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A general time domain finite element formulation and several efficient numerical techniques are combined to form a new method of analysis for the solution of three‐dimensional soil‐structure interaction problems in the time domain. For elastic systems the method is a very cost effective alternative to the frequency domain approach. However, the major advantage of the new method is its ability to be extended to non‐linear behaviour such as separation of foundation and soil or non‐linear material. The general equations of motion for the linear cases are expressed in terms of the relative displacements of the soil‐structure system with respect to the displacements of the buried part of the structure (volume methods). This formulation allows the load vector to be an exclusive function of the free field accelerations at the foundation level. The non‐linear case requires that the equation of motion be established in terms of the total interaction displacements. The soil is modelled with three‐dimensional solid elements in the near field and axisymmetric elements in the far field. Coupling between the two systems is enforced by expanding the displacements of the solid elements in terms of the axisymmetric ones. Reduction in the number of degrees of freedom is achieved by the use of orthogonal sets of Ritz functions. The reduced system of equations is uncoupled and solved very efficiently using the complex eigenvectors. A numerical example consisting of the response of a structure resting on a homogeneous half‐space is solved using the new method and one of the approaches in the frequency domain. Results given by both methods are remarkably similar.

To develop a homogenization technique to directly and efficiently take the eddy current effects in laminated magnetic cores within time domain finite element (FE) analyses.

The technique is developed for being used within a 3D magnetodynamic b‐conform FE formulation, e.g. using a magnetic vector potential. To avoid a fine FE discretization of all the laminations of a magnetic core, this one is considered as a source region that carries predefined current and magnetic flux density distributions describing the eddy currents and skin effect along each lamination thickness. Both these distributions are related and are first approximated with sub‐basis functions. Through the homogenization or averaging of the sub‐basis functions contributions in the FE formulation, the stacked laminations are then converted into continua, thus implicitly considering the eddy current loops produced by parallel magnetic fluxes. The continuum is then approximated with classical FE basis functions and can be defined on a coarser discretization.

The developed method appears attractive for directly and efficiently taking into account within finite element analyses the eddy current effects, i.e. the associated losses and magnetic flux reduction, that are particularly significant for high frequency excitations. The time domain analysis allows the consideration of both non‐linear and transient phenomena.

The averaging of sub‐basis functions contributions, describing fine distributions of fields, in an FE formulation leads to an original way of homogenizing laminated regions. The proposed method is naturally adapted for time domain analyses and in some sense generalizes what can be done more easily in the frequency domain.

A computer program named DOTIG1 was developed for the study, in the time domain, of the interaction of transient electromagnetic pulses (EMP) with structures modelled by thin wires. The numerical procedure used is described and the results obtained with DOTIG1 are compared with those obtained, in the frequency domain, by other authors, using the Fourier transform. The comparison is specifically applied to the scattering cases from a simple stick model of an aircraft, from a wire cross in front of an infinite perfect conductor and from a junction of two wires with different radii.

The purpose of this paper is to apply the novel instantaneous power flow balance (IPFB)-based identification strategy to a specific practical situation like nonlinear lap joints having single and double bolts. The paper also investigates the identification performance of the proposed power flow method over conventional acceleration-matching (AM) methods and other methods in the literature for nonlinear identification.

A parametric model of the joint assembly formulated using generic beam element is used for numerically simulating the experimental response under sinusoidal excitations. The proposed method uses the concept of substructure IPFB criteria, whereby the algebraic sum of power flow components within a substructure is equal to zero, for the formulation of an objective function. The joint parameter identification problem was treated as an inverse formulation by minimizing the objective function using the Particle Swarm Optimization (PSO) algorithm, with the unknown parameters as the optimization variables.

The errors associated with identified numerical results through the instantaneous power flow approach have been compared with the conventional AM method using the same model and are found to be more accurate. The outcome of the proposed method is also compared with other nonlinear time-domain structural identification (SI) methods from the literature to show the acceptability of the results.

In this paper, the concept of IPFB-based identification method was extended to a more specific practical application of nonlinear joints which is not reported in the literature. Identification studies were carried out for both single-bolted and double-bolted lap joints with noise-free and noise-contamination cases. In the current study, only the zone of interest (substructure) needs to be modelled, thus reducing computational complexity, and only interface sensors are required in this method. If the force application point is outside the substructure, there is no need to measure the forcing response also.

This paper describes a computer program DOTIG4, for the study in the time domain, of the interaction of transient electromagnetic pulses (EMP) with arbitrary perfect conducting (PEC) surfaces modelled by planar triangular patches. DOTIG4 is based on the solution of the Time Domain Electric Field Integral Equation (TD‐EFIE) by the method of moments (MoM) using a marching‐on‐in‐time procedure. The code is applied to transient scattering of several structures and to calculate the input impedance of several broadband antennas.

