Search results for: nonlinear state estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10003

Search results for: nonlinear state estimation

9283 Spatial Distribution of Socio-Economic Factors in Kogi State, Nigeria: Development Issues and Implication(s)

Authors: Yahya A. Sadiq, Grace F. Balogun, Olufemi J. Anjorin

Abstract:

This study analyzed the spatial distribution of socio-economic factors in Kogi state with a view to examining its implications on the development of the state. Consequently, questionnaires were administered on both the selected individual respondents (784) in the state and on the administrative offices (local council offices, 21) to solicit relevant information on the spatial distribution of socio-economic factors in their areas. The collected data were tabulated and analyzed using percentages. The study revealed commerce/trade, education, and health care, etc. as the major socio-economic factors in the state but with marked variation/imbalance in their spatial distribution across the study area. The rural-based local government areas have far less of such important facilities. Conclusively, it was recommended that there is need for socio-economic transformation of living conditions of people in the study area especially by positively redistributing local political power and the resources that are abound in the state will be felt by everybody including the commoners.

Keywords: development, local government areas (LGAs), spatial distribution, socio-economic factors

Procedia PDF Downloads 392
9282 QCARNet: Networks for Quality-Adaptive Compression Artifact

Authors: Seung Ho Park, Young Su Moon, Nam Ik Cho

Abstract:

We propose a convolution neural network (CNN) for quality adaptive compression artifact reduction named QCARNet. The proposed method is different from the existing discriminative models that learn a specific model at a certain quality level. The method is composed of a quality estimation CNN (QECNN) and a compression artifact reduction CNN (CARCNN), which are two functionally separate CNNs. By connecting the QECNN and CARCNN, each CARCNN layer is able to adaptively reduce compression artifacts and preserve details depending on the estimated quality level map generated by the QECNN. We experimentally demonstrate that the proposed method achieves better performance compared to other state-of-the-art blind compression artifact reduction methods.

Keywords: compression artifact reduction, deblocking, image denoising, image restoration

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9281 Steady State Modeling and Simulation of an Industrial Steam Boiler

Authors: Amina Lyria Deghal Cheridi, Abla Chaker, Ahcene Loubar

Abstract:

Relap5 system code is one among powerful tools, which is used in the area of design and safety evaluation. This work aims to simulate the behavior of a radiant steam boiler at the steady-state conditions using Relap5 code system. To perform this study, a detailed Relap5 model is built including all the parts of the steam boiler. The control and regulation systems are also considered. To reproduce the most important parameters and phenomena with an acceptable accuracy and fidelity, a strong qualification work is undertaken concerning the facility nodalization. It consists of making a comparison between the code results and the plant available data in steady-state operation mode. Therefore, the model qualification results at the steady-state are in good agreement with the steam boiler experimental data. The steam boiler Relap5 model has proved satisfactory; and the model was capable of predicting the main thermal-hydraulic steady-state conditions of the steam boiler.

Keywords: industrial steam boiler, model qualification, natural circulation, relap5/mod3.2, steady state simulation

Procedia PDF Downloads 261
9280 Arbitrarily Shaped Blur Kernel Estimation for Single Image Blind Deblurring

Authors: Aftab Khan, Ashfaq Khan

Abstract:

The research paper focuses on an interesting challenge faced in Blind Image Deblurring (BID). It relates to the estimation of arbitrarily shaped or non-parametric Point Spread Functions (PSFs) of motion blur caused by camera handshake. These PSFs exhibit much more complex shapes than their parametric counterparts and deblurring in this case requires intricate ways to estimate the blur and effectively remove it. This research work introduces a novel blind deblurring scheme visualized for deblurring images corrupted by arbitrarily shaped PSFs. It is based on Genetic Algorithm (GA) and utilises the Blind/Reference-less Image Spatial QUality Evaluator (BRISQUE) measure as the fitness function for arbitrarily shaped PSF estimation. The proposed BID scheme has been compared with other single image motion deblurring schemes as benchmark. Validation has been carried out on various blurred images. Results of both benchmark and real images are presented. Non-reference image quality measures were used to quantify the deblurring results. For benchmark images, the proposed BID scheme using BRISQUE converges in close vicinity of the original blurring functions.

