reducing sugars. The optimization of microwave pre-treatment of Chlorococcum sp. was achieved using response surface methodology (RSM). Microwave power (100 – 700 W), pre-treatment time (1 – 7 min), and acid-liquid ratio (1 – 5%) were selected as independent variables for RSM optimization. The optimum conditions were achieved at microwave power, pre-treatment time, and acid-liquid ratio of 700 W, 7 min, and 32.33:1, respectively. These conditions provided the highest amount of reducing sugars at 10.73 g/L. Process optimization predicted reducing sugar yields of 11.14 g/L on microwave-assisted pre-treatment of 2.52% HCl for 4.06 min at 700 watts. Experimental validation yielded reducing sugars of 15.67 g/L. These findings demonstrate that dairy wastewater and paper and pulp wastewater that could pose a serious environmental nuisance. They could be blended to form a suitable microalgae growth media, consolidating the potency of microalgae as a viable feedstock for fermentable sugars. Also, the outcome of this study supports the microalgal wastewater biorefinery concept, where wastewater remediation is coupled with bioenergy production.Keywords: wastewater cultivation, mixture design, lipid, biomass, nutrient removal, microwave, Chlorococcum, raceway pond, fermentable sugar, modelling, optimization
Procedia PDF Downloads 383875 Heat Transfer Process Parameter Optimization in SI/Ge Using TAGUCHI Method
Authors: Evln Ranga Charyulu, S. P. Venu Madhavarao, S. Udaya kumar, S. V. S. S. N. V. G. Krishna Murthy
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With the advent of new nanometer process technologies, it is possible to integrate billion transistors on a single substrate. When more and more functionality included there is the possibility of multi-million transistors switching simultaneously consuming more power and dissipating more power along with more leakage of current into the substrate of porous silicon or germanium material. These results in substrate heating and thermal noise generation coupled to signals of interest. The heating process is represented by coupled nonlinear partial differential equations in porous silicon and germanium. By identifying heat sources and heat fluxes may results in designing of ultra-low power circuits. The PDEs are solved by finite difference scheme assuming that boundary layer equations in porous silicon and germanium. Local heat fluxes along the vertical isothermal surface immersed in porous SI/Ge are considered. The parameters considered for optimization are thermal diffusivity, thermal expansion coefficient, thermal diffusion ratio, permeability, specific heat at constant temperatures, Rayleigh number, amplitude of wavy surface, mass expansion coefficient. The diffusion of heat was caused by the concentration gradient. Thermal physical properties are homogeneous and isotropic. By using L8, TAGUCHI method the parameters are optimized.Keywords: heat transfer, pde, taguchi optimization, SI/Ge
Procedia PDF Downloads 3353874 Optimisation of B2C Supply Chain Resource Allocation
Authors: Firdaous Zair, Zoubir Elfelsoufi, Mohammed Fourka
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The allocation of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players, manufacturers and Click & Mortars that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. Our contribution is a decision support system and tool for improving the allocation of resources in logistics chains e-commerce B2C context. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. In addition, every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource allocation in customized online shopping service mode, which is different from the supply chain resource allocation under traditional manufacturing or service circumstances. Then we realized an optimization model and algorithm for the development based on the analysis of the allocation of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.Keywords: e-commerce, supply chain, B2C, optimisation, resource allocation
Procedia PDF Downloads 2713873 Computationally Efficient Stacking Sequence Blending for Composite Structures with a Large Number of Design Regions Using Cellular Automata
Authors: Ellen Van Den Oord, Julien Marie Jan Ferdinand Van Campen
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This article introduces a computationally efficient method for stacking sequence blending of composite structures. The computational efficiency makes the presented method especially interesting for composite structures with a large number of design regions. Optimization of composite structures with an unequal load distribution may lead to locally optimized thicknesses and ply orientations that are incompatible with one another. Blending constraints can be enforced to achieve structural continuity. In literature, many methods can be found to implement structural continuity by means of stacking sequence blending in one way or another. The complexity of the problem makes the blending of a structure with a large number of adjacent design regions, and thus stacking sequences, prohibitive. In this work the local stacking sequence optimization is preconditioned using a method found in the literature that couples the mechanical behavior of the laminate, in the form of lamination parameters, to blending constraints, yielding near-optimal easy-to-blend designs. The preconditioned design is then fed to the scheme using cellular automata that have been developed by the authors. The method is applied to the benchmark 18-panel horseshoe blending problem to demonstrate its performance. The computational efficiency of the proposed method makes it especially suited for composite structures with a large number of design regions.Keywords: composite, blending, optimization, lamination parameters
Procedia PDF Downloads 2253872 Numerical Investigation of a Supersonic Ejector for Refrigeration System
Authors: Karima Megdouli, Bourhan Taschtouch
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Supersonic ejectors have many applications in refrigeration systems. And improving ejector performance is the key to improve the efficiency of these systems. One of the main advantages of the ejector is its geometric simplicity and the absence of moving parts. This paper presents a theoretical model for evaluating the performance of a new supersonic ejector configuration for refrigeration system applications. The relationship between the flow field and the key parameters of the new configuration has been illustrated by analyzing the Mach number and flow velocity contours. The method of characteristics (MOC) is used to design the supersonic nozzle of the ejector. The results obtained are compared with those obtained by CFD. The ejector is optimized by minimizing exergy destruction due to irreversibility and shock waves. The optimization converges to an efficient optimum solution, ensuring improved and stable performance over the whole considered range of uncertain operating conditions.Keywords: supersonic ejector, theoretical model, CFD, optimization, performance
Procedia PDF Downloads 74