Search results for: ecis modeling
3672 Comparative Assessment of a Distributed Model and a Lumped Model for Estimating of Sediments Yielding in Small Urban Areas
Authors: J.Zambrano Nájera, M.Gómez Valentín
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Increases in urbanization during XX century, have brought as one major problem the increased of sediment production. Hydraulic erosion is one of the major causes of increasing of sediments in small urban catchments. Such increments in sediment yielding in header urban catchments can caused obstruction of drainage systems, making impossible to capture urban runoff, increasing runoff volumes and thus exacerbating problems of urban flooding. For these reasons, it is more and more important to study of sediment production in urban watershed for properly analyze and solve problems associated to sediments. The study of sediments production has improved with the use of mathematical modeling. For that reason, it is proposed a new physically based model applicable to small header urban watersheds that includes the advantages of distributed physically base models, but with more realistic data requirements. Additionally, in this paper the model proposed is compared with a lumped model, reviewing the results, the advantages and disadvantages between the both of them.Keywords: erosion, hydrologic modeling, urban runoff, sediment modeling, sediment yielding, urban planning
Procedia PDF Downloads 3473671 The Evaluation of the Performance of Different Filtering Approaches in Tracking Problem and the Effect of Noise Variance
Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri
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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.Keywords: Gaussian approximation, Kalman smoother, parameter estimation, noise variance
Procedia PDF Downloads 4393670 Reliability Modeling of Repairable Subsystems in Semiconductor Fabrication: A Virtual Age and General Repair Framework
Authors: Keshav Dubey, Swajeeth Panchangam, Arun Rajendran, Swarnim Gupta
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In the semiconductor capital equipment industry, effective modeling of repairable system reliability is crucial for optimizing maintenance strategies and ensuring operational efficiency. However, repairable system reliability modeling using a renewal process is not as popular in the semiconductor equipment industry as it is in the locomotive and automotive industries. Utilization of this approach will help optimize maintenance practices. This paper presents a structured framework that leverages both parametric and non-parametric approaches to model the reliability of repairable subsystems based on operational data, maintenance schedules, and system-specific conditions. Data is organized at the equipment ID level, facilitating trend testing to uncover failure patterns and system degradation over time. For non-parametric modeling, the Mean Cumulative Function (Mean Cumulative Function) approach is applied, offering a flexible method to estimate the cumulative number of failures over time without assuming an underlying statistical distribution. This allows for empirical insights into subsystem failure behavior based on historical data. On the parametric side, virtual age modeling, along with Homogeneous and Non-Homogeneous Poisson Process (Homogeneous Poisson Process and Non-Homogeneous Poisson Process) models, is employed to quantify the effect of repairs and the aging process on subsystem reliability. These models allow for a more structured analysis by characterizing repair effectiveness and system wear-out trends over time. A comparison of various Generalized Renewal Process (GRP) approaches highlights their utility in modeling different repair effectiveness scenarios. These approaches provide a robust framework for assessing the impact of maintenance actions on system performance and reliability. By integrating both parametric and non-parametric methods, this framework offers a comprehensive toolset for reliability engineers to better understand equipment behavior, assess the effectiveness of maintenance activities, and make data-driven decisions that enhance system availability and operational performance in semiconductor fabrication facilities.Keywords: reliability, maintainability, homegenous poission process, repairable system
Procedia PDF Downloads 193669 Loading Factor Performance of a Centrifugal Compressor Impeller: Specific Features and Way of Modeling
Authors: K. Soldatova, Y. Galerkin
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A loading factor performance is necessary for the modeling of centrifugal compressor gas dynamic performance curve. Measured loading factors are linear function of a flow coefficient at an impeller exit. The performance does not depend on the compressibility criterion. To simulate loading factor performances, the authors present two parameters: a loading factor at zero flow rate and an angle between an ordinate and performance line. The calculated loading factor performances of non-viscous are linear too and close to experimental performances. Loading factor performances of several dozens of impellers with different blade exit angles, blade thickness and number, ratio of blade exit/inlet height, and two different type of blade mean line configuration. There are some trends of influence, which are evident – comparatively small blade thickness influence, and influence of geometry parameters is more for impellers with bigger blade exit angles, etc. Approximating equations for both parameters are suggested. The next phase of work will be simulating of experimental performances with the suggested approximation equations as a base.Keywords: loading factor performance, centrifugal compressor, impeller, modeling
