Search results for: optimal estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2576

Search results for: optimal estimation

596 A new Heuristic Algorithm for the Dynamic Facility Layout Problem with Budget Constraint

Authors: Parham Azimi, Hamid Reza Charmchi

Abstract:

In this research, we have developed a new efficient heuristic algorithm for the dynamic facility layout problem with budget constraint (DFLPB). This heuristic algorithm combines two mathematical programming methods such as discrete event simulation and linear integer programming (IP) to obtain a near optimum solution. In the proposed algorithm, the non-linear model of the DFLP has been changed to a pure integer programming (PIP) model. Then, the optimal solution of the PIP model has been used in a simulation model that has been designed in a similar manner as the DFLP for determining the probability of assigning a facility to a location. After a sufficient number of runs, the simulation model obtains near optimum solutions. Finally, to verify the performance of the algorithm, several test problems have been solved. The results show that the proposed algorithm is more efficient in terms of speed and accuracy than other heuristic algorithms presented in previous works found in the literature.

Keywords: Budget constraint, Dynamic facility layout problem, Integer programming, Simulation

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595 Optimization of Growth Conditions for Acidic Protease Production from Rhizopus oligosporus through Solid State Fermentation of Sunflower Meal

Authors: Abdul Rauf, Muhammad Irfan, Muhammad Nadeem, Ishtiaq Ahmed, Hafiz Muhammad Nasir Iqbal

Abstract:

Rhizopus oligosporus was used in the present study for the production of protease enzyme under SSF. Sunflower meal was used as by-product of oil industry incorporated with organic salts was employed for the production of protease enzyme. The main purpose of the present was to study different parameters of protease productivity, its yields and to optimize basal fermentation conditions. The optimal conditions found for protease production using sunflower meal as a substrate in the present study were inoculum size (1%), substrate (Sunflower meal), substrate concentration (20 g), pH (3), cultivation period (72 h), incubation temperature (35oC), substrate to diluent-s ratio (1:2) and tween 81 (1 mL). The maximum production of protease in the presence of cheaper substrate at low concentration and stability at acidic pH, these characteristics make the strain and its enzymes useful in different industry.

Keywords: Acidic protease, Rhizopus oligosporus, Mediaoptimization, Solid state Fermentation

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594 The Scale of Farms and Development Perspectives in Georgia

Authors: M. Chavleishvili, E. Kharaishvili, G. Erkomaishvili

Abstract:

The article presents the development trends of farms, estimates on the optimal scope of farming, as well as the experience of local and foreign countries in this area. As well, the advantages of small and large farms are discussed; herewith, the scales of farms are compared to the local reality. The study analyzes the results of farm operations and the possibilities of diversification of farms. The indicators of an effective use of land resources and land fragmentation are measured; also, a comparative analysis with other countries is presented, in particular, the measurements of agricultural lands for farming, as well as the indicators of population ensuring. The conducted research shows that most of the farms in Georgia are small and their development is at the initial stage, which outlines that the country has a high resource potential to increase the scale of the farming industry and its full integration into market relations. On the basis of the obtained results, according to the research on the scale of farming in Georgia and the identification of hampering factors of farming development, the conclusions are presented and the relevant recommendations are suggested.

Keywords: Farm cooperatives, farms, farm scale, land fragmentation, small and large farms.

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593 Quantitative Genetics Researches on Milk Protein Systems of Romanian Grey Steppe Breed

Authors: V. Maciuc, Şt. Creangă, I. Gîlcă, V. Ujică

Abstract:

The paper makes part from a complex research project on Romanian Grey Steppe, a unique breed in terms of biological and cultural-historical importance, on the verge of extinction and which has been included in a preservation programme of genetic resources from Romania. The study of genetic polymorphism of protean fractions, especially kappa-casein, and the genotype relations of these lactoproteins with some quantitative and qualitative features of milk yield represents a current theme and a novelty for this breed. In the estimation of the genetic parameters we used R.E.M.L. (Restricted Maximum Likelihood) method. The main lactoprotein from milk, kappa - casein (K-cz), characterized in the specialized literature as a feature having a high degree of hereditary transmission, behaves as such in the nucleus under study, a value also confirmed by the heritability coefficient (h2 = 0.57 %). We must mention the medium values for milk and fat quantity (h2=0.26, 0.29 %) and the fat and protein percentage from milk having a high hereditary influence h2 = 0.71 - 0.63 %. Correlations between kappa-casein and the milk quantity are negative and strong. Between kappa-casein and other qualitative features of milk (fat content 0.58-0.67 % and protein content 0.77- 0.87%), there are positive and very strong correlations. At the same time, between kappa-casein and β casein (β-cz), β lactoglobulin (β- lg) respectively, correlations are positive having high values (0.37 – 0.45 %), indicating the same causes and determining factors for the two groups of features.