Keywords: blind deconvolution, blind image deblurring, genetic algorithm, image restoration, image quality measures

Procedia PDF Downloads 436
9279 Simplified Analysis Procedure for Seismic Evaluation of Tall Building at Structure and Component Level

Authors: Tahir Mehmood, Pennung Warnitchai

Abstract:

Simplified static analysis procedures such Nonlinear Static Procedure (NSP) are gaining popularity for the seismic evaluation of buildings. However, these simplified procedures accounts only for the seismic responses of the fundamental vibration mode of the structure. Some other procedures which can take into account the higher modes of vibration, lack in accuracy to determine the component responses. Hence, such procedures are not suitable for evaluating the structures where many vibration modes may participate significantly or where component responses are needed to be evaluated. Moreover, these procedures were found to either computationally expensive or tedious to obtain individual component responses. In this paper, a simplified but accurate procedure is studied. It is called the Uncoupled Modal Response History Analysis (UMRHA) procedure. In this procedure, the nonlinear response of each vibration mode is first computed, and they are later on combined into the total response of the structure. The responses of four tall buildings are computed by this simplified UMRHA procedure and compared with those obtained from the NLRHA procedure. The comparison shows that the UMRHA procedure is able to accurately compute the global responses, i.e., story shears and story overturning moments, floor accelerations and inter-story drifts as well as the component level responses of these tall buildings with heights varying from 20 to 44 stories. The required computational effort is also extremely low compared to that of the Nonlinear Response History Analysis (NLRHA) procedure.

Keywords: higher mode effects, seismic evaluation procedure, tall buildings, component responses

Procedia PDF Downloads 338
9278 Mixed Frequency Excitation of an Electrostatically Actuated Resonator

Authors: Abdallah H. Ramini, Alwathiqbellah I. Ibrahim, Mohammad I. Younis

Abstract:

We investigate experimentally and theoretically the dynamics of a capacitive resonator under mixed frequency excitation of two AC harmonic signals. The resonator is composed of a proof mass suspended by two cantilever beams. Experimental measurements are conducted using a laser Doppler Vibrometer to reveal the interesting dynamics of the system when subjected to two-source excitation. A nonlinear single-degree-of-freedom model is used for the theoretical investigation. The results reveal combination resonances of additive and subtractive type, which are shown to be promising to increase the bandwidth of the resonator near primary resonance frequency. Our results also demonstrate the ability to shift the combination resonances to much lower or much higher frequency ranges. We also demonstrate the dynamic pull-in instability under mixed frequency excitation.

Keywords: electrostatically actuated resonator, multi-frequency excitation, nonlinear dynamics, AC harmonic signals

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9277 Optical Switching Based On Bragg Solitons in A Nonuniform Fiber Bragg Grating

Authors: Abdulatif Abdusalam, Mohamed Shaban

Abstract:

In this paper, we consider the nonlinear pulse propagation through a nonuniform birefringent fiber Bragg grating (FBG) whose index modulation depth varies along the propagation direction. Here, the pulse propagation is governed by the nonlinear birefringent coupled mode (NLBCM) equations. To form the Bragg soliton outside the photonic bandgap (PBG), the NLBCM equations are reduced to the well known NLS type equation by multiple scale analysis. As we consider the pulse propagation in a nonuniform FBG, the pulse propagation outside the PBG is governed by inhomogeneous NLS (INLS) rather than NLS. We, then, discuss the formation of soliton in the FBG known as Bragg soliton whose central frequency lies outside but close to the PBG of the grating structure. Further, we discuss Bragg soliton compression due to a delicate balance between the SPM and the varying grating induced dispersion. In addition, Bragg soliton collision, Bragg soliton switching and possible logic gates have also been discussed.

