890 resultados para System verification and analysis
Resumo:
The Office of Special Investigations at Iowa Department of Transportation (DOT) collects FWD data on regular basis to evaluate pavement structural conditions. The primary objective of this study was to develop a fully-automated software system for rapid processing of the FWD data along with a user manual. The software system automatically reads the FWD raw data collected by the JILS-20 type FWD machine that Iowa DOT owns, processes and analyzes the collected data with the rapid prediction algorithms developed during the phase I study. This system smoothly integrates the FWD data analysis algorithms and the computer program being used to collect the pavement deflection data. This system can be used to assess pavement condition, estimate remaining pavement life, and eventually help assess pavement rehabilitation strategies by the Iowa DOT pavement management team. This report describes the developed software in detail and can also be used as a user-manual for conducting simulation studies and detailed analyses. *********************** Large File ***********************
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The stability of air bubbles in fresh concrete can have a profound influence of the potential durability of the system, because excessive losses during placement and consolidation can compromise the ability of the mixture to resist freezing and thawing. The stability of air void systems developed by some air entraining admixtures (AEAs) could be affected by the presence of some polycarboxylate-based water reducing admixtures (WRAs). The foam drainage test provides a means of measuring the potential stability of air bubbles in a paste. A barrier to acceptance of the test was that there was little investigation of the correlation with field performance. The work reported here was a limited exercise seeking to observe the stability of a range of currently available AEA/WRA combinations in the foam drainage test; then, to take the best and the worst and observe their stabilities on concrete mixtures in the lab. Based on the data collected, the foam drainage test appears to identify stable combinations of AEA and WRA.
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Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.
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The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.
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Throughout history indigo was derived from various plants for example Dyer’s Woad (Isatis tinctoria L.) in Europe. In the 19th century were the synthetic dyes developed and nowadays indigo is mainly synthesized from by-products of fossil fuels. Indigo is a so-called vat dye, which means that it needs to be reduced to its water soluble leucoform before dyeing. Nowadays, most of the industrial reduction is performed chemically by sodium dithionite. However, this is considered environmentally unfavourable because of waste waters contaminating degradation products. Therefore there has been interest to find new possibilities to reduce indigo. Possible alternatives for the application of dithionite as the reducing agent are biologically induced reduction and electrochemical reduction. Glucose and other reducing sugars have recently been suggested as possible environmentally friendly alternatives as reducing agents for sulphur dyes and there have also been interest in using glucose to reduce indigo. In spite of the development of several types of processes, very little is known about the mechanism and kinetics associated with the reduction of indigo. This study aims at investigating the reduction and electrochemical analysis methods of indigo and give insight on the reduction mechanism of indigo. Anthraquinone as well as it’s derivative 1,8-dihydroxyanthraquinone were discovered to act as catalysts for the glucose induced reduction of indigo. Anthraquinone introduces a strong catalytic effect which is explained by invoking a molecular “wedge effect” during co-intercalation of Na+ and anthraquinone into the layered indigo crystal. The study includes also research on the extraction of plant-derived indigo from woad and the examination of the effect of this method to the yield and purity of indigo. The purity has been conventionally studied spectrophotometrically and a new hydrodynamic electrode system is introduced in this study. A vibrating probe is used in following electrochemically the leuco-indigo formation with glucose as a reducing agent.
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Validation and verification operations encounter various challenges in product development process. Requirements for increasing the development cycle pace set new requests for component development process. Verification and validation usually represent the largest activities, up to 40 50 % of R&D resources utilized. This research studies validation and verification as part of case company's component development process. The target is to define framework that can be used in improvement of the validation and verification capability evaluation and development in display module development projects. Validation and verification definition and background is studied in this research. Additionally, theories such as project management, system, organisational learning and causality is studied. Framework and key findings of this research are presented. Feedback system according of the framework is defined and implemented to the case company. This research is divided to the theory and empirical parts. Theory part is conducted in literature review. Empirical part is done in case study. Constructive methode and design research methode are used in this research A framework for capability evaluation and development was defined and developed as result of this research. Key findings of this study were that double loop learning approach with validation and verification V+ model enables defining a feedback reporting solution. Additional results, some minor changes in validation and verification process were proposed. There are a few concerns expressed on the results on validity and reliability of this study. The most important one was the selected research method and the selected model itself. The final state can be normative, the researcher may set study results before the actual study and in the initial state, the researcher may describe expectations for the study. Finally reliability of this study, and validity of this work are studied.
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A coupled system simulator, based on analytical circuit equations and a finite element method (FEM) model of the motor has been developed and it is used to analyse a frequency-converterfed industrial squirrel-cage induction motor. Two control systems that emulate the behaviour of commercial direct-torque-controlled (DTC) and vector-controlled industrial frequency converters have been studied, implemented in the simulation software and verified by extensive laboratory tests. Numerous factors that affect the operation of a variable speed drive (VSD) and its energy efficiency have been investigated, and their significance in the simulation of the VSD results has been studied. The dependency of the frequency converter, induction motor and system losses on the switching frequency is investigated by simulations and measurements at different speeds for both the vector control and the DTC. Intensive laboratory measurements have been carried out to verify the simulation results.
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Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.
