Search results for: statistical mechanics.

Authors: Cândida M. Pereira, Amílcar L. Ramalho, Jorge A. Ambrósio

Abstract:

In the numerical solution of the forward dynamics of a multibody system, the positions and velocities of the bodies in the system are obtained first. With the information of the system state variables at each time step, the internal and external forces acting on the system are obtained by appropriate contact force models if the continuous contact method is used instead of a discrete contact method. The local deformation of the bodies in contact, represented by penetration, is used to compute the contact force. The ability and suitability with current cylindrical contact force models to describe the contact between bodies with cylindrical geometries with particular focus on internal contacting geometries involving low clearances and high loads simultaneously is discussed in this paper. A comparative assessment of the performance of each model under analysis for different contact conditions, in particular for very different penetration and clearance values, is presented. It is demonstrated that some models represent a rough approximation to describe the conformal contact between cylindrical geometries because contact forces are underestimated.

Keywords: Clearance joints, Contact mechanics, Contact dynamics, Internal cylindrical contact, Multibody dynamics.

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Authors: Ali M. Al-Shaery

Abstract:

The purpose of this paper is to address the functions of sustainability dimensions in city information modelling and to present the required sustainability criteria that support establishing a sustainable planning framework for enhancing existing cities and developing future smart cities. The paper is divided into two sections. The first section is based on the examination of a wide and extensive array of cross-disciplinary literature in the last decade and a half to conceptualize the terms ‘sustainable’ and ‘smart city’, and map their associated criteria to city information modelling. The second section is based on analyzing two approaches relating to city information modelling, namely statistical and dynamic approaches, and their suitability in the development of cities’ action plans. The paper argues that the use of statistical approaches to embed sustainability dimensions in city information modelling have limited value. Despite the popularity of such approaches in addressing other dimensions like utility and service management in development and action plans of the world cities, these approaches are unable to address the dynamics across various city sectors with regards to economic, environmental and social criteria. The paper suggests an integrative dynamic and cross-disciplinary planning approach to embedding sustainability dimensions in city information modelling frameworks. Such an approach will pave the way towards optimal planning and implementation of priority actions of projects and investments. The approach can be used to achieve three main goals: (1) better development and action plans for world cities (2) serve the development of an integrative dynamic and cross-disciplinary framework that incorporates economic, environmental and social sustainability criteria and (3) address areas that require further attention in the development of future sustainable and smart cities. The paper presents an innovative approach for city information modelling and a well-argued, balanced hierarchy of sustainability criteria that can contribute to an area of research which is still in its infancy in terms of development and management.

Keywords: Information modelling, smart city, sustainable city, sustainability dimensions, sustainability criteria, city development planning.

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Authors: M. Adeel

Abstract:

The damage tolerance behavior of integrally and conventional stiffened panel is investigated based on the fracture mechanics and finite element analysis. The load bearing capability and crack growth characteristic of both types of the stiffened panels having same configuration subjected to distributed tensile load is examined in this paper. A fourteen-stringer stiffened panel is analyzed for a central skin crack propagating towards the adjacent stringers. Stress intensity factors and fatigue crack propagation rates of both types of the stiffened panels are then compared. The analysis results show that integral stiffening causes higher stress intensity factor than conventional stiffened panel as the crack tip passes through the stringer and the integrally stiffened panel has less load bearing capability than the riveted stiffened panel.

Keywords: Conventional Stiffened Structure, Damage Tolerance, Finite Element Analysis, Integrally Stiffened Structure, Stress Intensity Factor.

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Authors: P.G. Jayathilake, B.C. Khoo, Zhijun Tan

Abstract:

A two-dimensional thin-walled capsule of a flexible semi-permeable membrane is adhered onto a rigid planar substrate under adhesive forces (derived from a potential function) in the presence of osmosis across the membrane. The capsule is immersed in a hypotonic and diluted binary solution of a non-electrolyte solute. The Stokes flow problem is solved by the immersed interface method (IIM) with equal viscosities for the enclosed and surrounding fluid of the capsule. The numerical results obtained are verified against two simplified theoretical solutions and the agreements are good. The osmotic inflation of the adhered capsule is studied as a function of the solute concentration field, hydraulic conductivity, and the initial capsule shape. Our findings indicate that the contact length shrinks in dimension as capsule inflates in the hypotonic medium, and the equilibrium contact length does not depend on the hydraulic conductivity of the membrane and the initial shape of the capsule.

Keywords: Capsule-substrate adhesion, Fluid mechanics, Immersed interface method, Osmosis, Mass transfer.

