Search results for: random vibration analysis

Authors: Bang-Fuh Chen, Chih-Chun Chu

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The flow induced cylinder vibration or earthquake-induced cylinder motion are moving in an arbitrary direction with time. The phenomenon of flow across cylinder is highly nonlinear and a linear-superposition of flow pattern across separated oscillating direction of cylinder motion is not valid to obtain the flow pattern across a cylinder oscillating in multiple directions. A novel finite difference scheme is developed to simulate the viscous flow across an arbitrary moving circular cylinder and we call this a complete 2D (two-dimensional) flow-cylinder interaction. That is, the cylinder is simultaneously oscillating in x- and y- directions. The time-dependent domain and meshes associated with the moving cylinder are mapped to a fixed computational domain and meshes, which are time independent. The numerical results are validated by several bench mark studies. Several examples are introduced including flow across steam-wise, transverse oscillating cylinder and flow across rotating cylinder and flow across arbitrary moving cylinder. The Morison’s formula can not describe the complex interaction phenomenon between cross flow and oscillating circular cylinder. And the completed 2D computational fluid dynamic analysis should be made to obtain the correct hydrodynamic force acting on the cylinder.

Keywords: 2D cylinder, finite-difference method, flow-cylinder interaction, flow induced vibration

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Authors: Guillaume Leduc

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In this paper, we describe a broad setting under which the error of the approximation can be quantified, controlled, and for which convergence occurs at a speed of n⁻¹ for European and American options. We describe how knowledge of the error allows for arbitrarily fast acceleration of the convergence.

Keywords: random walk approximation, European and American options, rate of convergence, option pricing

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Authors: Abdullah Alnutayfat, Alexander Sutin

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One of the most important types of renewable energy resources is wind energy which can be produced by wind turbines. The blades of the wind turbine are exposed to the pressure of the harsh environment, which causes a significant issue for the wind power industry in terms of the maintenance cost and failure of blades. One of the reliable methods for blade inspection is the vibroacoustic structural health monitoring (SHM) method which examines information obtained from the structural vibrations of the blade. However, all vibroacoustic SHM techniques are based on comparing the structural vibration of intact and damaged structures, which places a practical limit on their use. Methods for nonlinear vibroacoustic SHM are more sensitive to damage and cracking and do not need to be compared to data from the intact structure. This paper presents the Vibro-Acoustic Modulation (VAM) method based on the modulation of high-frequency (probe wave) by low-frequency loads (pump wave) produced by the blade rotation. The blade rotation alternates bending stress due to gravity, leading to crack size variations and variations in the blade resonance frequency. This method can be used with the classical SHM vibration method in which the blade is excited by piezoceramic actuator patches bonded to the blade and receives the vibration response from another piezoceramic sensor. The VAM modification of this method analyzes the spectra of the detected signal and their sideband components. We suggest the VAM model as the simple mechanical oscillator, where the parameters of the oscillator (resonance frequency and damping) are varied due to low-frequency blade rotation. This model uses the blade vibration parameters and crack influence on the blade resonance properties from previous research papers to predict the modulation index (MI).

Keywords: wind turbine blades, damaged detection, vibro-acoustic structural health monitoring, vibro-acoustic modulation

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Authors: Nirmala Deenadayalu, Kwanele B. Mazibuko, Lethiwe D. Mthembu

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Sugarcane bagasse is the residue obtained after the extraction of sugar from the sugarcane. The main aim of this work was to produce catechol from sugarcane bagasse. The optimization of catechol production was investigated using a Box-Behnken design of experiments. The sugarcane bagasse was heated in a Parr reactor at a set temperature. The reactions were carried out at different temperatures (100-250) °C, catalyst loading (1% -10% KOH (m/v)) and reaction times (60 – 240 min) at 17 bar pressure. The solid and liquid fractions were then separated by vacuum filtration. The liquid fraction was analyzed for catechol using high-pressure liquid chromatography (HPLC) and characterized for the functional groups using Fourier transform infrared spectroscopy (FTIR). The optimized condition for catechol production was 175 oC, 240 min, and 10 % KOH with a catechol yield of 79.11 ppm. Since the maximum time was 240 min and 10 % KOH, a further series of experiments were conducted at 175 oC, 260 min, and 20 % KOH and yielded 2.46 ppm catechol, which was a large reduction in catechol produced. The HPLC peak for catechol was obtained at 2.5 min for the standards and the samples. The FTIR peak at 1750 cm⁻¹ was due to the C=C vibration band of the aromatic ring in the catechol present for both the standard and the samples. The peak at 3325 cm⁻¹ was due to the hydrogen-bonded phenolic OH vibration bands for the catechol. The ANOVA analysis was also performed on the set of experimental data to obtain the factors that most affected the amount of catechol produced.

