Search results for: thermodynamic optimization

Authors: Iannick Gagnon, Alain April

Abstract:

The performance of a metaheuristic on a given problem class depends on the class itself and the choice of parameters. Parameter tuning is the most time-consuming phase of the optimization process after the main calculations and it often nullifies the speed advantage of metaheuristics over traditional optimization algorithms. Several off-the-shelf parameter tuning algorithms are available, but when the objective function is expensive to evaluate, these can be prohibitively expensive to use. This paper presents a surrogate-like method for finding adequate parameters using fitness landscape analysis on simple benchmark functions and real-world objective functions. The result is a simple compound similarity metric based on the empirical correlation coefficient and a measure of convexity. It is then used to find the best benchmark functions to serve as surrogates. The near-optimal parameter set is then found using fractional factorial design. The real-world problem of NACA airfoil lift coefficient maximization is used as a preliminary proof of concept. The overall aim of this research is to reduce the computational overhead of metaheuristics parameterization.

Keywords: metaheuristics, stochastic optimization, particle swarm optimization, exploratory landscape analysis

Procedia PDF Downloads 126

Authors: Do-Jin Jang, Sung-Ah Kim

Abstract:

A kinetic façade responds to user requirements and environmental conditions.  In designing a kinetic façade, kinetic patterns play a key role in determining its performance. This paper proposes a biomimetic method for the multi-objective optimization for kinetic façade design. The autonomous decentralized control system is combined with flocking algorithm. The flocking agents are autonomously reacting to sensor values and bring about kinetic patterns changing over time. A series of experiments were conducted to verify the potential and limitations of the flocking based decentralized control. As a result, it could show the highest performance balancing multiple objectives such as solar radiation and openness among the comparison group.

Keywords: biomimicry, flocking algorithm, autonomous decentralized control, multi-objective optimization

Procedia PDF Downloads 492

Authors: Muhammad Zaheer Babar, Amer Kashif, Muhammad Rizwan Javed

Abstract:

Nowadays distributed generation integration is best way to overcome the increasing load demand. Optimal allocation of distributed generation plays a vital role in reducing system losses and improves voltage profile. In this paper, a Meta heuristic technique is proposed for allocation of DG in order to reduce power losses and improve voltage profile. The proposed technique is based on Multi Objective Particle Swarm optimization. Fewer control parameters are needed in this algorithm. Modification is made in search space of PSO. The effectiveness of proposed technique is tested on IEEE 33 bus test system. Single DG as well as multiple DG scenario is adopted for proposed method. Proposed method is more effective as compared to other Meta heuristic techniques and gives better results regarding system losses and voltage profile.

Keywords: Distributed generation (DG), Multi Objective Particle Swarm Optimization (MOPSO), particle swarm optimization (PSO), IEEE standard Test System

Procedia PDF Downloads 427

Authors: Hanmei Peng, Yiqun Wang, Mao Tan, Zhuocen Dai, Yongxin Su

Abstract:

Efficient energy management in multi-microgrid distribution systems holds significant importance for enhancing the economic benefits of regional power grids. To better balance conflicts among various stakeholders, a two-stage game-based collaborative optimization approach is proposed in this paper, effectively addressing the realistic scenario involving both competition and collaboration among stakeholders. The first stage, aimed at maximizing individual benefits, involves constructing a non-cooperative tariff game model for the distribution network and surplus microgrid. In the second stage, considering power flow and physical line capacity constraints we establish a cooperative P2P game model for the multi-microgrid distribution system, and the optimization involves employing the Lagrange method of multipliers to handle complex constraints. Simulation results demonstrate that the proposed approach can effectively improve the system economics while harmonizing individual and collective rationality.

Keywords: cooperative game, collaborative optimization, multi-microgrid distribution system, non-cooperative game

Procedia PDF Downloads 37

Authors: B. Sellami, M. Belloufi

Abstract:

Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, we propose a new two-parameter family of conjugate gradient methods for unconstrained optimization. The two-parameter family of methods not only includes the already existing three practical nonlinear conjugate gradient methods, but also has other family of conjugate gradient methods as subfamily. The two-parameter family of methods with the Wolfe line search is shown to ensure the descent property of each search direction. Some general convergence results are also established for the two-parameter family of methods. The numerical results show that this method is efficient for the given test problems. In addition, the methods related to this family are uniformly discussed.

