Search results for: swarm optimization
2542 Machine Learning and Metaheuristic Algorithms in Short Femoral Stem Custom Design to Reduce Stress Shielding
Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez
Abstract:
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 1952541 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
Abstract:
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 932540 Wind Turbines Optimization: Shield Structure for a High Wind Speed Conditions
Authors: Daniyar Seitenov, Nazim Mir-Nasiri
Abstract:
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 1792539 Optimization of End Milling Process Parameters for Minimization of Surface Roughness of AISI D2 Steel
Authors: Pankaj Chandna, Dinesh Kumar
Abstract:
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 5442538 Design and Optimization of Soil Nailing Construction
Authors: Fereshteh Akbari, Farrokh Jalali Mosalam, Ali Hedayatifar, Amirreza Aminjavaheri
Abstract:
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 1322537 Functional and Efficient Query Interpreters: Principle, Application and Performances’ Comparison
Authors: Laurent Thiry, Michel Hassenforder
Abstract:
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 1572536 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
Abstract:
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 4082535 Hybrid Hierarchical Routing Protocol for WSN Lifetime Maximization
Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif
Abstract:
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 4692534 Identifying Autism Spectrum Disorder Using Optimization-Based Clustering
Authors: Sharifah Mousli, Sona Taheri, Jiayuan He
Abstract:
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 1152533 Pilot Scale Deproteinization Study on Fish Scale Using Response Surface Methodology
Authors: Fatima Bellali, Mariem Kharroubi
Abstract:
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 1602532 Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System
Authors: S. Gherbi, F. Bouchareb
Abstract:
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 4332531 FEM for Stress Reduction by Optimal Auxiliary Holes in a Uniaxially Loaded Plate
Authors: Basavaraj R. Endigeri, Shriharsh Desphande
Abstract:
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 4392530 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
Abstract:
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 5462529 Optimization of Fenton Process for the Treatment of Young Municipal Leachate
Authors: Bouchra Wassate, Younes Karhat, Khadija El Falaki
Abstract:
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 2862528 Hybrid Approach for the Min-Interference Frequency Assignment
Authors: F. Debbat, F. T. Bendimerad
Abstract:
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 3852527 Development of a General Purpose Computer Programme Based on Differential Evolution Algorithm: An Application towards Predicting Elastic Properties of Pavement
Authors: Sai Sankalp Vemavarapu
Abstract:
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 1642526 Optimization of Biomass Production and Lipid Formation from Chlorococcum sp. Cultivation on Dairy and Paper-Pulp Wastewater
Authors: Emmanuel C. Ngerem
Abstract:
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 402525 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
Abstract:
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 3382524 Optimisation of B2C Supply Chain Resource Allocation
Authors: Firdaous Zair, Zoubir Elfelsoufi, Mohammed Fourka
Abstract:
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 2722523 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
Abstract:
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 2272522 Numerical Investigation of a Supersonic Ejector for Refrigeration System
Authors: Karima Megdouli, Bourhan Taschtouch
Abstract:
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 762521 A New Framework for ECG Signal Modeling and Compression Based on Compressed Sensing Theory
Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi
Abstract:
The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation
Procedia PDF Downloads 4622520 Ficus Carica as Adsorbent for Removal of Phenol from Aqueous Solutions: Modelling and Optimization
Authors: Tizi Hayet, Berrama Tarek, Bounif Nadia
Abstract:
Phenol and its derivatives are organic compounds utilized in the chemical industry. They are introduced into the environment by accidental spills and illegal release of industrial and municipal wastewater. Phenols are organic intermediaries that considered as potential pollutants. Adsorption is one of the purification and separation techniques used in this area. Algeria produces annually 131000 tones of fig; therefore, a large amount of fig leaves is generated, and the conversion of this waste into adsorbent allows the valorization of agricultural residue. The main purpose of this present work is to describe an application of the statistical method for modeling and optimization of the conditions of the phenol (Ph) adsorption from agricultural by-product locally available (fig leaves). The best experimental performance of Ph elimination on the adsorbent was obtained with: Adsorbent concentration (X2) = 0.2 g L-1; Initial concentration (X3) = 150 mg L-1; Speed agitation (X1) = 300 rpm.Keywords: low-cost adsorbents, fig leaves, full factorial design, phenol, biosorption
Procedia PDF Downloads 972519 Control of Oil Content of Fried Zucchini Slices by Partial Predrying and Process Optimization
Authors: E. Karacabey, Ş. G. Özçelik, M. S. Turan, C. Baltacıoğlu, E. Küçüköner
Abstract:
Main concern about deep-fat-fried food materials is their high final oil contents absorbed during frying process and/or after cooling period, since diet including high content of oil is accepted unhealthy by consumers. Different methods have been evaluated to decrease oil content of fried food stuffs. One promising method is partially drying of food material before frying. In the present study it was aimed to control and decrease the final oil content of zucchini slices by means of partial drying and to optimize process conditions. Conventional oven drying was used to decrease moisture content of zucchini slices at a certain extent. Process performance in terms of oil uptake was evaluated by comparing oil content of predried and then fried zucchini slices with those determined for directly fried ones. For predrying and frying processes, oven temperature and weight loss and frying oil temperature and time pairs were controlled variables, respectively. Zucchini slices were also directly fried for sensory evaluations revealing preferred properties of final product in terms of surface color, moisture content, texture and taste. These properties of directly fried zucchini slices taking the highest score at the end of sensory evaluation were determined and used as targets in optimization procedure. Response surface methodology was used for process optimization. The properties, determined after sensory evaluation, were selected as targets; meanwhile oil content was aimed to be minimized. Results indicated that final oil content of zucchini slices could be reduced from 58% to 46% by controlling conditions of predrying and frying processes. As a result, it was suggested that predrying could be one choose to reduce oil content of fried zucchini slices for health diet. This project (113R015) has been supported by TUBITAK.Keywords: health process, optimization, response surface methodology, oil uptake, conventional oven