Keywords: catechol, sugarcane bagasse, lignin, hydrothermal liquefaction

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Authors: R. Ruslee, H. Gollee

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Functional electrical stimulation (FES) is a commonly used technique in rehabilitation and often associated with rapid muscle fatigue which becomes the limiting factor in its applications. The objective of this study is to investigate the effects on the onset of fatigue of conventional synchronous stimulation, as well as asynchronous stimulation that mimic voluntary muscle activation targeting different motor units which are activated sequentially or randomly via multiple pairs of stimulation electrodes. We investigate three different approaches with various electrode configurations, as well as different patterns of stimulation applied to the gastrocnemius muscle: Conventional Synchronous Stimulation (CSS), Asynchronous Sequential Stimulation (ASS) and Asynchronous Random Stimulation (ARS). Stimulation was applied repeatedly for 300 ms followed by 700 ms of no-stimulation with 40 Hz effective frequency for all protocols. Ten able-bodied volunteers (28±3 years old) participated in this study. As fatigue indicators, we focused on the analysis of Normalized Fatigue Index (NFI), Fatigue Time Interval (FTI) and pre-post Twitch-Tetanus Ratio (ΔTTR). The results demonstrated that ASS and ARS give higher NFI and longer FTI confirming less fatigue for asynchronous stimulation. In addition, ASS and ARS resulted in higher ΔTTR than conventional CSS. In this study, we proposed a randomly distributed stimulation method for the application of FES and investigated its suitability for reducing muscle fatigue compared to previously applied methods. The results validated that asynchronous stimulation reduces fatigue, and indicates that random stimulation may improve fatigue resistance in some conditions.

Keywords: asynchronous stimulation, electrode configuration, functional electrical stimulation (FES), muscle fatigue, pattern stimulation, random stimulation, sequential stimulation, synchronous stimulation

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Authors: Mehrdad Nouri Khajavi, Gollamhassan Payganeh, Mohsen Fallah Tafti

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Fault diagnosis is an important aspect of maintaining rotating machinery health and increasing productivity. Many researches has been done in this regards. Many faults such as unbalance, misalignment, looseness, bearing faults, etc. have been considered and diagnosed with different techniques. Most of the researches in fault diagnosis of rotating machinery deal with single fault. Where as in reality faults usually occur simultaneously and it is, therefore, necessary to recognize them at the same time. In this research, two of the most common faults namely unbalance and misalignment have been considered simultaneously with different intensity and then identified and classified with the use of Multi-Layer Perception Neural Network (MLPNN). Processed Vibration signals are used as the input to the MLPNN, and the class of mixed unbalancy, and misalignment is the output of the NN.

Keywords: unbalance, parallel misalignment, combined faults, vibration signals

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Authors: A. GuhaRay, C. V. S. P. Kiranmayi, S. Rudraraju

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The present study considers the effect of variation of different geotechnical random variables in the design of stone column-foundation systems for assessing the bearing capacity and consolidation settlement of highly compressible soil. The soil and stone column properties, spacing, diameter and arrangement of stone columns are considered as the random variables. Probability of failure (P_f) is computed for a target degree of consolidation and a target safe load by Monte Carlo Simulation (MCS). The study shows that the variation in coefficient of radial consolidation (c_r) and cohesion of soil (c_s) are two most important factors influencing Pf. If the coefficient of variation (COV) of c_r exceeds 20%, P_f exceeds 0.001, which is unsafe following the guidelines of US Army Corps of Engineers. The bearing capacity also exceeds its safe value for COV of c_s > 30%. It is also observed that as the spacing between the stone column increases, the probability of reaching a target degree of consolidation decreases. Accordingly, design guidelines, considering both consolidation and bearing capacity of improved ground, are proposed for different spacing and diameter of stone columns and geotechnical random variables.

