Search results for: function optimization

Authors: Tomoaki Hashimoto

Abstract:

Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.

Keywords: optimal control, stochastic systems, discrete-time systems, probabilistic constraints

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Authors: Truong Nguyen Luan Vu, Le Hieu Giang, Le Linh

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The FOPI controller is proposed based on the main properties of the decoupling control scheme, as well as the fractional calculus. By using the simplified decoupling technique, the transfer function of decoupled apparent process is firstly separated into a set of n equivalent independent processes in terms of a ratio of the diagonal elements of original open-loop transfer function to those of dynamic relative gain array and the fraction – order PI controller is then developed for each control loops due to the Bode’s ideal transfer function that gives the desired fractional closed-loop response in the frequency domain. The simulation studies were carried out to evaluate the proposed design approach in a fair compared with the other existing methods in accordance with the structured singular value (SSV) theory that used to measure the robust stability of control systems under multiplicative output uncertainty. The simulation results indicate that the proposed method consistently performs well with fast and well-balanced closed-loop time responses.

Keywords: ideal transfer function of bode, fractional calculus, fractional order proportional integral (FOPI) controller, decoupling control system

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Authors: D. S. Nagesh, G. L. Datta

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In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases, design of experiments technique to postulate multiple linear regression equations have been used. Nowadays, Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: smaw, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: D. S. Nagesh, G. L. Datta

Abstract:

In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases design of experiments technique to postulate multiple linear regression equations have been used. Nowadays Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: SMAW, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: Won Mog Choi, Seong Kyeong Hong, Seok Young Jeong

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The stress on the buried pipeline under pavement is significantly affected by vehicle loads and elastic modulus of the soil surrounding the pipeline. The correct elastic modulus of soil has to be applied to the finite element model to investigate the effect of the vehicle loads on the buried pipeline using finite element analysis. The purpose of this study is to establish the approach to calculating the correct elastic modulus of soil using the optimization process. The optimal elastic modulus of soil, which minimizes the difference between the strain measured from vehicle driving test at the velocity of 35km/h and the strain calculated from finite element analyses, was calculated through the optimization process using multi-response surface methodology. Three elastic moduli of soil (road layer, original soil, dense sand) surrounding the pipeline were defined as the variables for the optimization. Further analyses with the optimal elastic modulus at the velocities of 4.27km/h, 15.47km/h, 24.18km/h were performed and compared to the test results to verify the applicability of multi-response surface methodology. The results indicated that the strain of the buried pipeline was mostly affected by the elastic modulus of original soil, followed by the dense sand and the load layer, as well as the results of further analyses with optimal elastic modulus of soil show good agreement with the test.

Keywords: pipeline, optimization, elastic modulus of soil, response surface methodology

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Authors: Boukari Nassim

Abstract:

This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

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Authors: Avantika Vats, Kushal Thakur

Abstract:

This paper displays the point at issue, improvement, and utilization of a Monarch Butterfly Optimization (MBO) rather than a Genetic Algorithm (GA) in cognitive radio for the channel portion. This approach offers a satisfactory approach to get the accessible range of both the users, i.e., primary users (PUs) and secondary users (SUs). The proposed enhancement procedure depends on a nature-inspired metaheuristic algorithm. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. Southern Canada and the northern USA (land 1), and Mexico (Land 2). The positions of the monarch butterflies are modernizing in two ways. At first, the offsprings are generated (position updating) by the migration operator and can be adjusted by the migration ratio. It is trailed by tuning the positions for different butterflies by the methods for the butterfly adjusting operator. To keep the population unaltered and minimize fitness evaluations, the aggregate of the recently produced butterflies in these two ways stays equivalent to the first population. The outcomes obviously display the capacity of the MBO technique towards finding the upgraded work values on issues regarding the genetic algorithm.

