Interpretation of the Dynamic Response of a Masonry Arch Rail Viaduct Using Finite-Element Modeling

Linear-elastic finite-element analysis is sometimes used to assess masonry arch bridges under service loads, despite the limitations of this method. Specifically, linear-elastic analysis can be sensitive to material properties, geometry, and support settlements, while also allowing the development of tensile stresses that may be unrealistic for masonry structures. However, even though linear-elastic methods remain appealing for their simplicity, it is rare to evaluate their output against experimental data. In this paper, detailed strain and displacement monitoring data for a masonry arch viaduct are used to evaluate a series of independently developed linear-elastic simulations of this structure. Although uncertainties in input parameters mean the magnitude of modeling results cannot be presumed accurate, the simulated response pattern was found to agree reasonably well with monitoring data in regions of low damage. However, more damaged regions produced a markedly different local response. Comparisons between the simulations revealed useful conclusions regarding common modeling assumptions, namely the importance of modeling backing material, spandrels, and foundation stiffness, to capture their influence on the arch response.This work forms part of a PhD, which is funded through an EPSRC Doctoral Training Partnership (grant reference number EP/M506485/1). Data collection was made possible by the Cambridge Centre for Smart Infrastructure and Construction, through additional EPSRC funding (grant reference number EP/L010917/1)

Evaluation of the response of a vaulted masonry structure to differential settlements using point cloud data and limit analyses

Differential settlements have adverse effects on the serviceability and stability of vaulted masonry structures. However, the existing monitoring and assessment techniques do not capture these effects in sufficient detail. In this paper, a new approach is proposed to better describe the influence of support movements on barrel vaults. In this approach, laser scan point clouds of a settling vaulted structure are compared. Different cloud comparison methods are used to accurately identify the displacements of small point cloud segments. In particular, a new cloud comparison method, which modifies the well-known iterative closest point (ICP) registration algorithm, is developed. By constraining ICP to ensure displacement continuity between adjoining point cloud segments, three dimensional movement estimates of the structure are obtained. These estimates delineate the settlement response by indicating the location and magnitude of cracking. This rich information is then used to identify the settlement response mechanism of the vault using limit state numerical analysis. Finally, by interpreting the numerical results with relevant serviceability criteria, a new method to quantify the influence of settlements on barrel vaulted masonry structures is proposed. This damage assessment technique is used to evaluate observed damage due to piling-induced settlements in a masonry viaduct at London Bridge Station.The work carried out was funded by EPSRC and Innovate UK, through the Cambridge Centre for Smart Infrastructure and Construction (Grant Reference Number EP/L010917/1)

Determination of free vibration properties of masonry arch bridges using the dynamic stiffness method

Masonry arch bridges constitute over half of the European bridge stock. The dynamic response of these bridges to traffic loads is influenced by their free vibration properties, i.e. their natural vibration frequencies and mode shapes. However, these properties have not been systematically examined to date. This paper utilises the dynamic stiffness method (DSM) to obtain an improved fundamental understanding of the free vibration properties of idealised single and multi-span arch bridges. In this approach, the piers and arches are modelled as an assembly of linear Timoshenko beam segments, the backing and infill are represented with axial struts and the underlying soil with concentrated spring elements. These idealisations enable rapid but accurate calculations of in-plane free vibration properties. To demonstrate this, the proposed procedure is applied to a simply-supported arch structure, a small-scale single-span arch bridge model and a multi-span arch bridge, where published experimental data is available. Then, free vibration analyses of representative single and multi-span arch bridges are performed. The results obtained from DSM analyses agree with detailed 3D finite element models and reveal the critical influence of backing elements and the interactions between adjacent spans on free vibration properties. Lastly, a range of arch bridge geometries are examined to reveal the shortcomings of existing provisions for modal frequency estimation in codes of guidance

Dynamic amplification in masonry arch railway bridges

Dynamic amplification of loads in masonry arch&nbsp;railway bridges&nbsp;is not well understood. There is a scarcity of experimental data and previous numerical studies have only addressed a few specific bridge geometries. Despite this, guidance documents provide empirical and unvalidated formulae to calculate dynamic amplification for masonry arch railway bridges. To improve our fundamental understanding of the problem, determine appropriate modelling strategies and evaluate the reliability of guidance documents, simple 2D and 3D models are explored in this paper. The 2D approach idealises key bridge components (pier, arch, fill and backing elements) with straight Timoshenko beams, springs and&nbsp;lumped masses. It uses an analytical&nbsp;dynamic stiffness&nbsp;formulation, which is computationally efficient and well-suited to explore a range of bridge models. The higher fidelity 3D modelling approach uses shell and solid finite elements and is used to evaluate the limitations of 2D models. In both approaches, linear-elastic&nbsp;material behaviour&nbsp;is assumed and train loads are idealised as moving vertical loads distributed over an effective area. The modelling results indicate a complex relationship between train speed and dynamic amplification that depends critically on bridge geometry and axle spacing. In general, the multi-span bridge configurations experienced higher dynamic amplification over operational train speeds. The results also higlight deficiencies in existing code provisions and demonstrates how efficient numerical models may replace these provisions.</p