Resumo:
Tässä työssä on tutkittu modulaarisen aktiivimagneettilaakeroidun koelaitteen mekaanista suunnittelua ja analysointia. Suurnopeusroottorin suunnittelun teoria on esitelty. Lisäksi monia analyyttisiä mallinnusmenetelmiä mekaanisten kuormitusten mallintamiseksi on esitelty. Koska kyseessä on suurnopeussähkökone, roottoridynamiikka ja sen soveltuvuus suunnittelussa on esitelty. Magneettilaakerien rakenteeseen ja toimintaan on tutustuttu osana tätä työtä. Kirjallisuuskatsaus nykyisistä koelaitteista esimerkiksi komponenttien ominaisuuksien tunnistamiseen ja roottoridynamiikan tutkimuksiin on esitelty. Työn rajauksena on konseptisuunnittelu muunneltavalle magneettilaakeroidulle (AMB) koelaitteelle ja suunnitteluprosessin dokumentointi. Muunneltavuuteen päädyttiin, koska se mahdollistaa erilaisten komponenttiasetteluiden testaamisen erilaisille magneettilaakerikokoonpanoille ja roottoreille. Pääpaino tässä työssä on suurnopeus induktiokoneen roottorin suunnittelussa ja mallintamisessa. Modulaaristen toimilaitteiden kuten magneettilaakerien ja induktiosähkömoottorin rakenne on esitelty ja modulaarisen rakenteen käytettävyyden hyödyistä koelaitekäytössä on dokumentoitu. Analyyttisiä ja elementtimenetelmään perustuvia tutkimusmenetelmiä on käytetty tutkittaessa suunniteltua suurnopeusroottoria. Suunnittelun ja analysoinnin tulokset on esitelty ja verrattu keskenään eri mallinnusmenetelmien välillä. Lisäksi johtopäätökset sähkömagneettisten osien liittämisen monimutkaisuudesta ja vaatimuksista roottoriin ja toimilaitteisiin sekä mekaanisten että sähkömagneettisten ominaisuuksien optimoimiseksi on dokumentoitu.
Resumo:
The thesis is the outcome of the experimental and theoretical investigations on a new compact drum-shaped microstrip antenna. A new compact antenna suitable for personal communication system(PCS), Global position System(GPS) and array applications is developed and analysed. The generalised cavity model and spatial fourier transform technique are suitably modified for the analysis of the antenna. The predicted results are compared with experimental results and excellent agreement is observed. The experimental work done by the author in related fields are incorporated as three appendices in this thesis. A single feed dual frequency microstrip antenne is presented in appendix A.Appendix B describes a new broadband dual frequeny microstrip antenna. The bandwidth enhancement effect of microstrip antennas through dielectric resonator loading is demonstarted in Appendix C.
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This thesis describes the development and analysis of an Isosceles Trapezoidal Dielectric Resonator Antenna (ITDRA) by realizing different DR orientations with suitable feed configurations enabling it to be used as multiband, dual band dual polarized and wideband applications. The motivation for this work has been inspired by the need for compact, high efficient, low cost antenna suitable for multi band application, dual band dual polarized operation and broadband operation with the possibility of using with MICs, and to ensure less expensive, more efficient and quality wireless communication systems. To satisfy these challenging demands a novel shaped Dielectric Resonator (DR) is fabricated and investigated for the possibility of above required properties by trying out different orientations of the DR on a simple microstrip feed and with slotted ground plane as well. The thesis initially discusses and evaluates recent and past developments taken place within the microwave industry on this topic through a concise review of literature. Then the theoretical aspects of DRA and different feeding techniques are described. Following this, fabrication and characterization of DRA is explained. To achieve the desired requirements as above both simulations and experimental measurements were undertaken. A 3-D finite element method (FEM) electromagnetic simulation tool, HFSSTM by Agilent, is used to determine the optimum geometry of the dielectric resonator. It was found to be useful in producing approximate results although it had some limitations. A numerical analysis technique, finite difference time domain (FDTD) is used for validating the results of wide band design at the end. MATLAB is used for modeling the ITDR and implementing FDTD analysis. In conclusion this work offers a new, efficient and relatively simple alternative for antennas to be used for multiple requirements in the wireless communication system.
Resumo:
Data centre is a centralized repository,either physical or virtual,for the storage,management and dissemination of data and information organized around a particular body and nerve centre of the present IT revolution.Data centre are expected to serve uniinterruptedly round the year enabling them to perform their functions,it consumes enormous energy in the present scenario.Tremendous growth in the demand from IT Industry made it customary to develop newer technologies for the better operation of data centre.Energy conservation activities in data centre mainly concentrate on the air conditioning system since it is the major mechanical sub-system which consumes considerable share of the total power consumption of the data centre.The data centre energy matrix is best represented by power utilization efficiency(PUE),which is defined as the ratio of the total facility power to the IT equipment power.Its value will be greater than one and a large value of PUE indicates that the sub-systems draw more power from the facility and the performance of the data will be poor from the stand point of energy conservation. PUE values of 1.4 to 1.6 are acievable by proper design and management techniques.Optimizing the air conditioning systems brings enormous opportunity in bringing down the PUE value.The air conditioning system can be optimized by two approaches namely,thermal management and air flow management.thermal management systems are now introduced by some companies but they are highly sophisticated and costly and do not catch much attention in the thumb rules.
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This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.
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This paper presents a model and analysis of a synchronous tandem flow line that produces different part types on unreliable machines. The machines operate according to a static priority rule, operating on the highest priority part whenever possible, and operating on lower priority parts only when unable to produce those with higher priorities. We develop a new decomposition method to analyze the behavior of the manufacturing system by decomposing the long production line into small analytically tractable components. As a first step in modeling a production line with more than one part type, we restrict ourselves to the case where there are two part types. Detailed modeling and derivations are presented with a small two-part-type production line that consists of two processing machines and two demand machines. Then, a generalized longer flow line is analyzed. Furthermore, estimates for performance measures, such as average buffer levels and production rates, are presented and compared to extensive discrete event simulation. The quantitative behavior of the two-part type processing line under different demand scenarios is also provided.
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An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.