Search results for: low Mach number models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5779

Search results for: low Mach number models

5689 Recent Trends in Supply Chain Delivery Models

Authors: Alfred L. Guiffrida

Abstract:

A review of the literature on supply chain delivery models which use delivery windows to measure delivery performance is presented. The review herein serves to meet the following objectives: (i) provide a synthesis of previously published literature on supply chain delivery performance models, (ii) provide in one paper a consolidation of research that can serve as a single source to keep researchers up to date with the research developments in supply chain delivery models, and (iii) identify gaps in the modeling of supply chain delivery performance which could stimulate new research agendas.

Keywords: Delivery performance, Delivery window, Supply chain delivery models, Supply chain performance.

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5688 Power MOSFET Models Including Quasi-Saturation Effect

Authors: Abdelghafour Galadi

Abstract:

In this paper, accurate power MOSFET models including quasi-saturation effect are presented. These models have no internal node voltages determined by the circuit simulator and use one JFET or one depletion mode MOSFET transistors controlled by an “effective” gate voltage taking into account the quasi-saturation effect. The proposed models achieve accurate simulation results with an average error percentage less than 9%, which is an improvement of 21 percentage points compared to the commonly used standard power MOSFET model. In addition, the models can be integrated in any available commercial circuit simulators by using their analytical equations. A description of the models will be provided along with the parameter extraction procedure.

Keywords: Power MOSFET, drift layer, quasi-saturation effect, SPICE model, circuit simulation.

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5687 Completion Number of a Graph

Authors: Sudhakar G

Abstract:

In this paper a new concept of partial complement of a graph G is introduced and using the same a new graph parameter, called completion number of a graph G, denoted by c(G) is defined. Some basic properties of graph parameter, completion number, are studied and upperbounds for completion number of classes of graphs are obtained , the paper includes the characterization also.

Keywords: Completion Number, Maximum Independent subset, Partial complements, Partial self complementary

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5686 Comparison of different Channel Modeling Techniques used in the BPLC Systems

Authors: Justinian Anatory, Nelson Theethayi

Abstract:

The paper compares different channel models used for modeling Broadband Power-Line Communication (BPLC) system. The models compared are Zimmermann and Dostert, Philipps, Anatory et al and Anatory et al generalized Transmission Line (TL) model. The validity of each model was compared in time domain with ATP-EMTP software which uses transmission line approach. It is found that for a power-line network with minimum number of branches all the models give similar signal/pulse time responses compared with ATP-EMTP software; however, Zimmermann and Dostert model indicates the same amplitude but different time delay. It is observed that when the numbers of branches are increased only generalized TL theory approach results are comparable with ATPEMTP results. Also the Multi-Carrier Spread Spectrum (MC-SS) system was applied to check the implication of such behavior on the modulation schemes. It is observed that using Philipps on the underground cable can predict the performance up to 25dB better than other channel models which can misread the actual performance of the system. Also modified Zimmermann and Dostert under multipath can predict a better performance of about 5dB better than the actual predicted by Generalized TL theory. It is therefore suggested for a realistic BPLC system design and analyses the model based on generalized TL theory be used.

Keywords: Broadband Power line Channel Models, loadimpedance, Branched network.

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5685 Optical Flow Technique for Supersonic Jet Measurements

Authors: H. D. Lim, Jie Wu, T. H. New, Shengxian Shi

Abstract:

This paper outlines the development of an experimental technique in quantifying supersonic jet flows, in an attempt to avoid seeding particle problems frequently associated with particle-image velocimetry (PIV) techniques at high Mach numbers. Based on optical flow algorithms, the idea behind the technique involves using high speed cameras to capture Schlieren images of the supersonic jet shear layers, before they are subjected to an adapted optical flow algorithm based on the Horn-Schnuck method to determine the associated flow fields. The proposed method is capable of offering full-field unsteady flow information with potentially higher accuracy and resolution than existing point-measurements or PIV techniques. Preliminary study via numerical simulations of a circular de Laval jet nozzle successfully reveals flow and shock structures typically associated with supersonic jet flows, which serve as useful data for subsequent validation of the optical flow based experimental results. For experimental technique, a Z-type Schlieren setup is proposed with supersonic jet operated in cold mode, stagnation pressure of 4 bar and exit Mach of 1.5. High-speed singleframe or double-frame cameras are used to capture successive Schlieren images. As implementation of optical flow technique to supersonic flows remains rare, the current focus revolves around methodology validation through synthetic images. The results of validation test offers valuable insight into how the optical flow algorithm can be further improved to improve robustness and accuracy. Despite these challenges however, this supersonic flow measurement technique may potentially offer a simpler way to identify and quantify the fine spatial structures within the shock shear layer.

