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An Irish Rail intercity train was instrumented for a period of one month with inertial sensors. In this paper, a novel calibration algorithm is proposed to determine, with reasonable accuracy, vehicle model parameters from the measured vehicle response data. Frequency domain decomposition (FDD) is used to find the dominant frequencies in the captured data. Randomly chosen 2 km data segments are chosen from a number of datasets, thereby averaging out the effects of variations in track longitudinal profile, track stiffness, signal noise and other unknowns. The remaining dominant peaks are taken to be vehicle frequencies. An optimization technique known as Cross Entropy is used to find vehicle mass and stiffness properties that best match modal vehicle eigenfrequencies identified in the frequency analysis. Finally, the calibrated vehicle is run over a measured track profile and the resulting model output is compared to measured data to validate the results. Key words: calibration, measurement, frequency domain decomposition, railway vehicle dynamics, cross entropy, optimization. Un train interurbain Irish Rail a ete instruments avec des capteurs inertiels pendant un mois. Dans le present document, un nouvel algorithme d'etalonnage est propose pour determiner, avec une precision raisonnable, les parametres de modelisation de vehicule a partir des donnees mesurees de reponse du vehicule. La decomposition du domaine des frequences (<< FDD >>) est utilisee pour trouver les frequences dominantes dans les donnees recueillies. Les segments de donnees sur 2 km choisis au hasard sont selectionnes a partir d'un certain nombre d'ensembles de donnees, ce qui permet d'obtenir une moyenne des effets des variations du profil longitudinal de la voie, de la rigidite de la voie, du bruit des signaux et d'autres inconnues. Les pics dominants restants sont consideres comme des frequences de vehicule. Une technique d'optimisation connue sous le nom d'entropie croisee (<< cross entropy >>) est utilisee pour trouver les proprietes de masse et de rigidite de vehicule qui correspondent le mieux aux frequences propres du vehicule identifiees dans l'analyse modale de frequences. Enfin, le vehicule etalonne passe sur un profil de voie mesure et les donnees du modele sont comparees aux donnees mesurees afin de valider les resultats. [Traduit par la Redaction] Mots-cles : etalonnage, mesure, decomposition du domaine des frequences, dynamique des vehicules ferroviaires, entropie croisee, optimisation., 1. Introduction Measurement of the inertial response of in-service trains has the potential to provide real-time railway track condition information to owners of the track asset. The increase in the [...]

Students' engagement is a fundamental challenge in large classrooms in higher education. In recent years, innovative technologies such as electronic learning and online polling platforms have made learning more engaging, effective, and interactive. By using these platforms, educators can create more inclusive and enriching learning environments. This paper presents a novel approach in which an online technology is employed to enhance students' learning experience. In this approach, features of an online polling platform, i.e., Slido, are employed to enhance students' engagement in an engineering module, i.e., 'Mechanics of Solids', which is recognised as a fundamentally challenging module with difficult subjects. This study investigates how the interactive features of such technologies, such as real-time polls, question and answer (Q&A) sessions, and quizzes, can provide a more active and practical learning environment by improving student engagement in the classroom. In total, six online polls were designed: one for ice-breaking, two on the topics of shear forces and bending moment, two on stresses, and one on deflection. Each poll was presented to the students, and they participated in them by scanning a QR code or typing the poll's code online. The rate of students' participation in polls is extensively discussed to show the effectiveness of the proposed method. The findings of this study show a significant increase in student participation in classroom activities compared to traditional methods. Student feedback also indicates a positive learning experience with the use of the proposed approach. It is shown that the proposed approach has the potential to transform the way engineering students engage with challenging subjects, leading to enhanced learning outcomes and a more positive learning experience. [ABSTRACT FROM AUTHOR]

