Search results for: Multistage Detectors (MSD)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 107

Search results for: Multistage Detectors (MSD)

17 Status Report of the GERDA Phase II Startup

Authors: Valerio D’Andrea

Abstract:

The GERmanium Detector Array (GERDA) experiment, located at the Laboratori Nazionali del Gran Sasso (LNGS) of INFN, searches for 0νββ of 76Ge. Germanium diodes enriched to ∼ 86 % in the double beta emitter 76Ge(enrGe) are exposed being both source and detectors of 0νββ decay. Neutrinoless double beta decay is considered a powerful probe to address still open issues in the neutrino sector of the (beyond) Standard Model of particle Physics. Since 2013, just after the completion of the first part of its experimental program (Phase I), the GERDA setup has been upgraded to perform its next step in the 0νββ searches (Phase II). Phase II aims to reach a sensitivity to the 0νββ decay half-life larger than 1026 yr in about 3 years of physics data taking. This exposing a detector mass of about 35 kg of enrGe and with a background index of about 10^−3 cts/(keV·kg·yr). One of the main new implementations is the liquid argon scintillation light read-out, to veto those events that only partially deposit their energy both in Ge and in the surrounding LAr. In this paper, the GERDA Phase II expected goals, the upgrade work and few selected features from the 2015 commissioning and 2016 calibration runs will be presented. The main Phase I achievements will be also reviewed.

Keywords: Gerda, double beta decay, germanium, LNGS.

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16 Behavioral Response of Bee Farmers to Climate Change in South East, Nigeria

Authors: Jude A. Mbanasor, Chigozirim N. Onwusiribe

Abstract:

The enigma climate change is no longer an illusion but a reality. In the recent years, the Nigeria climate has changed and the changes are shown by the changing patterns of rainfall, the sunshine, increasing level carbon and nitrous emission as well as deforestation. This study analyzed the behavioural response of bee keepers to variations in the climate and the adaptation techniques developed in response to the climate variation. Beekeeping is a viable economic activity for the alleviation of poverty as the products include honey, wax, pollen, propolis, royal jelly, venom, queens, bees and their larvae and are all marketable. The study adopted the multistage sampling technique to select 120 beekeepers from the five states of Southeast Nigeria. Well-structured questionnaires and focus group discussions were adopted to collect the required data. Statistical tools like the Principal component analysis, data envelopment models, graphs, and charts were used for the data analysis. Changing patterns of rainfall and sunshine with the increasing rate of deforestation had a negative effect on the habitat of the bees. The bee keepers have adopted the Kenya Top bar and Langstroth hives and they establish the bee hives on fallow farmland close to the cultivated communal farms with more flowering crops.

Keywords: Climate, smart, smallholder, farmer, socioeconomic, response.

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15 Effect of Valve Pressure Drop in Exergy Analysis of C2+ Recovery Plants Refrigeration Cycles

Authors: B. Tirandazi, M. Mehrpooya, A. Vatani

Abstract:

This paper provides an exergy analysis of the multistage refrigeration cycle used for C2+ recovery plant. The behavior of an industrial refrigeration cycle with refrigerant propane has been investigated by the exergy method. A computational model based on the exergy analysis is presented for the investigation of the effects of the valves on the exergy losses, the second law of efficiency, and the coefficient of performance (COP) of a vapor compression refrigeration cycle. The equations of exergy destruction and exergetic efficiency for the main cycle components such as evaporators, condensers, compressors, and expansion valves are developed. The relations for the total exergy destruction in the cycle and the cycle exergetic efficiency are obtained. An ethane recovery unit with its refrigeration cycle has been simulated to prepare the exergy analysis. Using a typical actual work input value; the exergetic efficiency of the refrigeration cycle is determined to be 39.90% indicating a great potential for improvements. The simulation results reveal that the exergetic efficiencies of the heat exchanger and expansion sections get the lowest rank among the other compartments of refrigeration cycle. Refrigeration calculations have been carried out through the analysis of T–S and P–H diagrams where coefficient of performance (COP) was obtained as 1.85. The novelty of this article includes the effect and sensitivity analysis of molar flow, pressure drops and temperature on the exergy efficiency and coefficient of performance of the cycle.

Keywords: exergy; Valve; CRP; refrigeration cycle; propane refrigerant; C2+ Recovery; Ethane Recovery;.