Keywords: Schlieren, optical flow, supersonic jets, shock shear layer.

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5684 Prediction of Computer and Video Game Playing Population: An Age Structured Model

Authors: T. K. Sriram, Joydip Dhar

Abstract:

Models based on stage structure have found varied applications in population models. This paper proposes a stage structured model to study the trends in the computer and video game playing population of US. The game paying population is divided into three compartments based on their age group. After simulating the mathematical model, a forecast of the number of game players in each stage as well as an approximation of the average age of game players in future has been made.

Keywords: Age structure, Forecasting, Mathematical modeling, Stage structure.

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5683 Analyzing and Comparing the Hot-spot Thermal Models of HV/LV Prefabricated and Outdoor Oil-Immersed Power Transformers

Authors: Ali Mamizadeh, Ires Iskender

Abstract:

The most important parameter in transformers life expectancy is the hot-spot temperature level which accelerates the rate of aging of the insulation. The aim of this paper is to present thermal models for transformers loaded at prefabricated MV/LV transformer substations and outdoor situations. The hot-spot temperature of transformers is studied using their top-oil temperature rise models. The thermal models proposed for hot-spot and top-oil temperatures of different operating situations are compared. Since the thermal transfer is different for indoor and outdoor transformers considering their operating conditions, their hot-spot thermal models differ from each other. The proposed thermal models are verified by the results obtained from the experiments carried out on a typical 1600 kVA, 30 /0.4 kV, ONAN transformer for both indoor and outdoor situations.

Keywords: Hot-spot Temperature, Dynamic Thermal Model, MV/LV Prefabricated, Oil Immersed Transformers

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5682 Predictability of the Two Commonly Used Models to Represent the Thin-layer Re-wetting Characteristics of Barley

Authors: M. A. Basunia

Abstract:

Thirty three re-wetting tests were conducted at different combinations of temperatures (5.7- 46.30C) and relative humidites (48.2-88.6%) with barley. Two most commonly used thinlayer drying and rewetting models i.e. Page and Diffusion were compared for their ability to the fit the experimental re-wetting data based on the standard error of estimate (SEE) of the measured and simulated moisture contents. The comparison shows both the Page and Diffusion models fit the re-wetting experimental data of barley well. The average SEE values for the Page and Diffusion models were 0.176 % d.b. and 0.199 % d.b., respectively. The Page and Diffusion models were found to be most suitable equations, to describe the thin-layer re-wetting characteristics of barley over a typically five day re-wetting. These two models can be used for the simulation of deep-bed re-wetting of barley occurring during ventilated storage and deep bed drying.

Keywords: Thin-layer, barley, re-wetting parameters, temperature, relative humidity.

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5681 A Formulation of the Latent Class Vector Model for Pairwise Data

Authors: Tomoya Okubo, Kuninori Nakamura, Shin-ichi Mayekawa

Abstract:

In this research, a latent class vector model for pairwise data is formulated. As compared to the basic vector model, this model yields consistent estimates of the parameters since the number of parameters to be estimated does not increase with the number of subjects. The result of the analysis reveals that the model was stable and could classify each subject to the latent classes representing the typical scales used by these subjects.

Keywords: finite mixture models, latent class analysis, Thrustone's paired comparison method, vector model

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5680 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

Authors: Yalong Jiang, Zheru Chi

Abstract:

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, capsule network, capacity optimization, character recognition, data augmentation; semantic segmentation.

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5679 Lean Impact Analysis Assessment Models: Development of a Lean Measurement Structural Model

Authors: Catherine Maware, Olufemi Adetunji

Abstract:

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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5678 Review of Models of Consumer Behaviour and Influence of Emotions in the Decision Making

Authors: Mikel Alonso López

Abstract:

In order to begin the process of studying the task of making consumer decisions, the main decision models must be analyzed. The objective of this task is to see if there is a presence of emotions in those models, and analyze how authors that have created them consider their impact in consumer choices. In this paper, the most important models of consumer behavior are analysed. This review is useful to consider an unproblematic background knowledge in the literature. The order that has been established for this study is chronological.