Keywords: bearing capacity, consolidation, geotechnical random variables, probability of failure, stone columns

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Authors: Marcel Meinhardt, Manfred Keuser, Thomas Braml

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Cracking of reinforced concrete is a complex phenomenon induced by direct loads or restraints affecting reinforced concrete structures as soon as the tensile strength of the concrete is exceeded. Hence it is important to predict where cracks will be located and how they will propagate. The bond theory and the crack formulas in the actual design codes, for example, DIN EN 1992-1-1, are all based on the assumption that the reinforcement bars are embedded in homogeneous concrete without taking into account the influence of transverse reinforcement and the real stress situation. However, it can often be observed that real structures such as walls, slabs or beams show a crack spacing that is orientated to the transverse reinforcement bars or to the stirrups. In most Finite Element Analysis studies, the smeared crack approach is used for crack prediction. The disadvantage of this model is that the typical strain localization of a crack on element level can’t be seen. The crack propagation in concrete is a discontinuous process characterized by different factors such as the initial random distribution of defects or the scatter of material properties. Such behavior presupposes the elaboration of adequate models and methods of simulation because traditional mechanical approaches deal mainly with average material parameters. This paper concerned with the modelling of the initiation and the propagation of cracks in reinforced concrete structures considering the influence of transverse reinforcement and the real stress distribution in reinforced concrete (R/C) beams/plates in bending action. Therefore, a parameter study was carried out to investigate: (I) the influence of the transversal reinforcement to the stress distribution in concrete in bending mode and (II) the crack initiation in dependence of the diameter and distance of the transversal reinforcement to each other. The numerical investigations on the crack initiation and propagation were carried out with a 2D reinforced concrete structure subjected to quasi static loading and given boundary conditions. To model the uncertainty in the tensile strength of concrete in the Finite Element Analysis correlated normally and lognormally distributed random filed with different correlation lengths were generated. The paper also presents and discuss different methods to generate random fields, e.g. the Covariance Matrix Decomposition Method. For all computations, a plastic constitutive law with softening was used to model the crack initiation and the damage of the concrete in tension. It was found that the distributions of crack spacing and crack widths are highly dependent of the used random field. These distributions are validated to experimental studies on R/C panels which were carried out at the Laboratory for Structural Engineering at the University of the German Armed Forces in Munich. Also, a recommendation for parameters of the random field for realistic modelling the uncertainty of the tensile strength is given. The aim of this research was to show a method in which the localization of strains and cracks as well as the influence of transverse reinforcement on the crack initiation and propagation in Finite Element Analysis can be seen.

Keywords: crack initiation, crack modelling, crack propagation, cracks, numerical simulation, random fields, reinforced concrete, stochastic

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Authors: Jakub Czyżycki, Paweł Twardowski

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Thin-walled components made of aluminum alloys are increasingly found in many fields of industry, and they dominate the aerospace industry. The machining of thinwalled structures encounters many difficulties related to the high susceptibility of the workpiece, which causes vibrations including the most unfavorable ones called chatter. The effect of these phenomena is the difficulty in obtaining the required geometric dimensions and surface quality. The purpose of this study is to analyze vibrations arising during machining of thin-walled workpieces made of aluminum alloy EN AW-7075. Samples representing actual thin-walled workpieces were examined in a different range of dimensions characterizing thin-walled workpieces. The tests were carried out in HSM high-speed machining (cutting speed vc = 1400 m/min) using a monolithic solid carbide endmill. Measurement of vibration was realized using a singlecomponent piezoelectric accelerometer 4508C from Brüel&Kjær which was mounted directly on the sample before machining, the measurement was made in the normal feed direction AfN. In addition, the natural frequency of the tested thin-walled components was investigated using a laser vibrometer for an broader analysis of the tested samples. The effect of vibrations on machining accuracy was presented in the form of surface images taken with an optical measuring device from Alicona. A classification of the vibrations produced during the test was carried out, and were analyzed in both the time and frequency domains. Observed significant influence of the thickness of the thin-walled component on the course of vibrations during machining.