Procedia PDF Downloads 3503668 Numerical Simulation of Solar Reactor for Water Disinfection
Authors: A. Sebti Bouzid, S. Igoud, L. Aoudjit, H. Lebik
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Mathematical modeling and numerical simulation have emerged over the past two decades as one of the key tools for design and optimize performances of physical and chemical processes intended to water disinfection. Water photolysis is an efficient and economical technique to reduce bacterial contamination. It exploits the germicidal effect of solar ultraviolet irradiation to inactivate pathogenic microorganisms. The design of photo-reactor operating in continuous disinfection system, required tacking in account the hydrodynamic behavior of water in the reactor. Since the kinetic of disinfection depends on irradiation intensity distribution, coupling the hydrodynamic and solar radiation distribution is of crucial importance. In this work we propose a numerical simulation study for hydrodynamic and solar irradiation distribution in a tubular photo-reactor. We have used the Computational Fluid Dynamic code Fluent under the assumption of three-dimensional incompressible flow in unsteady turbulent regimes. The results of simulation concerned radiation, temperature and velocity fields are discussed and the effect of inclination angle of reactor relative to the horizontal is investigated.Keywords: solar water disinfection, hydrodynamic modeling, solar irradiation modeling, CFD Fluent
Procedia PDF Downloads 3503667 A Framework for Building Information Modelling Execution Plan in the Construction Industry, Lagos State, Nigeria
Authors: Tosin Deborah Akanbi
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The Building Information Modeling Execution Plan (BEP) is a document that manifests the specifications for the adoption and execution of building information modeling in the construction sector in an organized manner so as to attain the listed goals. In this regard, the study examined the barriers to the adoption of building information modeling, evaluated the effect of building information modeling adoption characteristics on the key elements of a building information modeling execution plan and developed a strategic framework for a BEP in the Lagos State construction industry. Data were gathered through a questionnaire survey with 332 construction professionals in the study area. Three online structured interviews were conducted to support and validate the findings of the quantitative analysis. The results showed the significant relationships and connections between the variables in the framework: BIM usage and model quality control (aBIMskill -> dMQ, Beta = 0.121, T statistics = 1.829), BIM adoption characteristics and information exchange (bBIM_CH -> dIE, Beta = 0.128, T statistics = 1.727), BIM adoption characteristics and process design (bBIM_CH -> dPD, Beta = 0.170, T statistics = 2.754), BIM adoption characteristics and roles and responsibilities (bBIM_CH -> dRR, Beta = 0.131, T statistics = 2.181), interest BIM barriers and BIM adoption characteristics (cBBIM_INT -> bBIM_CH, Beta = 0.137, T statistics = 2.309), legal BIM barriers and BIM adoption characteristics (cBBIM_LEG -> bBIM_CH, Beta = 0.168, T statistics = 2.818), professional BIM barriers and BIM adoption characteristics (cBBIM_PRO -> bBIM_CH, Beta = 0.152, T statistics = 2.645). The results also revealed that seven final themes were generated, namely: model structure and process design, BIM information exchange and collaboration procedures, project goals and deliverables, project model quality control, roles and responsibilities, reflect Lagos state construction industry and validity of the BEP framework. Thus, there is a need for the policy makers to direct interventions to promote, encourage and support the understanding and adoption of BIM by emphasizing the various benefits of using the technology in the Lagos state construction industry.Keywords: building information modelling execution plan, BIM adoption characteristics, BEP framework, construction industry
Procedia PDF Downloads 173666 Thermodynamic Modeling of Methane Injection in Gas-Condensate Reservoir Core: A Case Study
Authors: F. S. Alavi, D. Mowla, F. Esmaeilzadeh
