A Comparison Between the Use of Physical Parameters and Correction Factors in Dynamic Model Updating

1995 ◽  
Author(s):  
Walter D’Ambrogio ◽  
Annalisa Fregolent
Keyword(s):  
Elasticity Modulus ◽  
Model Updating ◽  
Mass Density ◽  
Physical Parameters ◽  
Test Case ◽  
Correction Factors ◽  
Scale Factors ◽  
Updating Procedure ◽  
Geometrical Dimensions ◽  
Selection Of

Abstract The selection of quantities and/or variables that have to be corrected during the updating process is addressed in this paper. Among quantities, the major alternative is the choice between correction factors and physical parameters. The former represent scale factors used to adjust mass and stiffness submatrices of the analytical model, while the latter include parameters such as the elasticity modulus, mass density, geometrical dimensions, etc. Advantages and limitations in the process of updating physical parameters instead of correction factors are highlighted: it can be shown that only a limited number of physical parameters can be simultaneously updated for each element. The two approaches are compared using a previously developed updating procedure to solve an experimental test case.

Algorithms for Bayesian Model Class Selection of Higher-Dimensional Dynamic Systems

2007 ◽  
Author(s):  
Sai Hung Cheung ◽  
James L. Beck
Keyword(s):  
Bayesian Model ◽  
Model Updating ◽  
Structural Dynamic ◽  
Higher Dimensional ◽  
Significant Probability ◽  
Model Class ◽  
Updating Procedure ◽  
Model Class Selection ◽  
Dimensional Integral ◽  
Selection Of

In recent years, Bayesian model updating techniques based on measured data have been applied in structural health monitoring. Often we are faced with the problem of how to select the ‘best’ model from a set of competing candidate model classes for the system based on data. To tackle this problem, Bayesian model class selection is used, which provides a rigorous Bayesian updating procedure to give the probability of different candidate classes for a system, based on the data from the system. There may be cases where more than one model class has significant probability and each of these will give different predictions. Bayesian model class averaging provides a coherent mechanism to incorporate all the considered model classes in the probabilistic predictions for the system. However, both Bayesian model class selection and Bayesian model class averaging require the calculation of the evidence of the model class which requires the nontrivial computation of a multi-dimensional integral. In this paper, several methods for solving this computationally challenging problem of model class selection are presented, proposed and compared. The efficiency of the proposed methods is illustrated by an example involving a structural dynamic system.

scholarly journals Nanometre-Scale Visualization of Chemical Parameter Changes by T1-Weighted ODMR Imaging Using a Fluorescent Nanodiamond

Chemosensors ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 68
Author(s):  
Takahiro Fujisaku ◽  
Ryuji Igarashi ◽  
Masahiro Shirakawa
Keyword(s):  
Magnetic Resonance ◽  
Laser Pulse ◽  
Real Time ◽  
Physical Parameters ◽  
Biological Processes ◽  
Chemical Parameter ◽  
Ph Conditions ◽  
Optically Detected ◽  
Life Phenomena ◽  
Selection Of

The dynamics of physical parameters in cells is strongly related to life phenomena; thus, a method to monitor and visualize them on a single-organelle scale would be useful to reveal unknown biological processes. We demonstrate real-time nanometre-scale T1-weighted imaging using a fluorescent nanodiamond. We explored optically detected magnetic resonance (ODMR) contrast at various values of interval laser pulse (τ), showing that sufficient contrast is obtained by appropriate selection of τ. By this method, we visualized nanometre-scale pH changes using a functionalized nanodiamond whose T1 has a dependence on pH conditions.

