Modelling of spatial variations in vibration analysis with application to an automotive windshield

Hinke, L.; Pichler, L.; Pradlwarter, H. J.; Mace, B.R.; Waters, T.P.

doi:10.1016/j.finel.2010.07.013

Cited by 17 publications

(7 citation statements)

References 9 publications

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“…This approach is particularly beneficial in conjunction with the KL expansion, which provides the smallest number of terms in the series to represent the random field to a given accuracy [13,54]. Other sampling approaches, such as line-sampling [5,55], could take additional advantage of this formulation to reduce the number of samples needed to accurately calculate the response statistics. Details of the formulation will be shown for the examples of rod, beam and plate elements in the following sections.…”

Section: Hfe Approximation Using the Kl Expansionmentioning

confidence: 99%

“…(4) and therefore an analytical expression for the KL expansion can be used, as given in Eq. (5). The Gamma distribution is the best stochastic model for the Young's modulus according to a Maximum Entropy criterion [58], based on the available information about the random variable or process.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…Structural uncertainty modelling often involves modelling spatial random variability. It becomes even more relevant when dealing with, for instance, composite materials [5][6][7][8][9] or additive manufacturing [10,11]. One of the available tools to describe spatially correlated variability is the random field [12,13], which is a multidimensional random process using a probability measure.…”

Section: Introductionmentioning

confidence: 99%

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Structural vibration analysis with random fields using the hierarchical finite element method

Fabro

Ferguson

Mace

2019

J Braz. Soc. Mech. Sci. Eng.

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Element based techniques, like the Finite Element method, are the standard approach in industry for low frequency applications in structural dynamics. However, mesh requirements can significantly increase the computational cost for increasing frequencies. In addition, randomness in system properties starts to play a significant role and its inclusion in the model further increases the computational cost. In this paper, a hierarchical finite element formulation is presented which incorporates spatially random properties. Polynomial and trigonometric hierarchical functions are used in the element formulation. Material and geometrical spatially correlated randomness are represented by the Karhunen-Loève expansion, a series representation for random fields. It allows the element integration to be performed only once for each term of the series which has benefits for a sampling scheme and can be used for non-Gaussian distributions. Free vibration and forced response statistics are calculated using the proposed approach. Compared to the standard h-version, the hierarchical finite element approach produces smaller mass and stiffness matrices, without changing the number of nodes of the element, and tends to be computationally more efficient. These are key factors not only when considering solutions for higher frequencies but also in the calculation of response statistics using a sampling method such as Monte Carlo simulation.

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Section: Hfe Approximation Using the Kl Expansionmentioning

confidence: 99%

Section: Numerical Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Structural vibration analysis with random fields using the hierarchical finite element method

Fabro

Ferguson

Mace

2019

J Braz. Soc. Mech. Sci. Eng.

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“…Transitional diseases are classified as serious in that they often cause death as well as permanent or temporary complications such as polio, which causes permanent disability. [1], [2] Disease can be defined as resulting from the transmission of microorganisms, like the viruses, bacteria, fungi, or parasites from an infected person to another healthy person that leads to his illness. [3] Correspondence analysis was used as a tool for analyzing disease data; given that the symmetric analysis is a classification tool from two sides, the research covers all governorates of Iraq except the Kurdistan Region and the age groups and both gender [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Using Multivariate Analysis to Study the Spread of Transitional Diseases in Iraq

Rasheed

Al-saffar

Rasheed

2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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Medical and technological development has achieved continuous successes during the last period. However, the statistics received from the World Health Organization (WHO) show the suffering that millions of people are subjected to daily as a result of their exposure to transitional diseases. The most prevalent transitional disease in the Iraqi provinces and for all age groups for both genders is water pox disease, followed by cutaneous leishmaniosis and then mumps. The most affected governorate with transitional diseases is Baghdad Governorate (Rusafa Sector), followed by Dhi Qar Governorate and Baghdad (Al Karkh Sector). The most agegroups affected with transition diseases are the categories (5-9) years for males, followed by (5-9) years for females. The highest total contribution to the first axis was for cutaneous leishmaniasis, followed by mumps, then Basil dysentery, as for the absolute contribution in the first axis, it was Dhi Qar Governorate, followed by Baghdad. There are more than 14,000,000 people who die each year because of these diseases, and most infections are concentrated in developing countries, including Iraq. Hence, this research is vital to examine the extent of transitional diseases in Iraq for different age groups, both male and female gender. The use of the multivariate method, which is the correspondence analyses, it was found through the research that Baghdad (Rusafa Sector) has a high incidence of transitional diseases and the largest age group at risk of transitional diseases is (5-9) years form male gender.

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“…The derivation of these properties by measuring on simplified models (e.g. prismatic rod) [1,2] or via finite element modelling [3] is a rather common procedure for simple materials. However, the examination of real windshields -even free-free state (i.e.…”

Section: Introductionmentioning

confidence: 99%

Vibration Damping Measurement on Car Windshields

Vehovszky

Horváth²,

Slenczka³

et al. 2018

Period. Polytech. Mech. Eng.

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Knowledge of the damping properties of a windshield is a fundamental element of the acoustical characterization of a car.The measuring method of damping for a windshield is presented in the paper. The damping loss factor -as a basic measure of mechanical damping -was determined experimentally by two means: the reverberation time from impact hammer testing as well as the modal behavior from 3D laser scanning vibrometer measurements. The results proved that the modal shapes have a fundamental effect on the measured damping values.

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Modelling of spatial variations in vibration analysis with application to an automotive windshield

Cited by 17 publications

References 9 publications

Structural vibration analysis with random fields using the hierarchical finite element method

Structural vibration analysis with random fields using the hierarchical finite element method

Using Multivariate Analysis to Study the Spread of Transitional Diseases in Iraq

Vibration Damping Measurement on Car Windshields

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