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In this paper, the core of Sarkhoon Gas Condensate Reservoir located in the south of Iran was thermodynamically modeled in order to study the natural depletion process and methane injection phenomena for enhanced gas-condensate recovery using the Eclipse 300 compositional simulator. Modeling was performed for three different core lengths with different production and injection flow rates in both vertical and horizontal cases. According to the results, the final condensate in place value in the natural depletion process is approximately independent of the production rate for a given pressure drop. The final condensate in place value is lower in vertical cases compared to horizontal cases. An increase in the injection flow rate leads to a decrease in the percentage of gascondensate recovery. In cores of equal length, gas condensate recovery percent is higher in vertical cases in comparison to horizontal cases. For a constant injection rate, decreasing the core length leads to a decrease in gas condensate recovery.Keywords: reservoir simulation, methane injection, enhanced condensate recovery, reservoir core, modeling
Procedia PDF Downloads 943665 Modeling and Controlling the Rotational Degree of a Quadcopter Using Proportional Integral and Derivative Controller
Authors: Sanjay Kumar, Lillie Dewan
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The study of complex dynamic systems has advanced through various scientific approaches with the help of computer modeling. The common design trends in aerospace system design can be applied to quadcopter design. A quadcopter is a nonlinear, under-actuated system with complex aerodynamics parameters and creates challenges that demand new, robust, and effective control approaches. The flight control stability can be improved by planning and tracking the trajectory and reducing the effect of sensors and the operational environment. This paper presents a modern design Simmechanics visual modeling approach for a mechanical model of a quadcopter with three degrees of freedom. The Simmechanics model, considering inertia, mass, and geometric properties of a dynamic system, produces multiple translation and rotation maneuvers. The proportional, integral, and derivative (PID) controller is integrated with the Simmechanics model to follow a predefined quadcopter rotational trajectory for a fixed time interval. The results presented are satisfying. The simulation of the quadcopter control performed operations successfully.Keywords: nonlinear system, quadcopter model, simscape modelling, proportional-integral-derivative controller
Procedia PDF Downloads 1963664 Influence of Parameters of Modeling and Data Distribution for Optimal Condition on Locally Weighted Projection Regression Method
Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri
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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method
Procedia PDF Downloads 5023663 Hope as a Predictor for Complicated Grief and Anxiety: A Bayesian Structural Equational Modeling Study
Authors: Bo Yan, Amy Y. M. Chow
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Bereavement is recognized as a universal challenging experience. It is important to gather research evidence on protective factors in bereavement. Hope is considered as one of the protective factors in previous coping studies. The present study aims to add knowledge by investigating hope at the first month after death to predict psychological symptoms altogether including complicated grief (CG), anxiety, and depressive symptoms at the seventh month. The data were collected via one-on-one interview survey in a longitudinal project with Hong Kong hospice users (sample size 105). Most participants were at their middle age (49-year-old on average), female (72%), with no religious affiliation (58%). Bayesian Structural Equation Modeling (BSEM) analysis was conducted on the longitudinal dataset. The BSEM findings show that hope at the first month of bereavement negatively predicts both CG and anxiety symptoms at the seventh month but not for depressive symptoms. Age and gender are controlled in the model. The overall model fit is good. The current study findings suggest assessing hope at the first month of bereavement. Hope at the first month after the loss is identified as an excellent predictor for complicated grief and anxiety symptoms at the seventh month. The result from this sample is clear, so it encourages cross-cultural research on replicated modeling and development of further clinical application. Particularly, practical consideration for early intervention to increase the level of hope has the potential to reduce the psychological symptoms and thus to improve the bereaved persons’ wellbeing in the long run.Keywords: anxiety, complicated grief, depressive symptoms, hope, structural equational modeling
Procedia PDF Downloads 2043662 Investigating the Minimum RVE Size to Simulate Poly (Propylene carbonate) Composites Reinforced with Cellulose Nanocrystals as a Bio-Nanocomposite
Authors: Hamed Nazeri, Pierre Mertiny, Yongsheng Ma, Kajsa Duke