A statistical analysis of low-stress mechanical properties of warp-knitted fabrics

2016 ◽  
Vol 88 (4) ◽  
pp. 467-479 ◽  
Author(s):  
Ka-yan Yim ◽  
Chi-wai Kan
Keyword(s):  
Mechanical Properties ◽  
Evaluation System ◽  
Natural Fibers ◽  
Physical Parameters ◽  
Knitted Fabrics ◽  
Fabric Hand ◽  
Low Stress Mechanical Properties ◽  
Fabric Weight ◽  
Fabric Structures ◽  
Selection Of

Fabric hand is an indispensable characteristic for the selection of fabric and product development and the buying consideration for manufacturers and consumers. However, there is little comprehensive work on the hand feel property of warp-knitted fabrics due to the mainstream natural fibers (cotton, wool and silk) and other fabric structures (woven, weft-knitted and nonwoven). The increasing potential for the wide variety of applications and development of warp-knitted fabrics is not only because its fabric hand gives better determination for fabric marketing, but also because it provides extensive scope for fabric performance and appearance. This paper reports an experimental study on the integrated fabric hand behavior of a series of warp-knitted fabrics made for various apparel applications, such as sportswear, lingerie and leisure wear. These 105 fabrics were produced by varying different physical parameters, including fabric weight and fabric thickness. The Kawabata Evaluation System for Fabric (KES-F) was employed to obtain the fabric hand properties (primary hand value and total hand value) related with stiffness, smoothness and softness. All low-stress mechanical properties and fabric hand values from the testing results were used to verify the applicability of the KES-F on warp-knitted fabrics and to analyze the relationships of fabric parameters and hand characteristics. The results indicate that the KES-F is an appropriate tool to measure the hand attributes of warp-knitted samples, and moderate correlations between physical properties and mechanical behavior were found.

Validating and Updating Finite Element Models Using Experimental Measurements of Dynamics

1990 ◽  
Vol 204 (1) ◽  
pp. 45-50
Author(s):  
C F McCulloch ◽  
P Vanhonacker ◽  
E Dascotte
Keyword(s):  
Finite Element ◽  
Structural Dynamics ◽  
Model Updating ◽  
Measured Data ◽  
Physical Parameters ◽  
Experimental Measurements ◽  
Finite Element Models ◽  
Data Sets ◽  
Modal Data ◽  
Modelling Assumptions

A method is proposed for updating finite element models of structural dynamics using the results of experimental modal analysis, based on the sensitivities to changes in physical parameters. The method avoids many of the problems of incompatibility and inconsistency between the experimental and analytical modal data sets and enables the user to express confidence in measured data and modelling assumptions, allowing flexible but automated model updating.

Physical Realization of Generic-Element Parameters in Model Updating

2002 ◽  
Vol 124 (4) ◽  
pp. 628-633 ◽  
Author(s):  
H. Ahmadian ◽  
J. E. Mottershead ◽  
M. I. Friswell
Keyword(s):  
Model Updating ◽  
Finite Element Models ◽  
Physical Realization ◽  
Governing Equations ◽  
Stiffness Matrices ◽  
Model Predictions ◽  
Physical Effects ◽  
Realization Process ◽  
Physical Phenomena ◽  
Selection Of

The selection of parameters is most important to successful updating of finite element models. When the parameters are chosen on the basis of engineering understanding the model predictions are brought into agreement with experimental observations, and the behavior of the structure, even when differently configured, can be determined with confidence. Physical phenomena may be misrepresented in the original model, or may be absent altogether. In any case the updated model should represent an improved physical understanding of the structure and not simply consist of unrepresentative numbers which happen to cause the results of the model to agree with particular test data. The present paper introduces a systematic approach for the selection and physical realization of updated terms. In the realization process, the discrete equilibrium equation formed by mass, and stiffness matrices is converted to a continuous form at each node. By comparing the resulting differential equation with governing equations known to represent physical phenomena, the updated terms and their physical effects can be recognized. The approach is demonstrated by an experimental example.

scholarly journals NETWORK MODELLING AND SEMANTIC 3D CITY MODELS: TESTING THE MATURITY OF THE UTILITY NETWORK ADE FOR CITYGML WITH A WATER NETWORK TEST CASE

2018 ◽  
Vol IV-4 ◽  
pp. 13-20 ◽  
Author(s):  
I. Boates ◽  
G. Agugiaro ◽  
A. Nichersu
Keyword(s):  
Relational Database ◽  
Data Model ◽  
Database Schema ◽  
Future Research ◽  
Physical Parameters ◽  
Test Case ◽  
Network Modelling ◽  
Complex Development ◽  
Relational Database Schema ◽  
Utility Network