Keywords: cognitive radio, channel allocation, monarch butterfly optimization, evolutionary, computation

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Authors: Hossein Ghadimi, Alireza Alizadeh, Oveis Abedinia, Noradin Ghadimi

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This paper presents an enhanced Honey Bee Mating Optimization (HBMO) to solve the optimal design of multi machine power system stabilizer (PSSs) parameters, which is called the Interactive Honey Bee Mating Optimization (IHBMO). Power System Stabilizers (PSSs) are now routinely used in the industry to damp out power system oscillations. The design problem of the proposed controller is formulated as an optimization problem and IHBMO algorithm is employed to search for optimal controller parameters. The proposed method is applied to multi-machine power system (MPS). The method suggested in this paper can be used for designing robust power system stabilizers for guaranteeing the required closed loop performance over a prespecified range of operating and system conditions. The simplicity in design and implementation of the proposed stabilizers makes them better suited for practical applications in real plants. The non-linear simulation results are presented under wide range of operating conditions in comparison with the PSO and CPSS base tuned stabilizer one through FD and ITAE performance indices. The results evaluation shows that the proposed control strategy achieves good robust performance for a wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other controllers.

Keywords: power system stabilizer, IHBMO, multimachine, nonlinearities

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Authors: Fedorova Elena

Abstract:

In this article, we draw a distinction between two important functions of public policy in private international law. The first function is widely recognized and relates to the prevention of application of foreign laws and enforcement of foreign court judgments whenever their effects are incompatible with the domestic legal system of the forum. This effectively protects sovereign rights of the forum state as it allows to resist against the undesirable effects of foreign law-making and law-enforcement policies. The second function is less obvious, but not less important. As the internal private legal relationships, international private relationships are usually governed by rules of public policy, to which the parties can not derogate by mutual agreement. Thefore, for international private law relations public policy has a different function than previously mentioned: in this case, the public policy acts as a defense against unacceptable effects of the party autonomy. Thus, this second function of public policy consists in the limitation of the party autonomy wich effects would be unacceptable for the local legal system. In the frame of this second function the author will analyse two types of public policy which can limit the party autonomy: « substantial » public policy (which regulates the substance of international legal relationship) and « conflictual » public policy (which regulates the party autonomy to choose the law applicable for the substance of relationship). The author provides an analysis of these functions of the public policy in the field of international contract law because of the important role of the principle of party autonomy for international contract relations.

Keywords: public policy, general theory of private international law, substantial public policy, conflictual public policy

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

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The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications

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Authors: Zuyong Chen, Jianghao Wu, Yanlai Zhang

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Flapping-wing micro aerial vehicle (FMAV) is a new type of aircraft by mimicking the flying behavior to that of small birds or insects. Comparing to the traditional fixed wing or rotor-type aircraft, FMAV only needs to control the motion of flapping wings, by changing the size and direction of lift to control the flight attitude. Therefore, its transmission system should be designed very compact. Lightweight design can effectively extend its endurance time, while engineering experience alone is difficult to simultaneously meet the requirements of FMAV for structural strength and quality. Current researches still lack the guidance of considering nonlinear factors of 3D printing material when carrying out topology optimization, especially for the tiny FMAV transmission system. The coupling of non-linear material properties and non-linear contact behaviors of FMAV transmission system is a great challenge to the reliability of the topology optimization result. In this paper, topology optimization design based on FEA solver package Altair Optistruct for the transmission system of FMAV manufactured by 3D Printing was carried out. Firstly, the isotropic constitutive behavior of the Ultraviolet (UV) Cureable Resin used to fabricate the structure of FMAV was evaluated and confirmed through tensile test. Secondly, a numerical computation model describing the mechanical behavior of FMAV transmission structure was established and verified by experiments. Then topology optimization modeling method considering non-linear factors were presented, and optimization results were verified by dynamic simulation and experiments. Finally, detail discussions of different load status and constraints were carried out to explore the leading factors affecting the optimization results. The contributions drawn from this article helpful for guiding the lightweight design of FMAV are summarizing as follow; first, a dynamic simulation modeling method used to obtain the load status is presented. Second, verification method of optimized results considering non-linear factors is introduced. Third, based on or can achieve a better weight reduction effect and improve the computational efficiency rather than taking multi-states into account. Fourth, basing on makes for improving the ability to resist bending deformation. Fifth, constraint of displacement helps to improve the structural stiffness of optimized result. Results and engineering guidance in this paper may shed lights on the structural optimization and light-weight design for future advanced FMAV.