Keywords: breed, genetic preservation, lactoproteins, Romanian Grey Steppe

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592 An Investigation on Designing and Enhancing the Performance of H-Darrieus Wind Turbine of 10 kW at the Medium Range of Wind Speed in Vietnam

Authors: Ich Long Ngo, Dinh Tai Dang, Ngoc Tu Nguyen, Minh Duc Nguyen

Abstract:

This paper describes an investigation on designing and enhancing the performance of H-Darrieus Wind Turbine (HDWT) of 10 kW at the medium wind speed. The aerodynamic characteristics of this turbine were investigated by both theoretical and numerical approaches. The optimal design procedure was first proposed to enhance the power coefficient under various effects, such as airfoil type, number of blades, solidity, aspect ratio, and tip speed ratio. As a result, the overall design of the 10 kW HDWT was well achieved, and the power characteristic of this turbine was found by numerical approach. Additionally, the maximum power coefficient predicted is up to 0.41 at the tip speed ratio of 3.7 and wind speed of 8 m/s. Particularly, a generalized correlation of power coefficient with tip speed ratio and wind speed is first proposed. These results obtained are very useful for enhancing the performance of the HDWTs placed in a country with high wind power potential like Vietnam.

Keywords: Computational Fluid Dynamics, double multiple stream tube, H-Darrieus wind turbine, renewable energy.

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591 Estimation of Thermal Conductivity of Nanofluids Using MD-Stochastic Simulation Based Approach

Authors: Sujoy Das, M. M. Ghosh

Abstract:

The thermal conductivity of a fluid can be significantly enhanced by dispersing nano-sized particles in it, and the resultant fluid is termed as "nanofluid". A theoretical model for estimating the thermal conductivity of a nanofluid has been proposed here. It is based on the mechanism that evenly dispersed nanoparticles within a nanofluid undergo Brownian motion in course of which the nanoparticles repeatedly collide with the heat source. During each collision a rapid heat transfer occurs owing to the solidsolid contact. Molecular dynamics (MD) simulation of the collision of nanoparticles with the heat source has shown that there is a pulselike pick up of heat by the nanoparticles within 20-100 ps, the extent of which depends not only on thermal conductivity of the nanoparticles, but also on the elastic and other physical properties of the nanoparticle. After the collision the nanoparticles undergo Brownian motion in the base fluid and release the excess heat to the surrounding base fluid within 2-10 ms. The Brownian motion and associated temperature variation of the nanoparticles have been modeled by stochastic analysis. Repeated occurrence of these events by the suspended nanoparticles significantly contributes to the characteristic thermal conductivity of the nanofluids, which has been estimated by the present model for a ethylene glycol based nanofluid containing Cu-nanoparticles of size ranging from 8 to 20 nm, with Gaussian size distribution. The prediction of the present model has shown a reasonable agreement with the experimental data available in literature.

Keywords: Brownian dynamics, Molecular dynamics, Nanofluid, Thermal conductivity.

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590 Non-Sensitive Solutions in Multi-Objective Optimization of a Solar Photovoltaic/Thermal(PV/T) Air Collector

Authors: F. Sarhaddi, S. Farahat, M .A. Alavi, F. Sobhnamayan

Abstract:

In this paper, an attempt has been made to obtain nonsensitive solutions in the multi-objective optimization of a photovoltaic/thermal (PV/T) air collector. The selected objective functions are overall energy efficiency and exergy efficiency. Improved thermal, electrical and exergy models are used to calculate the thermal and electrical parameters, overall energy efficiency, exergy components and exergy efficiency of a typical PV/T air collector. A computer simulation program is also developed. The results of numerical simulation are in good agreement with the experimental measurements noted in the previous literature. Finally, multi-objective optimization has been carried out under given climatic, operating and design parameters. The optimized ranges of inlet air velocity, duct depth and the objective functions in optimal Pareto front have been obtained. Furthermore, non-sensitive solutions from energy or exergy point of view in the results of multi-objective optimization have been shown.