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14 A Smart Monitoring System for Preventing Gas Risks in Indoor

Authors: Gyoutae Park, Geunjun Lyu, Yeonjae Lee, Wooksuk Kim, Jaheon Gu, Sanguk Ahn, Hiesik Kim

Abstract:

In this paper, we propose a system for preventing gas risks through the use of wireless communication modules and intelligent gas safety appliances. Our system configuration consists of an automatic extinguishing system, detectors, a wall-pad, and a microcomputer controlled micom gas meter to monitor gas flow and pressure as well as the occurrence of earthquakes. The automatic fire extinguishing system checks for both combustible gaseous leaks and monitors the environmental temperature, while the detector array measures smoke and CO gas concentrations. Depending on detected conditions, the micom gas meter cuts off an inner valve and generates a warning, the automatic fire-extinguishing system cuts off an external valve and sprays extinguishing materials, or the sensors generate signals and take further action when smoke or CO are detected. Information on intelligent measures taken by the gas safety appliances and sensors are transmitted to the wall-pad, which in turn relays this as real time data to a server that can be monitored via an external network (BcN) connection to a web or mobile application for the management of gas safety. To validate this smart-home gas management system, we field-tested its suitability for use in Korean apartments under several scenarios.

Keywords: Gas sensor, leak, gas safety, gas meter, gas risk, wireless communication.

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13 A SWOT Analysis on Institutional Environments of University of the Punjab

Authors: Saghir Ahmad, Abid Hussain Ch., Atif Khalil, Misbah Malik

Abstract:

The major purpose of the study was to identify the institutional environments’ strengths, weaknesses, opportunities and threats of University of the Punjab, Lahore. The target population of the study was teachers of University of the Punjab Lahore. The sample of 235 teachers (155 males, 80 females) were selected through multistage stratified sampling technique. A questionnaire regarding the institutional environments of University SWOT Analysis “Strengths, Weaknesses, Opportunities, and Threats” was used to collect the required data for this study. The questionnaire consisted of two parts. The first part comprised of the demographic information (faculty, department, gender, teacher rank), while the second part included the statements regarding SWOT analysis (strengths, weaknesses, opportunities and threats). Reliability index (Cronbach’s Alpha) of the questionnaire was 0.87, which is statistically acceptable. Analysis of the data indicated that there was significant difference in the opinion of respondents. Teachers of Islamic studies and Laws had difference in their opinions regarding the institutional environment strengths, and opportunities and it was supported by the findings of the study. There was significant difference in opinions of male and female teachers regarding strengths and opportunities of university. And there was no significant difference in opinions of male and female teachers regarding weaknesses and threats of university.

Keywords: Institutional environments, SWOT analysis, teachers, University of the Punjab.

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12 An Algorithm of Finite Capacity Material Requirement Planning System for Multi-stage Assembly Flow Shop

Authors: T. Wuttipornpun, U. Wangrakdiskul, W. Songserm

Abstract:

This paper aims to develop an algorithm of finite capacity material requirement planning (FCMRP) system for a multistage assembly flow shop. The developed FCMRP system has two main stages. The first stage is to allocate operations to the first and second priority work centers and also determine the sequence of the operations on each work center. The second stage is to determine the optimal start time of each operation by using a linear programming model. Real data from a factory is used to analyze and evaluate the effectiveness of the proposed FCMRP system and also to guarantee a practical solution to the user. There are five performance measures, namely, the total tardiness, the number of tardy orders, the total earliness, the number of early orders, and the average flow-time. The proposed FCMRP system offers an adjustable solution which is a compromised solution among the conflicting performance measures. The user can adjust the weight of each performance measure to obtain the desired performance. The result shows that the combination of FCMRP NP3 and EDD outperforms other combinations in term of overall performance index. The calculation time for the proposed FCMRP system is about 10 minutes which is practical for the planners of the factory.

Keywords: Material requirement planning, Finite capacity, Linear programming, Permutation, Application in industry.

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11 A Novel SVM-Based OOK Detector in Low SNR Infrared Channels

Authors: J. P. Dubois, O. M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.

Keywords: Least square-support vector machine, on-off keying, matched filter, maximum likelihood detector, wireless infrared communication.