Keywords: flapping-wing micro aerial vehicle, 3d printing, topology optimization, finite element analysis, experiment

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Authors: Yasaman Esfandiari

Abstract:

Mechanical engineering has always dealt with amplification of the input power in power trains. One of the ways to achieve this goal is to use gears to change the amplitude and direction of the torque and the speed. However, the gears should be optimally designed to best achieve these objectives. In this study, helical gear systems are optimized to achieve maximum power. Material selection, space restriction, available facilities for manufacturing, the probability of tooth breakage, and tooth wear are taken into account and governing equations are derived. Finally, a Matlab code was generated to solve the optimization problem and the results are verified.

Keywords: design, gears, Matlab, optimization

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Authors: Aigul Manapova

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We consider an optimal control problem in the higher coefficient of nonlinear equations with a divergent elliptic operator and unbounded nonlinearity, and the Dirichlet boundary condition. The conditions imposed on the coefficients of the state equation are assumed to hold only in a small neighborhood of the exact solution to the original problem. This assumption suggests that the state equation involves nonlinearities of unlimited growth and considerably expands the class of admissible functions as solutions of the state equation. We obtain formulas for the first partial derivatives of the objective functional with respect to the control functions. To calculate the gradients the numerical solutions of the state and adjoint problems are used. We also prove that the gradient of the cost function is Lipchitz continuous.

Keywords: cost functional, differentiability, divergent elliptic operator, optimal control, unbounded nonlinearity

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Authors: A. Sohouli, A. Suleman

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This study focuses on reliability analysis of variable stiffness composite laminate structures to investigate the potential structural improvement compared to conventional (straight fibers) composite laminate structures. A computational framework was developed which it consists of a deterministic design step and reliability analysis. The optimization part is Discrete Material Optimization (DMO) and the reliability of the structure is computed by Monte Carlo Simulation (MCS) after using Stochastic Response Surface Method (SRSM). The design driver in deterministic optimization is the maximum stiffness, while optimization method concerns certain manufacturing constraints to attain industrial relevance. These manufacturing constraints are the change of orientation between adjacent patches cannot be too large and the maximum number of successive plies of a particular fiber orientation should not be too high. Variable stiffness composites may be manufactured by Automated Fiber Machines (AFP) which provides consistent quality with good production rates. However, laps and gaps are the most important challenges to steer fibers that effect on the performance of the structures. In this study, the optimal curved fiber paths at each layer of composites are designed in the first step by DMO, and then the reliability analysis is applied to investigate the sensitivity of the structure with different standard deviations compared to the straight fiber angle composites. The random variables are material properties and loads on the structures. The results show that the variable stiffness composite laminate structures are much more reliable, even for high standard deviation of material properties, than the conventional composite laminate structures. The reason is that the variable stiffness composite laminates allow tailoring stiffness and provide the possibility of adjusting stress and strain distribution favorably in the structures.

Keywords: material optimization, Monte Carlo simulation, reliability analysis, response surface method, variable stiffness composite structures

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Authors: Mona Baniahmadi, Saied Haghanifar

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Radio Frequency Identification (RFID) is regarded as a promising technology for the optimization of supply chain processes since it improves manufacturing and retail operations from forecasting demand for planning, managing inventory, and distribution. This study precisely aims at learning to know the RFID technology and at explaining how it can concretely be used for supply chain management and how it can help improving it in the case of Hejrat Company which is located in Iran and works on the distribution of medical drugs and cosmetics. This study uses some statistical analysis to calculate the expected benefits of an integrated RFID system on supply chain obtained through competitive advantages increases with decreasing cost factor. The study investigates how the cost of storage process, labor cost, the cost of missing goods, inventory management optimization, on-time delivery, order cost, lost sales and supply process optimization affect the performance of the integrated RFID supply chain regarding cost factors and provides a competitive advantage.

