A Method for Identification of Powerplant Joint Properties Using FRF Data and FEM Model

The evaluation of the structural performance and durability using only measurement data without any baseline data is practical. One measurement data type is the frequency response function (FRF) data set, which does not provide enough information about the health state because of the noise included in the data. Proper orthogonal modes (POMs) extracted from the FRF data in a prescribed frequency range are utilized as an index to recognize the existence of damage. The POMs represent the principal axes of inertia formed by the distribution of data on the modal coordinate curve. This work proposes a damage detection method to trace damage based on the POM energy curvature at the element of the finite element model. The validity of the proposed method is illustrated by a numerical experiment and an experimental test.

Damage detection in an offshore platform using incomplete noisy FRF data by a novel Bayesian model updating method

Linear systems are good approximations of the input-output relationship for many real systems. In practice, ensembles of nominally identical systems can seldom be adequately represented by a single linear system. Some accommodation needs to be made for representing inherent ensemble randomness. One approach would be to use a parameterized model of the system, with the random nature captured in discrete parameters of the parameterized model. Another approach is to use data measured from each system in the ensemble to represent the random nature of the ensemble in a non-parametric form. This is the approach described in this paper. There are several different types of data that could be collected from each system in the ensemble, each type capable of capturing the input-output behavior of the linear system: input-output time domain data, perhaps with specific excitation sequences; Markov parameters; and Frequency Response Functions (FRFs) to name a few. We choose to work with FRF data because many system attributes can be easily interpreted by inspection of the FRF. FRF data can also be used directly for control design. This paper develops a Karhunen-Loeve expansion representation for linear system behavior based on FRF data to develop a compact representation of the uncertainty inherent in an ensemble of systems. This non-parametric, compact, representation of the distribution of linear systems can then be used to characterize the performance and stability of a given feedback control law, as well as for control law design.

An experimental verification of a parameter estimation algorithm for finite-element (FE) model updating for damage quantification of a concrete beam with extensive damage is presented using the measured frequency response function (FRF) data. The intact stage of the beam and four progressive damage stages are investigated to update the FE model to quantify the damage across the beam. The method uses a subset of measured FRF data for FE model updating via a quasi-linear sensitivity equation of structural response. A least-squares algorithm with an appropriate weighting technique is used for parameter estimation. Proper selection of excitation frequency ranges for model updating is addressed. Predicted equivalent stiffnesses demonstrate the success and robustness of the method in damage quantification, even when using only a subset of the measured FRF data.

Summary An efficient approach to identify multiple cracks in a slender beam using the frequency response function data is presented. It is formulated in a general form from the dynamic stiffness equation of motion for a structure and then applied to a slender beam. The cracks are modeled by rotational springs and the frequency response function is computed based on a spectral element model by the spectral finite element. The procedure gives a linear relationship explicitly between the changes of the measured frequency response function and crack parameters. The inverse problem is solved iteratively for the depths and locations of the cracks through the sensitivity-based model updating. Some numerically simulated tests on beam examples are provided for validating the feasibility of the method to identify the cracks. The results are generally agreement with the target values. Finally, the effect of noise on the damage identification is discussed in the numerical examples.

In experimental modal analysis, the use of characterized excitation and the choice of window functions are fundamental to the estimation of system frequency response function (FRF) data. It greatly influences the quality of the resulting FRF measurements. Discussed are combination methods of several commonly-used excitation signals with window function, which is relative to lightly damped systems. Study shows that burst random signal with Rectangular works well for lightly damped structures, and pure random with Hanning will bring about higher error. A modal testing of white car body was done. Experimental parameters analysis are given to demonstrate the study result presented above. So it poses a practicable method for improving the accuracy of frequency response function (FRF) measurements of lightly damped structure by using proper excitation signal with appropriate window function.

P097 Direct measurement of electric fields in human and monkeys during transcranial electric stimulation

A ‘Sub-PolyMAX’ method is proposed in this paper not only for estimating modal parameters, but also for identifying structural flexibility by processing the impact test data in narrow frequency bands. The traditional PolyMAX method obtains denominator polynomial coefficients by minimizing the least square (LS) errors of frequency response function (FRF) estimates over the whole frequency range, but FRF peaks in different structural modes may have different levels of magnitude, which leads to the modal parameters identified for the modes with small FRF peaks being inaccurate. In contrast, the proposed Sub-PolyMAX method implements the LS solver in each subspace of the whole frequency range separately; thus the results identified from a narrow frequency band are not affected by FRF data in other frequency bands. In performing structural identification in narrow frequency bands, not in the whole frequency space, the proposed method has the following merits: (1) it produces accurate modal parameters, even for the modes with very small FRF peaks; (2) it significantly reduces computation cost by reducing the number of frequency lines and the model order in each LS implementation; (3) it accurately identifies structural flexibility from impact test data, from which structural deflection under any static load can be predicted. Numerical and laboratory examples are investigated to verify the effectiveness of the proposed method.