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The background of the present study is the use of environment-friendly biopolymer and biocomposite materials. Among the recently introduced biopolymers, poly (propylene carbonate) (PPC) has been gaining attention. This study focuses on the size of representative volume elements (RVE) in order to simulate PPC composites reinforced by cellulose nanocrystals (CNCs) as a bio-nanocomposite. Before manufacturing nanocomposites, numerical modeling should be implemented to explore and predict mechanical properties, which may be accomplished by creating and studying a suitable RVE. In other studies, modeling of composites with rod shaped fillers has been reported assuming that fillers are unidirectionally aligned. But, modeling of non-aligned filler dispersions is considerably more difficult. This study investigates the minimum RVE size to enable subsequent FEA modeling. The matrix and nano-fillers were modeled using the finite element software ABAQUS, assuming randomly dispersed fillers with a filler mass fraction of 1.5%. To simulate filler dispersion, a Monte Carlo technique was employed. The numerical simulation was implemented to find composite elastic moduli. After commencing the simulation with a single filler particle, the number of particles was increased to assess the minimum number of filler particles that satisfies the requirements for an RVE, providing the composite elastic modulus in a reliable fashion.Keywords: biocomposite, Monte Carlo method, nanocomposite, representative volume element
Procedia PDF Downloads 4423661 Modeling Residual Modulus of Elasticity of Self-Compacted Concrete Using Artificial Neural Networks
Authors: Ahmed M. Ashteyat
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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling
Procedia PDF Downloads 5343660 The Role of Uncertainty in the Integration of Environmental Parameters in Energy System Modeling
Authors: Alexander de Tomás, Miquel Sierra, Stefan Pfenninger, Francesco Lombardi, Ines Campos, Cristina Madrid
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Environmental parameters are key in the definition of sustainable energy systems yet excluded from most energy system optimization models. Still, decision-making may be misleading without considering them. Environmental analyses of the energy transition are a key part of industrial ecology but often are performed without any input from the users of the information. This work assesses the systemic impacts of energy transition pathways in Portugal. Using the Calliope energy modeling framework, 250+ optimized energy system pathways are generated. A Delphi study helps to identify the relevant criteria for the stakeholders as regards the environmental assessment, which is performed with ENBIOS, a python package that integrates life cycle assessment (LCA) with a metabolic analysis based on complex relations. Furthermore, this study focuses on how the uncertainty propagates through the model’s consortium. With the aim of doing so, a soft link between the Calliope/ENBIOS cascade and Brightway’s data capabilities is built to perform Monte Carlo simulations. These findings highlight the relevance of including uncertainty analysis as a range of values rather than informing energy transition results with a single value.Keywords: energy transition, energy modeling, uncertainty, sustainability
Procedia PDF Downloads 833659 Power System Modeling for Calculations in Frequency and Steady State Domain
Authors: G. Levacic, A. Zupan
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Application of new technological solutions and installation of new elements into the network requires special attention when investigating its interaction with the existing power system. Special attention needs to be devoted to the occurrence of harmonic resonance. Sources of increasing harmonic penetration could be wind power plants, Flexible Alternating Current Transmission System (FACTS) devices, underground and submarine cable installations etc. Calculation in frequency domain with various software, for example, the software for power systems transients EMTP-RV presents one of the most common ways to obtain the harmonic impedance of the system. Along calculations in frequency domain, such software allows performing of different type of calculations as well as steady-state domain. This paper describes a power system modeling with software EMTP-RV based on data from SCADA/EMS system. The power flow results on 220 kV and 400 kV voltage levels retrieved from EMTP-RV are verified by comparing with power flow results from power transmissions system planning software PSS/E. The determination of the harmonic impedance for the case of remote power plant connection with cable up to 2500 Hz is presented as an example of calculations in frequency domain.Keywords: power system modeling, frequency domain, steady state, EMTP-RV, PSS/E
Procedia PDF Downloads 3223658 One Dimensional Reactor Modeling for Methanol Steam Reforming to Hydrogen
Authors: Hongfang Ma, Mingchuan Zhou, Haitao Zhang, Weiyong Ying