Keywords: cost, competitive advantage, radio frequency identification, supply chain

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Authors: Muhammad Saqib Manzoor, Camille Dickson-Deane, Prashan Karunaratne

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Cobb-Douglas production (utility) function is a fundamental function widely used in economics teaching and research. The key reason is the function's characteristics to describe the actual production using inputs like labour and capital. The characteristics of the function like returns to scale, marginal, and diminishing marginal productivities are covered in the introductory units in both microeconomics and macroeconomics with a 2-dimensional static visualisation of the function. However, less insight is provided regarding three-dimensional surface, changes in the curvature properties due to returns to scale, the linkage of the short-run production function with its long-run counterpart and marginal productivities, the level curves, and the constraint optimisation. Since (freshman) learners have diverse prior knowledge and cognitive skills, the existing “one size fits all” approach is not very helpful. The aim of this study is to bridge this gap by introducing technological intervention with interactive animations of the three-dimensional surface and sequential unveiling of the characteristics mentioned above using Python software. A small classroom intervention has helped students enhance their analytical and visualisation skills towards active and authentic learning of this topic. However, to authenticate the strength of our approach, a quasi-Delphi study will be conducted to ask domain-specific experts, “What value to the learning process in economics is there using a 2-dimensional static visualisation compared to using a 3-dimensional dynamic visualisation?’ Here three perspectives of the intervention were reviewed by a panel comprising of novice students, experienced students, novice instructors, and experienced instructors in an effort to determine the learnings from each type of visualisations within a specific domain of knowledge. The value of this approach is key to suggesting different pedagogical methods which can enhance learning outcomes.

Keywords: cobb-douglas production function, quasi-Delphi method, effective teaching and learning, 3D-visualisations

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Authors: Alex Contarino

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Professional sports leagues often have a “free agency” period, during which teams may sign players with expiring contracts.To promote parity, many leagues operate under a salary cap that limits the amount teams can spend on player’s salaries in a given year. Similarly, in fantasy sports leagues, salary cap drafts are a popular method for selecting players. In order to sign a free agent in either setting, teams must bid against one another to buy the player’s services while ensuring the sum of their player’s salaries is below the salary cap. This paper models the bidding process for a free agent as a constrained optimization problem that can be solved using linear programming. The objective is to determine the largest bid that a team should offer the player subject to the constraint that the value of signing the player must exceed the value of using the salary cap elsewhere. Iteratively solving this optimization problem for each available free agent provides teams with an effective framework for maximizing the talent on their rosters. The utility of this approach is demonstrated for team sport roster construction and fantasy sport drafts, using recent data sets from both settings.

Keywords: linear programming, optimization, roster management, salary cap

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Authors: Wheyming Song, Hung-Hsiang Lin, Scott Lian

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In this research, we investigate the optimal dispatching rule for machines and manpower allocation in the solar ingot-wafer systems. The performance of the method is measured by the sales profit for each dollar paid to the operators in a one week at steady-state. The decision variables are identification-number of machines and operators when each job is required to be served in each process. We propose a rule which is a function of operator’s ability, corresponding salary, and standing location while in the factory. The rule is named ‘Multi-nominal distribution dispatch rule’. The proposed rule performs better than many traditional rules including generic algorithm and particle swarm optimization. Simulation results show that the proposed Multi-nominal distribution dispatch rule improvement on the sales profit dramatically.

Keywords: dispatching, solar ingot, simulation, flexsim

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Authors: N. Larbi, F. Debbat

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Wireless communication systems have changed dramatically and shown spectacular evolution over the past two decades. These radio technologies are engaged in a quest endless high-speed transmission coupled to a constant need to improve transmission quality. Various radio communication systems being developed use code division multiple access (CDMA) technique. This work analyses a hybrid honey bees mating optimization algorithm (HBMO) applied to multiuser detection (MuD) in CDMA communication systems. The HBMO is a swarm-based optimization algorithm, which simulates the mating process of real honey bees. We apply a hybridization of HBMO with simulated annealing (SA) in order to improve the solution generated by the HBMO. Simulation results show that the detection based on Hybrid HBMO, in term of bit error rate (BER), is viable option when compared with the classic detectors from literature under Rayleigh flat fading channel.