Keywords: unconstrained optimization, conjugate gradient method, line search, global convergence

Procedia PDF Downloads 420

Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

Abstract:

E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

Procedia PDF Downloads 88

Authors: Ahcene Habbi, Yassine Boudouaoui

Abstract:

This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: automatic design, learning, fuzzy rules, hybrid, swarm optimization

Procedia PDF Downloads 412

Authors: Roya Ahmadi Ahangar, Hamid Madadyari

Abstract:

The seeker optimization algorithm (SOA) is increasingly gaining popularity among the researchers society due to its effectiveness in solving some real-world optimization problems. This paper provides the load-frequency control method based on the SOA for removing oscillations in the power system. A three-zone power system includes a thermal zone, a hydraulic zone and a wind zone equipped with robust proportional-integral-differential (PID) controllers. The result of simulation indicates that load-frequency changes in the wind zone for the multi-zone system are damped in a short period of time. Meanwhile, in the oscillation period, the oscillations amplitude is not significant. The result of simulation emphasizes that the PID controller designed using the seeker optimization algorithm has a robust function and a better performance for oscillations damping compared to the traditional PID controller. The proposed controller’s performance has been compared to the performance of PID controller regulated with Particle Swarm Optimization (PSO) and. Genetic Algorithm (GA) and Artificial Bee Colony (ABC) algorithms in order to show the superior capability of the proposed SOA in regulating the PID controller. The simulation results emphasize the better performance of the optimized PID controller based on SOA compared to the PID controller optimized with PSO, GA and ABC algorithms.

Keywords: load-frequency control, multi zone, robust PID controller, wind generation

Procedia PDF Downloads 281

Authors: Mitchell Gohnert, Ryan Bradley

Abstract:

This paper reviews some fundamental concepts of structural optimization of shell structures, which is based on the type of materials used in construction and the shape of the structure. The first step of structural optimization is to break down all internal forces into fundamental principal stresses. The stress patterns direct our selection of structural shapes and the most appropriate type of construction material. In our selection of materials, it is essential to understand that all construction materials have flaws, or micro-cracks, which reduce the capacity of the material. Because of material defects, many construction materials perform significantly better when subjected to compressive forces. Structures are also more efficient if bending moments are eliminated; thus, it is essential to select natural structures, or structures where the natural flow of stress follows the axis of the shell. The shape of the structure, therefore, has a profound effect on stress levels. Stress may be reduced dramatically by simply changing the shape. Catenary, triangular and linear shapes are the fundamental structural forms to achieve optimal stress flow. If the natural flow of stress matches the shape of the structures, the most optimal shape is determined.

Keywords: arches, economy of stresses, material strength, optimization, shells

Procedia PDF Downloads 75

Authors: Omer Oral, Y. Emre Yilmaz

Abstract:

Topology optimization is an approach that optimizes material distribution within a given design space for a certain load and boundary conditions by providing performance goals. It uses various restrictions such as boundary conditions, set of loads, and constraints to maximize the performance of the system. It is different than size and shape optimization methods, but it reserves some features of both methods. In this study, interior structures of the parts were optimized by using SIMP (Solid Isotropic Material with Penalization) method. The volume of the part was preassigned parameter and minimum deflection was the objective function. The basic idea behind the theory was considered, and different methods were discussed. Rhinoceros 3D design tool was used with Grasshopper and TopOpt plugins to create and optimize parts. A Grasshopper algorithm was designed and tested for different beams, set of arbitrary located forces and support types such as pinned, fixed, etc. Finally, 2.5D shapes were obtained and verified by observing the changes in density function.