Keywords: Solar photovoltaic thermal (PV/T) air collector, Overall energy efficiency, Exergy efficiency, Multi-objectiveoptimization, Sensitivity analysis.

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589 Selection of Pichia kudriavzevii Strain for the Production of Single-Cell Protein from Cassava Processing Waste

Authors: Phakamas Rachamontree, Theerawut Phusantisampan, Natthakorn Woravutthikul, Peerapong Pornwongthong, Malinee Sriariyanun

Abstract:

A total of 115 yeast strains isolated from local cassava processing wastes were measured for crude protein content. Among these strains, the strain MSY-2 possessed the highest protein concentration (>3.5 mg protein/mL). By using molecular identification tools, it was identified to be a strain of Pichia kudriavzevii based on similarity of D1/D2 domain of 26S rDNA region. In this study, to optimize the protein production by MSY-2 strain, Response Surface Methodology (RSM) was applied. The tested parameters were the carbon content, nitrogen content, and incubation time. Here, the value of regression coefficient (R2) = 0.7194 could be explained by the model which is high to support the significance of the model. Under the optimal condition, the protein content was produced up to 3.77 g per L of the culture and MSY-2 strain contains 66.8 g protein per 100 g of cell dry weight. These results revealed the plausibility of applying the novel strain of yeast in single-cell protein production.

Keywords: Single cell protein, response surface methodology, yeast, cassava processing waste.

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588 Deep Reinforcement Learning for Optimal Decision-making in Supply Chains

Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol

Abstract:

We propose the use of Reinforcement Learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making make it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and a statistical analysis of the results. We study generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.

Keywords: Inventory Management, Reinforcement Learning, Supply Chain Optimization, Uncertainty.

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587 Process Optimisation for Internal Cylindrical Rough Turning of Nickel Alloy 625 Weld Overlay

Authors: Lydia Chan, Islam Shyha, Dale Dreyer, John Hamilton, Phil Hackney

Abstract:

Nickel-based superalloys are generally known to be difficult to cut due to their strength, low thermal conductivity, and high work hardening tendency. Superalloy such as alloy 625 is often used in the oil and gas industry as a surfacing material to provide wear and corrosion resistance to components. The material is typically applied onto a metallic substrate through weld overlay cladding, an arc welding technique. Cladded surfaces are always rugged and carry a tough skin; this creates further difficulties to the machining process. The present work utilised design of experiment to optimise the internal cylindrical rough turning for weld overlay surfaces. An L27 orthogonal array was used to assess effects of the four selected key process variables: cutting insert, depth of cut, feed rate, and cutting speed. The optimal cutting conditions were determined based on productivity and the level of tool wear.

Keywords: Cylindrical turning, nickel superalloy, turning of overlay, weld overlay.

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586 Statistical Description of Counterpoise Effective Length Based On Regressive Formulas

Authors: Petar Sarajcev, Josip Vasilj, Damir Jakus

Abstract:

This paper presents a novel statistical description of the counterpoise effective length due to lightning surges, where the (impulse) effective length had been obtained by means of regressive formulas applied to the transient simulation results. The effective length is described in terms of a statistical distribution function, from which median, mean, variance, and other parameters of interest could be readily obtained. The influence of lightning current amplitude, lightning front duration, and soil resistivity on the effective length has been accounted for, assuming statistical nature of these parameters. A method for determining the optimal counterpoise length, in terms of the statistical impulse effective length, is also presented. It is based on estimating the number of dangerous events associated with lightning strikes. Proposed statistical description and the associated method provide valuable information which could aid the design engineer in optimising physical lengths of counterpoises in different grounding arrangements and soil resistivity situations.

Keywords: Counterpoise, Grounding conductor, Effective length, Lightning, Monte Carlo method, Statistical distribution.