Keywords: Bragg grating, non uniform fiber, non linear pulse

Procedia PDF Downloads 306
9276 Automating and Optimization Monitoring Prognostics for Rolling Bearing

Authors: H. Hotait, X. Chiementin, L. Rasolofondraibe

Abstract:

This paper presents a continuous work to detect the abnormal state in the rolling bearing by studying the vibration signature analysis and calculation of the remaining useful life. To achieve these aims, two methods; the first method is the classification to detect the degradation state by the AOM-OPTICS (Acousto-Optic Modulator) method. The second one is the prediction of the degradation state using least-squares support vector regression and then compared with the linear degradation model. An experimental investigation on ball-bearing was conducted to see the effectiveness of the used method by applying the acquired vibration signals. The proposed model for predicting the state of bearing gives us accurate results with the experimental and numerical data.

Keywords: bearings, automatization, optimization, prognosis, classification, defect detection

Procedia PDF Downloads 111
9275 Modeling and System Identification of a Variable Excited Linear Direct Drive

Authors: Heiko Weiß, Andreas Meister, Christoph Ament, Nils Dreifke

Abstract:

Linear actuators are deployed in a wide range of applications. This paper presents the modeling and system identification of a variable excited linear direct drive (LDD). The LDD is designed based on linear hybrid stepper technology exhibiting the characteristic tooth structure of mover and stator. A three-phase topology provides the thrust force caused by alternating strengthening and weakening of the flux of the legs. To achieve best possible synchronous operation, the phases are commutated sinusoidal. Despite the fact that these LDDs provide high dynamics and drive forces, noise emission limits their operation in calm workspaces. To overcome this drawback an additional excitation of the magnetic circuit is introduced to LDD using additional enabling coils instead of permanent magnets. The new degree of freedom can be used to reduce force variations and related noise by varying the excitation flux that is usually generated by permanent magnets. Hence, an identified simulation model is necessary to analyze the effects of this modification. Especially the force variations must be modeled well in order to reduce them sufficiently. The model can be divided into three parts: the current dynamics, the mechanics and the force functions. These subsystems are described with differential equations or nonlinear analytic functions, respectively. Ordinary nonlinear differential equations are derived and transformed into state space representation. Experiments have been carried out on a test rig to identify the system parameters of the complete model. Static and dynamic simulation based optimizations are utilized for identification. The results are verified in time and frequency domain. Finally, the identified model provides a basis for later design of control strategies to reduce existing force variations.

Keywords: force variations, linear direct drive, modeling and system identification, variable excitation flux

Procedia PDF Downloads 362
9274 Model Order Reduction for Frequency Response and Effect of Order of Method for Matching Condition

Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

Abstract:

In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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9273 Vibroacoustic Modulation with Chirp Signal

Authors: Dong Liu

Abstract:

By sending a high-frequency probe wave and a low-frequency pump wave to a specimen, the vibroacoustic method evaluates the defect’s severity according to the modulation index of the received signal. Many studies experimentally proved the significant sensitivity of the modulation index to the tiny contact type defect. However, it has also been found that the modulation index was highly affected by the frequency of probe or pump waves. Therefore, the chirp signal has been introduced to the VAM method since it can assess multiple frequencies in a relatively short time duration, so the robustness of the VAM method could be enhanced. Consequently, the signal processing method needs to be modified accordingly. Various studies utilized different algorithms or combinations of algorithms for processing the VAM signal method by chirp excitation. These signal process methods were compared and used for processing a VAM signal acquired from the steel samples.

Keywords: vibroacoustic modulation, nonlinear acoustic modulation, nonlinear acoustic NDT&E, signal processing, structural health monitoring

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9272 Genetic Algorithms for Parameter Identification of DC Motor ARMAX Model and Optimal Control

Authors: A. Mansouri, F. Krim

Abstract:

This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.

Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation

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9271 Artificial Neural Network Model Based Setup Period Estimation for Polymer Cutting

Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

Abstract:

The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

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9270 Performance of Stiffened Slender Built up Steel I-Columns

Authors: M. E. Abou-Hashem El Dib, M. K. Swailem, M. M. Metwally, A. I. El Awady

Abstract:

The present work illustrates a parametric study for the effect of stiffeners on the performance of slender built up steel I-columns. To achieve the desired analysis, finite element technique is used to develop nonlinear three-dimensional models representing the investigated columns. The finite element program (ANSYS 13.0) is used as a calculation tool for the necessary nonlinear analysis. A validation of the obtained numerical results is achieved. The considered parameters in the study are the column slenderness ratio and the horizontal stiffener's dimensions as well as the number of stiffeners. The dimensions of the stiffeners considered in the analysis are the stiffener width and the stiffener thickness. Numerical results signify a considerable effect of stiffeners on the performance and failure load of slender built up steel I-columns.

Keywords: columns, local buckling, slender, stiffener, thin walled section

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9269 Modification of Rk Equation of State for Liquid and Vapor of Ammonia by Genetic Algorithm

Authors: S. Mousavian, F. Mousavian, V. Nikkhah Rashidabad

Abstract:

Cubic equations of state like Redlich–Kwong (RK) EOS have been proved to be very reliable tools in the prediction of phase behavior. Despite their good performance in compositional calculations, they usually suffer from weaknesses in the predictions of saturated liquid density. In this research, RK equation was modified. The result of this study shows that modified equation has good agreement with experimental data.

Keywords: equation of state, modification, ammonia, genetic algorithm

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9268 Quantification of the Non-Registered Electrical and Electronic Equipment for Domestic Consumption and Enhancing E-Waste Estimation: A Case Study on TVs in Vietnam

Authors: Ha Phuong Tran, Feng Wang, Jo Dewulf, Hai Trung Huynh, Thomas Schaubroeck

Abstract:

The fast increase and complex components have made waste of electrical and electronic equipment (or e-waste) one of the most problematic waste streams worldwide. Precise information on its size on national, regional and global level has therefore been highlighted as prerequisite to obtain a proper management system. However, this is a very challenging task, especially in developing countries where both formal e-waste management system and necessary statistical data for e-waste estimation, i.e. data on the production, sale and trade of electrical and electronic equipment (EEE), are often lacking. Moreover, there is an inflow of non-registered electronic and electric equipment, which ‘invisibly’ enters the EEE domestic market and then is used for domestic consumption. The non-registration/invisibility and (in most of the case) illicit nature of this flow make it difficult or even impossible to be captured in any statistical system. The e-waste generated from it is thus often uncounted in current e-waste estimation based on statistical market data. Therefore, this study focuses on enhancing e-waste estimation in developing countries and proposing a calculation pathway to quantify the magnitude of the non-registered EEE inflow. An advanced Input-Out Analysis model (i.e. the Sale–Stock–Lifespan model) has been integrated in the calculation procedure. In general, Sale-Stock-Lifespan model assists to improve the quality of input data for modeling (i.e. perform data consolidation to create more accurate lifespan profile, model dynamic lifespan to take into account its changes over time), via which the quality of e-waste estimation can be improved. To demonstrate the above objectives, a case study on televisions (TVs) in Vietnam has been employed. The results show that the amount of waste TVs in Vietnam has increased four times since 2000 till now. This upward trend is expected to continue in the future. In 2035, a total of 9.51 million TVs are predicted to be discarded. Moreover, estimation of non-registered TV inflow shows that it might on average contribute about 15% to the total TVs sold on the Vietnamese market during the whole period of 2002 to 2013. To tackle potential uncertainties associated with estimation models and input data, sensitivity analysis has been applied. The results show that both estimations of waste and non-registered inflow depend on two parameters i.e. number of TVs used in household and the lifespan. Particularly, with a 1% increase in the TV in-use rate, the average market share of non-register inflow in the period 2002-2013 increases 0.95%. However, it decreases from 27% to 15% when the constant unadjusted lifespan is replaced by the dynamic adjusted lifespan. The effect of these two parameters on the amount of waste TV generation for each year is more complex and non-linear over time. To conclude, despite of remaining uncertainty, this study is the first attempt to apply the Sale-Stock-Lifespan model to improve the e-waste estimation in developing countries and to quantify the non-registered EEE inflow to domestic consumption. It therefore can be further improved in future with more knowledge and data.