Keywords: Grasshopper, lattice structure, microstructures, Rhinoceros, solid isotropic material with penalization method, TopOpt, topology optimization

Procedia PDF Downloads 109

Authors: Shunichi Ohmori, Sirawadee Arunyanart, Kazuho Yoshimoto

Abstract:

We consider a periodic review inventory control problem of minimizing production cost, inventory cost, and lost-sales under demand uncertainty, in which product demands are not specified exactly and it is only known to belong to a given uncertainty set, yet the constraints must hold for possible values of the data from the uncertainty set. We propose a robust optimization formulation for obtaining lowest cost possible and guaranteeing the feasibility with respect to range of order quantity and inventory level under demand uncertainty. Our formulation is based on the adaptive robust counterpart, which suppose order quantity is affine function of past demands. We derive certainty equivalent problem via second-order cone programming, which gives 'not too pessimistic' worst-case.

Keywords: robust optimization, inventory control, supply chain managment, second-order programming

Procedia PDF Downloads 382

Authors: Aleksandar Jovanovic, Katarina Kukic, Ana Uzelac, Dusan Teodorovic

Abstract:

Wisdom of the Crowd (WoC) is a decentralized method that uses the collective intelligence of humans. Individual guesses may be far from the target, but when considered as a group, they converge on optimal solutions for a given problem. We will utilize WoC to address the challenge of controlling traffic lights within intersections from the streets of Kragujevac, Serbia. The problem at hand falls within the category of NP-hard problems. We will employ an algorithm that leverages the swarm intelligence of bees: Bee Colony Optimization (BCO). Data regarding traffic signal timing at a single intersection will be gathered from citizens through a survey. Results obtained in that manner will be compared to the BCO results for different traffic scenarios. We will use Vissim traffic simulation software as a tool to compare the performance of bees’ and humans’ collective intelligence.

Keywords: wisdom of the crowd, traffic signal control, combinatorial optimization, bee colony optimization

Procedia PDF Downloads 86

Authors: Himanshu Shekhar Maharana, S. K .Dash

Abstract:

Economic Load Dispatch (ELD) proves to be a vital optimization process in electric power system for allocating generation amongst various units to compute the cost of generation, the cost of emission involving global warming gases like sulphur dioxide, nitrous oxide and carbon monoxide etc. In this dissertation, we emphasize ramp rate constriction factor based particle swarm optimization (RRCPSO) for analyzing various performance objectives, namely cost of generation, cost of emission, and a dual objective function involving both these objectives through the experimental simulated results. A 6-unit 30 bus IEEE test case system has been utilized for simulating the results involving improved weight factor advanced ramp rate limit constraints for optimizing total cost of generation and emission. This method increases the tendency of particles to venture into the solution space to ameliorate their convergence rates. Earlier works through dispersed PSO (DPSO) and constriction factor based PSO (CPSO) give rise to comparatively higher computational time and less good optimal solution at par with current dissertation. This paper deals with ramp rate and constriction factor based well defined ramp rate PSO to compute various objectives namely cost, emission and total objective etc. and compares the result with DPSO and weight improved PSO (WIPSO) techniques illustrating lesser computational time and better optimal solution. 

Keywords: economic load dispatch (ELD), constriction factor based particle swarm optimization (CPSO), dispersed particle swarm optimization (DPSO), weight improved particle swarm optimization (WIPSO), ramp rate and constriction factor based particle swarm optimization (RRCPSO)

Procedia PDF Downloads 356

Authors: Seon Tae Kim, Robert Hegner, Goksel Ozuylasi, Panagiotis Stathopoulos, Eberhard Nicke

Abstract:

High-temperature heat pumps (HTHP) that can supply heat at temperatures above 200°C can enhance the energy efficiency of industrial processes and reduce the CO₂ emissions connected with the heat supply of these processes. In the current work, the thermodynamic performance of 3 different vapor compression cycles, which use R-718 (water) as a working medium, have been evaluated by using a commercial process simulation tool (EBSILON Professional). All considered cycles use two-stage vapor compression with intercooling between stages. The main aim of the study is to compare different intercooling strategies and study possible heat recovery scenarios within the intercooling process. This comparison has been carried out by computing the coefficient of performance (COP), the heat supply temperature level, and the respective mass flow rate of water for all cycle architectures. With increasing temperature difference between the heat source and heat sink, ∆T, the COP values decreased as expected, and the highest COP value was found for the cycle configurations where both compressors have the same pressure ratio (PR). The investigation on the HTHP capacities with optimized PR and exergy analysis has also been carried out. The internal heat exchanger cycle with the inward direction of secondary flow (IHX-in) showed a higher temperature level and exergy efficiency compared to other cycles. Moreover, the available operating range was estimated by considering mechanical limitations.