Keywords: Consumer behaviour, emotions, decision making, consumer psychology.

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5677 Natural Convection Heat Transfer from Inclined Cylinders: A Unified Correlation

Authors: Neetu Rani, Hema Setia, Marut Dutt. R.K. Wanchoo

Abstract:

An empirical correlation for predicting the heat transfer coefficient for a cylinder under free convection, inclined at any arbitrary angle with the horizontal has been developed in terms of Nusselt number, Prandtl number and Grashof number. Available experimental data was used to determine the parameters for the proposed correlation. The proposed correlation predicts the available data well within ±10%, for Prandtl number in the range 0.68-0.72 and Grashof number in the range 1.4×104–1.2×1010.

Keywords: Heat transfer, inclined cylinders, natural convection, Nusselt number, Prandtl number, Grashof number.

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5676 Exploring the Combinatorics of Motif Alignments Foraccurately Computing E-values from P-values

Authors: T. Kjosmoen, T. Ryen, T. Eftestøl

Abstract:

In biological and biomedical research motif finding tools are important in locating regulatory elements in DNA sequences. There are many such motif finding tools available, which often yield position weight matrices and significance indicators. These indicators, p-values and E-values, describe the likelihood that a motif alignment is generated by the background process, and the expected number of occurrences of the motif in the data set, respectively. The various tools often estimate these indicators differently, making them not directly comparable. One approach for comparing motifs from different tools, is computing the E-value as the product of the p-value and the number of possible alignments in the data set. In this paper we explore the combinatorics of the motif alignment models OOPS, ZOOPS, and ANR, and propose a generic algorithm for computing the number of possible combinations accurately. We also show that using the wrong alignment model can give E-values that significantly diverge from their true values.

Keywords: Motif alignment, combinatorics, p-value, E-value, OOPS, ZOOPS, ANR.

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5675 Deep Learning Based, End-to-End Metaphor Detection in Greek with Recurrent and Convolutional Neural Networks

Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

Abstract:

This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: Metaphor detection, deep learning, representation learning, embeddings.

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5674 Generative Adversarial Network Based Fingerprint Anti-Spoofing Limitations

Authors: Yehjune Heo

Abstract:

Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: Anti-spoofing, CNN, fingerprint recognition, GAN.

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5673 Transient Hydrodynamic and Thermal Behaviors of Fluid Flow in a Vertical Porous Microchannel under the Effect of Hyperbolic Heat Conduction Model

Authors: A. F. Khadrawi

Abstract:

The transient hydrodynamics and thermal behaviors of fluid flow in open-ended vertical parallel-plate porous microchannel are investigated semi-analytically under the effect of the hyperbolic heat conduction model. The model that combines both the continuum approach and the possibility of slip at the boundary is adopted in the study. The Effects of Knudsen number , Darcy number , and thermal relaxation time  on the microchannel hydrodynamics and thermal behaviors are investigated using the hyperbolic heat conduction models. It is found that as  increases the slip in the hydrodynamic and thermal boundary condition increases. This slip in the hydrodynamic boundary condition increases as  increases. Also, the slip in the thermal boundary condition increases as  decreases especially the early stage of time.

Keywords: free convection, hyperbolic heat conduction, macroscopic heat conduction models in microchannel, porous media, vertical microchannel, microchannel thermal, hydrodynamic behavior.

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5672 Innovative Methods of Improving Train Formation in Freight Transport

Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

Abstract:

The paper is focused on the operational model for transport the single wagon consignments on railway network by using two different models of train formation. The paper gives an overview of possibilities of improving the quality of transport services. Paper deals with two models used in problematic of train formatting - time continuously and time discrete. By applying these models in practice, the transport company can guarantee a higher quality of service and expect increasing of transport performance. The models are also applicable into others transport networks. The models supplement a theoretical problem of train formation by new ways of looking to affecting the organization of wagon flows.

Keywords: Train formation, wagon flows, marshalling yard, railway technology.