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Authors: Mahesh Chudasama, Harit Raval

Abstract:

Conical sections and shells made from metal plates are widely used in various industrial applications. 3-roller conical bending process is preferably used to produce such conical sections and shells. Bending mechanics involved in the process is complex and little work is done in this area. In the present paper an analytical model is developed to predict bending force which will be acting during 3-roller conical bending process. To verify the developed model, conical bending experiments are performed. Analytical results and experimental results were compared. Force predicted by analytical model is in close proximity of the experimental results. The error in the prediction is ±10%. Hence the model gives quite satisfactory results. Present model is also compared with the previously published bending force prediction model and it is found that the present model gives better results. The developed model can be used to estimate the bending force during 3-roller bending process and can be useful to the designers for designing the 3-roller conical bending machine.

Keywords: Bending-force, Experimental-verification, Internal-moment, Roll-bending.

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Authors: Yu Zhao, Min Zhang, Yuanqian Wang, Qiuyu Yu

Abstract:

The prediction of aesthetics of apparel is helpful for the development of a new type of apparel. This study is to build the quantitative relationship between the aesthetics and its design parameters. In particular, women’s pants have been preliminarily studied. This aforementioned relationship has been carried out by statistical analysis. The contributions of this study include the development of a more personalized apparel design mechanism and the provision of some empirical knowledge for the development of other products in the aspect of aesthetics.

Keywords: Aesthetics, crease line, cropped straight leg pants, knee width.

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Authors: Alexander Breitholz, Wolfgang Arlt, Ki-Pung Yoo

Abstract:

Group contribution based models are widely used in industrial applications for its convenience and flexibility. Although a number of group contribution models have been proposed, there were certain limitations inherent to those models. Models based on group contribution excess Gibbs free energy are limited to low pressures and models based on equation of state (EOS) cannot properly describe highly nonideal mixtures including acids without introducing additional modification such as chemical theory. In the present study new a new approach derived from quantum chemistry have been used to calculate necessary EOS group interaction parameters. The COSMO-RS method, based on quantum mechanics, provides a reliable tool for fluid phase thermodynamics. Benefits of the group contribution EOS are the consistent extension to hydrogen-bonded mixtures and the capability to predict polymer-solvent equilibria up to high pressures. The authors are confident that with a sufficient parameter matrix the performance of the lattice EOS can be improved significantly.

Keywords: COSMO-RS, Equation of State, Group contribution, Lattice Fluid, Phase equilibria.

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Authors: Malik I. Al-Amayreh, Mohammad I. Kilani, Ahmed S. Al-Salaymeh

Abstract:

This work presents a Computational Fluid Dynamics (CFD) simulation of a butterfly valve used to control the flow of combustible gas mixture in an industrial process setting.The work uses CFD simulation to analyze the flow characteristics in the vicinity of the valve, including the pressure distributions and Frequency spectrum of the pressure pulsations downstream the valves and the vortex shedding allow predicting the torque fluctuations acting on the valve shaft and the possibility of generating mechanical vibration and resonance.These fluctuations are due to aerodynamic torque resulting from fluid turbulence and vortex shedding in the valve vicinity. The valve analyzed is located in a pipeline between two opposing 90o elbows, which exposes the valve and the surrounding structure to the turbulence generated upstream and downstream the elbows at either end of the pipe.CFD simulations show that the best location for the valve from a vibration point of view is in the middle of the pipe joining the elbows.

Keywords: Butterfly Valve Vibration Analysis, Computational Fluid Dynamics, Fluid Flow Circuit Design, Fluid Mechanics.

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Authors: A. M. Pashayev, C. Ardil, D. D. Askerov, R. A. Sadiqov, P. S. Abdullayev

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In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

Keywords: Gas turbine engines, neural networks, fuzzy logic, fuzzy statistics.

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Authors: Roland Lang, Dietmar Bruckner, Rosemarie Velik, Tobias Deutsch

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Modern building automation needs to deal with very different types of demands, depending on the use of a building and the persons acting in it. To meet the requirements of situation awareness in modern building automation, scenario recognition becomes more and more important in order to detect sequences of events and to react to them properly. We present two concepts of scenario recognition and their implementation, one based on predefined templates and the other applying an unsupervised learning algorithm using statistical methods. Implemented applications will be described and their advantages and disadvantages will be outlined.

Keywords: Building automation, ubiquitous computing, scenariorecognition, surveillance system.

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: M. Jalali Azizpour, H. Mohammadi Majd

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In this paper, the effect of WC-12Co particle velocity in HVOF thermal spraying process on the coating thickness has been studied. The statistical results show that the spray distance and oxygen-to-fuel ratio are more effective factors on particle characterization and thickness of HVOF thermal spraying coatings. Spray Watch diagnostic system, scanning electron microscopy (SEM), X-ray diffraction and thickness measuring system were used for this purpose.

