bluuebunny/crossref_metadata_2025_split huggingface dataset:
Damage Identification in Masonry Wall Specimens: Shake Table Studies
Authors: Latha Lakshmi , Ray-Chaudhuri S 
Published: June 2024

Abstract
Over the past few decades, vibration-based structural health monitoring and damage detection have drawn significant research attentions world-wide. The major motivation for such a research emphasis is the need to develop reliable methods to monitor the performance of structures in real-time. Real-time or continuous monitoring is also beneficial for timely maintenance of structure and to avoid any undesired failure. In this study, the efficiency of a few vibration based damage detection approaches has been investigated for identifying damage in a few wall specimens of brick masonry structures. Masonry is one of the most common and oldest material which is being used for constructing buildings for many years. Like concrete, masonry is also a brittle and highly non-linear material with good compressive but poor tensile strength. In masonry structures, damage generally occurs in distributed fashion and the pattern of cracks is often very complex as compared to steel structures. In addition, damping changes with the level of damage. An experimental study using shake table has been performed on a few half-scale wall-specimens. A suit of ground motions were selected based on Indian Code specified design ground motion spectrum. These motions were then scaled from very low intensity to high intensity by introducing amplitude scale factor with respect to the code specified level. The purpose of varying intensity input was to introduce progressive damage when subjected to the these excitations. In between each scale change, shake table tests with low intensity white-noise motions were performed. The purpose of white noise run in between two consecutive level of excitation was to simulate an ambient vibration condition for system identification. The specimens and the shake table were instrumented with accelerometers and displacement sensors to measure the input and responses. Various vibration-based techniques such as frequency domain decomposition and natural excitation technique (NExT) coupled with Eigen realization algorithm (ERA) techniques have been used for extraction of modal properties. It has been found from the experimental results that damage level can be easily correlated with a few damage identification parameters.
Investigating the relation between complex mode shapes and local damage for structural assessment
Authors: Masciotta Maria-Giovanna , Pellegrini Daniele 
Published: June 2024

Abstract
Modal parameters define the inherent characteristics of real-world structures, being therefore employed as reference information for various purposes, including the assessment of structural damage, the evaluation of operational and environmental effects, and the calibration of realistic numerical models. Among frequencies, damping ratios and mode shapes, the latter have been proved far more effective in localizing structural damage given their spatial dependency on the nodal coordinates of vibrating systems. Most of modal analysis applications resort to the real part of these quantities for vibration-based damage identification of structural systems, assuming them as classically damped. However, the classical viscous damping assumption is often idealistic for real-world structures as the damping matrix cannot be considered as proportional to mass and stiffness matrices. It follows that the mode shapes of real systems are complex in nature, and their complexity level can vary with damage. Based on the above considerations, this work intends to shed light on the relationship between structural damage and modal complexity. Numerical investigations are carried out to track the variation of complex mode shapes in a multi-span bridge subjected to progressive damage scenarios and to infer about the generalization of a new index that relies on the variation of the imaginary content of complex eigenmodes to detect, locate and assess the structural damage.
System identification in time domain of flexible aircraft using panel methods
Authors: Paula Thiago Rosado de , Sarmento Andrew Gomes Pereira , Fernandes Vitor Paixão , Fisher Clécio , Machado Raphaela Carvalho , Silva Roberto Gil Annes da , Sandoval Góes Luiz Carlos 
Published: June 2024

Abstract
The motivation to accurately model the dynamics of flexible aircraft grew with the development of energy-efficient aircraft, consequently, great aspect ratio aircraft. The development of an accurate model that represents the flight dynamics of a flexible aircraft has been pursued by industry and aeronautical research organizations during the last decades. One of these approaches is to find a flexible aircraft model using systems identification methods. This research aims to apply an integrated model containing longitudinal and lateral directional rigid body dynamics, coupled to the first four flexible body modes, for identification and validation from flight test data. The Unmanned Aerial Vehicle (UAV) Eolo with the flexible wing is used during the experiments. Initially, a finite element structural model (FEM) based on beam elements, concentrated masses, and rigid bars was used. The quasi-stationary panel model based on the Vortex Lattice Method (VLM) was adopted for the aerodynamic model. Two diagonal matrices were used to correct the aerodynamic influence coefficients (AIC) matrix obtained via VLM before and post-multiplication for aircraft identification. The estimation of the main diagonal elements of each matrix was obtained through the Output Error Method in the time domain. A model validation analysis was carried out, which shows a good correlation between the model and measurement data. In conclusion, getting correction matrices instead of stability derivatives is beneficial because matrices can be used more directly during the aeronautical design and observe the behavior concerning loads.
Highly stable kinematic nonlinear simulations using a Taylor basis
Authors: Andersen S , Poulsen P N 
Published: June 2024

