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This report is done as a part of my thesis work concerning development and application of different advanced data processing methods for blade tip timing experimental data. Initial work involves understanding the basics behind blade tip timing measurement method, critical issues affecting the implementation of these methods and the challenges faced in data processing. Then, the existing auto-regressive, sine fitting and spectral data processing methods are applied to an industrial test case to investigate the implementation of these advanced methods and to examine their feasibility towards industrial data. Operation of these different methods are studied and the frequencies/engine orders computed from each method are compared with the Campbell data (FEM) for validation. Feasibility and limitations of different methods are analyzed and discussed. Then, different windowing techniques are applied to the basic spectral methods such as non-uniform Fourier transform and Lomb-Scargle periodogram to study the effects of windowing the data on frequency spectrum results. Cross spectrum is applied to non-uniform Fourier transform and Lomb-Scargle periodogram to study its impact on identifying true frequencies in case of severe corruption of replicas. Next, sine fitting method is developed for two frequency identification i.e. to detect simultaneous resonances. This method is tested and validated using the data generated from multi-mode tip timing simulator which is updated from the existing blade tip timing simulator. Finally, the feasibility of this methods is analyzed and discussed.
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The present volume contains results gained from the EU-funded 6th Framework project, DESider (Detached Eddy Simulation for Industrial Aerodynamics). 18 European organisations from industry, research and universities, have collaborated on topics centred around the improvement of hybrid RANS-LES methods, the investigation and validation of these methods in respect of a variety of aerodynamic, aeroelastic and aeroacoustic test cases – including novel URANS methods and the new SAS turbulence modelling strategy. The book presents an introduction to the project, exhibits partners’ methods and approaches, and provides comprehensive reports (i.e. definition as well as results) of all applications treated in the project.
Eddies -- Measurement -- Simulation methods. --- Reynolds stress -- Measurement -- Simulation methods. --- Turbulence -- Measurement -- Simulation methods. --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Civil Engineering --- Turbulence --- Engineering. --- Hydraulic engineering. --- Physics. --- Mathematical models. --- Natural philosophy --- Philosophy, Natural --- Engineering, Hydraulic --- Construction --- Applied mathematics. --- Engineering mathematics. --- Computational intelligence. --- Fluid mechanics. --- Engineering Fluid Dynamics. --- Applications of Mathematics. --- Computational Intelligence. --- Numerical and Computational Physics. --- Physical sciences --- Dynamics --- Industrial arts --- Technology --- Hydromechanics --- Continuum mechanics --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics --- Fluid mechanics --- Hydraulics --- Shore protection --- Mathematics. --- Numerical and Computational Physics, Simulation. --- Math --- Science
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This is an annual research series devoted to the examination of occupational stress, health and well being, with particular emphasis on the multi-disciplinary nature of occupational stress. The intent is to pull together the various streams of research from a variety of disciplines to better capture the significant bodies of work in occupational stress and well being. A multidisciplinary and international perspective is provided to give a thorough and critical assessment of issues in occupational stress and well being. The theme for this volume is: Employee Health, Coping, and Methodologies.
Ajustement (Psychologie) --- Adjustment (Psychology) -- Research. --- Human services personnel -- United States -- Job stress -- Research. --- Job stress -- Measurement -- Methodology. --- Stress (Physiology) -- Research -- Methodology. --- Stress (Physiology). --- Adaptation, Psychological --- Occupational Health --- Physiological stress --- Accommodation (Psychology) --- Adaptation (Psychology) --- Adapting behavior --- Adaptive behavior --- Coping behavior --- Maladjustment (Psychology) --- Job stress. --- Stress (Physiology) --- Adjustment (Psychology) --- Tension (Physiology) --- Adaptation (Biology) --- Occupational stress --- On-the-job stress --- Organizational stress --- Stress in the workplace --- Work stress --- Workplace stress --- Psychology, Industrial --- Stress (Psychology) --- Work --- Personality --- Psychology --- Adaptability (Psychology) --- Physiological aspects --- Psychological aspects --- Stress dû au travail --- Stress --- Job stress --- E-books --- Business & Economics --- Occupational & industrial psychology. --- Management. --- Applied Psychology.
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Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).
NSGA-II --- wind force --- wavelet packet decomposition --- structural health monitoring --- amplitude spectrum --- environmental noise --- patch antenna --- damage identification --- event-triggered sensing --- Particle Swarm Optimization (PSO) algorithm --- high-speed train --- low-velocity impacts --- concrete structures --- sensors distribution optimization --- acceleration --- digital sampling moiré --- crack --- displacement sensor --- length effect --- FBG sensor array --- SHM --- space window --- Bayesian blind source separation --- feature selection --- stress detection --- wheel minor defect --- strain --- uniaxial stress measurement --- turbine --- impact identification --- helical antenna --- energy analysis of wavelet band --- strain wave --- time window --- structural steel members --- steel frame --- acoustoelastic effect --- demand-based nodes --- online wayside detection --- sensor --- bridge --- sensitivity --- acoustic emission --- bending stiffness --- wireless smart sensors --- distributed dense sensor network --- mapping construction --- data fusion --- fuzzy classification --- shear-wave birefringence --- normal mode --- piezoelectric wafer active sensors --- resonant frequency --- electromagnetic oscillation --- settlement --- sensor optimization --- modal frequencies --- perturbation theory --- feature extraction --- Virtual Distortion Method (VDM) --- reflective optical sensor --- fibre bundle --- smartphones --- crack identification --- active sensing --- test vehicle --- calibration --- stretching method --- model updating --- rotary ultrasonic array --- 2D crack growth --- data processing --- damage detection --- impactor stiffness --- tip clearance --- transmission tower --- phase spectrum --- concrete crack --- structural impact monitoring --- shaking table tests --- optical crack growth sensor --- steel strand --- passive sensing --- sudden event monitoring --- aero engine --- principal component analysis
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