Search results for: nonlinear dynamic model

Authors: M. Ömer Timurağaoğlu, Adem Doğangün, Ramazan Livaoğlu

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The evaluation of performance of infilled reinforced concrete (RC) frames has been a significant challenge for engineers. The strengthening of infill walls has been an important concern to enhance the behavior of RC infilled frames. The aim of this study is to investigate the behaviour of retrofitted infill walls of RC frames using finite element analysis. For this purpose, a one storey, one bay infilled and strengthened infilled RC frame which have the same geometry and material properties with the frames tested in laboratory are modelled using different analytical approaches. A fibrous material is used to strengthen infill walls and frame. As a consequence, the results of the finite element analysis were evaluated of whether these analytical approaches estimate the behavior or not. To model the infilled and strengthened infilled RC frames, a finite element program ABAQUS is used. Finally, data obtained from the nonlinear finite element analysis is compared with the experimental results.

Keywords: finite element analysis, infilled RC frames, infill wall, strengthening

Procedia PDF Downloads 529

Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

Procedia PDF Downloads 207

Authors: Marlene Perez Villalpando, Kelly Joel Gurubel Tun

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In this paper, we propose an optimal control strategy for a hydroelectric power plant subject to input disturbances like meteorological phenomena. The engineering characteristics of the system are described by a nonlinear model. The random availability of renewable sources is predicted by a high-order neural network trained with an extended Kalman filter, whereas the power generation is regulated by the optimal control law. The main advantage of the system is the stabilization of the amount of power generated in the plant. A control supervisor maintains stability and availability in hydropower reservoirs water levels for power generation. The proposed approach demonstrated a good performance to stabilize the reservoir level and the power generation along their desired trajectories in the presence of disturbances.

Keywords: hydropower, high order neural network, Kalman filter, optimal control

Procedia PDF Downloads 298

Authors: William Chung

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This paper is to study the use of multiple subproblems in Dantzig-Wolfe decomposition of linear programming (DW-LP). Traditionally, the decomposed LP consists of one LP master problem and one LP subproblem. The master problem and the subproblem is solved alternatively by exchanging the dual prices of the master problem and the proposals of the subproblem until the LP is solved. It is well known that convergence is slow with a long tail of near-optimal solutions (asymptotic convergence). Hence, the performance of DW-LP highly depends upon the number of decomposition steps. If the decomposition steps can be greatly reduced, the performance of DW-LP can be improved significantly. To reduce the number of decomposition steps, one of the methods is to increase the number of proposals from the subproblem to the master problem. To do so, we propose to add a quadratic approximation function to the LP subproblem in order to develop a set of approximate-LP subproblems (multiple subproblems). Consequently, in each decomposition step, multiple subproblems are solved for providing multiple proposals to the master problem. The number of decomposition steps can be reduced greatly. Note that each approximate-LP subproblem is nonlinear programming, and solving the LP subproblem must faster than solving the nonlinear multiple subproblems. Hence, using multiple subproblems in DW-LP is the tradeoff between the number of approximate-LP subproblems being formed and the decomposition steps. In this paper, we derive the corresponding algorithms and provide some simple computational results. Some properties of the resulting algorithms are also given.

Keywords: approximate subproblem, Dantzig-Wolfe decomposition, large-scale models, multiple subproblems

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Authors: Guebli Abdelkader, Regiueg Madani, Sbaa Bouabdellah

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The goals of this study are to find ways to determine the value of dynamic priorities in motor learning between some basic skills in beginner’s basketball (U14), based on skills of shooting and defense against the shooter. Our role is to expose the statistical results in compare & correlation between samples of study in tests skills for the shooting and defense against the shooter. In order to achieve this objective, we have chosen 40 boys in middle school represented in four groups, two controls group’s (CS1, CS2) ,and two experimental groups (ES1: training on skill of shooting, skill of defense against the shooter, ES2: experimental group training on skill of defense against the shooter, skill of shooting). For the statistical analysis, we have chosen (F & T) tests for the statistical differences, and test (R) for the correlation analysis. Based on the analyses statistics, we confirm the importance of classifying priorities of basketball basic skills during the motor learning process. Admit that the benefits of experimental group training are to economics in the time needed for acquiring new motor kinetic skills in basketball. In the priority of ES2 as successful dynamic motor learning method to enhance the basic skills among beginner’s basketball.