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10 A Development of the Multiple Intelligences Measurement of Elementary Students

Authors: Chaiwat Waree

Abstract:

This research aims at development of the Multiple Intelligences Measurement of Elementary Students. The structural accuracy test and normality establishment are based on the Multiple Intelligences Theory of Gardner. This theory consists of eight aspects namely linguistics, logic and mathematics, visual-spatial relations, body and movement, music, human relations, self-realization/selfunderstanding and nature. The sample used in this research consists of elementary school students (aged between 5-11 years). The size of the sample group was determined by Yamane Table. The group has 2,504 students. Multistage Sampling was used. Basic statistical analysis and construct validity testing were done using confirmatory factor analysis. The research can be summarized as follows; 1. Multiple Intelligences Measurement consisting of 120 items is content-accurate. Internal consistent reliability according to the method of Kuder-Richardson of the whole Multiple Intelligences Measurement equals .91. The difficulty of the measurement test is between .39-.83. Discrimination is between .21-.85. 2). The Multiple Intelligences Measurement has construct validity in a good range, that is 8 components and all 120 test items have statistical significance level at .01. Chi-square value equals 4357.7; p=.00 at the degree of freedom of 244 and Goodness of Fit Index equals 1.00. Adjusted Goodness of Fit Index equals .92. Comparative Fit Index (CFI) equals .68. Root Mean Squared Residual (RMR) equals 0.064 and Root Mean Square Error of Approximation equals 0.82. 3). The normality of the Multiple Intelligences Measurement is categorized into 3 levels. Those with high intelligence are those with percentiles of more than 78. Those with moderate/medium intelligence are those with percentiles between 24 and 77.9. Those with low intelligence are those with percentiles from 23.9 downwards.

Keywords: Multiple Intelligences, Measurement, Elementary Students.

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9 Turbine Compressor Vibration Analysis and Rotor Movement Evaluation by Shaft Center Line Method (The Case History Related to Main Turbine Compressor of an Olefin Plant in Iran Oil Industries)

Authors: Omid A. Zargar

Abstract:

Vibration monitoring methods of most critical equipment like main turbine and compressors always plays important role in preventive maintenance and management consideration in big industrial plants. There are a number of traditional methods like monitoring the overall vibration data from Bently Nevada panel and the time wave form (TWF) or fast Fourier transform (FFT) monitoring. Besides, Shaft centerline monitoring method developed too much in recent years. There are a number of arguments both in favor of and against this method between people who work in preventive maintenance and condition monitoring systems (vibration analysts). In this paper basic principal of Turbine compressor vibration analysis and rotor movement evaluation by shaft centerline method discussed in details through a case history. This case history is related to main turbine compressor of an olefin plant in Iran oil industry. In addition, some common mistakes that may occur by vibration analyst during the process discussed in details. It is worthy to know that, these mistakes may one of the reasons that sometimes this method seems to be not effective. Furthermore, recent patent and innovation in shaft position and movement evaluation are discussed in this paper.

Keywords: Shaft centerline position, attitude angle, journal bearing, sleeve bearing, tilting pad, steam turbine, main compressor, multistage compressor, condition monitoring, non-contact probe

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8 ANN based Multi Classifier System for Prediction of High Energy Shower Primary Energy and Core Location

Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

Abstract:

Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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7 Overloading Scheme for Cellular DS-CDMA using Quasi-Orthogonal Sequences and Iterative Interference Cancellation Receiver

Authors: Preetam Kumar, Saswat Chakrabarti

Abstract:

Overloading is a technique to accommodate more number of users than the spreading factor N. This is a bandwidth efficient scheme to increase the number users in a fixed bandwidth. One of the efficient schemes to overload a CDMA system is to use two sets of orthogonal signal waveforms (O/O). The first set is assigned to the N users and the second set is assigned to the additional M users. An iterative interference cancellation technique is used to cancel interference between the two sets of users. In this paper, the performance of an overloading scheme in which the first N users are assigned Walsh-Hadamard orthogonal codes and extra users are assigned the same WH codes but overlaid by a fixed (quasi) bent sequence [11] is evaluated. This particular scheme is called Quasi- Orthogonal Sequence (QOS) O/O scheme, which is a part of cdma2000 standard [12] to provide overloading in the downlink using single user detector. QOS scheme are balance O/O scheme, where the correlation between any set-1 and set-2 users are equalized. The allowable overload of this scheme is investigated in the uplink on an AWGN and Rayleigh fading channels, so that the uncoded performance with iterative multistage interference cancellation detector remains close to the single user bound. It is shown that this scheme provides 19% and 11% overloading with SDIC technique for N= 16 and 64 respectively, with an SNR degradation of less than 0.35 dB as compared to single user bound at a BER of 0.00001. But on a Rayleigh fading channel, the channel overloading is 45% (29 extra users) at a BER of 0.0005, with an SNR degradation of about 1 dB as compared to single user performance for N=64. This is a significant amount of channel overloading on a Rayleigh fading channel.