Abstract
The simulation of kinematic nonlinear systems is typically very time-consuming. The computational cost is primarily related to a time-consuming evaluation of the internal restoring forces performed before each integration step. Using basis projection is a way to reduce the computational cost and, thereby, the simulation time. The present work considers a novel Taylor basis that can significantly improve the stability of the central difference time integration scheme for kinematic nonlinear simulations. It is illustrated that the time step stability limit for a kinematic nonlinear simulation using Taylor basis projection is more or less identical to the analytical stability limit known from linear systems. Furthermore, an example shows that the time step stability limit in simulations using Taylor basis projection can be two orders of magnitude higher than the stability limit of a standard kinematic nonlinear simulation. Thus, Taylor basis projection has the potential to significantly reduce the number of time steps and, thereby, the computational cost.
AI-Based Surrogate Models for Multibody Dynamics Systems
Authors: Koutsoupakis J , Giagopoulos D 
Published: June 2024

Abstract
Advancements in computer sciences and technology allow for implementation of detailed numerical models of a system such as the Finite Element (FE) or Multibody Dynamics (MBD) models. Complex mechanical systems can easily be modelled in detail, yielding accurate results. This opportunity provided by these high-fidelity numerical models has led to the broad application of such methods in development and prototyping of mechanical systems, their optimization and fault analysis and so on. The capability of detailed modelling however usually comes at a great computational cost, with the simulation time needed for a problem in many cases rising exponentially, rendering these models impractical. This problem becomes even more profound when one considers the recent integration of model-based data in data-driven methods where a large number of datasets is usually required, and multiple iterations of the same model must be simulated in order to produce the desired number of samples. To mitigate these short-comings, surrogate modelling has been extensively used in applications including large systems or repetitive runs in the form of Reduced Order Models (ROMs) to reduce the computations time and render these simulation-driven methods more viable. Use of these ROMs however is limited to cases where low loss of information is ensured, and the features lost due to the model simplification are insignificant. The developments in Artificial Intelligence (AI) and its applications have demonstrated its potential to accurately describe the relationships between a model’s inputs and outputs and as such using an AI algorithm as a surrogate model is a promising alternative. A properly trained AI algorithm can usually fit to FE and MBD models and yield accurate results at a fraction of the computational burden. To this end, an AI-based surrogate modelling framework is proposed in this work, with application on an experimental gear drivetrain system. A detailed MBD of the actual system is initially constructed and optimized via a black box optimization method in order to better simulate the physical system. A variety of supervised AI algorithms such as regression models and Convolutional Neural Networks (CNNs) is then examined as a surrogate to the various mechanisms of the system, aiming to replace them with the goal of reducing the simulation time while maintaining the high accuracy and fidelity of the original model. The various algorithms are then compared in terms of time reduction and accuracy both to each other and to the initial MBD model in order to conclude to the best suited for the application. The results are also compared to the measured response data of the physical system to ensure the validity of the models and prove the viability of the proposed method through its use on a relatively complex model. The proposed framework provides an alternative to the commonly used ROM methods and the presented application acts as a benchmark case for its implementation to more complex systems and different operating conditions.
Parametric Study on Structural Damage Classification with Numerically Simulated Vibration Data
Authors: Seventekidis Panagiotis , Karyofyllas George , Giagopoulos Dimitrios 
Published: June 2024

Abstract
Monitoring the health and working conditions of critical structures and machines can prevent failures and arrange for effective maintenance schedules. Access to vibration data from states with damages is valuable in order to train models that can perform explicit classification of faults in later states. This usually requires expensive and sometimes not feasible destructive tests in various operating conditions. Recent works have employed numerical models in order to simulate such scenarios. However, simulated data carries usually systematic errors in terms of the originally identified structure on the healthy state. In the present work, a test structure of a simple truss is studied with a Finite Element Model for vibration data generation. Training data sets are generated containing different errors in terms of damping, stiffness and mode shape accordance in order to emulate real application faults. The training data sets are used after in a Convolutional Neural Network for damage classification. It is investigated how different simulation error sources affect the generalization in terms of correct damage case prediction on a reference data set. The results may aid in strategies for focus on specific FE model updating parameters in order to generate reliable simulated training data
Modeling error assessment of reduced-order finite element models for SHM: A case study of Milad Tower
Authors: Sanayei Masoud , Esfandiari Akbar , Vahedi Maryam , Behboodi Saeed , Dabbaghchian Iman 
Published: June 2024