Keywords: Grinding, HVOF, Thermal spray, WC-Co.

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Authors: Sotiris B. Kotsiantis

Abstract:

Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.

Keywords: Regressors, statistical learning.

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Authors: Weifeng Wang, Xianwei Zeng, Jianping Ding

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Nanomaterials have attracted considerable attention during the last two decades, due to their unusual electrical, mechanical and other physical properties as compared with their bulky counterparts. The mechanical properties of nanostructured materials show strong size dependency, which has been explained within the framework of continuum mechanics by including the effects of surface stress. The size-dependent deformations of two-dimensional nanosized structures with surface effects are investigated in the paper by the finite element method. Truss element is used to evaluate the contribution of surface stress to the total potential energy and the Gurtin and Murdoch surface stress model is implemented with ANSYS through its user programmable features. The proposed approach is used to investigate size-dependent stress concentration around a nanosized circular hole and the size-dependent effective moduli of nanoporous materials. Numerical results are compared with available analytical results to validate the proposed modeling approach.

Keywords: Nanomaterials, finite element method, sizedependency, surface stress

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Authors: Shaun Cox, Michael Oakes, Stefan Wermter, Maurice Hawthorne

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We report on the results of a pilot study in which a data-mining tool was developed for mining audiology records. The records were heterogeneous in that they contained numeric, category and textual data. The tools developed are designed to observe associations between any field in the records and any other field. The techniques employed were the statistical chi-squared test, and the use of self-organizing maps, an unsupervised neural learning approach.

Keywords: Audiology, data mining, chi-squared, self-organizing maps

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Authors: Luciano Nieddu, Giuseppe Manfredi

Abstract:

In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures the information on the closed two-dimensional contour of an image, on images of industrial mineral ores.

Keywords: K-means, Industrial ores classification, Invariant Features, Supervised Classification.

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Authors: Surendran M, Palani G. S, Nagesh R. Iyer

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Multi-site damage (MSD) has been a challenge to aircraft, civil and power plant structures. In real life components are subjected to cracking at many vulnerable locations such as the bolt holes. However, we do not consider for the presence of multiple cracks. Unlike components with a single crack, these components are difficult to predict. When two cracks approach one another, their stress fields influence each other and produce enhancing or shielding effect depending on the position of the cracks. In the present study, numerical studies on fracture analysis have been conducted by using the developed code based on the modified virtual crack closure integral (MVCCI) technique and finite element analysis (FEA) software ABAQUS for computing SIF of plates with multiple cracks. Various parametric studies have been carried out and the results have been compared with literature where ever available and also with the solution, obtained by using ABAQUS. By conducting extensive numerical studies expressions for SIF have been obtained for collinear cracks and non-aligned cracks.

Keywords: Crack interaction, Fracture mechanics, Multiple site damage, stress intensity factor, collinear cracks, non-aligned cracks.

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Authors: Ε. Giovanis

Abstract:

In this paper we present a Adaptive Neuro-Fuzzy System (ANFIS) with inputs the lagged dependent variable for the prediction of Gross domestic Product growth rate in six countries. We compare the results with those of Autoregressive (AR) model. We conclude that the forecasting performance of neuro-fuzzy-system in the out-of-sample period is much more superior and can be a very useful alternative tool used by the national statistical services and the banking and finance industry.

Keywords: Autoregressive model, Forecasting, Gross DomesticProduct, Neuro-Fuzzy

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Authors: Gökhan Silahtaroğlu

Abstract:

Clustering large populations is an important problem when the data contain noise and different shapes. A good clustering algorithm or approach should be efficient enough to detect clusters sensitively. Besides space complexity, time complexity also gains importance as the size grows. Using hierarchies we developed a new algorithm to split attributes according to the values they have and choosing the dimension for splitting so as to divide the database roughly into equal parts as much as possible. At each node we calculate some certain descriptive statistical features of the data which reside and by pruning we generate the natural clusters with a complexity of O(n).

Keywords: Clustering, tree, split, pruning, entropy, gini.