Keywords: DS-CDMA, Iterative Interference CancellationOrthogonal codes, Overloading.

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6 A Large Ion Collider Experiment (ALICE) Diffractive Detector Control System for RUN-II at the Large Hadron Collider

Authors: J. C. Cabanillas-Noris, M. I. Martínez-Hernández, I. León-Monzón

Abstract:

The selection of diffractive events in the ALICE experiment during the first data taking period (RUN-I) of the Large Hadron Collider (LHC) was limited by the range over which rapidity gaps occur. It would be possible to achieve better measurements by expanding the range in which the production of particles can be detected. For this purpose, the ALICE Diffractive (AD0) detector has been installed and commissioned for the second phase (RUN-II). Any new detector should be able to take the data synchronously with all other detectors and be operated through the ALICE central systems. One of the key elements that must be developed for the AD0 detector is the Detector Control System (DCS). The DCS must be designed to operate safely and correctly this detector. Furthermore, the DCS must also provide optimum operating conditions for the acquisition and storage of physics data and ensure these are of the highest quality. The operation of AD0 implies the configuration of about 200 parameters, from electronics settings and power supply levels to the archiving of operating conditions data and the generation of safety alerts. It also includes the automation of procedures to get the AD0 detector ready for taking data in the appropriate conditions for the different run types in ALICE. The performance of AD0 detector depends on a certain number of parameters such as the nominal voltages for each photomultiplier tube (PMT), their threshold levels to accept or reject the incoming pulses, the definition of triggers, etc. All these parameters define the efficiency of AD0 and they have to be monitored and controlled through AD0 DCS. Finally, AD0 DCS provides the operator with multiple interfaces to execute these tasks. They are realized as operating panels and scripts running in the background. These features are implemented on a SCADA software platform as a distributed control system which integrates to the global control system of the ALICE experiment.

Keywords: AD0, ALICE, DCS, LHC.

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5 Physical-Mechanical Characteristics of Monocrystalline Si1-xGex (x≤0,02) Solid Solutions

Authors: I. Kurashvili, A. Sichinava, G. Bokuchava, G. Darsavelidze

Abstract:

Si-Ge solid solutions (bulk poly- and mono-crystalline samples, thin films) are characterized by high perspectives for application in semiconductor devices, in particular, optoelectronics and microelectronics. From this point of view, complex studying of structural state of the defects and structural-sensitive physical properties of Si-Ge solid solutions depending on the contents of Si and Ge components is very important. Present work deals with the investigations of microstructure, microhardness, internal friction and shear modulus of Si1-xGex(x≤0,02) bulk monocrystals conducted at room temperature. Si-Ge bulk crystals were obtained by Czochralski method in [111] crystallographic direction. Investigated monocrystalline Si-Ge samples are characterized by p-type conductivity and carriers’ concentration 5.1014-1.1015cm-3. Microhardness was studied on Dynamic Ultra Micro hardness Tester DUH-201S with Berkovich indenter. Investigate samples are characterized with 0,5x0,5x(10-15)mm3 sizes, oriented along [111] direction at torsion oscillations ≈1Hz, multistage changing of internal friction and shear modulus has been revealed in an interval of strain amplitude of 10-5-5.10-3. Critical values of strain amplitude have been determined at which hysteretic changes of inelastic characteristics and microplasticity are observed. The critical strain amplitude and elasticity limit values are also determined. Dynamic mechanical characteristics decreasing trend is shown with increasing Ge content in Si-Ge solid solutions. Observed changes are discussed from the point of view of interaction of various dislocations with point defects and their complexes in a real structure of Si-Ge solid solutions.

Keywords: Internal friction, microhardness, relaxation processes, shear modulus, Si-Ge.