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One dimensional pseudo-homogenous modeling has been performed for methanol steam reforming reactor. The results show that the models can well predict the industrial data. The reactor had minimum temperature along axial because of endothermic reaction. Hydrogen productions and temperature profiles along axial were investigated regarding operation conditions such as inlet mass flow rate and mass fraction of methanol, inlet temperature of external thermal oil. Low inlet mass flow rate of methanol, low inlet temperature, and high mass fraction of methanol decreased minimum temperature along axial. Low inlet mass flow rate of methanol, high mass fraction of methanol, and high inlet temperature of thermal oil made cold point forward. Low mass fraction, high mass flow rate, and high inlet temperature of thermal oil increased hydrogen production. One dimensional models can be a guide for industrial operation.Keywords: reactor, modeling, methanol, steam reforming
Procedia PDF Downloads 2983657 A609 Modeling of AC Servomotor Using Genetic Algorithm and Tests for Control of a Robotic Joint
Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé
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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control
Procedia PDF Downloads 5203656 The BNCT Project Using the Cf-252 Source: Monte Carlo Simulations
Authors: Marta Błażkiewicz-Mazurek, Adam Konefał
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The project can be divided into three main parts: i. modeling the Cf-252 neutron source and conducting an experiment to verify the correctness of the obtained results, ii. design of the BNCT system infrastructure, iii. analysis of the results from the logical detector. Modeling of the Cf-252 source included designing the shape and size of the source as well as the energy and spatial distribution of emitted neutrons. Two options were considered: a point source and a cylindrical spatial source. The energy distribution corresponded to various spectra taken from specialized literature. Directionally isotropic neutron emission was simulated. The simulation results were compared with experimental values determined using the activation detector method using indium foils and cadmium shields. The relative fluence rate of thermal and resonance neutrons was compared in the chosen places in the vicinity of the source. The second part of the project related to the modeling of the BNCT infrastructure consisted of developing a simulation program taking into account all the essential components of this system. Materials with moderating, absorbing, and backscattering properties of neutrons were adopted into the project. Additionally, a gamma radiation filter was introduced into the beam output system. The analysis of the simulation results obtained using a logical detector located at the beam exit from the BNCT infrastructure included neutron energy and their spatial distribution. Optimization of the system involved changing the size and materials of the system to obtain a suitable collimated beam of thermal neutrons.Keywords: BNCT, Monte Carlo, neutrons, simulation, modeling
Procedia PDF Downloads 293655 In silico Model of Transamination Reaction Mechanism
Authors: Sang-Woo Han, Jong-Shik Shin
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w-Transaminase (w-TA) is broadly used for synthesizing chiral amines with a high enantiopurity. However, the reaction mechanism of w-TA has been not well studied, contrary to a-transaminase (a-TA) such as AspTA. Here, we propose in silico model on the reaction mechanism of w-TA. Based on the modeling results which showed large free energy gaps between external aldimine and quinonoid on deamination (or ketimine and quinonoid on amination), withdrawal of Ca-H seemed as a critical step which determines the reaction rate on both amination and deamination reactions, which is consistent with previous researches. Hyperconjugation was also observed in both external aldimine and ketimine which weakens Ca-H bond to elevate Ca-H abstraction.Keywords: computational modeling, reaction intermediates, w-transaminase, in silico model
Procedia PDF Downloads 5453654 Theoretical Study of Carbonic Anhydrase-Ii Inhibitors for Treatment of Glaucoma
Authors: F. Boukli Hacene, W. Soufi, S. Ghalem
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Glaucoma disease is a progressive degenerative optic neuropathy, with irreversible visual field deficits and high eye pressure being one of the risk factors. Sulfonamides are carbonic anhydrase-II inhibitors that aim to decrease the secretion of aqueous humor by direct inhibition of this enzyme at the level of the ciliary processes. These drugs present undesirable effects that are difficult to accept by the patient. In our study, we are interested in the inhibition of carbonic anhydrase-II by different natural ligands (curcumin analogues) using molecular modeling methods using molecular operating environment (MOE) software to predict their interaction with this enzyme.Keywords: carbonic anhydrase-II, curcumin analogues, drug research, molecular modeling
Procedia PDF Downloads 893653 Modeling of Coupled Mechanical State and Diffusion in Composites with Impermeable Fibers
Authors: D. Gueribiz, F. Jacquemin, S. Fréour