ABSTRACTIn this paper, the capabilities of an enhanced sensitivity relation for the structural model updating are validated using a subset of the measured frequency response function (FRF) and natural frequency data of a laboratory concrete beam. The sensitivity relation of FRF is expressed implicitly as a function of the change of the mode shapes and incomplete measured natural frequencies of the damaged structure. In order to achieve more accurate parameters estimation results, an enhanced sensitivity relation is proposed by incorporating the measured natural frequencies of the damaged structures in the mathematical formulation. Solution of sensitivity equations by Least Square algorithm yields to the damage parameters. The method is applied to experimental data of a pin-roller concrete beam subjected to the extensive damage cases. The experimental results prove robust model updating results by the proposed method.

Modelling the behaviour of Pneumatic Artificial Muscle (PAM) has proven difficult due to its highly complicated structure, nonlinear nature of rubbery material, and air compressibility. To overcome these limitations, a FEM (Finite Element Method) model using Abaqus and CATIA is derived for the quantitative analysis on the impact of different factors on the pulling force of PAM. In the Abaqus a two parameter Mooney–Rivlin model is utilized to consider the hyper-elastic nature of flexible material. Then both Abaqus and CATIA are used in the parametric design of a 3-Dimensional model of PAM. Furthermore, the FEM model is employed to predict the static force exerted by PAM and the results show that the model is promising. The FEM model produces closer results to the test data for the typical PAM. Nonlinear behaviour of PAM is found to be obvious with an increase in both the contraction and the air pressure, different from the linear curves obtained by the fundamental geometrical model. Nonlinear changes in the PAM force are also observed in the numerical study on the effect of structural factors including initial braid angle, initial diameter, initial wall thickness, and flexible material. Besides, these phenomena can be explained by a connection between mechanical and morphological behaviour of PAMs with the FEM model. Generally, this modelling approach is more accurate compared to the fundamental theoretical model and more cost competitive compared to the empirical methods.

Damage indices based on structural dynamic characteristics are often used to detect damage in the structures. In this study, a new index for identifying damages in base-isolated structures is proposed using the frequency response function (FRF). Since calculation of the FRF data is time- and memory-consuming for problems of large size, the two-dimensional principal component analysis technique is employed to decrease the data size. The damage indices calculated, representing the health state of the structure, are stored in a database, which are then used to detect the damage location and severity by utilizing the lookup table method. The proposed damage detection method is applied to four concrete frame models, one of which is fixed at the base and the others are isolated by elastomeric bearings. The FRF data are polluted with three different noise values (5%, 10% and 15%) in order to evaluate the uncertainty of measurements. The accuracy of the proposed indices is compared with each other for various parameters such as noise values, bearings characteristics, base conditions and different damage scenarios. The results show the precision of the proposed method.

The thermal conductivity of emulsion-polymerized styrene–butadiene rubber (ESBR) composites filled with carbon nanotubes (CNTs), zinc oxide (ZnO) and alumina (Al2O3) was predicted using the finite element method (FEM). Two-dimensional (2D) FEM models, which involved the effects of aspect ratio (AR), shape, orientation and thermal conductivity anisotropy (TCA) of the CNTs, and interfacial thermal resistance (ITR), were used to simulate the microstructure of CNT filled ESBR composites. Also, 2D and three-dimensional (3D) FEM models were developed to simulate the microstructure of Al2O3 or ZnO filled ESBR composites. An increase in the thermal conductivity with increasing Al2O3 or ZnO loadings was predicted by the FEM. The orientation angle (OA) of the CNTs and the ITR strongly affect the thermal conductivity as predicted by the FEM. The TCA of the CNTs also has a prominent effect on the thermal conductivity when CNTs have a relatively small OA. At a given filler loading, the thermal conductivity increased with the increasing intrinsic thermal conductivity of the filler over a certain range for a particular shape of filler. The thermal conductivities predicted by the FEM were compared with those predicted by Agari's models and the experimental results. The trends of the thermal conductivity predicted by the FEM agreed with the experimental data. The thermal conductivity of the ESBR composites predicted by 2D and 3D spherical particle filler (SPF) FEM models as a function of ZnO and Al2O3 loading showed that the 3D SPF FEM model agreed well with the experimental results at low loadings (not higher than 20 phr), while the 2D SPF FEM model agreed well with the experimental results at high loadings (higher than 80 phr). In addition to being used for the analysis of existing composites, the proposed FEM models are useful for the design and optimization of new composite materials, and are expected to provide a more insightful understanding into the thermal conductivity of polymeric composites.

