Search results for: Fault prediction

Authors: T.P. Andamuthu, Dr. P. Balasubramanie

Abstract:

The intermittent connectivity modifies the “always on" network assumption made by all the distributed query processing systems. In modern- day systems, the absence of network connectivity is considered as a fault. Since the last upload, it might not be feasible to transmit all the data accumulated right away over the available connection. It is possible that vital information may be delayed excessively when the less important information takes place of the vital information. Owing to the restricted and uneven bandwidth, it is vital that the mobile nodes make the most advantageous use of the connectivity when it arrives. Hence, in order to select the data that needs to be transmitted first, some sort of data prioritization is essential. A continuous query processing system for intermittently connected mobile networks that comprises of a delaytolerant continuous query processor distributed across the mobile hosts has been proposed in this paper. In addition, a mechanism for prioritizing query results has been designed that guarantees enhanced accuracy and reduced delay. It is illustrated that our architecture reduces the client power consumption, increases query efficiency by the extensive simulation results.

Keywords: Broadcast, Location, Mobile host, Mobility, Query.

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Authors: Sidhartha Panda, N. P. Padhy

Abstract:

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to design a robust power system stabilizer (PSS). The design problem of the proposed controller is formulated as an optimization problem and PSO is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. Further, all the simulations results are compared with a conventionally designed power system stabilizer to show the superiority of the proposed design approach.

Keywords: Particle swarm optimization, power system stabilizer, low frequency oscillations, power system stability.

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Authors: F. Caliskan

Abstract:

This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.

Keywords: Aircraft Icing, Stability Derivatives, Neural NetworkIdentification, Reconfiguration.

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Authors: Saad Chakkor, Mostafa Baghouri, Abderrahmane Hajraoui

Abstract:

In new energy development, wind power has boomed. It is due to the proliferation of wind parks and their operation in supplying the national electric grid with low cost and clean resources. Hence, there is an increased need to establish a proactive maintenance for wind turbine machines based on remote control and monitoring. That is necessary with a real-time wireless connection in offshore or inaccessible locations while the wired method has many flaws. The objective of this strategy is to prolong wind turbine lifetime and to increase productivity. The hardware of a remote control and monitoring system for wind turbine parks is designed. It takes advantage of GPRS or Wi-Max wireless module to collect data measurements from different wind machine sensors through IP based multi-hop communication. Computer simulations with Proteus ISIS and OPNET software tools have been conducted to evaluate the performance of the studied system. Study findings show that the designed device is suitable for application in a wind park.

Keywords: Embedded System, Monitoring, Wind Turbine, Faults Diagnosis, TCP/IP Protocol, Real Time, Web.

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Authors: D. Satish Kumar, S. Karthik

Abstract:

A dual tiered network model is designed to overcome the problem of energy alert and fault tolerance. This model minimizes the delay time and overcome failure of links. Performance analysis of the dual tiered network model is studied in this paper where the CA and LS schemes are compared with DEO optimal. We then evaluate  the Integrated Network Topological Control and Key Management (INTK) Schemes, which was proposed to add security features of the wireless sensor networks. Clustering efficiency, level of protections, the time complexity is some of the parameters of INTK scheme that were analyzed. We then evaluate the Cluster based Energy Competent n-coverage scheme (CEC n-coverage scheme) to ensure area coverage for wireless sensor networks.

Keywords: CEC n-coverage scheme, Clustering efficiency, Dual tired network, Wireless sensor networks.

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Authors: Awadhesh Kumar Singh

Abstract:

Checkpointing is one of the commonly used techniques to provide fault-tolerance in distributed systems so that the system can operate even if one or more components have failed. However, mobile computing systems are constrained by low bandwidth, mobility, lack of stable storage, frequent disconnections and limited battery life. Hence, checkpointing protocols having lesser number of synchronization messages and fewer checkpoints are preferred in mobile environment. There are two different approaches, although not orthogonal, to checkpoint mobile computing systems namely, time-based and index-based. Our protocol is a fusion of these two approaches, though not first of its kind. In the present exposition, an index-based checkpointing protocol has been developed, which uses time to indirectly coordinate the creation of consistent global checkpoints for mobile computing systems. The proposed algorithm is non-blocking, adaptive, and does not use any control message. Compared to other contemporary checkpointing algorithms, it is computationally more efficient because it takes lesser number of checkpoints and does not need to compute dependency relationships. A brief account of important and relevant works in both the fields, time-based and index-based, has also been included in the presentation.

