Search results for: Dynamic algorithm

Authors: C. Bisu, M. Zapciu, A. Gérard

Abstract:

This paper proposes a method to vibration analysis in order to on-line monitoring and predictive maintenance during the milling process. Adapting envelope method to diagnostics and the analysis for milling tool materials is an important contribution to the qualitative and quantitative characterization of milling capacity and a step by modeling the three-dimensional cutting process. An experimental protocol was designed and developed for the acquisition, processing and analyzing three-dimensional signal. The vibration envelope analysis is proposed to detect the cutting capacity of the tool with the optimization application of cutting parameters. The research is focused on Hilbert transform optimization to evaluate the dynamic behavior of the machine/ tool/workpiece.

Keywords: diagnostics, envelope, milling, vibration

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Authors: Teodora Bakardjieva, Galya Gercheva

Abstract:

In this paper an open agent-based modular framework for personalized and adaptive curriculum generation in e-learning environment is proposed. Agent-based approaches offer several potential advantages over alternative approaches. Agent-based systems exhibit high levels of flexibility and robustness in dynamic or unpredictable environments by virtue of their intrinsic autonomy. The presented framework enables integration of different types of expert agents, various kinds of learning objects and user modeling techniques. It creates possibilities for adaptive e-learning process. The KM e-learning system is in a process of implementation in Varna Free University and will be used for supporting the educational process at the University.

Keywords: agents, e-Learning, knowledge management, knowledge sharing, artificial intelligence

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Authors: Cristian Chacha, David Asiain, Jesús Ponce de León, José Ramón Beltrán

Abstract:

This work explores and characterizes the behavior of the AFE AD5941 in impedance measurement using an embedded algorithm that allows using a constant current AC source. The main aim of this research is to improve the exact measurement of impedance values for their application in EDA-focused wearable devices. Through comprehensive study and characterization, it has been observed that employing a measurement sequence with a constant current source produces results with increased dispersion but higher accuracy and a more linear behavior with respect to error. As a result, this approach leads to a more accurate system for impedance measurement.

Keywords: Electrodermal Activity, constant current AC source, wearable, precision, accuracy, impedance.

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Authors: N. Bhalaji, A. R. Sivaramkrishnan, Sinchan Banerjee, V. Sundar, A. Shanmugam

Abstract:

Nodes in mobile Ad Hoc Network (MANET) do not rely on a central infrastructure but relay packets originated by other nodes. Mobile ad hoc networks can work properly only if the participating nodes collaborate in routing and forwarding. For individual nodes it might be advantageous not to collaborate, though. In this conceptual paper we propose a new approach based on relationship among the nodes which makes them to cooperate in an Adhoc environment. The trust unit is used to calculate the trust values of each node in the network. The calculated trust values are being used by the relationship estimator to determine the relationship status of nodes. The proposed enhanced protocol was compared with the standard DSR protocol and the results are analyzed using the network simulator-2.

Keywords: Reliable Routing, DSR, Grudger, Adhoc network.

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Authors: Pradya Pornnimitkul, Suwich Kunaruttanapruk, Bamrung Tau Sieskul, Somchai Jitapunkul

Abstract:

In this paper, we investigate a blind channel estimation method for Multi-carrier CDMA systems that use a subspace decomposition technique. This technique exploits the orthogonality property between the noise subspace and the received user codes to obtain channel of each user. In the past we used Singular Value Decomposition (SVD) technique but SVD have most computational complexity so in this paper use a new algorithm called URV Decomposition, which serve as an intermediary between the QR decomposition and SVD, replaced in SVD technique to track the noise space of the received data. Because of the URV decomposition has almost the same estimation performance as the SVD, but has less computational complexity.

Keywords: Channel estimation, MC-CDMA, SVD, URV.

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi

Abstract:

In this paper a real-time obstacle avoidance approach for both autonomous and non-autonomous dynamical systems (DS) is presented. In this approach the original dynamics of the controller which allow us to determine safety margin can be modulated. Different common types of DS increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle especially when robot moves very fast in changeable complex environments. The method is validated by simulation and influence of different autonomous and non-autonomous DS such as important characteristics of limit cycles and unstable DS. Furthermore, the position of different obstacles in complex environment is explained. Finally, the verification of avoidance trajectories is described through different parameters such as safety factor.

Keywords: Limit cycles, Nonlinear dynamical system, Real time obstacle avoidance.