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Authors: Chaudhary Itisha, Shankar Manu

Abstract:

Patient satisfaction represents a crucial aspect in the evaluation of health care services. Preoperative teaching provides the patient with pertinent information concerning the surgical process and the intended surgical procedure as well as anticipated patient behavior (anxiety, fear), expected sensation, and the probable outcomes. Although patient education is part of Accreditation protocols, it is not uniform at most places. The aim of this study was to try to assess the benefit of preoperative patient education on selected post-operative outcome parameters; mainly, post-operative pain scores, requirement of additional analgesia, return to activity of daily living and overall patient satisfaction, and try to standardize few education protocols. Dependent variables were measured before and after the treatment on a study population of 302 volunteers. Educational intervention was provided by the Investigator in the preoperative period to the study group through personal counseling. An information booklet contained detailed information was also provided. Statistical Analysis was done using Chi square test, Mann Whitney u test and Fischer Exact Test on a total of 302 subjects. P value <0.05 was considered as level of statistical significance and p<0.01 was considered as highly significant. This study suggested that patients who are given a structured, individualized and elaborate preoperative education and counseling have a better ability to cope up with postoperative pain in the immediate post-operative period. However, there was not much difference when the patients have had almost complete recovery. There was no difference in the requirement of additional analgesia among the two groups. There is a positive effect of preoperative counseling on expected return to the activities of daily living and normal work schedule. However, no effect was observed on the activities in the immediate post-operative period. There is no difference in the overall satisfaction score among the two groups of patients. Thus this study concludes that there is a positive benefit as suggested by the results for pre-operative patient education. Although the difference in various parameters studied might not be significant over a long term basis, they definitely point towards the benefits of preoperative patient education. 

Keywords: Patient education, post-operative pain, patient satisfaction, post-operative outcome.

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Authors: Shannon Steinmetz, Ellen Gethner

Abstract:

In this paper a theoretical foundation is developed to segment, analyze and associate patterns within audio. We explore this on imagery via sonified audio applied to our segmentation framework. The approach involves a geodesic estimator within the statistical manifold, parameterized by musical centricity. We demonstrate viability by processing a database of random imagery to produce statistically significant clusters of similar imagery content.

Keywords: Sonification, musical information geometry, image content extraction, automated quantification, audio segmentation, pattern recognition.

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Authors: Ahmed Shariful Alam, Abu Hena M. Mustafa Kamal, M. Abdul Rahman, M. Nasmus Sakib Khan Shabbir, Atiqul Islam

Abstract:

According to the rules of quantum mechanics there is a non-vanishing probability of for an electron to tunnel through a thin insulating barrier or a thin capacitor which is not possible according to the laws of classical physics. Tunneling of electron through a thin insulating barrier or tunnel junction is a random event and the magnitude of current flowing due to the tunneling of electron is very low. As the current flowing through a Single Electron Transistor (SET) is the result of electron tunneling through tunnel junctions of its source and drain the supply voltage requirement is also very low. As a result, the power consumption across a Single Electron Transistor is ultra-low in comparison to that of a MOSFET. In this paper simulations have been done with PSPICE for an inverter built with both SETs and MOSFETs. 35mV supply voltage was used for a SET built inverter circuit and the supply voltage used for a CMOS inverter was 3.5V.

Keywords: ITRS, enhancement type MOSFET, island, DC analysis, transient analysis, power consumption, background charge co-tunneling.

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Authors: Kourosh Nazarian

Abstract:

Many of the engineering materials, such as behavioral metals, have at least a certain level of linear behavior. It means that if the stresses are doubled, the deformations would be also doubled. In fact, these materials have linear elastic properties. Soils do not follow this law, for example, when compressed, soils become gradually tighter. On the surface of the ground, the sand can be easily deformed with a finger, but in high compressive stresses, they gain considerable hardness and strength. This is mainly due to the increase in the forces among the separate particles. Creeps also deform the soils under a constant load over time. Clay and peat soils have creep behavior. As a result of this phenomenon, structures constructed on such soils will continue their collapse over time. In this paper, the researchers analyzed and modeled the stresses and creeps in the southern plains of Kerman province in Iran through library-documentary, quantitative and software techniques, and field survey. The results of the modeling showed that these plains experienced severe stresses and had a collapse of about 26 cm in the last 15 years and also creep evidence was discovered in an area with a gradient of 3-6 degrees.

Keywords: Stress, creep, surface runoff.

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Authors: Somruay Apichatibutarapong

Abstract:

The purpose of this study was to address and comparison of the attitudes towards the statistics course for undergraduate students. Data were collected from 120 students in Faculty of Sciences and Technology, Suan Sunandha Rajabhat University who enrolled in the statistics course. The quantitative approach was used to investigate the assessment and comparison of attitudes towards statistics course. It was revealed that the overall attitudes somewhat agree both in pre-test and post-test. In addition, the comparison of students’ attitudes towards the statistic course (Form A) has no difference in the overall attitudes. However, there is statistical significance in all dimensions and overall attitudes towards the statistics course (Form B).