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5671 Numerical Study of Cyclic Behavior of Shallow Foundations on Sand Reinforced with Geogrid and Grid-Anchor

Authors: Alireza Hajiani Boushehrian, Nader Hataf, Arsalan Ghahramani

Abstract:

When the foundations of structures under cyclic loading with amplitudes less than their permissible load, the concern exists often for the amount of uniform and non-uniform settlement of such structures. Storage tank foundations with numerous filling and discharging and railways ballast course under repeating transportation loads are examples of such conditions. This paper deals with the effects of using the new generation of reinforcements, Grid-Anchor, for the purpose of reducing the permanent settlement of these foundations under the influence of different proportions of the ultimate load. Other items such as the type and the number of reinforcements as well as the number of loading cycles are studied numerically. Numerical models were made using the Plaxis3D Tunnel finite element code. The results show that by using gridanchor and increasing the number of their layers in the same proportion as that of the cyclic load being applied, the amount of permanent settlement decreases up to 42% relative to unreinforced condition depends on the number of reinforcement layers and percent of applied load and the number of loading cycles to reach a constant value of dimensionless settlement decreases up to 20% relative to unreinforced condition.

Keywords: Shallow foundation, Reinforced soil, Cyclic loading, Grid-Anchor, Numerical analysis.

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5670 The Effect of Multi-Layer Bandage on the Interface Pressure Applied by Compression Bandages

Authors: Jawad Al Khaburi, Abbas A. Dehghani-Sanij, E. Andrea Nelson, Jerry Hutchinson

Abstract:

Medical compression bandages are widely used in the treatment of chronic venous disorder. In order to design effective compression bandages, researchers have attempted to describe the interface pressure applied by multi-layer bandages using mathematical models. This paper reports on the work carried out to compare and validate the mathematical models used to describe the interface pressure applied by multi-layer bandages. Both analytical and experimental results showed that using simple multiplication of a number of bandage layers with the pressure applied by one layer of bandage or ignoring the increase in the limb radius due to former layers of bandage will result in overestimating the pressure. Experimental results showed that the mathematical models, which take into consideration the increase in the limb radius due to former bandage layers, are more accurate than the one which does not.

Keywords: Compression bandages, FlexiForce, interface pressure, venous ulcer

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5669 Data Annotation Models and Annotation Query Language

Authors: Neerja Bhatnagar, Benjoe A. Juliano, Renee S. Renner

Abstract:

This paper presents data annotation models at five levels of granularity (database, relation, column, tuple, and cell) of relational data to address the problem of unsuitability of most relational databases to express annotations. These models do not require any structural and schematic changes to the underlying database. These models are also flexible, extensible, customizable, database-neutral, and platform-independent. This paper also presents an SQL-like query language, named Annotation Query Language (AnQL), to query annotation documents. AnQL is simple to understand and exploits the already-existent wide knowledge and skill set of SQL.

Keywords: annotation query language, data annotations, data annotation models, semantic data annotations

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5668 Recognition of Gene Names from Gene Pathway Figures Using Siamese Network

Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

Abstract:

The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than Optical Character Recognition (OCR) results.

Keywords: Biological pathway, image understanding, gene name recognition, object detection, Siamese network, Visual Geometry Group.

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5667 Stochastic Repair and Replacement with a Single Repair Channel

Authors: Mohammed A. Hajeeh

Abstract:

This paper examines the behavior of a system, which upon failure is either replaced with certain probability p or imperfectly repaired with probability q. The system is analyzed using Kolmogorov's forward equations method; the analytical expression for the steady state availability is derived as an indicator of the system’s performance. It is found that the analysis becomes more complex as the number of imperfect repairs increases. It is also observed that the availability increases as the number of states and replacement probability increases. Using such an approach in more complex configurations and in dynamic systems is cumbersome; therefore, it is advisable to resort to simulation or heuristics. In this paper, an example is provided for demonstration.

Keywords: Repairable models, imperfect, availability, exponential distribution.

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5666 Extrapolation of Clinical Data from an Oral Glucose Tolerance Test Using a Support Vector Machine

Authors: Jianyin Lu, Masayoshi Seike, Wei Liu, Peihong Wu, Lihua Wang, Yihua Wu, Yasuhiro Naito, Hiromu Nakajima, Yasuhiro Kouchi

Abstract:

To extract the important physiological factors related to diabetes from an oral glucose tolerance test (OGTT) by mathematical modeling, highly informative but convenient protocols are required. Current models require a large number of samples and extended period of testing, which is not practical for daily use. The purpose of this study is to make model assessments possible even from a reduced number of samples taken over a relatively short period. For this purpose, test values were extrapolated using a support vector machine. A good correlation was found between reference and extrapolated values in evaluated 741 OGTTs. This result indicates that a reduction in the number of clinical test is possible through a computational approach.