Abstract
Condition assessment, model updating, and basic studies of large and complex structures subjected to static and dynamic loadings necessitate establishing a reasonably low order model to enhance computational efficiency. An essential requirement for the development of a low-order model is to preserve the main characteristics of the full-scale model within the frequency range of interest or the desired static and/or dynamic response. In this regard, a novel reduced-order model (ROM) is developed based on a full-scale model (FSM) built using commercial finite element analysis software. Utilizing the common lumped mass matrix can introduce mass modeling errors. Hence, a method is proposed to extract the reduced consistent mass matrix model (RCMM) for use in the ROM. The modeling errors in the proposed ROM is studied for comparison with the static and dynamic responses. It can curtail capability of parameter estimation to capture the physical behavior of the structure using the ROM. Modeling error simulations prior to actual field-testing is highly recommended to determine the feasibility of non-destructive tests for successful system identification. The Milad telecommunication tower is the sixth tallest tower in the world, with a height of 435 meters. Using the proposed method, the consistency of the generated ROM based on the RCMM is verified with the Milad Tower’s FSM. In this regard, displacements due to equivalent static wind loads, natural frequencies, mode shapes, slopes of mode shapes, and time history response for earthquake loading are compared. The proposed ROM assessments utilizing RCMM confirm the accuracy of the static and dynamic characteristics.
Critical Speed and Dynamic Response of High-Speed Railway in Ballastless Track
Authors: Wu Ying , fu Haoran , Bian Xuecheng 
Published: June 2024

Abstract
The current requirements for train speed are getting higher and higher. When the train increases to the critical speed, it will cause resonance of track and substructure, which will adversely affect the train driving safety. At present, ballastless track is widely used in high-speed railway, and the vibration characteristics is different from ballasted track. Based on 2.5D finite element method, this paper establishes the vehicle-track-subgrade coupling model to analyze the critical speed of ballastless track under different foundation conditions. The relationship between critical speed and shear wave velocity of homogenous and layered subsoil is obtained through parametric analysis. The results show that the critical speed of bal-lastless track under homogenous subsoil depends on the Rayleigh wave velocity of subgrade. Besides, the presence of subgrade can improve the critical speed to be greater than the Ray-leigh wave speed of homogenous subsoil. Moreover, the critical speed of ballastless track un-der layered subsoil is influenced by the shear wave speed ratio of adjacent soil layers. Finally, the proposed empirical formula is of guiding significance for the construction of ballastless track.
Prediction of Ground and Building Vibrations Induced by High-speed Trains using a 3D Coupled Numerical Model Based on a Spectral Element Analysis Code
Authors: Feng Duo , Paolucci Roberto , Mazzieri Ilario 
Published: June 2024

Abstract
Controlling the vibrations induced by high-speed trains on environmental infrastructures, especially buildings situated along railway tracks, is an essential demand and a challenging task. In order to accurately predict the dynamic response of the ground and adjacent buildings to railway-induced vibrations, we conduct numerical validation based on an existing in-situ model test in Portugal. This validation is done using the spectral element numerical code SPEED, developed at Politecnico di Milano, which considers a fully coupled 3D model of both the ground and building. The mechanical parameters of the track structure, modeled by the beam on elastic foundation, are obtained by iteratively calibrating the analytical dynamic receptance curve according to the experimental data. We use a multi-objective optimization-based method to estimate the equivalent rectangular sections of building structural components. The recorded dynamic vertical responses of the nearby ground and building slab under the excitation of 219 km/h moving trains are compared with the numerical results. Specific attention is paid to the frequency range that dominates the dynamic response of the building to discuss the accuracy of the results.
Under ballast mats as mitigation measure for structure borne noise from railroad – assessment of effect on track deflection
Authors: Norén-Cosgriff Karin , Brekke Arild , Ekblad Alf , Aasen Trygve 
Published: June 2024