Simplified methods are often used for load estimations during the initial design of the foundations of offshore wind turbines (OWTs). However, the reliability of simplified methods for designing different OWTs needs to be studied. This paper provides a comparative study to evaluate the reliability of simplified approaches. The foundation loads are calculated for OWTs at the mudline level using a simplified approach and OpenFAST simulations and compared. Three OWTs, NREL 5 MW, DTU 10 MW, and IEA 15 MW, are used as reference models. An Extreme Turbulence Model wind load at a rated wind speed, combined with a 50-year Extreme Wave Height (EWH) and Extreme Operating Gust (EOG) wind load and a 1-year maximum wave height are used as the load combinations in this study. In addition, the extreme loads are calculated using both approaches for various metocean data from five different wind farms. Further, the pile penetration lengths calculated using the mudline loads via two methods are compared. The results show that the simplified method provides conservative results for the estimated loads compared to the OpenFAST results, where the extent of conservativism is studied. For example, the bending moment and shear force at the mudline using the simplified approach are 23% to 69% and 32% to 53% higher compared to the OpenFAST results, respectively. In addition, the results show that the simplified approach can be effectively used during the initial phases of monopile foundation design by using factors such as 1.5 and 2 for the shear force and bending moment, respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a new deep-learning framework for drive-by bridge condition monitoring. The proposed approach represents a bridge monitoring regime that enables the presence, type, location, and severity of bridge damage to be identified purely from measurements taken on a passing vehicle, without needing any pre-measured training data. The computational framework adopts a numerical vehicle--bridge interaction (VBI) model, which is automatically calibrated using only the vehicle vibration measurements. The calibrated model is used to generate labeled training data, eliminating the practical difficulties associated with collecting training data for damaged bridge scenarios. The numerically simulated data are used to train a convolutional neural network that can then classify the actual damage characteristics of a bridge. The method is tested using a laboratory-scale VBI model, and results show that the algorithm can accurately identify the presence of seized bearings and cracking in the bridge beams. The algorithm shows good accuracy when identifying the type and extent of damage. The location of bearing damage can generally be identified; however, the location of cracking is less accurate at lower damage levels. The proposed framework represents a significant improvement on existing techniques for indirect bridge monitoring. [ABSTRACT FROM AUTHOR]

The International Roughness Index (IRI) is widely accepted as a measure of pavement condition. However it was developed as an indicator of passenger comfort as they travel in a vehicle on the pavement. In this paper, for the assumed failure model adopted, IRI is not found to be a good indicator of remaining pavement service life. The 3D continuous wavelet transform is proposed and shown to be a more effective indicator. Specific scales related to natural frequencies of the vehicle fleet, particularly the body mass frequency, are more significant than others. A weighted mean of the wavelet coefficients for these scales is used as an indicator of remaining life. One hundred randomly generated class A profiles are generated and their histories of damage progression throughout their lives are simulated. The new indicator is applied to the initial profiles to determine which ones are more vulnerable to damage than others. In numerical simulations using the assumed damage model, the wavelet based indicator is shown to be well correlated with service life. Key words: wavelet, IRI, pavement, dynamic, deterioration, damage, traffic. L'indice de rugosite international (IRI) est largement accepte comme etant une mesure de l'etat de la chaussee. Cependant, cet indice a ete developpe en tant qu'indicateur de confort des passagers alors ils voyagent dans un vehicule sur la chaussee. Dans cette etude, en ce qui concerne le modele de defaillance hypothetique adopte, l'IRI ne s'avere pas etre un bon indicateur de la duree de vie restante de la chaussee. Une transformee continue par ondelettes a trois dimensions est presentee et on montre que celle-ci est un indicateur plus efficace. Des echelles specifiques liees aux frequences naturelles du parc de vehicules, particulierement la frequence de la masse du corps, sont plus determinantes que d'autres. Une moyenne ponderee des coefficients d'ondelettes pour ces echelles est utilisee comme indicateur de vie restante. 100 profils de classe A aleatoirement produits sont degages et leurs historiques de progression de defaillance au cours de leurs vies utiles sont simulees. Le nouvel indicateur est applique aux profils initiaux afin de determiner lesquels sont plus vulnerables aux dommages que d'autres. Dans les simulations numeriques au moyen du modele de defaillance hypothetique, l'indicateur base sur les ondelettes s'avere etre bien correle a la duree de vie utile. [Traduit par la Redaction] Mots-cles : ondelette, IRI, structure de chaussee, dynamique, deterioration, dommage, circulation., 1. Introduction Road authorities need to routinely monitor flexible pavements to determine their condition to facilitate better maintenance planning. As a proxy of pavement condition, most developed countries measure the [...]

The Ibrahim time domain (ITD) identification technique was one of the first techniques formulated for multiple output modal analysis based on impulse response functions or general free decays. However, the technique has not been used much in recent decades due to the fact that the technique was originally formulated for single input systems that suffer from well-known problems in case of closely spaced modes. In this paper, a known, but more modern formulation of the ITD technique is discussed. In this formulation the technique becomes multiple input by adding some Toeplitz matrices over a set of free decays. It is shown that a special participation matrix can be defined that cancels out whenever the system matrix is estimated. The participation matrix becomes rank deficient if a mode is missing in the responses, but if any mode is present in one of the considered free decays, the participation matrix has full rank. This secures that all modes will be contained in the estimated system matrix. Finally, it is discussed how correlation functions estimated from the operational responses of structures can be used as free decays for the multiple-input ITD formulation, and the estimation errors of the identification technique are investigated in a simulation study with closely spaced modes. The simulation study shows that the multiple-input formulation provides estimates with significantly smaller errors on both mode shape and natural frequency estimates. [ABSTRACT FROM AUTHOR]