Electrothermal purification is an effective method for achieving over 99.9 pct purity for graphite particles with minimal environmental impact. However, the lack of a suitable heat and electric resistivity model has hindered the scaling up of electrically heated fluidized bed (EHFB) reactors for graphite purification. In this study, three commercial natural graphite flake populations were tested in a bench-scale fluidized bed reactor at temperatures of up to 1000 °C. The experiments varied key parameters, including the graphite particle size, particle bed temperature, fluidization index, and electrode depth within the particle bed. Controlling the fluidized bed reactor at high temperatures requires an understanding of bed resistivity and how current flows throughout the EHFB system. The results show that fluidized bed resistivity decreases with temperature, with a diminished effect at higher temperatures. Smaller particles exhibit a higher resistance, likely due to a larger number of contact points required to pass current between the electrodes. In this study, a Finite Difference Method (FDM) model was developed using Visual Basic for Applications (VBA) in Excel®. Additionally, a Finite Element Method (FEM) model was created using COMSOL Multiphysics®. The FDM model assumes the current flows only radially, whereas the FEM model accounts for both radial and vertical current flow. The FDM model was validated against experimental data. Additionally, the FDM model was verified through a comparison with the FEM model. The FDM model showed good agreement with experimental resistance data and moderate agreement with power consumption, while the FEM model provided more accurate predictions by accounting for a detailed geometry and heat loss mechanisms. Achieving a uniform temperature distribution within the fluidized bed is influenced by the electrode’s contact area. Deeper immersion of the electrode enhances thermal uniformity and provides results that more closely match experimental observations.

A three-dimensional finite element method (FEM) model simulating the electrochemical behaviour of Pt coplanar thin-film electrodes used for liquid cell transmission electron microscopy measurements was developed. The model included reaction kinetics and it was applied for the oxygen evolution reaction (OER). Kinetic parameters of OER in the liquid cell were experimentally acquired and applied to the FEM model. Comparison between the experimental and simulated polarization curves demonstrated the reliability of the FEM predictions. The simulations were used to produce maps of the potential and current density distributions of the working and counter electrodes as well as for calculating the distribution of the current density in the liquid electrolyte. Two distinctive electrode geometries were evaluated with the FEM model. It was predicted that non-symmetrical electrode designs can cause unexpected electrochemical behaviour with respect to the electrolyte current density between working and counter electrodes accompanied by the presence of hot spots. The findings suggest that FEM simulations could be key to designing well-performing electrochemical microcells for liquid phase electron microscopy experiments.

Slope stability in the Himalayas is a critical issue due to the region's unique geological and tectonic characteristics. The rocks of Himalayas are fragile and weak due to complex deformational structures causing the instability of slopes which are common, posing significant risks to infrastructure and communities. The central Nepal is characterized by similar problems and while constructing the engineering structures, challenges might be encountered. This study is aimed at modelling slope stability along the Malekhu-Dhadingbeshi road section of NH43 lying at the central Nepal lesser Himalaya using Kinematic analysis and Finite Element Method (FEM) modelling. The FEM modelling was conducted using two different computer programs. It was carried out at six different potential slopes with multifaceted geometry composed of slightly to moderately weathered quartzites and phyllites. The potential slope sections were identified using satellite imagery and field observations with key indicators including the condition of the slope toe, the presence of dislodged rocks and the formation of tension cracks. Their geometries were then created from the survey data obtained from topographic survey in the field. Input parameters for the modeling, such as cohesion and friction angle were calculated using the Hoek-Brown criterion while unit weight, elastic modulus and uniaxial compressive strength of rocks were determined from laboratory tests. The modelling was carried out under static condition provided there are no external influences from seismic activity or water forces. Out of six identified slopes sections, three of them were found to be critical during kinematic analysis, which were further modelled using FEM. Results from FEM revealed the non-significant total displacement at all of the three slope sections with higher critical Strength Reduction Factor (SRF) making the slopes stable. The findings also highlight the strength of the slopes under current conditions, providing valuable information for infrastructure planning in the region.