Keywords: basic skills, basketball, motor learning, children

Procedia PDF Downloads 170

Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour

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The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.

Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system

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Authors: K. Passbakhsh

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Determination of reinforcement forces is one of the most important and main discussions in designing retaining walls. By determining these forces we refrain from conservative planning. By numerically modeling the reinforced soil retaining walls under dynamic loading reinforcement forces can be calculated. In this study we try to approach the gained forces by pseudo-static method according to FHWA code and gained forces from numerical modeling by finite element method, by selecting seismic horizontal coefficient for different wall height. PLAXIS software was used for numerical analysis. Then the effect of reinforcement stiffness and soil type on reinforcement forces is examined.

Keywords: reinforced soil, PLAXIS, reinforcement forces, retaining walls

Procedia PDF Downloads 358

Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) wherein the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation and Control design team. This paper discusses the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), steady state, transient state

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents modeling of a Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: PV modeling, AC PV Module, datasheet, VI curves irradiance, temperature, MPPT, Matlab/Simulink

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Ali Raza, Rūta Rimašauskienė

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In the current work, the fused deposition modelling (FDM) technique is used to manufacture PLA reinforced with carbon fibre composite structures with two unique layer patterns, 0°\0° and 0°\90°. The purpose of the study is to investigate the dynamic characteristics of each fabricated composite structure. The Macro Fiber Composite (MFC) is embedded with 0°/0° and 0°/90° structures to investigate the effect of an MFC (M8507-P2 type) patch on vibration amplitude suppression under dynamic loading circumstances. First, modal analysis testing was performed using a Polytec 3D laser vibrometer to identify bending mode shapes, natural frequencies, and vibration amplitudes at the corresponding natural frequencies. To determine the stiffness of each structure, several loads were applied at the free end of the structure, and the deformation was recorded using a laser displacement sensor. The findings confirm that a structure with 0°\0° layers pattern was found to have more stiffness compared to a 0°\90° structure. The maximum amplitude suppression in each structure was measured using a laser displacement sensor at the first resonant frequency when the control voltage signal with optimal phase was applied to the MFC. The results confirm that the 0°/0° pattern's structure exhibits a higher displacement reduction than the 0°/90° pattern. Moreover, stiffer structures have been found to perform amplitude suppression more effectively.

Keywords: carbon fibre composite, MFC, modal analysis stiffness, stiffness

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Authors: Ashika Govender

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This study seeks to determine whether Okun’s Law is valid for the South African economy, using time series data for the period 2004 to 2014. The data were accessed from the South African Reserve Bank and Stats SA. The stationarity of the variables was analysed by applying unit root tests via the Augmented Dickey-Fuller test (ADF), the Phillips-Perron (PP) test, and the Kwiatkowski–Phillips–Schmidt–Shin test (KPSS) test. The study used an ordinary least square (OLS) model in analysing the dynamic version of Okun’s law. The Error Correction Model (ECM) was used to analyse the short-run impact of GDP growth on unemployment, as well as the speed of adjustment. The results indicate a short run and long run relationship between unemployment rate and GDP growth rate in period 2004q1-2014q4, suggesting that Okun’s law is valid for the South African economy. With a 1 percent increase in GDP, unemployment can decrease by 0.13 percent, ceteris paribus. The research culminates in important policy recommendations, highlighting the relationship between unemployment and economic growth in the spirit of the National Development Plan.

Keywords: unemployment, economic growth, Okun's law, South Africa

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Authors: Catherine Maware, Olufemi Adetunji

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The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: impact measurement model, lean bundles, lean manufacturing, organizational performance

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Authors: Fikret Yalcinkaya, Hamza Unsal