Keywords: high temperature heat pump, industrial process, vapor compression cycle, R-718 (water), thermodynamic analysis

Procedia PDF Downloads 128

Authors: Arshad Mehmood Ch, Riaz Ahmad, Imran Ali Ch, Waqas Durrani

Abstract:

This study deals with the application of Ant Colony Optimization (ACO) approach to solve no-wait flowshop scheduling problem (NW-FSSP). ACO algorithm so developed has been coded on Matlab computer application. The paper covers detailed steps to apply ACO and focuses on judging the strength of ACO in relation to other solution techniques previously applied to solve no-wait flowshop problem. The general purpose approach was able to find reasonably accurate solutions for almost all the problems under consideration and was able to handle a fairly large spectrum of problems with far reduced CPU effort. Careful scrutiny of the results reveals that the algorithm presented results better than other approaches like Genetic algorithm and Tabu Search heuristics etc; earlier applied to solve NW-FSSP data sets.

Keywords: no-wait, flowshop, scheduling, ant colony optimization (ACO), makespan

Procedia PDF Downloads 408

Authors: Carlos Alberto Rivera-corredor, Angie Dayana Vargas-Ceballos, Edison Gilpavas, Izabela Dobrosz-Gómez, Miguel Ángel Gómez-García

Abstract:

Hexavalent chromium, Cr (VI) is present in the effluents from different industries such as electroplating, mining, leather tanning, etc. This compound is of great academic and industrial concern because of its toxic and carcinogenic behavior. Its dumping to both environmental and public health for animals and humans causes serious problems in water sources. The amount of Cr (VI) in industrial wastewaters ranges from 0.5 to 270,000 mgL-1. According to the Colombian standard for water quality (NTC-813-2010), the maximum allowed concentration for the Cr (VI) in drinking water is 0.05 mg L-1. To comply with this limit, it is essential that industries treat their effluent to reduce the Cr (VI) to acceptable levels. Numerous methods have been reported for the treatment removing metal ions from aqueous solutions such as: reduction, ion exchange, electrodialysis, etc. Adsorption has become a promising method for the purification of metal ions in water, since its application corresponds with an economic and efficient technology. The absorbent selection and the kinetic and thermodynamic study of the adsorption conditions are key to the development of a suitable adsorption technology. The Ce0.25Zr0.75O2.nH2O presents higher adsorption capacity between a series of hydrated mixed oxides Ce1-xZrxO2 (x = 0, 0.25, 0.5, 0.75, 1). This work presents the kinetic and thermodynamic study of Cr (VI) adsorption on Ce0.25Zr0.75O2.nH2O. Experiments were performed under the following experimental conditions: initial Cr (VI) concentration = 25, 50 and 100 mgL-1, pH = 2, adsorbent charge = 4 gL-1, stirring time = 60 min, temperature=20, 28 and 40 °C. The Cr (VI) concentration was spectrophotometrically estimated by the method of difenilcarbazide with monitoring the absorbance at 540 nm. The Cr (VI) adsorption over hydrated Ce0.25Zr0.75O2.nH2O models was analyzed using pseudo-first and pseudo-second order kinetics. The Langmuir and Freundlich models were used to model the experimental data. The convergence between the experimental values and those predicted by the model, is expressed as a linear regression correlation coefficient (R2) and was employed as the model selection criterion. The adsorption process followed the pseudo-second order kinetic model and obeyed the Langmuir isotherm model. The thermodynamic parameters were calculated as: ΔH°=9.04 kJmol-1,ΔS°=0.03 kJmol-1 K-1, ΔG°=-0.35 kJmol-1 and indicated the endothermic and spontaneous nature of the adsorption process, governed by physisorption interactions.