Abstract
The limit values commonly used in Sweden and Norway for structure borne noise from railroad are strict when seen in an international context. At the same time, tunnels with low coverage are regularly built through densely populated areas, which can cause complaints about high structural borne noise levels in nearby dwellings. Traditionally, ballasted tracks are used in most railway tunnels in Norway and Sweden and under ballast mats (UBM) are the usual structure borne noise mitigation measure. Since UBMs that meet technical regulations for rail in many cases do not provide sufficient effect, dispensations have been granted for the use of softer ballast mats in some projects. However, there is limited information about the effect of softer UBMs on maintenance and about whether soft UBMs lead to excessive rail deflections, which could affect the track adversely. There is therefore a need for more knowledge about how UBMs affect the track and especially at higher speeds. When assessing the effect of UBMs on the track, both information about the track displacement amplitude and the shape of the deflection curve is important. As a first step, a pilot study has been carried out to find a suitable method to measure rail deflection, which can be used for long-term monitoring in tunnels with UBM to gather more information. Three measurement methods were compared in a laboratory test rig: Linear Variable Differential (LVDT) displacement sensors, Fiber Bragg Grating (FBG) optical strain sensors, and high sensitivity low frequency accelerometers. The results indicate that by using a high-sensitivity, low-frequency (DC) accelerometer in combination FBG strain sensors, both an accurate determination of the displacement amplitude and information about the shape of the deflection curve can be obtained.
Vibration mitigation using seismic metamaterials on layered soil
Authors: Carneiro David , Kabirian Zohre , Reumers Pieter , Lombaert Geert , Degrande Geert 
Published: June 2024

Abstract
This paper investigates how the soil profile affects the vibration mitigation performance of seismic metamaterials in a wide frequency band (1 – 80 Hz). A 3D coupled finite element - boundary element (FE-BE) model with an efficient substructuring method is developed to analyze the vibration reduction performance of seismic metamaterials on top of a layered soil. Resonators are modeled as single degree of freedom systems on top of square concrete surface foundations. The response of uniform and graded metasurfaces on a homogeneous and layered halfspace due to harmonic point load are compared. The narrow band gap obtained for a uniform metasurface on a homogeneous halfspace is widened over a broader range of frequencies (40 – 70 Hz) using inverse metawedges. For layered soil conditions, vibration mitigation in a wide frequency band still emerges using metawedges. Their efficiency, however, is reduced.
On the improvement of design space subsets formulation for iteratively optimizing structural systems
Authors: Khalid M A , Bansal S 
Published: June 2024

Abstract
Structural optimization is the process of identifying the optimal set of design parameters for a structural system. Optimization techniques provide an effective approach for rationally improving structural engineering design, both for the structural system with deterministic and uncertain parameters. It is unanimously agreed that in engineering design applications, knowledge about a planned system is never comprehensive. These uncertainties resulting from incomplete information are often assessed probabilistically. In this probabilistic framework, the system design process is referred to as stochastic system design, and the concomitant design optimization problem is alluded to as stochastic optimization. The stochastic optimization process has been widely used in civil, mechanical, and aeronautical engineering designs. Stochastic system optimization includes two stages where initially the performance measure is approximated either by Taylor series approximation or the metamodels, and in the second stage, the approximated performance function is optimized by implementing the available optimization techniques such as nonlinear programming methods, gradient-based methods, metaheuristic methods, etc. Approaches available in literature can effectively take into account the uncertainties, but still, achieving higher accuracy and lower computational cost remains a challenging task for designing complex and realistic structural systems. To obliviate these aforementioned limitations, a simulation-based approach known as Stochastic Subset Optimization (SSO) is found to be very effective. The basic principle in the original SSO is to reduce the design space size iteratively, which has high plausibility of containing the optimal design solution. However, the success of the approach depends on the shape selection of the design space while implementing the SSO. Therefore, in the present study, the dependency of the original SSO over the selection of the shape of the design subset is overcome by exploring the design space based on the density of simulated design samples with the design space. This improves the applicability of the SSO to the complex, realistic problem. Two benchmark optimization problems: a 2-dimensional bowl-shaped sphere function and a helical compression spring design, are solved with the proposed approach to demonstrate the efficiency of the proposed approach.
Accurate frequency response function estimation using noise measurements in experimental modal analysis
Authors: Steffensen M T , Tcherniak D , Thomsen J J 
Published: June 2024

Abstract
In experimental structural dynamics, reliable estimation of Frequency Response Functions (FRF) is important to correctly characterize a mechanical system. In Experimental Modal Analysis (EMA), the FRFs are used as input to a modal parameter estimation algorithm to obtain the modal characteristics of the system. Errors due to noisy measurements are inevitably present in the FRFs and propagate to the modal parameters. A consistent FRF-estimator with low uncertainty is therefore needed. Different FRF estimators have been proposed with some consistency when certain noise-related assumptions are fulfilled (H1, H2, etc.). To choose the appropriate frequency response function estimator, information about the noise in the experimental setup is desirable. In this work it is shown how to use measurements of noise, to characterize different noise components in the experimental setup and determine the appropriate number of averages needed for the experimental setup. The identified noise components can be used to identify the main source of uncertainty in the experimental setup and which FRF estimator to use.