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To understand how neurons work, it is required to combine experimental studies on neural science with numerical simulations of neuron models in a computer environment. In this regard, the simplicity and applicability of spiking neuron modeling functions have been of great interest in computational neuron science and numerical neuroscience in recent years. Spiking neuron models can be classified by exhibiting various neuronal behaviors, such as spiking and bursting. These classifications are important for researchers working on theoretical neuroscience. In this paper, three different spiking neuron models; Izhikevich, Adaptive Exponential Integrate Fire (AEIF) and Hindmarsh Rose (HR), which are based on first order differential equations, are discussed and compared. First, the physical meanings, derivatives, and differential equations of each model are provided and simulated in the Matlab environment. Then, by selecting appropriate parameters, the models were visually examined in the Matlab environment and it was aimed to demonstrate which model can simulate well-known biological neuron behaviours such as Tonic Spiking, Tonic Bursting, Mixed Mode Firing, Spike Frequency Adaptation, Resonator and Integrator. As a result, the Izhikevich model has been shown to perform Regular Spiking, Continuous Explosion, Intrinsically Bursting, Thalmo Cortical, Low-Threshold Spiking and Resonator. The Adaptive Exponential Integrate Fire model has been able to produce firing patterns such as Regular Ignition, Adaptive Ignition, Initially Explosive Ignition, Regular Explosive Ignition, Delayed Ignition, Delayed Regular Explosive Ignition, Temporary Ignition and Irregular Ignition. The Hindmarsh Rose model showed three different dynamic neuron behaviours; Spike, Burst and Chaotic. From these results, the Izhikevich cell model may be preferred due to its ability to reflect the true behavior of the nerve cell, the ability to produce different types of spikes, and the suitability for use in larger scale brain models. The most important reason for choosing the Adaptive Exponential Integrate Fire model is that it can create rich ignition patterns with fewer parameters. The chaotic behaviours of the Hindmarsh Rose neuron model, like some chaotic systems, is thought to be used in many scientific and engineering applications such as physics, secure communication and signal processing.

Keywords: Izhikevich, adaptive exponential integrate fire, Hindmarsh Rose, biological neuron behaviours, spiking neuron models

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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In this paper, a set of Filipino Phonetically Balanced Word list consisting of 250 words (PBW250) were constructed for a phoneme-level ASR system for the Filipino language. The Entropy Maximization is used to obtain phonological balance in the list. Entropy of phonemes in a word is maximized, providing an optimal balance in each word’s phonological distribution using the Add-Delete Method (PBW algorithm) and is compared to the modified PBW algorithm implemented in a dynamic algorithm approach to obtain optimization. The gained entropy score of 4.2791 and 4.2902 for the PBW and modified algorithm respectively. The PBW250 was recorded by 40 respondents, each with 2 sets data. Recordings from 30 respondents were trained to produce an acoustic model that were tested using recordings from 10 respondents using the HMM Toolkit (HTK). The results of test gave the maximum accuracy rate of 97.77% for a speaker dependent test and 89.36% for a speaker independent test.

Keywords: entropy maximization, Filipino language, Hidden Markov Model, phonetically balanced words, speech recognition

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Authors: Lukas Vierus, Thomas Schuster

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A general framework is examined for dynamic tensor field tomography within an inhomogeneous medium characterized by refraction and absorption, treated as an inverse source problem concerning the associated transport equation. Guided by Fermat’s principle, the Riemannian metric within the specified domain is determined by the medium's refractive index. While considerable literature exists on the inverse problem of reconstructing a tensor field from its longitudinal ray transform within a static Euclidean environment, limited inversion formulas and algorithms are available for general Riemannian metrics and time-varying tensor fields. It is established that tensor field tomography, akin to an inverse source problem for a transport equation, persists in dynamic scenarios. Framing dynamic tensor tomography as an inverse source problem embodies a comprehensive perspective within this domain. Ensuring well-defined forward mappings necessitates establishing existence and uniqueness for the underlying transport equations. However, the bilinear forms of the associated weak formulations fail to meet the coercivity condition. Consequently, recourse to viscosity solutions is taken, demonstrating their unique existence within suitable Sobolev spaces (in the static case) and Sobolev-Bochner spaces (in the dynamic case), under a specific assumption restricting variations in the refractive index. Notably, the adjoint problem can also be reformulated as a transport equation, with analogous results regarding uniqueness. Analytical solutions are expressed as integrals over geodesics, facilitating more efficient evaluation of forward and adjoint operators compared to solving partial differential equations. Certainly, here's the revised sentence in English: Numerical experiments are conducted using a Nesterov-accelerated Landweber method, encompassing various fields, absorption coefficients, and refractive indices, thereby illustrating the enhanced reconstruction achieved through this holistic modeling approach.