<p><strong>Abstract.</strong> Recent advances in semantic 3D city modelling and a demand from utility network operators for multi-utility data models integration have contributed to the emergence of an open Application Domain Extension (ADE) of the CityGML data model tailored to multiple types of utility networks. This extension, called the Utility Network ADE, is still in active development. However, work is already well underway to create data samples and to develop methods of modelling thereupon. In this paper, a mapping of the Utility Network ADE data model to a relational database schema is introduced. A sample of a freshwater network using the Utility Network ADE and based on data from the city of Nanaimo, Canada, is also presented. This sample has also been imported into a relational database schema built upon the 3DCityDB (a database implementation of CityGML) extended with a schema of the Utility Network ADE. Further to this, a series of basic network analysis functions have been defined and implemented in SQL to interact with the database so as to carry out sample atomic processes involved in network modelling, such as reading semantic properties of elements, calculating composite physical parameters of the network as a whole, and performing simple topological routing to serve as a guiding example for further and more complex development. A brief outlook is also presented, suggesting areas with high potential for future research and development of this nascent data model.</p>

A Sensitivity-Enhancing Control Approach for Structural Model Updating

2007 ◽  
Author(s):  
L. J. Jiang ◽  
K. W. Wang ◽  
J. Tang
Keyword(s):  
Closed Loop ◽  
Structural Model ◽  
Natural Frequencies ◽  
Model Updating ◽  
Measurement Data ◽  
Frequency Measurement ◽  
Physical Parameters ◽  
Fe Model ◽  
Initial Model ◽  
Closed Loop Systems

Model updating plays an important role in structural design and dynamic analysis. The process of model updating aims to produce an improved mathematical model by correlating the initial model with the experimentally measured data. There are a variety of techniques available for model updating using dynamic and static measurements of the structure’s behavior. This paper focuses on the model updating methods using the measured natural frequencies of the structure. The practice of model updating using only the natural frequencies encounters two well-known limitations: deficiency of frequency measurement data, and low sensitivity of measured natural frequencies with respect to the physical parameters that need to be updated. To overcome these limitations, a novel model updating method is presented in this paper. First, closed-loop control is applied to the structure to enhance the sensitivity of natural frequencies to the updating parameters. Second, by including the natural frequencies based on a series of sensitivity-enhanced closed-loop systems, we can significantly enrich the frequency measurement data available for model updating. Using the natural frequencies of these sensitivity-enhanced closed-loop systems, an iterative process is utilized to update the physical parameters in the initial model. To demonstrate and verify the proposed method, case studies are carried out using a cantilevered beam structure. The natural frequencies of a series of sensitivity-enhanced closed-loop systems are utilized to update the mass and stiffness parameters in the initial FE model. Results show that the modeling errors in the mass and stiffness parameters can be accurately identified by using the proposed model updating method.

Optimization of space-constrained micro-perforated absorbers by causality criteria

2021 ◽  
Vol 263 (6) ◽  
pp. 275-286
Author(s):  
Teresa Bravo ◽  
Cedric Maury
Keyword(s):  
Absorption Coefficient ◽  
Low Frequency ◽  
Single Layer ◽  
Optimization Procedure ◽  
Separation Distance ◽  
Physical Parameters ◽  
Total Absorption ◽  
Causality Criterion ◽  
Selection Of ◽  
Total Absorption Coefficient

The problem of space-constrained absorbers in the low frequency range constitutes an area of continuous research. Micro-perforated panels are advantageous because they can be tuned by a proper selection of their constitutive physical parameters including the diameter of the perforations and their separation distance, their thickness and the length of the backing cavity. However, such optimal selection is not straightforward, especially when considering multi-layer partitions. Current optimization algorithms are based on the maximization of the total absorption coefficient averaged over a frequency band, that requires a compromise between the bandwidth and the thickness of the control device. In this work, the problem is analysed on the basis of a causality criterion. This principle is generalized from its formulation in the field of electromagnetism to obtain a relation that correlates the thickness-to-bandwidth performance of a micro-perforated absorber to its total absorption coefficient. Using this relation, an optimization procedure is presented for the sequential selection of the optimal physical parameters for single-layer partitions. An excellent agreement has been found between the optimal values obtained by the causality criterion and those achieved by critical coupling conditions.

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