Keywords: e-waste, non-registered electrical and electronic equipment, TVs, Vietnam

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9267 Using Dynamic Bayesian Networks to Characterize and Predict Job Placement

Authors: Xupin Zhang, Maria Caterina Bramati, Enrest Fokoue

Abstract:

Understanding the career placement of graduates from the university is crucial for both the qualities of education and ultimate satisfaction of students. In this research, we adapt the capabilities of dynamic Bayesian networks to characterize and predict students’ job placement using data from various universities. We also provide elements of the estimation of the indicator (score) of the strength of the network. The research focuses on overall findings as well as specific student groups including international and STEM students and their insight on the career path and what changes need to be made. The derived Bayesian network has the potential to be used as a tool for simulating the career path for students and ultimately helps universities in both academic advising and career counseling.

Keywords: dynamic bayesian networks, indicator estimation, job placement, social networks

Procedia PDF Downloads 363
9266 Application of the Total Least Squares Estimation Method for an Aircraft Aerodynamic Model Identification

Authors: Zaouche Mohamed, Amini Mohamed, Foughali Khaled, Aitkaid Souhila, Bouchiha Nihad Sarah

Abstract:

The aerodynamic coefficients are important in the evaluation of an aircraft performance and stability-control characteristics. These coefficients also can be used in the automatic flight control systems and mathematical model of flight simulator. The study of the aerodynamic aspect of flying systems is a reserved domain and inaccessible for the developers. Doing tests in a wind tunnel to extract aerodynamic forces and moments requires a specific and expensive means. Besides, the glaring lack of published documentation in this field of study makes the aerodynamic coefficients determination complicated. This work is devoted to the identification of an aerodynamic model, by using an aircraft in virtual simulated environment. We deal with the identification of the system, we present an environment framework based on Software In the Loop (SIL) methodology and we use MicrosoftTM Flight Simulator (FS-2004) as the environment for plane simulation. We propose The Total Least Squares Estimation technique (TLSE) to identify the aerodynamic parameters, which are unknown, variable, classified and used in the expression of the piloting law. In this paper, we define each aerodynamic coefficient as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting control.

Keywords: aircraft aerodynamic model, total least squares estimation, piloting the aircraft, robust control, Microsoft Flight Simulator, MQ-1 predator

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9265 Numerical Approach to a Mathematical Modeling of Bioconvection Due to Gyrotactic Micro-Organisms over a Nonlinear Inclined Stretching Sheet

Authors: Madhu Aneja, Sapna Sharma

Abstract:

The water-based bioconvection of a nanofluid containing motile gyrotactic micro-organisms over nonlinear inclined stretching sheet has been investigated. The governing nonlinear boundary layer equations of the model are reduced to a system of ordinary differential equations via Oberbeck-Boussinesq approximation and similarity transformations. Further, the modified set of equations with associated boundary conditions are solved using Finite Element Method. The impact of various pertinent parameters on the velocity, temperature, nanoparticles concentration, density of motile micro-organisms profiles are obtained and analyzed in details. The results show that with the increase in angle of inclination δ, velocity decreases while temperature, nanoparticles concentration, a density of motile micro-organisms increases. Additionally, the skin friction coefficient, Nusselt number, Sherwood number, density number are computed for various thermophysical parameters. It is noticed that increasing Brownian motion and thermophoresis parameter leads to an increase in temperature of fluid which results in a reduction in Nusselt number. On the contrary, Sherwood number rises with an increase in Brownian motion and thermophoresis parameter. The findings have been validated by comparing the results of special cases with existing studies.