Keywords: adsorption, hexavalent chromium, kinetics, thermodynamics

Procedia PDF Downloads 266

Authors: Varsha Singh, Kishan Fuse

Abstract:

This paper presents a study of the grey-Taguchi method to optimize CNC milling parameters of AA6061 T6 aluminium alloy. Grey-Taguchi method combines Taguchi method based design of experiments (DOE) with grey relational analysis (GRA). Multi-response optimization of different quality characteristics as surface roughness, material removal rate, cutting forces is done using grey relational analysis (GRA). The milling parameters considered for experiments include cutting speed, feed per tooth, and depth of cut. Each parameter with three levels is selected. A grey relational grade is used to estimate overall quality characteristics performance. The Taguchi’s L9 orthogonal array is used for design of experiments. MINITAB 17 software is used for optimization. Analysis of variance (ANOVA) is used to identify most influencing parameter. The experimental results show that grey relational analysis is effective method for optimizing multi-response characteristics. Optimum results are finally validated by performing confirmation test.

Keywords: ANOVA, CNC milling, grey relational analysis, multi-response optimization

Procedia PDF Downloads 289

Authors: Vivek Upadhayay, Siddharth Deshmukh

Abstract:

In recent years utilization of renewable energy sources has increased majorly because of the increase in global warming concerns. Organization these days are generally operated by Micro grid or smart grid on a small level. Power optimization and optimal load tripping is possible in a smart grid based industry. In any plant or industry loads can be divided into different categories based on their importance to the plant and power requirement pattern in the working days. Coming up with an idea to divide loads in different such categories and providing different power management algorithm to each category of load can reduce the power cost and can come handy in balancing stability and reliability of power. An objective function is defined which is subjected to a variable that we are supposed to minimize. Constraint equations are formed taking difference between the power usages pattern of present day and same day of previous week. By considering the objectives of minimal load tripping and optimal power distribution the proposed problem formulation is a multi-object optimization problem. Through normalization of each objective function, the multi-objective optimization is transformed to single-objective optimization. As a result we are getting the optimized values of power required to each load for present day by use of the past values of the required power for the same day of last week. It is quite a demand response scheduling of power. These minimized values then will be distributed to each load through an algorithm used to optimize the power distribution at a greater depth. In case of power storage exceeding the power requirement, profit can be made by selling exceeding power to the main grid.

Keywords: power flow optimization, power trading enhancement, smart grid, multi-object optimization

Procedia PDF Downloads 505

Authors: Jhon Vargas, Gilberto Osorio-Gomez, Tatiana Manrique

Abstract:

This work presents an optimal driving strategy proposal for a 125 c.c. street-type hybrid electric motorcycle with a parallel configuration. The results presented in this article are complementary regarding the control proposal of a hybrid motorcycle. In order to carry out such developments, a representative dynamic model of the motorcycle is used, in which also are described different optimization functionalities for predetermined driving modes. The purpose is to implement an off-line optimal driving strategy which distributes energy to both engines by minimizing an objective torque requirement function. An optimal dynamic contribution is found from the optimization routine, and the optimal percentage contribution for vehicle cruise speed is implemented in the proposed online PID controller.

Keywords: dynamic model, driving strategies, parallel hybrid motorcycle, PID controller, optimization

Procedia PDF Downloads 159

Authors: E. Moradimaram, H. Sayehvand

Abstract:

In recent years the increasing use of fossil fuels has led to various environmental problems including urban pollution, ozone layer depletion and acid rains. Moreover, with the increased number of industrial centers and higher consumption of these fuels, the end point of the fossil energy reserves has become more evident. Considering the environmental pollution caused by fossil fuels and their limited availability, renewable sources can be considered as the main substitute for non-renewable resources. One of these resources is the Organic Rankine Cycles (ORCs). These cycles while having high safety, have low maintenance requirements. Combining the ORCs with other systems, such as ejector and reheater will increase overall cycle efficiency. In this study, ejector and reheater are used to improve the thermal efficiency (ηth), exergy efficiency (η_ex) and net output power (w_net); therefore, the ORCs with reheater (RORCs) are proposed. A computational program has been developed to calculate the thermodynamic parameters required in Engineering Equations Solver (EES). In this program, the analysis of the first and second law in RORC is conducted, and a comparison is made between them and the ORCs with Ejector (EORC). R245fa is selected as the working fluid and water is chosen as low temperature heat source with a temperature of 95 °C and a mass transfer rate of 1 kg/s. The pressures of the second evaporator and reheater are optimized in terms of maximum exergy efficiency. The environment is at 298.15 k and at 101.325 kpa. The results indicate that the thermodynamic parameters in the RORC have improved compared to EORC.

Keywords: Organic Rankine Cycle (ORC), Organic Rankine Cycle with Reheater (RORC), Organic Rankine Cycle with Ejector (EORC), exergy efficiency

Procedia PDF Downloads 138

Authors: Igor Povar, Catherine Goyet

Abstract:

The seawater is subject to multiple external stressors (ES) including rising atmospheric CO2 and ocean acidification, global warming, atmospheric deposition of pollutants and eutrophication, which deeply alter its chemistry, often on a global scale and, in some cases, at the degree significantly exceeding that in the historical and recent geological verification. In ocean systems the micro- and macronutrients, heavy metals, phosphor- and nitrogen-containing components exist in different forms depending on the concentrations of various other species, organic matter, the types of minerals, the pH etc. The major limitation to assessing more strictly the ES to oceans, such as pollutants (atmospheric greenhouse gas, heavy metals, nutrients as nitrates and phosphates) is the lack of theoretical approach which could predict the ocean resistance to multiple external stressors. In order to assess the abovementioned ES, the research has applied and developed the buffer theory approach and theoretical expressions of the formal chemical thermodynamics to ocean systems, as heterogeneous aqueous systems. The thermodynamic expressions of complex chemical equilibria, involving acid-base, complex formation and mineral ones have been deduced. This thermodynamic approach utilizes thermodynamic relationships coupled with original mass balance constraints, where the solid phases are explicitly expressed. The ocean sensitivity to different external stressors and changes in driving factors are considered in terms of derived buffering capacities or buffer factors for heterogeneous systems. Our investigations have proved that the heterogeneous aqueous systems, as ocean and seas are, manifest their buffer properties towards all their components, not only to pH, as it has been known so far, for example in respect to carbon dioxide, carbonates, phosphates, Ca2+, Mg2+, heavy metal ions etc. The derived expressions make possible to attribute changes in chemical ocean composition to different pollutants. These expressions are also useful for improving the current atmosphere-ocean-marine biogeochemistry models. The major research questions, to which the research responds, are: (i.) What kind of contamination is the most harmful for Future Ocean? (ii.) What are chemical heterogeneous processes of the heavy metal release from sediments and minerals and its impact to the ocean buffer action? (iii.) What will be the long-term response of the coastal ocean to the oceanic uptake of anthropogenic pollutants? (iv.) How will change the ocean resistance in terms of future chemical complex processes and buffer capacities and its response to external (anthropogenic) perturbations? The ocean buffer capacities towards its main components are recommended as parameters that should be included in determining the most important ocean factors which define the response of ocean environment at the technogenic loads increasing. The deduced thermodynamic expressions are valid for any combination of chemical composition, or any of the species contributing to the total concentration, as independent state variable.

Keywords: atmospheric greenhouse gas, chemical thermodynamics, external stressors, pollutants, seawater

Procedia PDF Downloads 113

Authors: Hai Hoang, Thanh Xuan Nguyen Thi, Guillaume Galliero

Abstract:

Coarse-Grained (CG) molecular simulations have shown to be an efficient way to estimate thermophysical (static and dynamic) properties of fluids. Several strategies have been developed and reported in the literature for defining CG molecular models. Among them, those based on a top-down strategy (i.e. CG molecular models related to macroscopic observables), despite being heuristic, have increasingly gained attention. This is probably due to its simplicity in implementation and its ability to provide reasonable results for not only simple but also complex systems. Regarding simple Force-Fields associated with these CG molecular models, it has been found that the four parameters Mie chain model is one of the best compromises to describe thermophysical static properties (e.g. phase diagram, saturation pressure). However, parameterization procedures of these Mie-chain GC molecular models given in literature are generally insufficient to simultaneously provide static and dynamic (e.g. viscosity) properties. To deal with such situations, we have extended the corresponding states by using a quantity associated with the liquid viscosity. Results obtained from molecular simulations have shown that our approach is able to yield good estimates for both static and dynamic thermophysical properties for various real non-associating fluids. In addition, we will show that on simple (e.g. phase diagram, saturation pressure) and complex (e.g. thermodynamic response functions, thermodynamic energy potentials) static properties, results of our scheme generally provides improved results compared to existing approaches.

Keywords: coarse-grained model, mie potential, molecular simulations, thermophysical properties, phase equilibria

Procedia PDF Downloads 312

Authors: Ali Mohammadi Bolban Abad, Fariborz Ahmadi

Abstract:

Optimization in manufacture is a method to use limited resources to obtain the best performance and reduce waste. In this paper a new algorithm based on eurygaster life is introduced to obtain a plane in which task order and completion time of resources are defined. Evaluation results show our approach has less make span when the resources are allocated with some products in comparison to genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, NP-Hard problems, production scheduling

Procedia PDF Downloads 354

Authors: Shu-Bo Yang, Wei Wu, Yuan-Heng Liu

Abstract:

This research aims to design a heat-exchanger type of methanol reformer coupled with a preheating design in gPROMS® environment. The endothermic methanol steam reforming reaction (MSR) and the exothermic preferential oxidation reaction (PROX) occur in the inner tube and the outer tube of the reformer, respectively. The effective heat transfer manner between the inner and outer tubes is investigated. It is verified that the countercurrent-flow type reformer provides the higher hydrogen yield than the cocurrent-flow type. Since the hot spot temperature appears in the outer tube, an improved scheme is proposed to suppress the hot spot temperature by splitting the excess air flowing into two sites. Finally, an optimization algorithm for maximizing the hydrogen yield is employed to determine optimal operating conditions.

Keywords: methanol reformer, methanol steam reforming, optimization, simulation

Procedia PDF Downloads 311

Authors: Sheetal Kumar Parwar, J. Deb Barma, A. Majumder

Abstract:

Submerged arc welding is a very complex process. It is a very efficient and high performance welding process. In this present study an attempt have been done to reduce the welding distortion by increased amount of oxide flux through TiO2 in submerged arc welding process. Care has been taken to avoid the excessiveness of the adding agent for attainment of significant results. Data Envelopment Analysis (DEA) based BAT algorithm is used for the parametric optimization purpose in which DEA Data Envelopment Analysis is used to convert multi response parameters into a single response parameter. The present study also helps to know the effectiveness of the addition of TiO2 in active flux during submerged arc welding process.

Keywords: BAT algorithm, design of experiment, optimization, submerged arc welding

Procedia PDF Downloads 610

Authors: Elsayed Ahmed Elsayed, Azza Noor El-Deen, Mohamed A. Farid, Mohamed A. Wadaan

Abstract:

Recently, a great attention has been paid to the use of dietary carbohydrates as prebiotic functional foods. Among the new commercially available products, fructooligosaccharides (FOS), which are microbial produced from sucrose, have attracted special interest due to their valuable properties and, thus, have a great economic potential for the sugar industrial branch. They are non-cariogenic sweeteners of low caloric value, as they are not hydrolyzed by the gastro-intestinal enzymes, promoting selectively the growth of the bifidobacteria in the colon, helping to eliminate the harmful microbial species to human and animal health and preventing colon cancer. FOS has been also found to reduce cholesterol, phospholipids and triglyceride levels in blood. FOS has been mainly produced by microbial fructosyltransferase (FTase) enzymes. The present work outlines bioprocess optimization for different cultivation parameters affecting the production of FTase by Penicillium aurantiogriseum AUMC 5605. The optimization involves both traditional as well as fractional factorial design approaches. Additionally, the production process will be compared under batch and fed-batch conditions. Finally, the optimized process conditions will be applied to 5-L stirred tank bioreactor cultivations.