Keywords: Checkpointing, forced checkpoint, mobile computing, recovery, time-coordinated.

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Authors: N. Šarlija, S. Pfeifer, M. Jeger, A. Bilandžić

Abstract:

Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.

Keywords: Growth measurement constructs, logistic regression, prediction of growth potential, small and medium-sized enterprises.

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Authors: Wang Yichen, Haruka Yamashita

Abstract:

In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: Recurrent Neural Network, players lineup, basketball data, decision making model.

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Authors: Rafik Medjoudj, Rabah Medjoudj, D. Aissani

Abstract:

The electrical substation components are often subject to degradation due to over-voltage or over-current, caused by a short circuit or a lightning. A particular interest is given to the circuit breaker, regarding the importance of its function and its dangerous failure. This component degrades gradually due to the use, and it is also subject to the shock process resulted from the stress of isolating the fault when a short circuit occurs in the system. In this paper, based on failure mechanisms developments, the wear out of the circuit breaker contacts is modeled. The aim of this work is to evaluate its reliability and consequently its residual lifetime. The shock process is based on two random variables such as: the arrival of shocks and their magnitudes. The arrival of shocks was modeled using homogeneous Poisson process (HPP). By simulation, the dates of short-circuit arrivals were generated accompanied with their magnitudes. The same principle of simulation is applied to the amount of cumulative wear out contacts. The objective reached is to find the formulation of the wear function depending on the number of solicitations of the circuit breaker.

Keywords: reliability, short-circuit, models of shocks.

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Authors: Maysam Saidi, Reza Maddahian, Bijan Farhanieh

Abstract:

In this research a comparison between k-epsilon and LES model for a deoiling hydrocyclone is conducted. Flow field of hydrocyclone is obtained by three-dimensional simulations with OpenFOAM code. Potential of prediction for both methods of this complex swirl flow is discussed. Large eddy simulation method results have more similarity to experiment and its results are presented in figures from different hydrocyclone cross sections.

Keywords: Deoiling hydrocyclones, k-epsilon model, Largeeddy simulation, OpenFOAM

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Authors: Sadaoui Djaouida

Abstract:

In the paper, the predictive control method is proposed to control the synchronization of two perturbed satellites attitude motion. Based on delayed feedback control of continuous-time systems combines with the prediction-based method of discrete-time systems, this approach only needs a single controller to realize synchronization, which has considerable significance in reducing the cost and complexity for controller implementation.

Keywords: Predictive control, Synchronization, Satellite attitude.

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Authors: Sheela Tiwari, R. Naresh, R. Jha

Abstract:

The paper presents an investigation in to the effect of neural network predictive control of UPFC on the transient stability performance of a multimachine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers, and an improved damping of the power oscillations as compared to the conventional PI controller.

Keywords: Identification, Neural networks, Predictive control, Transient stability, UPFC.

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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: Yoshio Kurosawa

Abstract:

The applications of soundproof materials for reduction of high frequency automobile interior noise have been researched. This paper presents a sound pressure prediction technique including wind noise by Hybrid Statistical Energy Analysis (HSEA) in order to reduce weight of acoustic insulations. HSEA uses both analytical SEA and experimental SEA. As a result of chassis dynamo test and road test, the validity of SEA modeling was shown, and utility of the method was confirmed.

Keywords: Vibration, noise, car, statistical energy analysis.

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Authors: Roohi Shabrin S., Devi Prasad B., Prabu D., Pallavi R. S., Revathi P.

Abstract:

Due to memory leaks, often-valuable system memory gets wasted and denied for other processes thereby affecting the computational performance. If an application-s memory usage exceeds virtual memory size, it can leads to system crash. Current memory leak detection techniques for clusters are reactive and display the memory leak information after the execution of the process (they detect memory leak only after it occur). This paper presents a Dynamic Memory Monitoring Agent (DMMA) technique. DMMA framework is a dynamic memory leak detection, that detects the memory leak while application is in execution phase, when memory leak in any process in the cluster is identified by DMMA it gives information to the end users to enable them to take corrective actions and also DMMA submit the affected process to healthy node in the system. Thus provides reliable service to the user. DMMA maintains information about memory consumption of executing processes and based on this information and critical states, DMMA can improve reliability and efficaciousness of cluster computing.

Keywords: Dynamic Memory Monitoring Agent (DMMA), Cluster Computing, Memory Leak, Fault Tolerant Framework, Dynamic Memory Leak Detection (DMLD).