Procedia PDF Downloads 3662518 First Investigation on CZTS Electron affinity and Thickness Optimization using SILVACO-Atlas 2D Simulation
Authors: Zeineb Seboui, Samar Dabbabi
Abstract:
In this paper, we study the performance of Cu₂ZnSnS₄ (CZTS) based solar cell. In our knowledge, it is for the first time that the FTO/ZnO:Co/CZTS structure is simulated using the SILVACO-Atlas 2D simulation. Cu₂ZnSnS₄ (CZTS), ZnO:Co and FTO (SnO₂:F) layers have been deposited on glass substrates by the spray pyrolysis technique. The extracted physical properties, such as thickness and optical parameters of CZTS layer, are considered to create a new input data of CZTS based solar cell. The optimization of CZTS electron affinity and thickness is performed to have the best FTO/ZnO: Co/CZTS efficiency. The use of CZTS absorber layer with 3.99 eV electron affinity and 3.2 µm in thickness leads to the higher efficiency of 16.86 %, which is very important in the development of new technologies and new solar cell devices.Keywords: CZTS solar cell, characterization, electron affinity, thickness, SILVACO-atlas 2D simulation
Procedia PDF Downloads 772517 The Design Optimization for Sound Absorption Material of Multi-Layer Structure
Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Kyu Park
Abstract:
Sound absorbing material is used as automotive interior material. Sound absorption coefficient should be predicted to design it. But it is difficult to predict sound absorbing coefficient because it is comprised of several material layers. So, its targets are achieved through many experimental tunings. It causes a lot of cost and time. In this paper, we propose the process to estimate the sound absorption coefficient with multi-layer structure. In order to estimate the coefficient, physical properties of each material are used. These properties also use predicted values by Foam-X software using the sound absorption coefficient data measured by impedance tube. Since there are many physical properties and the measurement equipment is expensive, the values predicted by software are used. Through the measurement of the sound absorption coefficient of each material, its physical properties are calculated inversely. The properties of each material are used to calculate the sound absorption coefficient of the multi-layer material. Since the absorption coefficient of multi-layer can be calculated, optimization design is possible through simulation. Then, we will compare and analyze the calculated sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If this method is used when developing automotive interior materials with multi-layer structure, the development effort can be reduced because it can be optimized by simulation. So, cost and time can be saved.Keywords: sound absorption material, sound impedance tube, sound absorption coefficient, optimization design
Procedia PDF Downloads 2882516 A Game-Theory-Based Price-Optimization Algorithm for the Simulation of Markets Using Agent-Based Modelling
Authors: Juan Manuel Sanchez-Cartas, Gonzalo Leon
Abstract:
A price competition algorithm for ABMs based on game theory principles is proposed to deal with the simulation of theoretical market models. The algorithm is applied to the classical Hotelling’s model and to a two-sided market model to show it leads to the optimal behavior predicted by theoretical models. However, when theoretical models fail to predict the equilibrium, the algorithm is capable of reaching a feasible outcome. Results highlight that the algorithm can be implemented in other simulation models to guarantee rational users and endogenous optimal behaviors. Also, it can be applied as a tool of verification given that is theoretically based.Keywords: agent-based models, algorithmic game theory, multi-sided markets, price optimization
Procedia PDF Downloads 4552515 Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market
Authors: Ioannis P. Panapakidis, Marios N. Moschakis
Abstract:
The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.Keywords: deregulated energy market, forecasting, machine learning, system marginal price
Procedia PDF Downloads 2152514 Optimum Design of Grillage Systems Using Firefly Algorithm Optimization Method
Authors: F. Erdal, E. Dogan, F. E. Uz
Abstract:
In this study, firefly optimization based optimum design algorithm is presented for the grillage systems. Naming of the algorithm is derived from the fireflies, whose sense of movement is taken as a model in the development of the algorithm. Fireflies’ being unisex and attraction between each other constitute the basis of the algorithm. The design algorithm considers the displacement and strength constraints which are implemented from LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Construction). It selects the appropriate W (Wide Flange)-sections for the transverse and longitudinal beams of the grillage system among 272 discrete W-section designations given in LRFD-AISC so that the design limitations described in LRFD are satisfied and the weight of the system is confined to be minimal. Number of design examples is considered to demonstrate the efficiency of the algorithm presented.Keywords: firefly algorithm, steel grillage systems, optimum design, stochastic search techniques
Procedia PDF Downloads 4342513 Applications of Artificial Neural Networks in Civil Engineering
Authors: Naci Büyükkaracığan
Abstract:
Artificial neural networks (ANN) is an electrical model based on the human brain nervous system and working principle. Artificial neural networks have been the subject of an active field of research that has matured greatly over the past 55 years. ANN now is used in many fields. But, it has been viewed that artificial neural networks give better results in particular optimization and control systems. There are requirements of optimization and control system in many of the area forming the subject of civil engineering applications. In this study, the first artificial intelligence systems are widely used in the solution of civil engineering systems were examined with the basic principles and technical aspects. Finally, the literature reviews for applications in the field of civil engineering were conducted and also artificial intelligence techniques were informed about the study and its results.Keywords: artificial neural networks, civil engineering, Fuzzy logic, statistics
Procedia PDF Downloads 412