Keywords: prebiotics, fructooligosaccharides, optimization, cultivation

Procedia PDF Downloads 363

Authors: Abir Derouiche, Abdesslem Layeb

Abstract:

Association Rule Mining (ARM) is one of the most popular data mining tasks and it is widely used in various areas. The search for association rules is an NP-complete problem that is why metaheuristics have been widely used to solve it. The present paper presents the ARM as an optimization problem and surveys the proposed approaches in the literature based on metaheuristics.

Keywords: Optimization, Metaheuristics, Data Mining, Association rules Mining

Procedia PDF Downloads 136

Authors: Fahad Y. Al-dawish

Abstract:

The current trend by a large number of organizations and individuals to use cloud computing. Many consider it a significant shift in the field of computing. Cloud computing are distributed and parallel systems consisting of a collection of interconnected physical and virtual machines. With increasing request and profit of cloud computing infrastructure, diverse computing processes can be executed on cloud environment. Many organizations and individuals around the world depend on the cloud computing environments infrastructure to carry their applications, platform, and infrastructure. One of the major and essential issues in this environment related to allocating incoming tasks to suitable virtual machine (cloud task scheduling). Cloud task scheduling is classified as optimization problem, and there are several meta-heuristic algorithms have been anticipated to solve and optimize this problem. Good task scheduler should execute its scheduling technique on altering environment and the types of incoming task set. In this research project a cloud task scheduling methodology based on ant colony optimization ACO algorithm, we call it ACO-TS Ant Colony Optimization for Task Scheduling has been proposed and compared with different scheduling algorithms (Random, First Come First Serve FCFS, and Fastest Processor to the Largest Task First FPLTF). Ant Colony Optimization (ACO) is random optimization search method that will be used for assigning incoming tasks to available virtual machines VMs. The main role of proposed algorithm is to minimizing the makespan of certain tasks set and maximizing resource utilization by balance the load among virtual machines. The proposed scheduling algorithm was evaluated by using Cloudsim toolkit framework. Finally after analyzing and evaluating the performance of experimental results we find that the proposed algorithm ACO-TS perform better than Random, FCFS, and FPLTF algorithms in each of the makespaan and resource utilization.

Keywords: cloud Task scheduling, ant colony optimization (ACO), cloudsim, cloud computing

Procedia PDF Downloads 398

Authors: Ibrahim Aydogdu, Alper Akin

Abstract:

In this study, the development of minimizing the cost and the CO2 emission of the RC retaining wall design has been performed by Biogeography Based Optimization (BBO) algorithm. This has been achieved by developing computer programs utilizing BBO algorithm which minimize the cost and the CO2 emission of the RC retaining walls. Objective functions of the optimization problem are defined as the minimized cost, the CO2 emission and weighted aggregate of the cost and the CO2 functions of the RC retaining walls. In the formulation of the optimum design problem, the height and thickness of the stem, the length of the toe projection, the thickness of the stem at base level, the length and thickness of the base, the depth and thickness of the key, the distance from the toe to the key, the number and diameter of the reinforcement bars are treated as design variables. In the formulation of the optimization problem, flexural and shear strength constraints and minimum/maximum limitations for the reinforcement bar areas are derived from American Concrete Institute (ACI 318-14) design code. Moreover, the development length conditions for suitable detailing of reinforcement are treated as a constraint. The obtained optimum designs must satisfy the factor of safety for failure modes (overturning, sliding and bearing), strength, serviceability and other required limitations to attain practically acceptable shapes. To demonstrate the efficiency and robustness of the presented BBO algorithm, the optimum design example for retaining walls is presented and the results are compared to the previously obtained results available in the literature.

Keywords: bio geography, meta-heuristic search, optimization, retaining wall

Procedia PDF Downloads 378

Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

Abstract:

A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

Procedia PDF Downloads 123