Keywords: BER, DS-CDMA multiuser detection, genetic algorithm, hybrid HBMO, simulated annealing

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Authors: Boris Melnikov, Dmitrii Chaikovskii, Elena Melnikova

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The traveling salesman problem (TSP) is a well-known optimization problem that seeks to find the shortest possible route that visits a set of points and returns to the starting point. In this paper, we apply some heuristics of the TSP for the task of restoring the DNA matrix. This restoration problem is often considered in biocybernetics. For it, we must recover the matrix of distances between DNA sequences if not all the elements of the matrix under consideration are known at the input. We consider the possibility of using this method in the testing of distance calculation algorithms between a pair of DNAs to restore the partially filled matrix.

Keywords: optimization problems, DNA matrix, partially filled matrix, traveling salesman problem, heuristic algorithms

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Authors: Amanpreet Kaur

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Wavelet transform (WT) is a powerful statistical tool used in applied mathematics for signal and image processing. The different mother, wavelet basis function, has been compared to select the optimal wavelet function that represents the electromyogram signal characteristics of upper limb amputees. Four different EMG electrode has placed on different location of shoulder muscles. Twenty one wavelet functions from different wavelet families were investigated. These functions included Daubechies (db1-db10), Symlets (sym1-sym5), Coiflets (coif1-coif5) and Discrete Meyer. Using mean square error value, the significance of the mother wavelet functions has been determined for teres, pectorals, and infraspinatus around shoulder muscles. The results show that the best mother wavelet is the db3 from the Daubechies family for efficient classification of the signal.

Keywords: Daubechies, upper limb amputation, shoulder muscles, Symlets, Coiflets

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Authors: I. F. Ejim, F. L. Kamen

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Aims: In this experiment, algae oil extraction with a combination of n-hexane and ethanol was investigated. The effects of extraction solvent concentration, extraction time and temperature on the yield and quality of oil were studied using Response Surface Methodology (RSM). Experimental Design: Optimization of algae oil extraction using Box-Behnken design was used to generate 17 experimental runs in a three-factor-three-level design where oil yield, specific gravity, acid value and saponification value were evaluated as the response. Result: In this result, a minimum oil yield of 17% and maximum of 44% was realized. The optimum values for yield, specific gravity, acid value and saponification value from the overlay plot were 40.79%, 0.8788, 0.5056 mg KOH/g and 180.78 mg KOH/g respectively with desirability of 0.801. The maximum point prediction was yield 40.79% at solvent concentration 66.68 n-hexane, temperature of 40.0°C and extraction time of 4 hrs. Analysis of Variance (ANOVA) results showed that the linear and quadratic coefficient were all significant at p<0.05. The experiment was validated and results obtained were with the predicted values. Conclusion: Algae oil extraction was successfully optimized using RSM and its quality indicated it is suitable for many industrial uses.

Keywords: algae oil, response surface methodology, optimization, Box-Bohnken, extraction

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Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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Carefully scheduling the operations of pumps can be resulted to significant energy savings. Schedules can be defined either implicit, in terms of other elements of the network such as tank levels, or explicit by specifying the time during which each pump is on/off. In this study, two new explicit representations based on time-controlled triggers were analyzed, where the maximum number of pump switches was established beforehand, and the schedule may contain fewer switches than the maximum. The optimal operation of pumping stations was determined using a Jumping Particle Swarm Optimization (JPSO) algorithm to achieve the minimum energy cost. The model integrates JPSO optimizer and EPANET hydraulic network solver. The optimal pump operation schedule of VanZyl water distribution system was determined using the proposed model and compared with those from Genetic and Ant Colony algorithms. The results indicate that the proposed model utilizing the JPSP algorithm outperformed the others and is a versatile management model for the operation of real-world water distribution system.