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4 Oscillation Effect of the Multi-stage Learning for the Layered Neural Networks and Its Analysis

Authors: Isao Taguchi, Yasuo Sugai

Abstract:

This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.

Keywords: data selection, function approximation problem, multistage leaning, neural network, voluntary oscillation.

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3 Alumina Supported Copper-Manganese Catalysts for Combustion of Exhaust Gases: Catalysts Characterization

Authors: Krasimir I. Ivanov, Elitsa N. Kolentsova, Dimitar Y. Dimitrov, Georgi V. Avdeev, Tatyana T. Tabakova

Abstract:

In recent research copper and manganese systems were found to be the most active in CO and organic compounds oxidation among the base catalysts. The mixed copper manganese oxide has been widely studied in oxidation reactions because of their higher activity at low temperatures in comparison with single oxide catalysts. The results showed that the formation of spinel CuxMn3−xO4 in the oxidized catalyst is responsible for the activity even at room temperature. That is why the most of the investigations are focused on the hopcalite catalyst (CuMn2O4) as the best coppermanganese catalyst. Now it’s known that this is true only for CO oxidation, but not for mixture of CO and VOCs. The purpose of this study is to investigate the alumina supported copper-manganese catalysts with different Cu/Mn molar ratio in terms of oxidation of CO, methanol and dimethyl ether. The catalysts were prepared by impregnation of γ-Al2O3 with copper and manganese nitrates and the catalytic activity measurements were carried out in two stage continuous flow equipment with an adiabatic reactor for simultaneous oxidation of all compounds under the conditions closest possible to the industrial. Gas mixtures on the input and output of the reactor were analyzed with a gas chromatograph, equipped with FID and TCD detectors. The texture characteristics were determined by low-temperature (- 196oС) nitrogen adsorption in a Quantachrome Instruments NOVA 1200e (USA) specific surface area & pore analyzer. Thermal, XRD and TPR analyses were performed. It was established that the active component of the mixed Cu- Mn/γ–alumina catalysts strongly depends on the Cu/Mn molar ratio. Highly active alumina supported Cu-Mn catalysts for CO, methanol and DME oxidation were synthesized. While the hopcalite is the best catalyst for CO oxidation, the best compromise for simultaneous oxidation of all components is the catalyst with Cu/Mn molar ratio 1:5.

Keywords: Supported copper-manganese catalysts, CO and VOCs oxidation.

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2 Multi-Objective Optimization of Gas Turbine Power Cycle

Authors: Mohsen Nikaein

Abstract:

Because of importance of energy, optimization of power generation systems is necessary. Gas turbine cycles are suitable manner for fast power generation, but their efficiency is partly low. In order to achieving higher efficiencies, some propositions are preferred such as recovery of heat from exhaust gases in a regenerator, utilization of intercooler in a multistage compressor, steam injection to combustion chamber and etc. However thermodynamic optimization of gas turbine cycle, even with above components, is necessary. In this article multi-objective genetic algorithms are employed for Pareto approach optimization of Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective optimization a number of conflicting objective functions are to be optimized simultaneously. The important objective functions that have been considered for optimization are entropy generation of RIGT cycle (Ns) derives using Exergy Analysis and Gouy-Stodola theorem, thermal efficiency and the net output power of RIGT Cycle. These objectives are usually conflicting with each other. The design variables consist of thermodynamic parameters such as compressor pressure ratio (Rp), excess air in combustion (EA), turbine inlet temperature (TIT) and inlet air temperature (T0). At the first stage single objective optimization has been investigated and the method of Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used for multi-objective optimization. Optimization procedures are performed for two and three objective functions and the results are compared for RIGT Cycle. In order to investigate the optimal thermodynamic behavior of two objectives, different set, each including two objectives of output parameters, are considered individually. For each set Pareto front are depicted. The sets of selected decision variables based on this Pareto front, will cause the best possible combination of corresponding objective functions. There is no superiority for the points on the Pareto front figure, but they are superior to any other point. In the case of three objective optimization the results are given in tables.

Keywords: Exergy, Entropy Generation, Brayton Cycle, DesignParameters, Optimization, Genetic Algorithm, Multi-Objective.

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1 Multistage Condition Monitoring System of Aircraft Gas Turbine Engine

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

Abstract:

Researches show that probability-statistical 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 the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem 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. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. 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 drawing 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. 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 stageby- stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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