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585 Machine Learning in Production Systems Design Using Genetic Algorithms

Authors: Abu Qudeiri Jaber, Yamamoto Hidehiko Rizauddin Ramli

Abstract:

To create a solution for a specific problem in machine learning, the solution is constructed from the data or by use a search method. Genetic algorithms are a model of machine learning that can be used to find nearest optimal solution. While the great advantage of genetic algorithms is the fact that they find a solution through evolution, this is also the biggest disadvantage. Evolution is inductive, in nature life does not evolve towards a good solution but it evolves away from bad circumstances. This can cause a species to evolve into an evolutionary dead end. In order to reduce the effect of this disadvantage we propose a new a learning tool (criteria) which can be included into the genetic algorithms generations to compare the previous population and the current population and then decide whether is effective to continue with the previous population or the current population, the proposed learning tool is called as Keeping Efficient Population (KEP). We applied a GA based on KEP to the production line layout problem, as a result KEP keep the evaluation direction increases and stops any deviation in the evaluation.

Keywords: Genetic algorithms, Layout problem, Machinelearning, Production system.

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584 Improving Location Management in Mobile IPv4 Networks

Authors: Haidar Safa, Hassan Artail, Ahmad Mehio, Hicham Zahr, Ziad Matragi

Abstract:

The Mobile IP Standard has been developed to support mobility over the Internet. This standard contains several drawbacks as in the cases where packets are routed via sub-optimal paths and significant amount of signaling messages is generated due to the home registration procedure which keeps the network aware of the current location of the mobile nodes. Recently, a dynamic hierarchical mobility management strategy for mobile IP networks (DHMIP) has been proposed to reduce home registrations costs. However, this strategy induces a packet delivery delay and increases the risk of packet loss. In this paper, we propose an enhanced version of the dynamic hierarchical strategy that reduces the packet delivery delay and minimizes the risk of packet loss. Preliminary results obtained from simulations are promising. They show that the enhanced version outperforms the original dynamic hierarchical mobility management strategy version.

Keywords: Location management, Mobile IP (MIP), Home Agent, Foreign Agent.

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583 Discrimination of Alcoholic Subjects using Second Order Autoregressive Modelling of Brain Signals Evoked during Visual Stimulus Perception

Authors: Ramaswamy Palaniappan

Abstract:

In this paper, a second order autoregressive (AR) model is proposed to discriminate alcoholics using single trial gamma band Visual Evoked Potential (VEP) signals using 3 different classifiers: Simplified Fuzzy ARTMAP (SFA) neural network (NN), Multilayer-perceptron-backpropagation (MLP-BP) NN and Linear Discriminant (LD). Electroencephalogram (EEG) signals were recorded from alcoholic and control subjects during the presentation of visuals from Snodgrass and Vanderwart picture set. Single trial VEP signals were extracted from EEG signals using Elliptic filtering in the gamma band spectral range. A second order AR model was used as gamma band VEP exhibits pseudo-periodic behaviour and second order AR is optimal to represent this behaviour. This circumvents the requirement of having to use some criteria to choose the correct order. The averaged discrimination errors of 2.6%, 2.8% and 11.9% were given by LD, MLP-BP and SFA classifiers. The high LD discrimination results show the validity of the proposed method to discriminate between alcoholic subjects.

Keywords: Linear Discriminant, Neural Network, VisualEvoked Potential.

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582 Robust Power System Stabilizer Design Using Particle Swarm Optimization Technique

Authors: Sidhartha Panda, N. P. Padhy

Abstract:

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to design a robust power system stabilizer (PSS). The design problem of the proposed controller is formulated as an optimization problem and PSO is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. Further, all the simulations results are compared with a conventionally designed power system stabilizer to show the superiority of the proposed design approach.

Keywords: Particle swarm optimization, power system stabilizer, low frequency oscillations, power system stability.