Keywords: bioconvection, finite element method, gyrotactic micro-organisms, inclined stretching sheet, nanofluid

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9264 Degree of Bending in Axially Loaded Tubular KT-Joints of Offshore Structures: Parametric Study and Formulation

Authors: Hamid Ahmadi, Shadi Asoodeh

Abstract:

The fatigue life of tubular joints commonly found in offshore industry is not only dependent on the value of hot-spot stress (HSS), but is also significantly influenced by the through-the-thickness stress distribution characterized by the degree of bending (DoB). The determination of DoB values in a tubular joint is essential for improving the accuracy of fatigue life estimation using the stress-life (S–N) method and particularly for predicting the fatigue crack growth based on the fracture mechanics (FM) approach. In the present paper, data extracted from finite element (FE) analyses of tubular KT-joints, verified against experimental data and parametric equations, was used to investigate the effects of geometrical parameters on DoB values at the crown 0˚, saddle, and crown 180˚ positions along the weld toe of central brace in tubular KT-joints subjected to axial loading. Parametric study was followed by a set of nonlinear regression analyses to derive DoB parametric formulas for the fatigue analysis of KT-joints under axial loads. The tubular KT-joint is a quite common joint type found in steel offshore structures. However, despite the crucial role of the DoB in evaluating the fatigue performance of tubular joints, this paper is the first attempt to study and formulate the DoB values in KT-joints.

Keywords: tubular KT-joint, fatigue, degree of bending (DoB), axial loading, parametric formula

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9263 Friction Estimation and Compensation for Steering Angle Control for Highly Automated Driving

Authors: Marcus Walter, Norbert Nitzsche, Dirk Odenthal, Steffen Müller

Abstract:

This contribution presents a friction estimator for industrial purposes which identifies Coulomb friction in a steering system. The estimator only needs a few, usually known, steering system parameters. Friction occurs on almost every mechanical system and has a negative influence on high-precision position control. This is demonstrated on a steering angle controller for highly automated driving. In this steering system the friction induces limit cycles which cause oscillating vehicle movement when the vehicle follows a given reference trajectory. When compensating the friction with the introduced estimator, limit cycles can be suppressed. This is demonstrated by measurements in a series vehicle.

Keywords: friction estimation, friction compensation, steering system, lateral vehicle guidance

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9262 Allometric Models for Biomass Estimation in Savanna Woodland Area, Niger State, Nigeria

Authors: Abdullahi Jibrin, Aishetu Abdulkadir

Abstract:

The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

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9261 Design of Rigid L-Shaped Retaining Walls

Authors: Ahmed Rouili

Abstract:

Cantilever L-shaped walls are known to be relatively economical as retaining solution. The design starts by proportioning the wall dimensions for which the stability is checked for. A ratio between the lengths of the base and the stem, falling between 0,5 to 0,7, ensure the stability requirements in most cases. However, the displacement pattern of the wall in terms of rotations and translations, and the lateral pressure profile, do not have the same figure for all wall’s proportioning, as it is usually assumed. In the present work, the results of a numerical analysis are presented, different wall geometries were considered. The results show that the proportioning governs the equilibrium between the instantaneous rotation and the translation of the wall-toe, also, the lateral pressure estimation based on the average value between the at-rest and the active pressure, recommended by most design standards, is found to be not applicable for all walls.