Keywords: high-speed machining, thin-walled elements, thin-walled components, milling, vibrations

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Authors: Mandira Mishra, Mark Allen

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This meta-analysis explored whether rejection sensitivity relates to facets of romantic relationships. A comprehensive literature search identified 60 studies (147 effect sizes; 16,955 participants) that met inclusion criteria. Data were analysed using inverse-variance weighted random effects meta-analysis. Mean effect sizes from 21 meta-analyses provided evidence that more rejection sensitive individuals report lower levels of relationship satisfaction and relationship closeness, lower levels of perceived partner satisfaction, a greater likelihood of intimate partner violence (perpetration and victimization), higher levels of relationship concerns and relationship conflict, and higher levels of jealousy and self-silencing behaviours. There was also some evidence that rejection sensitive individuals are more likely to engage in risky sexual behaviour and are more prone to sexual compulsivity. There was no evidence of publication bias and various levels of heterogeneity in computed averages. Random effects meta-regression identified participant age and sex as important moderators of pooled mean effects. These findings provide a foundation for the theoretical development of rejection sensitivity in romantic relationships and should be of interest to relationship and marriage counsellors and other relationship professionals.

Keywords: intimate partner violence, relationship satisfaction, commitment, sexual orientation, risky sexual behaviour

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Sajjad Asefi, Hossein Afrakhte

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This paper presents the evaluation of reliability indices of an electrical distribution system using Monte Carlo simulation technique accounting Time To Switch (TTS) for each section. In this paper, the distribution system has been assumed by accounting random repair time omission. For simplicity, we have assumed the reliability analysis to be based on exponential law. Each segment has a specified rate of failure (λ) and repair time (r) which will give us the mean up time and mean down time of each section in distribution system. After calculating the modified mean up time (MUT) in years, mean down time (MDT) in hours and unavailability (U) in h/year, TTS have been added to the time which the system is not available, i.e. MDT. In this paper, we have assumed the TTS to be a random variable with Log-Normal distribution.

Keywords: distribution system, Monte Carlo simulation, reliability, repair time, time to switch (TTS)

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Authors: Yue Hu, Xilu Zhao, Takao Yamaguchi, Manabu Sasajima, Yoshio Koike, Akira Hara

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This study tried optimization of design parameter of a cone loudspeaker unit as an example of the high flexibility of the products design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to each design the parameter of the loudspeaker. To overcome the limitation of the design problem in practice, this paper proposes a new an acoustic analysis algorithm to optimize design the parameter of the loudspeaker. The material character of cone paper and the loudspeaker edge was the design parameter, and the vibration displacement of the cone paper was the objective function. The results of the analysis were compared with the predicted value. They had high accuracy to the predicted value. These results suggest that, though the parameter design is difficult by experience and intuition, it can be performed comparatively easily using the optimization design by the developed acoustic analysis software.

Keywords: air viscosity, loudspeaker, cone paper, edge, optimization

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Authors: Yu-Chieh Huang, Pei-Shih Chen, Tao-Hsin Tung

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Background: Urinary tract infection is the most common bacterial infection to our best knowledge. Objective: This study is to investigate whether cranberry ingesting could improve the urinary tract infection. Methods: We searched the PubMed and Cochrane Library for relevant randomized controlled trials without language limitations between 9 March 1994 and June 30, 2017, with a priori defined inclusion and exclusion criteria. The search terms included (cranberry OR Vaccinium macrocarpon OR Vaccinium oxy-coccus OR Vaccinium microcarpum OR Vaccinium erythrocarpum OR Vaccinium) AND (urinary tract infection OR bacteriuria OR pyuria) AND (effect OR effective-ness OR efficacy) AND (random OR randomized). Results: There were 26 studies met the selection criteria included among 4709 eligible participants. We analyzed all trials in meta-analysis. The random-effects pooled risk ratio (RR) for the group using cranberry versus using placebo was 0.75; 95%CI[0.63, 0.880]; p-value=0.0002) and heterogeneity was 56%. Furthermore, we divided the subjects into different subgroup to analysis. Ingesting cranberry seemed to be more effective in some subgroups, including the patients with recurrent UTI (RR, 0.71; 95%CI[0.54,0.93]; p-value=0.002) (I²= 65%) and female population (RR, 0.73, 95%CI[0.58,0.92]; p-value=0.002) (I²= 59%). The prevention effect was not different between cranberry and trimethoprim (RR, 1.25, 95%CI[0.67, 2.33]; p-value=0.49) (I²= 68%). No matter the forms of cranberry were capsules or juice, the efficacy was useful. Conclusions: It is showed that cranberry ingesting is usefully associated with prevention UTI. There are more effective in prevention of UTI in some groups.