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581 ORPP with MAIEP Based Technique for Loadability Enhancement

Authors: Norziana Aminudin, Titik Khawa Abdul Rahman, Ismail Musirin

Abstract:

One of the factors to maintain system survivability is the adequate reactive power support to the system. Lack of reactive power support may cause undesirable voltage decay leading to total system instability. Thus, appropriate reactive power support scheme should be arranged in order to maintain system stability. The strength of a system capacity is normally denoted as system loadability. This paper presents the enhancement of system loadability through optimal reactive power planning technique using a newly developed optimization technique, termed as Multiagent Immune Evolutionary Programming (MAIEP). The concept of MAIEP is developed based on the combination of Multiagent System (MAS), Artificial Immune System (AIS) and Evolutionary Programming (EP). In realizing the effectiveness of the proposed technique, validation is conducted on the IEEE-26-Bus Reliability Test System. The results obtained from pre-optimization and post-optimization process were compared which eventually revealed the merit of MAIEP.

Keywords: Load margin, MAIEP, Maximum loading point, ORPP.

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580 Secure Resource Selection in Computational Grid Based on Quantitative Execution Trust

Authors: G.Kavitha, V.Sankaranarayanan

Abstract:

Grid computing provides a virtual framework for controlled sharing of resources across institutional boundaries. Recently, trust has been recognised as an important factor for selection of optimal resources in a grid. We introduce a new method that provides a quantitative trust value, based on the past interactions and present environment characteristics. This quantitative trust value is used to select a suitable resource for a job and eliminates run time failures arising from incompatible user-resource pairs. The proposed work will act as a tool to calculate the trust values of the various components of the grid and there by improves the success rate of the jobs submitted to the resource on the grid. The access to a resource not only depend on the identity and behaviour of the resource but also upon its context of transaction, time of transaction, connectivity bandwidth, availability of the resource and load on the resource. The quality of the recommender is also evaluated based on the accuracy of the feedback provided about a resource. The jobs are submitted for execution to the selected resource after finding the overall trust value of the resource. The overall trust value is computed with respect to the subjective and objective parameters.

Keywords: access control, feedback, grid computing, reputation, security, trust, trust parameter.

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579 Optimal Water Conservation in a Mechanical Cooling Tower Operations

Authors: M. Boumaza, Y. Bakhabkhi

Abstract:

Water recycling represents an important challenge for many countries, in particular in countries where this natural resource is rare. On the other hand, in many operations, water is used as a cooling medium, as a high proportion of water consumed in industry is used for cooling purposes. Generally this water is rejected directly to the nature. This reject will cause serious environment damages as well as an important waste of this precious element.. On way to solve these problems is to reuse and recycle this warm water, through the use of natural cooling medium, such as air in a heat exchanger unit, known as a cooling tower. A poor performance, design or reliability of cooling towers will result in lower flow rate of cooling water an increase in the evaporation of water, an hence losses of water and energy. This paper which presents an experimental investigate of thermal and hydraulic performances of a mechanical cooling tower, enables to show that the water evaporation rate, Mev, increases with an increase in the air and water flow rates, as well as inlet water temperature and for fixed air flow rates, the pressure drop (ΔPw/Z) increases with increasing , L, due to the hydrodynamic behavior of the air/water flow.

Keywords: water, recycle, performance, cooling tower

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578 A Robust Optimization Model for the Single-Depot Capacitated Location-Routing Problem

Authors: Abdolsalam Ghaderi

Abstract:

In this paper, the single-depot capacitated location-routing problem under uncertainty is presented. The problem aims to find the optimal location of a single depot and the routing of vehicles to serve the customers when the parameters may change under different circumstances. This problem has many applications, especially in the area of supply chain management and distribution systems. To get closer to real-world situations, travel time of vehicles, the fixed cost of vehicles usage and customers’ demand are considered as a source of uncertainty. A combined approach including robust optimization and stochastic programming was presented to deal with the uncertainty in the problem at hand. For this purpose, a mixed integer programming model is developed and a heuristic algorithm based on Variable Neighborhood Search(VNS) is presented to solve the model. Finally, the computational results are presented and future research directions are discussed.

Keywords: Location-routing problem, robust optimization, Stochastic Programming, variable neighborhood search.