Keywords: Statistics attitude, Student’s attitude, Statistics, Attitude test.

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Authors: Fatiha Teklal, Bachir Kacimi, Arezki Djebbar

Abstract:

The study and application of composite materials are a truly interdisciplinary endeavor that has been enriched by contributions from chemistry, physics, materials science, mechanics and manufacturing engineering. The understanding of the interface (or interphase) in composites is the central point of this interdisciplinary effort. From the early development of composite materials of various nature, the optimization of the interface has been of major importance. Even more important, the ideas linking the properties of composites to the interface structure are still emerging. In our study, we need a direct characterization of the interface; the micromechanical tests we are addressing seem to meet this objective and we chose to use two complementary tests simultaneously. The microindentation test that can be applied to real composites and the drop test, preferred to the pull-out because of the theoretical possibility of studying systems with high adhesion (which is a priori the case with our systems). These two tests are complementary because of the principle of the model specimen used for both the first "compression indentation" and the second whose fiber is subjected to tensile stress called the drop test. Comparing the results obtained by the two methods can therefore be rewarding.

Keywords: Interface, micromechanics, pull-out, composite, fiber, matrix.

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Authors: Ernst D. Schmitter

Abstract:

Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.

Keywords: Transient signals, statistics, wavelets, neural networks

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Authors: Al Mutawa A. Amir, Liaqat Ali, Faisal Ali

Abstract:

After the World War II, the world economy was disrupted and changed due to oil and its prices. The research in this paper presents the basic statistical features and economic characteristics of the Gulf economy. The main features of the Gulf economies and its heavy dependence on oil exports, its dualism between modern and traditional sectors and its rapidly increasing affluences are particularly emphasized.  In this context, the research in this paper discussed the problems of growth versus development and has attempted to draw the implications for the future economic development of this area.

Keywords: Oil prices, Gulf Cooperation Council, economic growth, Gulf oil.

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Authors: Liping Zhou, Liang Bao, Yiqin Lin, Yimin Wei, Qinghua Wu

Abstract:

This article is devoted to the numerical solution of large-scale quadratic eigenvalue problems. Such problems arise in a wide variety of applications, such as the dynamic analysis of structural mechanical systems, acoustic systems, fluid mechanics, and signal processing. We first introduce a generalized second-order Krylov subspace based on a pair of square matrices and two initial vectors and present a generalized second-order Arnoldi process for constructing an orthonormal basis of the generalized second-order Krylov subspace. Then, by using the projection technique and the refined projection technique, we propose a restarted generalized second-order Arnoldi method and a restarted refined generalized second-order Arnoldi method for computing some eigenpairs of largescale quadratic eigenvalue problems. Some theoretical results are also presented. Some numerical examples are presented to illustrate the effectiveness of the proposed methods.

Keywords: Quadratic eigenvalue problem, Generalized secondorder Krylov subspace, Generalized second-order Arnoldi process, Projection technique, Refined technique, Restarting.

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Authors: F. Urem, K. Fertalj, Ž. Mikulić

Abstract:

This paper presents the possibilities of using Weibull statistical distribution in modeling the distribution of defects in ERP systems. There follows a case study, which examines helpdesk records of defects that were reported as the result of one ERP subsystem upgrade. The result of the applied modeling is in modeling the reliability of the ERP system from a user perspective with estimated parameters like expected maximum number of defects in one day or predicted minimum of defects between two upgrades. Applied measurement-based analysis framework is proved to be suitable in predicting future states of the reliability of the observed ERP subsystems.

Keywords: ERP, reliability, Weibull

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Authors: M. Palizvan, M. H. Sadr, M. T. Abadi

Abstract:

The representative volume element (RVE) plays a central role in the mechanics of random heterogeneous materials with a view to predicting their effective properties. In this paper, a computational homogenization methodology, developed to determine effective linear elastic properties of composite materials, is extended to predict the effective nonlinear elastoplastic response of long fiber reinforced composite. Finite element simulations of volumes of different sizes and fiber volume fractures are performed for calculation of the overall response RVE. The dependencies of the overall stress-strain curves on the number of fibers inside the RVE are studied in the 2D cases. Volume averaged stress-strain responses are generated from RVEs and compared with the finite element calculations available in the literature at moderate and high fiber volume fractions. For these materials, the existence of an RVE is demonstrated for the sizes of RVE corresponding to 10–100 times the diameter of the fibers. In addition, the response of small size RVE is found anisotropic, whereas the average of all large ones leads to recover the isotropic material properties.

Keywords: Homogenization, periodic boundary condition, elastoplastic properties, RVE.

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