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During their service life, composite materials are submitted to humid environments. The moisture absorbed by their matrix polymer induced internal stresses which can lead to multi-scale damage and may reduce the lifetime of composite structures. The estimation of internal stresses is based at a first on realistic evaluation of the diffusive behavior of composite materials. Generally, the modeling and simulation of the diffusive behavior of composite materials are extensively investigated through decoupled models based on the assumption of Fickien behavior. For these approaches, the concentration and the deformation (or stresses), the two state variables of the problem considered are governed by independent equations which are solved separately. In this study, a model coupling diffusive behavior with stresses state for a polymer matrix composite reinforced with impermeable fibers is proposed, the investigation of diffusive behavior is based on a more general thermodynamic approach which introduces a dependence of diffusive behavior on internal stresses state. The coupled diffusive behavior modeling was established in first for homogeneous and isotropic matrix and it is, thereafter, extended to impermeable unidirectional composites.Keywords: composites materials, moisture diffusion, effective moisture diffusivity, coupled moisture diffusion
Procedia PDF Downloads 3083652 Experimental Correlation for Erythrocyte Aggregation Rate in Population Balance Modeling
Authors: Erfan Niazi, Marianne Fenech
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Red Blood Cells (RBCs) or erythrocytes tend to form chain-like aggregates under low shear rate called rouleaux. This is a reversible process and rouleaux disaggregate in high shear rates. Therefore, RBCs aggregation occurs in the microcirculation where low shear rates are present but does not occur under normal physiological conditions in large arteries. Numerical modeling of RBCs interactions is fundamental in analytical models of a blood flow in microcirculation. Population Balance Modeling (PBM) is particularly useful for studying problems where particles agglomerate and break in a two phase flow systems to find flow characteristics. In this method, the elementary particles lose their individual identity due to continuous destructions and recreations by break-up and agglomeration. The aim of this study is to find RBCs aggregation in a dynamic situation. Simplified PBM was used previously to find the aggregation rate on a static observation of the RBCs aggregation in a drop of blood under the microscope. To find aggregation rate in a dynamic situation we propose an experimental set up testing RBCs sedimentation. In this test, RBCs interact and aggregate to form rouleaux. In this configuration, disaggregation can be neglected due to low shear stress. A high-speed camera is used to acquire video-microscopic pictures of the process. The sizes of the aggregates and velocity of sedimentation are extracted using an image processing techniques. Based on the data collection from 5 healthy human blood samples, the aggregation rate was estimated as 2.7x103(±0.3 x103) 1/s.Keywords: red blood cell, rouleaux, microfluidics, image processing, population balance modeling
Procedia PDF Downloads 3553651 Effects of Different Meteorological Variables on Reference Evapotranspiration Modeling: Application of Principal Component Analysis
Authors: Akinola Ikudayisi, Josiah Adeyemo
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The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.Keywords: irrigation, principal component analysis, reference evapotranspiration, Vaalharts
Procedia PDF Downloads 2583650 Modeling User Departure Time Choice for Trips in Urban Streets
Authors: Saeed Sayyad Hagh Shomar
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Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using questionnaire of stated preference models users’ departure time choice affected by congestion pricing plan in downtown Tehran. Experimental results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.Keywords: modeling, departure time, travel timing, time of the day, congestion pricing, transportation planning
Procedia PDF Downloads 4333649 Using Gaussian Process in Wind Power Forecasting
Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui
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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.Keywords: wind power, Gaussien process, modelling, forecasting
Procedia PDF Downloads 4173648 Modeling of Power Network by ATP-Draw for Lightning Stroke Studies
Authors: John Morales, Armando Guzman
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Protection relay algorithms play a crucial role in Electric Power System stability, where, it is clear that lightning strokes produce the mayor percentage of faults and outages of Transmission Lines (TLs) and Distribution Feeders (DFs). In this context, it is imperative to develop novel protection relay algorithms. However, in order to get this aim, Electric Power Systems (EPS) network have to be simulated as real as possible, especially the lightning phenomena, and EPS elements that affect their behavior like direct and indirect lightning, insulator string, overhead line, soil ionization and other. However, researchers have proposed new protection relay algorithms considering common faults, which are not produced by lightning strokes, omitting these imperative phenomena for the transmission line protection relays behavior. Based on the above said, this paper presents the possibilities of using the Alternative Transient Program ATP-Draw for the modeling and simulation of some models to make lightning stroke studies, especially for protection relays, which are developed through Transient Analysis of Control Systems (TACS) and MODELS language corresponding to the ATP-Draw.Keywords: back-flashover, faults, flashover, lightning stroke, modeling of lightning, outages, protection relays