Keywords: attenuated refractive dynamic ray transform of tensor fields, geodesics, transport equation, viscosity solutions

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Authors: Huey-Kuo Chen

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Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper.

Keywords: travel choices, B algorithm, entropy maximization, dynamic traffic assignment

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Authors: Y. Yang, Dian Ming Xing, Qiu Hua Du

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Based on the Motorized Momentum Exchange Tether (MMET), with the principle of momentum exchange, the three dimension flexible dynamics of continuous cislunar payloads transferring system (CCPTS) is built by Lagrange method and its numerical solution is solved by Mathematica software. In the derivation precession of potential energy, this paper uses the Tylor expansion method to simplify the Lagrange equation. Furthermore, the tension coming from the centripetal load is considered in the elastic potential energy. The comparison simulation results between the 3D rigid model and 3D flexible model of CCPTS shows that the tether flexibility has important influence on CCPTS’s orbital parameters (such as radius of CCPTS’s COM and the true anomaly) and the tether’s rotational movement, the relative deviation of radius and the true anomaly between the two dynamic models is about 0.00678% and 0.00259%, the relative deviation of the angle of tether-span and local gravity gradient is about 3.55%. Additionally, the external torque has an apparent influence on the tether’s axial vibration.

Keywords: cislunar transfer, dynamics, momentum exchange, tether

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Authors: Andreea Halunga, Chris D. Orme, Takashi Yamagata

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This paper proposes a heteroskedasticity-robust Breusch-Pagan test of the null hypothesis of zero cross-section (or contemporaneous) correlation in linear panel-data models, without necessarily assuming independence of the cross-sections. The procedure allows for either fixed, strictly exogenous and/or lagged dependent regressor variables, as well as quite general forms of both non-normality and heteroskedasticity in the error distribution. The asymptotic validity of the test procedure is predicated on the number of time series observations, T, being large relative to the number of cross-section units, N, in that: (i) either N is fixed as T→∞; or, (ii) N²/T→0, as both T and N diverge, jointly, to infinity. Given this, it is not expected that asymptotic theory would provide an adequate guide to finite sample performance when T/N is "small". Because of this, we also propose and establish asymptotic validity of, a number of wild bootstrap schemes designed to provide improved inference when T/N is small. Across a variety of experimental designs, a Monte Carlo study suggests that the predictions from asymptotic theory do, in fact, provide a good guide to the finite sample behaviour of the test when T is large relative to N. However, when T and N are of similar orders of magnitude, discrepancies between the nominal and empirical significance levels occur as predicted by the first-order asymptotic analysis. On the other hand, for all the experimental designs, the proposed wild bootstrap approximations do improve agreement between nominal and empirical significance levels, when T/N is small, with a recursive-design wild bootstrap scheme performing best, in general, and providing quite close agreement between the nominal and empirical significance levels of the test even when T and N are of similar size. Moreover, in comparison with the wild bootstrap "version" of the original Breusch-Pagan test our experiments indicate that the corresponding version of the heteroskedasticity-robust Breusch-Pagan test appears reliable. As an illustration, the proposed tests are applied to a dynamic growth model for a panel of 20 OECD countries.

Keywords: cross-section correlation, time-series heteroskedasticity, dynamic panel data, heteroskedasticity robust Breusch-Pagan test

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Authors: T. Sahbani, M. Bouteraa, R. Wamkeue

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Wind Turbine are considered to be one of the more efficient system of energy production nowadays, a reason that leads the main industrial companies in wind turbine construction and researchers in over the world to look for better performance and one of the ways for that is the use of the synchronous permanent magnet generator. In this context, this work is about developing an analytical model that could simulate different situation in which the synchronous generator may go through, and of course this model match perfectly with the numerical and experimental model.