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Authors: Byung-kyoo Jung, Weui-bong Jeong

Abstract:

In most cases, it is considerably difficult to directly measure structural vibration with a lot of sensors because of complex geometry, time and equipment cost. For this reason, this paper deals with the problem of locating sensors on a plate model by four advanced sensor placement optimization (S.P.O) techniques. It also suggests the evaluation index representing the characteristic of orthogonal between each of natural modes. The index value provides the assistance to selecting of proper S.P.O technique and optimal positions for monitoring of dynamic systems without the experiment.

Keywords: Genetic algorithm, Modal assurance criterion, Sensor placement optimization.

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

Abstract:

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

 

Keywords: Equation of state, modification, ammonia, genetic algorithm.

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Authors: N. Rugthaicharoencheep, A. Charlangsut, B. Ainsuk, A. Phayomhom

Abstract:

This paper presents the significant factor and give some suggestion that should know before design. The main objective of this paper is guide the first step for someone who attends to design of grounding system before study in details later. The overview of grounding system can protect damage from fault such as can save a human life and power system equipment. The unsafe conditions have three cases. Case 1) maximum touch voltage exceeds the safety criteria. In this case, the conductor compression ratio of the ground gird should be first adjusted to have optimal spacing of ground grid conductors. If it still over limit, earth resistivity should be consider afterward. Case 2) maximum step voltage exceeds the safety criteria. In this case, increasing the number of ground grid conductors around the boundary can solve this problem. Case 3) both of maximum touch and step voltage exceed the safety criteria. In this case, follow the solutions explained in case 1 and case 2. Another suggestion, vary depth of ground grid until maximum step and touch voltage do not exceed the safety criteria.

Keywords: Grounding System, Touch Voltage, Step Voltage, Safety Criteria.

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Authors: S.G. Srivani, Chandrasekhar Reddy Atla, K.P.Vittal

Abstract:

This paper presents the development of adaptive distance relay for protection of parallel transmission line with mutual coupling. The proposed adaptive relay, automatically adjusts its operation based on the acquisition of the data from distance relay of adjacent line and status of adjacent line from line circuit breaker IED (Intelligent Electronic Device). The zero sequence current of the adjacent parallel transmission line is used to compute zero sequence current ratio and the mutual coupling effect is fully compensated. The relay adapts to changing circumstances, like failure in communication from other relays and non - availability of adjacent transmission line. The performance of the proposed adaptive relay is tested using steady state and dynamic test procedures. The fault transients are obtained by simulating a realistic parallel transmission line system with mutual coupling effect in PSCAD. The evaluation test results show the efficacy of adaptive distance relay over the conventional distance relay.

Keywords: Adaptive relaying, distance measurement, mutualcoupling, quadrilateral trip characteristic, zones of protection.

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Authors: Ghalem Belalem, Yahya Slimani

Abstract:

Large scale systems such as computational Grid is a distributed computing infrastructure that can provide globally available network resources. The evolution of information processing systems in Data Grid is characterized by a strong decentralization of data in several fields whose objective is to ensure the availability and the reliability of the data in the reason to provide a fault tolerance and scalability, which cannot be possible only with the use of the techniques of replication. Unfortunately the use of these techniques has a height cost, because it is necessary to maintain consistency between the distributed data. Nevertheless, to agree to live with certain imperfections can improve the performance of the system by improving competition. In this paper, we propose a multi-layer protocol combining the pessimistic and optimistic approaches conceived for the data consistency maintenance in large scale systems. Our approach is based on a hierarchical representation model with tree layers, whose objective is with double vocation, because it initially makes it possible to reduce response times compared to completely pessimistic approach and it the second time to improve the quality of service compared to an optimistic approach.

Keywords: Data Grid, replication, consistency, optimistic approach, pessimistic approach.

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Authors: Mohammad Jafarifar

Abstract:

Multiphase Induction Machine (IM) is normally controlled using rotor field oriented vector control. Under phase(s) loss, the machine currents can be optimally controlled to satisfy certain optimization criteria. In this paper we discuss the performance of double manifold sliding mode observer (DM-SMO) in Sensorless control of multiphase induction machine under unsymmetrical condition (one phase loss). This observer is developed using the IM model in the stationary reference frame. DM-SMO is constructed by adding extra feedback term to conventional single mode sliding mode observer (SM-SMO) which proposed in many literature. This leads to a fully convergent observer that also yields an accurate estimate of the speed and stator currents. It will be shown by the simulation results that the estimated speed and currents by the method are very well and error between real and estimated quantities is negligible. Also parameter sensitivity analysis shows that this method is rather robust against parameter variation.