Keywords: JPSO, operation, optimization, water distribution system

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Authors: Chunye Gong, Ming Tie, Jie Liu, Weimin Bao, Xinbiao Gan, Shengguo Li, Bo Yang, Xuguang Chen, Tiaojie Xiao, Yang Sun

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Large-scale CFD simulation relies on high-performance parallel computing, and the load balance is the key role which affects the parallel efficiency. This paper focuses on the load-balancing problem of parallel CFD simulation with structured mesh. A mathematical model for this load-balancing problem is presented. The genetic algorithm, fitness computing, two-level code are designed. Optimal selector, robust operator, and local optimization operator are designed. The properties of the presented genetic algorithm are discussed in-depth. The effects of optimal selector, robust operator, and local optimization operator are proved by experiments. The experimental results of different test sets, DLR-F4, and aircraft design applications show the presented load-balancing algorithm is robust, quickly converged, and is useful in real engineering problems.

Keywords: genetic algorithm, load-balancing algorithm, optimal variation, local optimization

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Authors: Iván Rivet, Narges Dialami, Miguel Cervera, Michele Chiumenti

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Process parameters in Additive Manufacturing (AM) play a critical role in the mechanical performance of the final component. In order to find the input configuration that guarantees the optimal performance of the printed part, the process-performance relationship must be found. Fused Filament Fabrication (FFF) is the selected demonstrative AM technology due to its great popularity in the industrial manufacturing world. A material model that considers the different printing patterns present in a FFF part is used. A voxelized mesh is built from the manufacturing toolpaths described in the G-Code file. An Adaptive Mesh Refinement (AMR) based on the octree strategy is used in order to reduce the complexity of the mesh while maintaining its accuracy. High-fidelity and cost-efficient Finite Element (FE) simulations are performed and the influence of key process parameters in the mechanical performance of the component is analyzed. A robust optimization process based on appropriate failure criteria is developed to find the printing direction that leads to the optimal mechanical performance of the component. The Tsai-Wu failure criterion is implemented due to the orthotropy and heterogeneity constitutive nature of FFF components and because of the differences between the strengths in tension and compression. The optimization loop implements a modified version of an Anomaly Detection (AD) algorithm and uses the computed metrics to obtain the optimal printing direction. The developed methodology is verified with a case study on an industrial demonstrator.

Keywords: additive manufacturing, optimization, printing direction, mechanical performance, voxelization

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Authors: Mohamed Mousa

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Sacristies in the supply of freshwater, strict regulations on discharging wastewater and the support to encourage sustainable development by water minimization techniques leads to raise the interest of water reusing, regeneration, and recycling. Water is considered a vital element in chemical industries. In this study, an optimization model will be developed to determine the optimal design of refinery’s water network system via source interceptor sink that involves several network alternatives, then a Mixed-Integer Non-Linear programming (MINLP) was used to obtain the optimal network superstructure based on flowrates, the concentration of contaminants, etc. The main objective of the model is to reduce the fixed cost of piping installation interconnections, reducing the operating cots of all streams within the refiner’s water network, and minimize the concentration of pollutants to comply with the environmental regulations. A real case study for one of the Egyptian refineries was studied by GAMS / BARON global optimization platform, and the water network had been retrofitted and optimized, leading to saving around 195 m³/ hr. of freshwater with a total reduction reaches to 26 %.

Keywords: freshwater minimization, modelling, GAMS, BARON, water network design, wastewater reudction

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Authors: Karima Megdouli

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The ejector, a central element within the CO₂ transcritical ejection refrigeration system, holds significant importance in enhancing refrigeration capacity and minimizing compressor power usage. This study's objective is to introduce a technique for enhancing the effectiveness of the CO₂ transcritical two-phase ejector, utilizing Taguchi and ANOVA analysis. The investigation delves into the impact of geometric parameters, secondary flow temperature, and primary flow pressure on the efficiency of the ejector. Results indicate that employing a combination of Taguchi and ANOVA offers increased reliability and superior performance when optimizing the design of the CO₂ two-phase ejector.