The purpose of this paper was to perform an experimental investigation to analyze vibration and noise of unloaded gearbox with different oil quality. All motor-driven machinery used in the modern world can develop faults. The maintenance plans include analyzing the external relevant information of critical components, in order to evaluate its internal state. From the beginning of the twentieth century, different technologies have been used to process signals of dynamical systems.

A proposed neural network (NN) is also employed to predict vibration parameters of the experimental test rig. Moreover, four types of oils are used for gearbox to predict reliable oil. Vibration signals extracted from rotating parts of machineries carry lot many information within them about the condition of the operating machine. Further processing of these raw vibration signatures measured at a convenient location of the machine unravels the condition of the component or the assembly under study. The experimental stand for testing an unloaded gearbox is composed by actuated direct current (DC) driving system.

This paper deals with the effectiveness of wavelet-based features for fault diagnosis of a gearbox using two types of artificial neural networks (ANNs) and stress analyzed with computer-based software ANNs. The results improved that the proposed NN has superior performance to adapt experimental results.

This paper is one such attempt to apply machine learning methods like ANN. This work deals with extraction of wavelet features from the vibration data of a gearbox system and classification of gear faults using ANNs.

These kind of NN-based approaches are novel approaches to predict real-time vibration and acceleration parameters of unloaded gearbox with five types of oils. Also, the investigation contains new information about studied process, containing elements of novelty.

The focus of preventive maintenance (PM) programmes in industry is shifting from a pure statistical basis to online condition monitoring. Examines the shortcomings of statistical‐based PM which are contributing to this shift, and the potential benefits of and current research issues within condition‐based PM. Notes that statistics and quality control techniques will continue to play a critical role in this evolution.

The purpose of this paper is to study the fault diagnosis of internal combustion (IC) engine gearbox using vibration signals with signal processing and machine learning (ML) techniques.

Vibration signals from the gearbox are acquired for healthy and induced faulty conditions of the gear. In this study, 50% tooth fault and 100% tooth fault are chosen as gear faults in the driver gear. The acquired signals are processed and analyzed using signal processing and ML techniques.

The obtained results show that variation in the amplitude of the crankshaft rotational frequency (CRF) and gear mesh frequency (GMF) for different conditions of the gearbox with various load conditions. ML techniques were also employed in developing the fault diagnosis system using statistical features. J48 decision tree provides better classification accuracy about 85.1852% in identifying gearbox conditions.

The proposed approach can be used effectively for fault diagnosis of IC engine gearbox. Spectrum and continuous wavelet transform (CWT) provide better information about gear fault conditions using time–frequency characteristics.

In this paper, experiments are conducted on real-time running condition of IC engine gearbox while considering combustion. Eddy current dynamometer is attached to output shaft of the engine for applying load. Spectrum, cepstrum, short-time Fourier transform (STFT) and wavelet analysis are performed. Spectrum, cepstrum and CWT provide better information about gear fault conditions using time–frequency characteristics. ML techniques were used in analyzing classification accuracy of the experimental data to detect the gearbox conditions using various classifiers. Hence, these techniques can be used for detection of faults in the IC engine gearbox and other reciprocating/rotating machineries.

To show a possible implementation of surface impedance boundary conditions (SIBCs) in a time domain formulation based on the cell method (CM).

The implementation is based on vector fitting (VF), a technique which allows a time domain representation of a rational approximation of the surface impedance to be found.

It is shown that very little computational effort is needed to find a very good VF approximation of simple SIBCs and that such approximation is easily fitted into existing CM codes.

The extension to higher order SIBCs has not been taken into account.

The proposed approach avoids the use of convolution integrals, is accurate and easy to implement.

This paper introduces the use of VF for the approximate time domain representation of SIBCs.

This paper aims to introduce an efficient time-domain formulation of adjustable accuracy for a consistent and trustworthy computation of electromagnetic field characteristics in randomly varying configurations. The developed methodology is carefully certified via comprehensive comparisons with the corresponding outcomes obtained by the Monte Carlo approach.

The presented methodology uses higher-order approximations of Taylor series expansions of stochastic multivariable functions for the rapid estimation of the electromagnetic field component mean value and confidence intervals of their variance. Toward this objective, new time-update equations for the mean value and the variance of the involved electromagnetic field are elaborately derived.

The featured technique presents an efficient alternative to the excessively resource-consuming Monte Carlo finite-difference time-domain (MC–FDTD) implementation, which requires an unduly number of realizations to achieve a satisfying convergence. The higher-order stochastic algorithm retrieves accurately the statistical properties of all electromagnetic field in a single simulation, presenting promising accuracy, stability and convergence.

The adjustable-accuracy higher-order scheme introduces a new framework for the derivation of the stochastic explicit time-update equations and precisely computes the required confidence intervals for the electromagnetic field variance instead of the variance itself, which can be deemed a key advantage over existing schemes. This fully controllable formulation results in significantly more accurate calculations of the electromagnetic field variance, especially for larger fluctuations of the involved electromagnetic media parameters.