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577 A Study on the Waterfront Scales around Small Rivers

Authors: Gwang-Soon Lim, Jae-One Jung, Dae-HeeKim, Hong-SeokKim

Abstract:

The purpose of this study was to suggest some optimal waterfront scales around small rivers by reviewing domestic and foreign survey reports about concept and relevant systems of the ecological cities, analyzing the data collected from a survey about scales and facilities of waterfront green zones around small rivers. The questionnaire survey was conducted by sampling professional designers, developers, the citizens living in the GunpoSanbon district covered by no river system and the citizens living in such districts covered by a river system. The question items were about need, uses, scale and facilities of waterfront in common, and about satisfaction with waterfront in case of citizen groups. In short, most of the subjects in 5 groups preferred 10~20 wide waterfront green zone. And it is judged that the results of this study about uses and facilities of the waterfront green zone and its scales would provide for some basic data useful to future waterfront green zone and urban development plans.

Keywords: Ecological city, Small river, Waterfront zone, Urban development plan

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576 Experimental Investigation on Freeze-Concentration Process Desalting for Highly Saline Brines

Authors: H. Al-Jabli

Abstract:

Using the freeze-melting process for the disposing of high saline brines was the aim of the paper by confirming the performance estimation of the treatment system. A laboratory bench scale freezing technique test unit was designed, constructed, and tested at Doha Research Plant (DRP) in Kuwait. The principal unit operations that have been considered for the laboratory study are: ice crystallization, separation, washing, and melting. The applied process is characterized as “the secondary-refrigerant indirect freezing”, which is utilizing normal freezing concept. The high saline brine was used as definite feed water, i.e. average TDS of 250,000 ppm. Kuwait desalination plants were carried out in the experimental study to measure the performance of the proposed treatment system. Experimental analysis shows that the freeze-melting process is capable of dropping the TDS of the feed water from 249,482 ppm to 56,880 ppm of the freeze-melting process in the two-phase’s course, whereas overall recovery results of the salt passage and salt rejection are 31.11%, 19.05%, and 80.95%, correspondingly. Therefore, the freeze-melting process is encouraging for the proposed application, as it shows on the results, which approves the process capability of reducing a major amount of the dissolved salts of the high saline brine with reasonable sensible recovery. This process might be reasonable with other brine disposal processes.

Keywords: High saline brine, freeze-melting process, ice crystallization, brine disposal process.

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575 Robot Operating System-Based SLAM for a Gazebo-Simulated Turtlebot2 in 2d Indoor Environment with Cartographer Algorithm

Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

Abstract:

The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, Gazebo, Rviz, Turtlebot2, SLAM algorithms, 2d Indoor environment, Cartographer.

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574 Open-Loop Vector Control of Induction Motor with Space Vector Pulse Width Modulation Technique

Authors: Karchung, S. Ruangsinchaiwanich

Abstract:

This paper presents open-loop vector control method of induction motor with space vector pulse width modulation (SVPWM) technique. Normally, the closed loop speed control is preferred and is believed to be more accurate. However, it requires a position sensor to track the rotor position which is not desirable to use it for certain workspace applications. This paper exhibits the performance of three-phase induction motor with the simplest control algorithm without the use of a position sensor nor an estimation block to estimate rotor position for sensorless control. The motor stator currents are measured and are transformed to synchronously rotating (d-q-axis) frame by use of Clarke and Park transformation. The actual control happens in this frame where the measured currents are compared with the reference currents. The error signal is fed to a conventional PI controller, and the corrected d-q voltage is generated. The controller outputs are transformed back to three phase voltages and are fed to SVPWM block which generates PWM signal for the voltage source inverter. The open loop vector control model along with SVPWM algorithm is modeled in MATLAB/Simulink software and is experimented and validated in TMS320F28335 DSP board.

Keywords: Electric drive, induction motor, open-loop vector control, space vector pulse width modulation technique.

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573 Application of STATCOM-SMES Compensator for Power System Dynamic Performance Improvement

Authors: Reza Sedaghati, Mojtaba Hakimzadeh, Mohammad Hasan Raouf, Mostafa Mirzadeh

Abstract:

Nowadays the growth of distributed generation within the bulk power system is feasible by using the optimal control of the transmission lines power flow. Static Synchronous Compensators (STATCOM) is effective for improving voltage stability but it can only exchange reactive power with the power grid. The integration of Superconducting Magnetic Energy Storage (SMES) with a STATCOM can extend the traditional STATCOM capabilities to four-quadrant bulk power system power flow control and providing exchange both the active and reactive power related to the STATCOM with the ac network. This paper shows how the SMES system can be connected to the ac system via the DC bus of a STATCOM and also analyzes how the integration of STATCOM and SMES allows the bus voltage regulation and power oscillation damping (POD) to be achieved simultaneously. The dynamic performance of the integrated STATCOM-SMES is evaluated through simulation by using PSCAD/EMTDC software and the compensation effectiveness of this integrated compensator is shown.