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Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

Abstract:

Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: Cooperative networks, normalized capacity, sensing time.

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Authors: A. Jabbari, R. Jedermann, W. Lang

Abstract:

The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.

Keywords: Fault detection and Isolation, Neural network, Temperature measurement, measurement approximation and classification.

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Authors: Yi Feng, Jingwen Li, Lei Huang, Changping Liu

Abstract:

In this paper we proposed a novel method to acquire the ROI (Region of interest) of unsupervised and touch-less palmprint captured from a web camera in real-time. We use Viola-Jones approach and skin model to get the target area in real time. Then an innovative course-to-fine approach to detect the key points on the hand is described. A new algorithm is used to find the candidate key points coarsely and quickly. In finely stage, we verify the hand key points with the shape context descriptor. To make the user much comfortable, it can process the hand image with different poses, even the hand is closed. Experiments show promising result by using the proposed method in various conditions.

Keywords: Palmprint recoginition, hand detection, touch-lesspalmprint, ROI localization.

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Authors: Ae Hee Park, So Hyun Park, Hee Yong Youn

Abstract:

Multi-agent system is composed by several agents capable of reaching the goal cooperatively. The system needs an agent platform for efficient and stable interaction between intelligent agents. In this paper we propose a flexible and scalable agent platform by composing the containers with multiple hierarchical agent groups. It also allows efficient implementation of multiple domain presentations of the agents unlike JADE. The proposed platform provides both group management and individual management of agents for efficiency. The platform has been implemented and tested, and it can be used as a flexible foundation of the dynamic multi-agent system targeting seamless delivery of ubiquitous services.

Keywords: Agent platform, container, multi-agent system, services, ubiquitous computing

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Authors: Xia Huang, Wenhui Tang, Banghai Jiang, Xianwen Ran

Abstract:

In this paper, a plane-strain orthotropic elasto-plastic dynamic constitutive model is established, and with this constitutive model, the thermal shock wave induced by intense pulsed X-ray radiation in cylinder shell composite is simulated by the finite element code, then the properties of thermal shock wave propagation are discussed. The results show that the thermal shock wave exhibit different shapes under the radiation of soft and hard X-ray, and while the composite is radiated along different principal axes, great differences exist in some aspects, such as attenuation of the peak stress value, spallation and so on.

Keywords: anisotropic constitutive model, thermal shock wave, X-ray, cylinder shell composite.

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Authors: Rajoo Pandey

Abstract:

The performance of an image filtering system depends on its ability to detect the presence of noisy pixels in the image. Most of the impulse detection schemes assume the presence of salt and pepper noise in the images and do not work satisfactorily in case of uniformly distributed impulse noise. In this paper, a new algorithm is presented to improve the performance of switching median filter in detection of uniformly distributed impulse noise. The performance of the proposed scheme is demonstrated by the results obtained from computer simulations on various images.

Keywords: Switching median filter, Impulse noise, Imagefiltering, Impulse detection.

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Authors: Kefaya Qaddoum

Abstract:

The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: Neural network, conformal prediction, cancer classification, regression.

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Authors: Ahmad M. Sarhan, Omar I. Al Helalat

Abstract:

In this paper, an Arabic letter recognition system based on Artificial Neural Networks (ANNs) and statistical analysis for feature extraction is presented. The ANN is trained using the Least Mean Squares (LMS) algorithm. In the proposed system, each typed Arabic letter is represented by a matrix of binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input matrix, are fed to an ANN. Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the current ANN solutions.

Keywords: ANN, Backpropagation, Gaussian, LMS, MSE, Neuron, standard deviation, Widrow-Hoff rule.

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Authors: Fu Hao, Sun Gang, Tang Laiying, Cui Junfeng

Abstract:

To solve the quick and accurate level-adjusting problem in the process of spacecraft precise mating, automatic leveling and equalizing hoist device for spacecraft is developed. Based on lifting point adjustment by utilizing XY-workbench, the leveling and equalizing controller by a self-adaptive control algorithm is proposed. By simulation analysis and lifting test using engineering prototype, validity and reliability of the hoist device is verified, which can meet the precision mating requirements of practical applications for spacecraft.