Keywords: SVM regression, OGTT, diabetes, mathematical model

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5665 Improve Safety Performance of Un-Signalized Intersections in Oman

Authors: Siham G. Farag

Abstract:

The main objective of this paper is to provide a new methodology for road safety assessment in Oman through the development of suitable accident prediction models. GLM technique with Poisson or NBR using SAS package was carried out to develop these models. The paper utilized the accidents data of 31 un-signalized T-intersections during three years. Five goodness-of-fit measures were used to assess the overall quality of the developed models. Two types of models were developed separately; the flow-based models including only traffic exposure functions, and the full models containing both exposure functions and other significant geometry and traffic variables. The results show that, traffic exposure functions produced much better fit to the accident data. The most effective geometric variables were major-road mean speed, minor-road 85th percentile speed, major-road lane width, distance to the nearest junction, and right-turn curb radius. The developed models can be used for intersection treatment or upgrading and specify the appropriate design parameters of T-intersections. Finally, the models presented in this thesis reflect the intersection conditions in Oman and could represent the typical conditions in several countries in the middle east area, especially gulf countries.

Keywords: Accidents Prediction Models (APMs), Generalized Linear Model (GLM), T-intersections, Oman.

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5664 Numerical Analysis of All-Optical Microwave Mixing and Bandpass Filtering in an RoF Link

Authors: S. Khosroabadi, M. R. Salehi

Abstract:

In this paper, all-optical signal processors that perform both microwave mixing and bandpass filtering in a radio-over-fiber (RoF) link are presented. The key device is a Mach-Zehnder modulator (MZM) which performs all-optical microwave mixing. An up-converted microwave signal is obtained and other unwanted frequency components are suppressed at the end of the fiber span.

Keywords: Microwave mixing, bandpass filtering, all-optical, signal processing, MZM.

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5663 Deterioration Assessment Models for Water Pipelines

Authors: L. Parvizsedghy, I. Gkountis, A. Senouci, T. Zayed, M. Alsharqawi, H. El Chanati, M. El-Abbasy, F. Mosleh

Abstract:

The aging and deterioration of water pipelines in cities worldwide result in more frequent water main breaks, water service disruptions, and flooding damage. Therefore, there is an urgent need for undertaking proper maintenance procedures to avoid breaks and disastrous failures. However, due to budget limitations, the maintenance of water pipeline networks needs to be prioritized through efficient deterioration assessment models. Previous studies focused on the development of structural or physical deterioration assessment models, which require expensive inspection data. But, this paper aims at developing deterioration assessment models for water pipelines using statistical techniques. Several deterioration models were developed based on pipeline size, material type, and soil type using linear regression analysis. The categorical nature of some variables affecting pipeline deterioration was considered through developing several categorical models. The developed models were validated with an average validity percentage greater than 95%. Moreover, sensitivity analysis was carried out against different classifications and it displayed higher importance of age of pipes compared to other factors. The developed models will be helpful for the water municipalities and asset managers to assess the condition of their pipes and prioritize them for maintenance and inspection purposes.

Keywords: Water pipelines, deterioration assessment models, regression analysis.

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5662 Crashworthiness Optimization of an Automotive Front Bumper in Composite Material

Authors: S. Boria

Abstract:

In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: Composite material, crashworthiness, finite element analysis, optimization.

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5661 Flow and Heat Transfer of a Nanofluid over a Shrinking Sheet

Authors: N. Bachok, N. L. Aleng, N. M. Arifin, A. Ishak, N. Senu

Abstract:

The problem of laminar fluid flow which results from the shrinking of a permeable surface in a nanofluid has been investigated numerically. The model used for the nanofluid incorporates the effects of Brownian motion and thermophoresis. A similarity solution is presented which depends on the mass suction parameter S, Prandtl number Pr, Lewis number Le, Brownian motion number Nb and thermophoresis number Nt. It was found that the reduced Nusselt number is decreasing function of each dimensionless number.

Keywords: Boundary layer, Nanofluid, Shrinking sheet, Brownian motion, Thermophoresis, Similarity solution.

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5660 Comparative Study of Bending Angle in Laser Forming Process Using Artificial Neural Network and Fuzzy Logic System

Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

Abstract:

Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: Artificial neural network, bending angle, fuzzy logic, laser forming.

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