Keywords: ejector, supersonic, Taguchi, ANOVA, optimization

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Authors: Rizky Oktaviana

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The main purpose of studying lies in improving students’ understanding. Teachers usually use written test to measure students’ understanding about learning material especially mathematical learning material. This common method actually has a lack point, such that in mathematics content, written test only show procedural steps to solve mathematical problems. Therefore, teachers unable to see whether students actually understand about mathematical concepts and the relation between concepts or not. One of the best tools to observe students’ understanding about the mathematical concepts is concept map. The goal of this research is to describe junior high school students understanding about mathematical concepts through Concept Maps based on the difference of mathematical ability. There were three steps in this research; the first step was choosing the research subjects by giving mathematical ability test to students. The subjects of this research are three students with difference mathematical ability, high, intermediate and low mathematical ability. The second step was giving concept mapping training to the chosen subjects. The last step was giving concept mapping task about the function to the subjects. Nodes which are the representation of concepts of function were provided in concept mapping task. The subjects had to use the nodes in concept mapping. Based on data analysis, the result of this research shows that subject with high mathematical ability has formal understanding, due to that subject could see the connection between concepts of function and arranged the concepts become concept map with valid hierarchy. Subject with intermediate mathematical ability has relational understanding, because subject could arranged all the given concepts and gave appropriate label between concepts though it did not represent the connection specifically yet. Whereas subject with low mathematical ability has poor understanding about function, it can be seen from the concept map which is only used few of the given concepts because subject could not see the connection between concepts. All subjects have instrumental understanding for the relation between linear function concept, quadratic function concept and domain, co domain, range.

Keywords: concept map, concept mapping, mathematical concepts, understanding

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Authors: K. R. Balabiyev, A. O. Kaipbayeva

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The article discusses the legal framework of the government’s environmental function and analyzes the role of the national policy in protection of wetlands. The problem is of interest for it deals with the most important branch of economy–utilization of Kazakhstan’s natural resources, protection of health and environmental well being of the population. Development of a long-term environmental program addressing the protection of wetlands represents the final stage of the government’s environmental policy, and is a relatively new function for the public administration system. It appeared due to the environmental measures that require immediate decisions to be taken. It is an integral part of the effort in the field of management of state-owned natural resource, as well as of the measures aimed at efficient management of natural resources to avoid their early depletion or contamination.

Keywords: environmental focus, government’s environmental function, protection of wetlands, Kazakhstan

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Authors: Salah R. Al Zaidee, Ali S. Mahdi

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Except for simple problems of statically determinate structures, optimum design problems in structural engineering have implicit objective functions where structural analysis and design are essential within each searching loop. With these implicit functions, the structural engineer is usually enforced to write his/her own computer code for analysis, design, and searching for optimum design among many feasible candidates and cannot take advantage of available software for structural analysis, design, and searching for the optimum solution. The meta-model is a regression model used to transform an implicit objective function into objective one and leads in turn to decouple the structural analysis and design processes from the optimum searching process. With the meta-model, well-known software for structural analysis and design can be used in sequence with optimum searching software. In this paper, the meta-model has been used to develop an explicit objective function for plane steel frames subjected to dead, live, and seismic forces. Frame topology is assumed as predefined based on architectural and functional requirements. Columns and beams sections and different connections details are the main design variables in this study. Columns and beams are grouped to reduce the number of design variables and to make the problem similar to that adopted in engineering practice. Data for the implicit objective function have been generated based on analysis and assessment for many design proposals with CSI SAP software. These data have been used later in SPSS software to develop a pure quadratic nonlinear regression model for the explicit objective function. Good correlations with a coefficient, R², in the range from 0.88 to 0.99 have been noted between the original implicit functions and the corresponding explicit functions generated with meta-model.

Keywords: meta-modal, objective function, steel frames, seismic analysis, design

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