Keywords: automatic leveling and equalizing, hoist device, lifting point adjustment, self-adaptive control

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Authors: S. W. Lo, C.-H. Yu

Abstract:

A new design of aerostatic thrust bearing is proposed for high static stiffness. The bearing body, which is mead of polymer covered with metallic membrane, is held by a circular ring. Such a support helps form a concave air gap to grasp the air pressure. The polymer body, which can be made rapidly by either injection or molding is able to provide extra damping under dynamic loading. The smooth membrane not only serves as the bearing surface but also protects the polymer body. The restrictor is a capillary inside a silicone tube. It can passively compensate the variation of load by expanding the capillary diameter for more air flux. In the present example, the stiffness soars from 15.85 N/μm of typical bearing to 349.85 N/μm at bearing elevation 9.5 μm; meanwhile the load capacity also enhances from 346.86 N to 704.18 N.

Keywords: Aerostatic, bearing, polymer, static stiffness.

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Authors: László Lengyel, Tihamér Levendovszky, Hassan Charaf

Abstract:

This paper presents the visual control flow support of Visual Modeling and Transformation System (VMTS), which facilitates composing complex model transformations out of simple transformation steps and executing them. The VMTS Visual Control Flow Language (VCFL) uses stereotyped activity diagrams to specify control flow structures and OCL constraints to choose between different control flow branches. This work discusses the termination properties of VCFL and provides an algorithm to support the termination analysis of VCFL transformations.

Keywords: Control Flow, Metamodel-Based Visual Model Transformation, OCL, Termination Properties, UML.

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Authors: G. Candel, D. Naccache

Abstract:

t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embedding. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic, and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n2) to O(n2/k), and the memory requirement from n2 to 2(n/k)2 which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: Concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning.

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Authors: M. Altekin, R. F. Yükseler

Abstract:

Geometrically nonlinear axisymmetric bending of a shallow spherical shell with a point support at the apex under linearly varying axisymmetric load was investigated numerically. The edge of the shell was assumed to be simply supported or clamped. The solution was obtained by the finite difference and the Newton-Raphson methods. The thickness of the shell was considered to be uniform and the material was assumed to be homogeneous and isotropic. Sensitivity analysis was made for two geometrical parameters. The accuracy of the algorithm was checked by comparing the deflection with the solution of point supported circular plates and good agreement was obtained.

Keywords: Bending, nonlinear, plate, point support, shell.

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Authors: Khaled M. EL-Naggar, Khaled A. AL-Rumaih

Abstract:

This paper presents performance comparison of three estimation techniques used for peak load forecasting in power systems. The three optimum estimation techniques are, genetic algorithms (GA), least error squares (LS) and, least absolute value filtering (LAVF). The problem is formulated as an estimation problem. Different forecasting models are considered. Actual recorded data is used to perform the study. The performance of the above three optimal estimation techniques is examined. Advantages of each algorithms are reported and discussed.

Keywords: Forecasting, Least error squares, Least absolute Value, Genetic algorithms

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Authors: U. Yavas, M. Gokasan

Abstract:

Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.

Keywords: Predictive control, engine control, engine modeling, PID control, feedforward compensation.

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Authors: Thiago M. R. Dias, Gray F. Moita, Paulo E. M. Almeida

Abstract:

Although the World Wide Web is considered the largest source of information there exists nowadays, due to its inherent dynamic characteristics, the task of finding useful and qualified information can become a very frustrating experience. This study presents a research on the information mining systems in the Web; and proposes an implementation of these systems by means of components that can be built using the technology of Web services. This implies that they can encompass features offered by a services oriented architecture (SOA) and specific components may be used by other tools, independent of platforms or programming languages. Hence, the main objective of this work is to provide an architecture to Web mining systems, divided into stages, where each step is a component that will incorporate the characteristics of SOA. The separation of these steps was designed based upon the existing literature. Interesting results were obtained and are shown here.

Keywords: Web Mining, Service Oriented Architecture, WebServices.

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Authors: Yong Zhang, Ruimin Hu

Abstract:

This paper presents a vocoder to obtain high quality synthetic speech at 600 bps. To reduce the bit rate, the algorithm is based on a sinusoidally excited linear prediction model which extracts few coding parameters, and three consecutive frames are grouped into a superframe and jointly vector quantization is used to obtain high coding efficiency. The inter-frame redundancy is exploited with distinct quantization schemes for different unvoiced/voiced frame combinations in the superframe. Experimental results show that the quality of the proposed coder is better than that of 2.4kbps LPC10e and achieves approximately the same as that of 2.4kbps MELP and with high robustness.