Keywords: cranberry, effectiveness, prevention, urinary tract infect

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Authors: Chandra Gupt Porwal

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Excessive vibration means increased wear, increased repair efforts, bad product selection & quality and high energy consumption. This may be sometimes experienced by cavitation or suction/discharge re-circulation which could occur only when net positive suction head available NPSHA drops below the net positive suction head required NPSHR. Cavitation can cause axial surging if it is excessive, will damage mechanical seals, bearings, possibly other pump components frequently and shorten the life of the impeller. Efforts have been made to explain Suction Energy (SE), Specific Speed (Ns), Suction Specific Speed (Nss), NPSHA, NPSHR & their significance, possible reasons of cavitation /internal re-circulation, its diagnostics and remedial measures to arrest and prevent cavitation in this paper. A case study is presented by the author highlighting that the root cause of unwanted noise and vibration is due to cavitation, caused by high specific speeds or inadequate net- positive suction head available which results in damages to material surfaces of impeller & suction bells and degradation of machine performance, its capacity and efficiency too. The author strongly recommends revisiting the technical specifications of CW pumps to provide sufficient NPSH margin ratios > 1.5, for future projects and Nss be limited to 8500 -9000 for cavitation free operation.

Keywords: best efficiency point (BEP), net positive suction head NPSHA, NPSHR, specific speed NS, suction specific speed NSS

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Authors: K. Pietrykowski, M. Bialy, M. Duk

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One of the main disadvantages of radial engines is non-uniformity of operating cycles of each cylinder. This paper discusses the results of the kinematic analysis of pistons motion of the ASz-62IR radial engine. The ASz-62IR engine is produced in Poland and mounted in the M-18 Dromader and the An-2. The results are shown as the courses of the motion of the pistons. The discrepancies in the courses for individual pistons can result in different masses of the charge to fill the cylinders. Besides, pistons acceleration of individual cylinders is different, which triggers an additional vibration in the engine.

Keywords: nonuniformity, kinematic analysis, piston motion, radial engine

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Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: Cai-Wan Chang-Jian, Han-Ting Tsai

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In the processing industry of metal forming, rolling is the most used method of processing. In a cold rolling factory of stainless steel, there occurs a product defect on temper rolling process within cold rolling. It is called 'roll marks', which is a phenomenon of undesirable flatness problem. In this research, we performed a series of experimental measurements on the roll marks, and we used optical sensors to measure it and compared the vibration frequency of roll marks with the vibration frequency of key components in the skin pass mill. We found there is less correlation between the above mentioned data. Finally, we took measurement on the motor driver in rolling mill. We found that the undulation frequency of motor could match with the frequency of roll marks, and then we have confirmed that the motor’s undulation caused roll marks.

Keywords: roll mark, plane strain, rolling mill, stainless steel

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

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The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

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Authors: Ardalan Sabamehr, Ashutosh Bagchi

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Recently, Structural Health Monitoring (SHM) based on the vibration of structures has attracted the attention of researchers in different fields such as: civil, aeronautical and mechanical engineering. Operational Modal Analysis (OMA) have been developed to identify modal properties of infrastructure such as bridge, building and so on. Frequency Domain Decomposition (FDD), Stochastic Subspace Identification (SSI) and Continuous Wavelet Transform (CWT) are the three most common methods in output only modal identification. FDD, SSI, and CWT operate based on the frequency domain, time domain, and time-frequency plane respectively. So, FDD and SSI are not able to display time and frequency at the same time. By the way, FDD and SSI have some difficulties in a noisy environment and finding the closed modes. CWT technique which is currently developed works on time-frequency plane and a reasonable performance in such condition. The other advantage of wavelet transform rather than other current techniques is that it can be applied for the non-stationary signal as well. The aim of this paper is to compare three most common modal identification techniques to find modal properties (such as natural frequency, mode shape, and damping ratio) of three story steel frame which was built in Concordia University Lab by use of ambient vibration. The frame has made of Galvanized steel with 60 cm length, 27 cm width and 133 cm height with no brace along the long span and short space. Three uniaxial wired accelerations (MicroStarin with 100mv/g accuracy) have been attached to the middle of each floor and gateway receives the data and send to the PC by use of Node Commander Software. The real-time monitoring has been performed for 20 seconds with 512 Hz sampling rate. The test is repeated for 5 times in each direction by hand shaking and impact hammer. CWT is able to detect instantaneous frequency by used of ridge detection method. In this paper, partial derivative ridge detection technique has been applied to the local maxima of time-frequency plane to detect the instantaneous frequency. The extracted result from all three methods have been compared, and it demonstrated that CWT has the better performance in term of its accuracy in noisy environment. The modal parameters such as natural frequency, damping ratio and mode shapes are identified from all three methods.