Keywords: cantilever wall, proportioning, numerical analysis, lateral pressure estimation

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9260 An Equivalent Circuit Model Approach for Battery Pack Simulation in a Hybrid Electric Vehicle System Powertrain

Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

Abstract:

The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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9259 Design of a Sliding Mode Control Using Nonlinear Sliding Surface and Nonlinear Observer Applied to the Trirotor Mini-Aircraft

Authors: Samir Zeghlache, Abderrahmen Bouguerra, Kamel Kara, Djamel Saigaa

Abstract:

The control of the trirotor helicopter includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. This paper presents a control strategy for an underactuated six degrees of freedom (6 DOF) trirotor helicopter, based on the coupling of the fuzzy logic control and sliding mode control (SMC). The main purpose of this work is to eliminate the chattering phenomenon. To achieve our purpose we have used a fuzzy logic control to generate the hitting control signal, also the non linear observer is then synthesized in order to estimate the unmeasured states. Finally simulation results are included to indicate the trirotor UAV with the proposed controller can greatly alleviate the chattering effect and remain robust to the external disturbances.

Keywords: fuzzy sliding mode control, trirotor helicopter, dynamic modelling, underactuated systems

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9258 Presenting a Model Based on Artificial Neural Networks to Predict the Execution Time of Design Projects

Authors: Hamed Zolfaghari, Mojtaba Kord

Abstract:

After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

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9257 Artificial Neural Networks Controller for Active Power Filter Connected to a Photovoltaic Array

Authors: Rachid Dehini, Brahim Berbaoui

Abstract:

The main objectives of shunt active power filter (SAPF) is to preserve the power system from unwanted harmonic currents produced by nonlinear loads, as well as to compensate the reactive power. The aim of this paper is to present a (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF) feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: SAPF, harmonics current, photovoltaic cells, MPPT, artificial neural networks (ANN)

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9256 Modified Tendon Model Considered Structural Nonlinearity in PSC Structures

Authors: Yangsu Kwon, Hyo-Gyoung Kwak

Abstract:

Nonlinear tendon constitutive model for nonlinear analysis of pre-stressed concrete structures are presented. Since the post-cracking behavior of concrete structures, in which bonded reinforcements such as tendons and/or reinforcing steels are embedded, depends on many influencing factors(the tensile strength of concrete, anchorage length of reinforcements, concrete cover, and steel spacing) that are deeply related to the bond characteristics between concrete and reinforcements, consideration of the tension stiffening effect on the basis of the bond-slip mechanism is necessary to evaluate ultimate resisting capacity of structures. In this paper, an improved tendon model, which considering the slip effect between concrete and tendon, and effect of tension stiffening, is suggested. The validity of the proposed models is established by comparing between the analytical results and experimental results in pre-stressed concrete beams.

Keywords: bond-slip, prestressed concrete, tendon, ultimate strength

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9255 A Hybrid Adomian Decomposition Method in the Solution of Logistic Abelian Ordinary Differential and Its Comparism with Some Standard Numerical Scheme

Authors: F. J. Adeyeye, D. Eni, K. M. Okedoye

Abstract:

In this paper we present a Hybrid of Adomian decomposition method (ADM). This is the substitution of a One-step method of Taylor’s series approximation of orders I and II, into the nonlinear part of Adomian decomposition method resulting in a convergent series scheme. This scheme is applied to solve some Logistic problems represented as Abelian differential equation and the results are compared with the actual solution and Runge-kutta of order IV in order to ascertain the accuracy and efficiency of the scheme. The findings shows that the scheme is efficient enough to solve logistic problems considered in this paper.

Keywords: Adomian decomposition method, nonlinear part, one-step method, Taylor series approximation, hybrid of Adomian polynomial, logistic problem, Malthusian parameter, Verhulst Model

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9254 Comparison of Two-Phase Critical Flow Models for Estimation of Leak Flow Rate through Cracks

Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano

Abstract:

The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.

Keywords: crack, critical flow, leak, roughness

Procedia PDF Downloads 168