Keywords: Speech coding, Vector quantization, linear predicition, Mixed sinusoidal excitation

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Authors: V. Keim, J. Spachtholz, J. Hammer

Abstract:

The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: Complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation.

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Authors: C. Perez, O. Reinoso, N. Garcia, J. M. Sabater, L. Gracia

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For high-speed control of robots, a good knowledge of system modelling is necessary to obtain the desired bandwidth. In this paper, we present a cartesian robot with a pan/tilt unit in end-effector (5 dof). This robot is implemented with powerful direct drive AC induction machines. The dynamic model, parameter identification and model validation of the robot are studied (including actuators). This work considers the cartesian robot coupled and non linear (contrary to normal considerations for this type of robots). The mechanical and control architecture proposed in this paper is efficient for industrial and research application in which high speed, well known model and very high accuracy are required.

Keywords: Robot modelling, parameter identification and validation, AC servo-motors.

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Authors: Travis Wiens, Greg Schoenau, Rich Burton

Abstract:

It is well known that a linear dynamic system including a delay will exhibit limit cycle oscillations when a bang-bang sensor is used in the feedback loop of a PID controller. A similar behaviour occurs when a delayed feedback signal is used to train a neural network. This paper develops a method of predicting this behaviour by linearizing the system, which can be shown to behave in a manner similar to an integral controller. Using this procedure, it is possible to predict the characteristics of the neural network driven limit cycle to varying degrees of accuracy, depending on the information known about the system. An application is also presented: the intelligent control of a spark ignition engine.

Keywords: Control and automation, artificial neural networks, limit cycle

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Authors: M. H. Omar

Abstract:

Cheating on standardized tests has been a major concern as it potentially minimizes measurement precision. One major way to reduce cheating by collusion is to administer multiple forms of a test. Even with this approach, potential collusion is still quite large. A Latin-square treatment structure for distributing multiple forms is proposed to further reduce the colluding potential. An index to measure the extent of colluding potential is also proposed. Finally, with a simple algorithm, the various Latin-squares were explored to find the best structure to keep the colluding potential to a minimum.

Keywords: Colluding pairs, Scale for Colluding Potential, Latin-Square Structure, Minimization of Cheating.

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Authors: Wartika, Kridanto Surendro, Husni Sastramiharja, Iping Supriana S.

Abstract:

The condition of the market is currently very dynamic, demanding organizations which is use system information to support the achievement of objectives should be necessarily improve the ability of information systems in accordance with the changes. Improved information systems capabilities need to align with the resource capabilities in internal environment of the organization, and vice versa. Alignment model between information systems and environment organizational in this capability perspective is expected can assist management in making the strategy for enhance the capability of information systems in accordance with resources internally within the organization, efficiency in the process of development, and optimization of contributions information systems in achieving organizational goals.

Keywords: Capability, alignment, information system, environmental organizations.

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Authors: Hyoungseob Lee, Donghyun Choi, Yunho Lee, Dongho Won, Seungjoo Kim

Abstract:

Recently, with the appearance of smart cards, many user authentication protocols using smart card have been proposed to mitigate the vulnerabilities in user authentication process. In 2004, Das et al. proposed a ID-based user authentication protocol that is secure against ID-theft and replay attack using smart card. In 2009, Wang et al. showed that Das et al.-s protocol is not secure to randomly chosen password attack and impersonation attack, and proposed an improved protocol. Their protocol provided mutual authentication and efficient password management. In this paper, we analyze the security weaknesses and point out the vulnerabilities of Wang et al.-s protocol.

Keywords: Message Alteration Attack, Impersonation Attack

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Authors: Parastou Kharazmi, Folke Björk

Abstract:

Some of the main causes for degradation of polymeric materials are thermal aging, hydrolysis, oxidation or chemical degradation by acids, alkalis or water. The first part of this paper provides a brief summary of advances in technology, methods and specification of composite materials for relining as a rehabilitation technique for sewage systems. The second part summarizes an investigation on frequently used composite materials for relining in Sweden, the rubber filled epoxy composite and reinforced polyester composite when they were immersed in deionized water or in dry conditions, and elevated temperatures up to 80°C in the laboratory. The tests were conducted by visual inspection, microscopy, Dynamic Mechanical Analysis (DMA), Differential Scanning Calorimetry (DSC) as well as mechanical testing, three point bending and tensile testing.

Keywords: Composite, epoxy, polyester, relining, sewage.

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