Keywords: MATLAB, synchronous permanent magnet generator, wind turbine, analytical model

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Authors: Michal Biały, Konrad Pietrykowski, Rafal Sochaczewski

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The kinematics and dynamics analysis of crank-piston system of aircraft engine. The object of the study was the high power aircraft engine ASz 62-IR. This engine is produced by a Polish company WSK "PZL-KALISZ" S.A.". All analyzes were performed numerically using CAD and CAE environment. Three-dimensional model of the crank-piston system was developed based on real engine located in the Laboratory of Centre of Innovation and Advanced Technologies of Lublin University of Technology. During the development of the model, the technique of reverse engineering - 3D scanning was used. ASz 62-IR engine is characterized by a radial type of crank-piston system. In this system the cylinders are arranged radially around the circle. This crank-piston system consists of a main connecting rod and eight additional connecting rods. In addition, three-dimensional model consists of a piston pins, pistons and piston rings. As a result of the specific engine design, characteristics of the piston individual movement are slightly different from each other. But the model assumes that they are the same during the analysis. Three-dimensional model of the engine was implemented into the MSC Adams software. The environment of MSC Adams allows for multibody simulation of the dynamic phenomena. This determines the state parameters of the moving elements, among which the load or force distribution on each kinematic node can be distinguished. Materials and characteristic materials parameters were adopted on the basis of commonly used materials for engine parts. The mass values of individual elements were adopted on the basis of real engine parts. The piston gas forces were replaced by calculation of pressure variations recorded during engine tests on the engine test bench. The research the changes of forces acting in the individual kinematic pairs of crank-piston system. The model allows to determine the load on the crankshaft main bearings. This gives the possibility for the main supports forces analysis The model allows for testing and simulation of kinematics and dynamics of a radial aircraft engine. This is the first stage of the work, which aims to numerical simulation of vibration of multi-cylinder aircraft engine. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: aircraft engine, CAD, CAE, dynamics, kinematics, MSC Adams, numerical simulation

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Authors: Mohamadreza Hatefi, Malihe Hadadnezhad

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It is well established that jump-landing-related biomechanical deficiencies, such as dynamic knee valgus (DKV), can be improved by using various forms of feedback; However, the effectiveness of these interventions synchronously on athletes' jumping performance remains unknown. Twenty-one recreational athletes with DKV performed countermovement jump (CMJ) and drop vertical jump (DVJ) tasks before and after feedback intervention while the kinematic, force plate and electromyography data of the lower extremity were synchronously captured. The athletes’ jumping performance was calculated by using the reactive strength index-modified (RSIₘₒ𝒹). The athletes at the post-intervention exhibited significantly less hip adduction and more tibial internal rotation during both CMJ and DVJ tasks and maximum knee flexion just during DVJ task. Moreover, athletes exhibited increased time to take-off and consequently decreased RSIₘₒ𝒹 during DVJ task, but no difference was observed in CMJ task. Feedback immediately improved DKV without disturbing the athletes’ jumping height during both tasks, But athletes exhibited increased time to take-off and consequently decreased RSIₘₒ𝒹 only during DVJ task, which suggests that the results may differ according to the nature of jumping task. Nevertheless, the effectiveness of landing-related biomechanical deficiencies improvement on athletes' jumping performance must be investigated in the long-term as a new movement pattern.

Keywords: reactive strength index, feedback, biomechanics, dynamic knee valgus

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Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

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Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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Authors: Nini Johana Marin Rodriguez

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This paper applies DCC, EWMA and OGARCH models to compare the dynamic correlations between exchange rates, oil prices, exchange rates and stock markets to examine the time-varying conditional correlations to the daily oil prices and index returns in relation to the US dollar/local currency for developed (Canada and Mexico) and emerging Latin American markets (Brazil, Chile, Colombia and Peru). Changes in correlation interactions are indicative of structural changes in market linkages with implications to contagion and interdependence. For each pair of stock price-exchange rate and oil price-US dollar/local currency, empirical evidence confirms of a strengthening negative correlation in the last decade. Methodologies suggest only two events have significatively impact in the countries analyzed: global financial crisis and Europe crisis, both events are associated with shifts of correlations to stronger negative level for most of the pairs analyzed. While, the first event has a shifting effect on mainly emerging members, the latter affects developed members. The identification of these relationships provides benefits in risk diversification and inflation targeting.

Keywords: crude oil, dynamic conditional correlation, exchange rates, interdependence, stock prices

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Authors: Hui Hsin Huang

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The downstream manufactures will order their materials from different upstream suppliers to maintain a certain level of the demand. This paper proposes a bivariate model to portray this phenomenon of material demand. We use empirical data to estimate the parameters of model and evaluate the RMSD of model calibration. The results show that the model has better fitness.