Keywords: STATCOM-SMES compensator, Power Oscillation Damping (POD), stabilizing, signal, voltage.

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572 Maximum Power Point Tracking for Small Scale Wind Turbine Using Multilayer Perceptron Neural Network Implementation without Mechanical Sensor

Authors: Piyangkun Kukutapan, Siridech Boonsang

Abstract:

The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: Maximum power point tracking, multilayer perceptron neural network, optimal duty cycle.

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571 Disaggregating and Forecasting the Total Energy Consumption of a Building: A Case Study of a High Cooling Demand Facility

Authors: Juliana Barcelos Cordeiro, Khashayar Mahani, Farbod Farzan, Mohsen A. Jafari

Abstract:

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Keywords: Energy consumption forecasting, energy efficiency, load disaggregation, pattern recognition approach.

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570 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques

Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

Abstract:

The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial neural network, competitive dynamics, logistic regression, text classification, text mining.

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569 Post-Cracking Behaviour of High Strength Fiber Concrete Prediction and Validation

Authors: Andrejs Krasnikovs, Olga Kononova, Amjad Khabbaz, Edgar Machanovsky, Artur Machanovsky

Abstract:

Fracture process in mechanically loaded steel fiber reinforced high-strength (SFRHSC) concrete is characterized by fibers bridging the crack providing resistance to its opening. Structural SFRHSC fracture model was created; material fracture process was modeled, based on single fiber pull-out laws, which were determined experimentally (for straight fibers, fibers with end hooks (Dramix), and corrugated fibers (Tabix)) as well as obtained numerically ( using FEM simulations). For this purpose experimental program was realized and pull-out force versus pull-out fiber length was obtained (for fibers embedded into concrete at different depth and under different angle). Model predictions were validated by 15x15x60cm prisms 4 point bending tests. Fracture surfaces analysis was realized for broken prisms with the goal to improve elaborated model assumptions. Optimal SFRHSC structures were recognized.

Keywords: crack, fiber concrete, fiber pull-out, strength.

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568 Stability of Stochastic Model Predictive Control for Schrödinger Equation with Finite Approximation

Authors: Tomoaki Hashimoto

Abstract:

Recent technological advance has prompted significant interest in developing the control theory of quantum systems. Following the increasing interest in the control of quantum dynamics, this paper examines the control problem of Schrödinger equation because quantum dynamics is basically governed by Schrödinger equation. From the practical point of view, stochastic disturbances cannot be avoided in the implementation of control method for quantum systems. Thus, we consider here the robust stabilization problem of Schrödinger equation against stochastic disturbances. In this paper, we adopt model predictive control method in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. The objective of this study is to derive the stability criterion for model predictive control of Schrödinger equation under stochastic disturbances.

Keywords: Optimal control, stochastic systems, quantum systems, stabilization.

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567 Mecano-Reliability Approach Applied to a Water Storage Tank Placed on Ground

Authors: Amar Aliche, Hocine Hammoum, Karima Bouzelha, Arezki Ben Abderrahmane

Abstract:

Traditionally, the dimensioning of storage tanks is conducted with a deterministic approach based on partial coefficients of safety. These coefficients are applied to take into account the uncertainties related to hazards on properties of materials used and applied loads. However, the use of these safety factors in the design process does not assure an optimal and reliable solution and can sometimes lead to a lack of robustness of the structure. The reliability theory based on a probabilistic formulation of constructions safety can respond in an adapted manner. It allows constructing a modelling in which uncertain data are represented by random variables, and therefore allows a better appreciation of safety margins with confidence indicators. The work presented in this paper consists of a mecano-reliability analysis of a concrete storage tank placed on ground. The classical method of Monte Carlo simulation is used to evaluate the failure probability of concrete tank by considering the seismic acceleration as random variable.

Keywords: Reliability approach, storage tanks, Monte Carlo simulation, seismic acceleration.

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