Keywords: Multiphase induction machine, field oriented control, sliding mode, unsymmetrical condition, manifold.

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Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

Abstract:

Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: Banking system, data envelopment analysis, DEA, integrated resilience engineering, IRE, performance evaluation, perturbation analysis.

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Authors: R. B. Mishra

Abstract:

Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.

Keywords: BDI, HMM, neural activation, optimal states, working conditions.

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Authors: Chei-Chang Chiou, Sen-Wei Wang, Yu-Min Wang

Abstract:

The purpose of this study is to investigate the relationship between corporate governance and pricing for initial public offerings (IPOs). Empirical result finds that the prediction of pricing of IPOs with corporate governance added can have a rather higher degree of predicting accuracy than that of non governance added during the training and testing samples. Therefore, it can be observed that corporate governance mechanism can affect the pricing of IPOs

Keywords: Artificial neural networks, corporate governance, initial public offerings.

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Authors: WooYoung Jung, HoYoung Son

Abstract:

This study presented to reduce earthquake damage and emergency rehabilitation of critical structures such as schools, hightech factories, and hospitals due to strong ground motions associated with climate changes. Regarding recent trend, a strong earthquake causes serious damage to critical structures and then the critical structure might be influenced by sequence aftershocks (or tsunami) due to fault plane adjustments. Therefore, in order to improve seismic performance of critical structures, retrofitted or strengthening study of the structures under aftershocks sequence after emergency rehabilitation of the structures subjected to strong earthquakes is widely carried out. Consequently, this study used composite material for emergency rehabilitation of the structure rather than concrete and steel materials because of high strength and stiffness, lightweight, rapid manufacturing, and dynamic performance. Also, this study was to develop or improve the seismic performance or seismic retrofit of critical structures subjected to strong ground motions and earthquake aftershocks, by utilizing GFRP-Corrugated Infill Panels (GCIP).

Keywords: Composite material, GFRP, Infill Panel, Aftershock, Seismic Retrofitting.

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Authors: A. M. Tahsini, S. A. Hosseini

Abstract:

In the present study, the surface temperature history of the adaptor part in a two-stage supersonic launch vehicle is accurately predicted. The full Navier-Stokes equations are used to estimate the aerodynamic heat flux and the one-dimensional heat conduction in solid phase is used to compute the temperature history. The instantaneous surface temperature is used to improve the applied heat flux, to improve the accuracy of the results.

Keywords: Aerodynamic heating, Heat conduction, Numerical simulation, Supersonic flight, Launch vehicle.

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Authors: A. Chidley, F. Roger, A. Traidia

Abstract:

A method is presented for using thermo-mechanical fatigue analysis as a tool in the design of automotive heat exchangers. Use of infra-red thermography to measure the real thermal history in the heat exchanger reduces the time necessary for calculating design parameters and improves prediction accuracy. Thermal shocks are the primary cause of heat exchanger damage. Thermo-mechanical simulation is based on the mean behavior of the aluminum tubes used in the heat exchanger. An energetic fatigue criterion is used to detect critical zones.

Keywords: Heat exchanger, Fatigue, Thermal shocks. I.

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Authors: S. Panda, N. P. Patidar, R. Singh

Abstract:

Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.

Keywords: Real-Coded Genetic Algorithm (RCGA), Static Var Compensator (SVC), Power System Stabilizer (PSS), Low Frequency Oscillations, Power System Stability.

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Authors: Sidhartha Panda, N. P. Padhy, R.N.Patel

Abstract:

In this paper, genetic algorithm (GA) opmization technique is applied to design Flexible AC Transmission System (FACTS)-based damping controllers. Two types of controller structures, namely a proportional-integral (PI) and a lead-lag (LL) are considered. The design problem of the proposed controllers is formulated as an optimization problem and GA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The proposed controllers are tested on a weakly connected power system subjected to different disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC-based controllers improve greatly the voltage profile of the system under severe disturbances. Further, the dynamic performances of both the PI and LL structured FACTS-controller are analyzed at different loading conditions and under various disturbance condition as well as under unbalanced fault conditions..

Keywords: Genetic algorithm, proportional-integral controller, lead-lag controller, power system stability, FACTS.

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