Keywords: recency, ordering time, materials demand quantity, multi-source ordering

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Authors: Srinivasan Chandrasekaran, R. Nagavinothini

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Offshore platforms for ultra-deep waters are form-dominant by design; hybrid systems with large flexibility in horizontal plane and high rigidity in vertical plane are preferred due to functional complexities. Offshore triceratops is relatively a new-generation offshore platform, whose deck is partially isolated from the supporting buoyant legs by ball joints. They allow transfer of partial displacements of buoyant legs to the deck but restrain transfer of rotational response. Buoyant legs are in turn taut-moored to the sea bed using pre-tension tethers. Present study will discuss detailed dynamic analysis and preliminary design of the chosen geometric, which is necessary as a proof of validation for such design applications. A detailed numeric analysis of triceratops at 2400 m water depth under random waves is presented. Preliminary design confirms member-level design requirements under various modes of failure. Tether configuration, proposed in the study confirms no pull-out of tethers as stress variation is comparatively lesser than the yield value. Presented study shall aid offshore engineers and contractors to understand suitability of triceratops, in terms of design and dynamic response behaviour.

Keywords: offshore structures, triceratops, random waves, buoyant legs, preliminary design, dynamic analysis

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Authors: A. H. Meysami

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In this paper, the hot compression tests were carried on X45CrNiW189 valve steel (X45) in the temperature range of 1000–1200°C and the strain rate range of 0.004–0.5 s^(-1) in order to study the high temperature softening behavior of the steel. For the exact prediction of flow stress, the effective stress - effective strain curves were obtained from experiments under various conditions. On the basis of experimental results, the dynamic recrystallization fraction (DRX), AGS, hot deformation and activation energy behavior were investigated. It was found that the calculated results were in a good agreement with the experimental flow stress and microstructure of the steel for different conditions of hot deformation.

Keywords: X45CrNiW189, valve steel, hot compression test, dynamic recrystallization, hot deformation

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Authors: Paul Han, Jun-Geol Baek

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In the flat panel display industry, the scheduler and dispatching system to meet production target quantities and the deadline of production are the major production management system which controls each facility production order and distribution of WIP (Work in Process). In dispatching system, delivery time is a key factor for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors and a forecasting model of delivery time. Of survival analysis techniques to select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the Accelerated Failure Time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the Mean Square Error (MSE) criteria, the AFT model decreased by 33.8% compared to the existing prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing a delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

Keywords: delivery time, survival analysis, Cox PH model, accelerated failure time model

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Authors: Adel. M. Sharaf, Foad H. Gandoman

Abstract:

Nowadays, Photovoltaic-PV Farms/ Parks and large PV-Smart Grid Interface Schemes are emerging and commonly utilized in Renewable Energy distributed generation. However, PV-hybrid-Dc-Ac Schemes using interface power electronic converters usually has negative impact on power quality and stabilization of modern electrical network under load excursions and network fault conditions in smart grid. Consequently, robust FACTS based interface schemes are required to ensure efficient energy utilization and stabilization of bus voltages as well as limiting switching/fault onrush current condition. FACTS devices are also used in smart grid-Battery Interface and Storage Schemes with PV-Battery Storage hybrid systems as an elegant alternative to renewable energy utilization with backup battery storage for electric utility energy and demand side management to provide needed energy and power capacity under heavy load conditions. The paper presents a robust interface PV-Li-Ion Battery Storage Interface Scheme for Distribution/Utilization Low Voltage Interface using FACTS stabilization enhancement and dynamic maximum PV power tracking controllers. Digital simulation and validation of the proposed scheme is done using MATLAB/Simulink software environment for Low Voltage- Distribution/Utilization system feeding a hybrid Linear-Motorized inrush and nonlinear type loads from a DC-AC Interface VSC-6-pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion Storage Battery.

Keywords: AC FACTS, smart grid, stabilization, PV-battery storage, Switched Filter-Compensation (SFC)

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Authors: Amin Sedighfar, M. R. Moniri

Abstract:

Determination of state of charge (SOC) in today’s world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the SOC estimation algorithm is expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and all of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate. 

Keywords: Kalman filter, neural networks, state-of-charge, VRLA battery

Procedia PDF Downloads 192