Keywords: ambient vibration, frequency domain decomposition, stochastic subspace identification, continuous wavelet transform

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Authors: Ali Nourollah, Mohsen Movahedinejad

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In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The merge algorithm has the time complexity of O ((r+s) *l) where r and s are the size of merging polygons and l shows the number of intersecting edges removed from the polygonal chain. It will be shown that 1 < l < r+s. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

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Authors: F. Boukazouha, G. Poulin-Vittrant, M. Rguiti, M. Lethiecq

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Since its invention, by virtue of its remarkable features, the piezoelectric transformer (PT) has drawn the attention of the scientific community. In past years, it has been extensively studied and its performances have been continuously improved. Nowadays, such devices are designed in more and more sophisticated architectures with associated models describing their behavior quite accurately. However, the different studies usually carried out on such devices mainly focus on their electrical characteristics induced by direct piezoelectric effects such as voltage gain, efficiency or supplied power. In this work, we are particularly interested in the characterization of mechanical displacements induced by the inverse piezoelectric effect in a PT in vibration. For this purpose, a detailed three-dimensional finite element analysis is proposed to examine the mechanical behavior of a Rosen-type transformer made of a single bar of soft PZT (P191) and with dimensions 22mm×2.35mm×2.5mm. At the first three modes of vibration, output voltage and mechanical displacements ux, uy and uz along the length, the width and the thickness, respectively, are calculated. The amplitude of displacements varies in a range from a few nanometers to a few hundred nanometers. The validity of the simulations was successfully confirmed by experiments carried out on a prototype using a laser interferometer. A good match was observed between simulation and experimental results, especially for us at the second mode. Such 3D simulations thus appear as a helpful tool for a better understanding of mechanical phenomena in Rosen-type PT.

Keywords: piezoelectricity, gain, dispalcement, simulations

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Authors: P. Karimi, A. H. Khedmati Bazkiaei

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The main goal of this study is to test differential neural network as a controller of smart structure and is to enumerate its advantages and disadvantages in comparison with other controllers. In this study, the smart structure has been considered as a Euler Bernoulli cantilever beam and it has been tried that it be under control with the use of vibration neural network resulting from movement. Also, a linear observer has been considered as a reference controller and has been compared its results. The considered vibration charts and the controlled state have been recounted in the final part of this text. The obtained result show that neural observer has better performance in comparison to the implemented linear observer.

Keywords: smart material, on-line differential artificial neural network, active control, finite element method

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Authors: David Ugalde, Arturo Castillo, Leopoldo Breschi

Abstract:

The Tuned Mass Dampers (TMDs) are an effective system for mitigating vibrations in building structures. These dampers have traditionally focused on the protection of high-rise buildings against earthquakes and wind loads. The Camara Chilena de la Construction (CChC) building, built in 2018 in Santiago, Chile, is a 21-story RC wall building equipped with a 150-ton TMD and instrumented with six permanent accelerometers, offering an opportunity to monitor the dynamic response of this damped structure. This paper presents the system identification of the CChC building using power spectral density plots of ambient vibration and two seismic events (5.5 Mw and 6.7 Mw). Linear models of the building with and without the TMD are used to compute the theoretical natural periods through modal analysis and simulate the response of the building through response history analysis. Results show that natural periods obtained from both ambient vibrations and earthquake records are quite similar to the theoretical periods given by the modal analysis of the building model. Some of the experimental periods are noticeable by simple inspection of the earthquake records. The accelerometers in the first story better captured the modes related to the building podium while the upper accelerometers clearly captured the modes related to the tower. The earthquake simulation showed smaller accelerations in the model with TMD that are similar to that measured by the accelerometers. It is concluded that the system identification through power spectral density shows consistency with the expected dynamic properties. The structural health monitoring of the CChC building confirms the advantages of seismic protection technologies such as TMDs in seismic prone areas.