Procedia PDF Downloads 3163647 Non-Linear Numerical Modeling of the Interaction of Twin Tunnels-Structure
Authors: A. Bayoumi, M. Abdallah, F. Hage Chehade
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Structures on the ground surface bear impact from the tunneling-induced settlement, especially when twin tunnels are constructed. The tunneling influence on the structure is considered as a critical issue based on the construction procedure and relative position of tunnels. Lebanon is suffering from a traffic phenomenon caused by the lack of transportation systems. After several traffic counts and geotechnical investigations in Beirut city, efforts aim for the construction of tunneling systems. In this paper, we present a non-linear numerical modeling of the effect of the twin tunnels constructions on the structures located at soil surface for a particular site in Beirut. A parametric study, which concerns the geometric configuration of tunnels, the distance between their centers, the construction order, and the position of the structure, is performed. The tunnel-soil-structure interaction is analyzed by using the non-linear finite element modeling software PLAXIS 2D. The results of the surface settlement and the bending moment of the structure reveal significant influence when the structure is moved away, especially in vertical aligned tunnels.Keywords: bending moment, elastic modulus, horizontal twin tunnels, soil, structure location, surface settlement, vertical twin tunnels
Procedia PDF Downloads 2973646 Architecture - Performance Relationship in GPU Computing - Composite Process Flow Modeling and Simulations
Authors: Ram Mohan, Richard Haney, Ajit Kelkar
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Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance
Procedia PDF Downloads 3633645 Automatic Assignment of Geminate and Epenthetic Vowel for Amharic Text-to-Speech System
Authors: Tadesse Anberbir, Felix Bankole, Tomio Takara, Girma Mamo
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In the development of a text-to-speech synthesizer, automatic derivation of correct pronunciation from the grapheme form of a text is a central problem. Particularly deriving phonological features which are not shown in orthography is challenging. In the Amharic language, geminates and epenthetic vowels are very crucial for proper pronunciation but neither is shown in orthography. In this paper, we proposed and integrated a morphological analyzer into an Amharic Text-to-Speech system, mainly to predict geminates and epenthetic vowel positions, and prepared a duration modeling method. Amharic Text-to-Speech system (AmhTTS) is a parametric and rule-based system that adopts a cepstral method and uses a source filter model for speech production and a Log Magnitude Approximation (LMA) filter as the vocal tract filter. The naturalness of the system after employing the duration modeling was evaluated by sentence listening test and we achieved an average Mean Opinion Score (MOS) 3.4 (68%) which is moderate. By modeling the duration of geminates and controlling the locations of epenthetic vowel, we are able to synthesize good quality speech. Our system is mainly suitable to be customized for other Ethiopian languages with limited resources.Keywords: Amharic, gemination, speech synthesis, morphology, epenthesis
Procedia PDF Downloads 873644 Fault Diagnosis in Confined Systems
Authors: Nesrine Berber, Hafid Haffaf, Abdel Madjid Meghabar
Abstract:
In the last decade, technology has continued to grow and has changed the structure of our society. Today, new technologies including the information and communication (ICT) play a main role which importance continues to grow, now it's become indispensable to the economic, social and cultural. Thus, ICT technology has proven to be as a promising intervention in the area of road transport. The supervision model of class of train of intelligent and autonomous vehicles leads us to give some defintions about IAV and the different technologies used for communication between them. Our aim in this work is to present an hypergraph modeling a class of train of Intelligent and Autonomous Vehicles (IAV).Keywords: intelligent transportation system, intelligent autonomous vehicles, Ad Hoc network, wireless technologies, hypergraph modeling, supervision
Procedia PDF Downloads 5463643 A Stochastic Diffusion Process Based on the Two-Parameters Weibull Density Function
Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos
Abstract:
Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function
Procedia PDF Downloads 308