Keywords: system identification, tuned mass damper, wall buildings, seismic protection

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Authors: Nouby Ghazaly

Abstract:

The present paper investigates experimentally the effect coefficient of friction at different operation conditions on the variation of the brake temperature, brake force, and brake vibration with the braking time. All the experimental tests were carried out using brake dynamometer which designed and constructed in Vehicle Dynamic Laboratory. The results indicate that the brake temperature increases with the increase of the normal force and sliding speed especially with the increase of the braking time. The normal force has the effect on increasing the brake force. On the contrary, the vehicle speed has the effect on decreasing the brake force. Both the normal force and sliding speed affect the brake vibration according to the friction behavior.

Keywords: brake dynamometer, coefficient of friction, drum brake vibrations, friction behavior

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Authors: Seon Soon Choi

Abstract:

The essential purpose is to present the good fatigue crack propagation model describing a stochastic fatigue crack growth behavior in a rolled magnesium alloy, AZ31, under various load ratio conditions. Fatigue crack propagation experiments were carried out in laboratory air under four conditions of load ratio, R, using AZ31 to investigate the crack growth behavior. The stochastic fatigue crack growth behavior was analyzed using an interpolation of random variable, Z, introduced to an empirical fatigue crack propagation model. The empirical fatigue models used in this study are Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was found that the random variable is useful in describing the stochastic fatigue crack growth behaviors under various load ratio conditions. The good probabilistic model describing a stochastic fatigue crack growth behavior under various load ratio conditions was also proposed.

Keywords: magnesium alloys, fatigue crack propagation model, load ratio, interpolation of random variable

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Authors: Desmond Adair, Kairat Ismailov, Martin Jaeger

Abstract:

Modelling of Timoshenko beams on elastic foundations has been widely used in the analysis of buildings, geotechnical problems, and, railway and aerospace structures. For the elastic foundation, the most widely used models are one-parameter mechanical models or two-parameter models to include continuity and cohesion of typical foundations, with the two-parameter usually considered the better of the two. Knowledge of free vibration characteristics of beams on an elastic foundation is considered necessary for optimal design solutions in many engineering applications, and in this work, the efficient and accurate variational iteration method is developed and used to calculate natural frequencies of a Timoshenko beam on a two-parameter foundation. The variational iteration method is a technique capable of dealing with some linear and non-linear problems in an easy and efficient way. The calculations are compared with those using a finite-element method and other analytical solutions, and it is shown that the results are accurate and are obtained efficiently. It is found that the effect of the presence of the two-parameter foundation is to increase the beam’s natural frequencies and this is thought to be because of the shear-layer stiffness, which has an effect on the elastic stiffness. By setting the two-parameter model’s stiffness parameter to zero, it is possible to obtain a one-parameter foundation model, and so, comparison between the two foundation models is also made.

Keywords: Timoshenko beam, variational iteration method, two-parameter elastic foundation model

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Authors: Raef Cherif, Houssine Bakkali, Wafaa El Khatiri, Yacine Yaddaden

Abstract:

The analysis of how vibrations are transmitted between components is required in many engineering applications. Transfer path analysis (TPA) has been a valuable engineering tool for solving Noise, Vibration, and Harshness (NVH problems using sub-structuring applications. The most challenging part of a TPA analysis is estimating the equivalent forces at the contact points between the active and the passive side. Component TPA in situ Method calculates these forces by inverting the frequency response functions (FRFs) measured at the passive subsystem, relating the motion at indicator points to forces at the interface. However, matrix inversion could pose problems due to the ill-conditioning of the matrices leading to inaccurate results. This paper establishes a TPA model for an academic system consisting of two plates linked by four springs. A numerical study has been performed to improve the interface forces identification. Several parameters are studied and discussed, such as the singular value rejection and the number and position of indicator points chosen and used in the inversion matrix.

Keywords: transfer path analysis, matrix inverse method, indicator points, SVD decomposition

Procedia PDF Downloads 78