A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation

Publication status: PublishedAbstractTransformer architecture based on the attention mechanism achieves impressive results in natural language processing (NLP) tasks. This paper transfers the successful experience to a 3D point cloud segmentation task. Inspired by newly proposed 3D Transformer neural networks, this paper introduces a new Transformer‐based module, which is called Local Geo‐Transformer. To alleviate the heavy memory consumption of the original Transformer, Local Geo‐Transformer only performs the attention mechanism in local regions. It is designed to mitigate the information loss caused by the subsampling of point clouds for segmentation. Global Geo‐Transformer is proposed to exploit the global relationships between features with the lowest resolution. The new architecture is validated on a masonry bridge dataset developed by the authors for their earlier work on a previous segmentation network called BridgeNet. The new version of the network with Transformer architecture, BridgeNetv2, outperforms BridgeNet in all metrics. BridgeNetv2 is also shown to be lightweight and memory efficient, well‐adapted to large‐scale point cloud segmentation tasks in civil engineering.</jats:p

Dynamic response of single and multi-span beams under a moving load using dynamic stiffness formulations and Galerkin's method

© 2020 European Association for Structural Dynamics. All rights reserved.This paper is concerned with the dynamic response analysis of single and multi-span beams under moving point loads. The Dynamic Stiffness Method (DSM) is used to calculate the mode frequencies and shapes of single, two and four-span Bernoulli-Euler beams. The exact mode shapes obtained from dynamic stiffness formulations are used to derive generalized mass, stiffness and force terms for normal modes using Galerkin 's method. This enables efficient and accurate calculation of the time-history response of the investigated structures. This is demonstrated by comparing the results from this study with advanced finite element simulations of the same problem from the literature. The results validate the accuracy of this approach and demonstrate how this technique can be used to model dynamic amplification of bridges under the influence of moving loads

Distributed sensing of a masonry vault due to nearby piling

Piles were constructed inside historic brick barrel vaults during the London Bridge Station Redevelopment. In order to ensure safe operation of the tracks above, movements of the vaults were monitored regularly by total stations. Concurrently, two distributed sensing technologies, fibre optic cables and laser scanners, were used to investigate the vault response to settlements. This paper discusses the monitoring data retrieved from these ‘point’ and ‘distributed’ sensing technologies and evaluates their use in structural assessment. The total station data are examined first. It is characterized by high precision and limited spatial coverage due to the use of optical targets. As a result, the total station data are useful for threshold detection but do not provide a detailed understanding of structural response or damage. In contrast, by utilizing distributed fibre optic sensors based on Brillouin optical domain reflectometry, the strain development in the structure during piling is quantified. The location and width of resulting crack openings are also determined, providing useful indicators for damage evaluation. The comparison of point clouds from laser scanners obtained at different stages of pile construction further expands the spatial coverage by detecting global movement of the structure on all visible surfaces. Using these data, the two hinge-response mechanism of the vault is revealed. The rich distributed data enable the calibration of the 2D mechanism and the finite element models, elucidating the contribution of arch stiffness, arch and backfill interaction, potential lateral movements and inter-ring sliding to the response

Terrestrial Laser Scanning based deformation monitoring for masonry buildings subjected to ground movements induced by underground construction

[EN] Tunnelling and deep excavation activities cause ground movements. Monitoring the influence of these ground movements on nearby surface assets is a major component of urban underground construction projects. Such projects often require large-scale and comprehensive monitoring of nearby buildings to track displacements and identify structural damage. Masonry assets are particularly vulnerable to ground movements due to the low tensile strength of the material; these structures may experience unsightly cracking and structural stability issues. Current monitoring practice for these buildings is labour intensive and cannot fully characterise the response of the assets due to the limited number of measurement points. This paper presents a non-contact monitoring solution using terrestrial laser scan (TLS) data, which develops a modified non-rigid iterative closest point (N-ICP) algorithm. This algorithm optimises the displacement fields by establishing point to point correspondences that penalise non-smooth deformations and deviations from landmarks (i.e. feature points where displacements are known). The algorithm outputs rich 3D displacement fields that can be used in established assessment and decision-making procedures. To demonstrate this algorithm's ability to estimate 3D displacement fields from point clouds, several synthetic datasets are processed in this study. The results demonstrate the algorithm's potential for recovering underlying deformations with the help of landmarks and optimisation weightings.Liu, Y.; Acikgoz, S.; Burd, H. (2023). Terrestrial Laser Scanning based deformation monitoring for masonry buildings subjected to ground movements induced by underground construction. Editorial Universitat Politècnica de València. 375-382. https://doi.org/10.4995/JISDM2022.2022.1387237538

Extraction of key geometric parameters from segmented masonry arch bridge point clouds

[EN] Masonry arch bridges constitute the majority of the European bridge stock. Most of these bridges were constructed in the 19th century and feature a wide range of geometric characteristics. Since construction drawings rarely exist, the first step in the assessment of these bridges is the characterisation of their in-situ geometry, which may involve significant geometric distortions. In recent years, LIDAR devices have been widely used by bridge owners due to their ability to remotely and rapidly collect point cloud data. To enable the engineering assessment practice to benefit from this data, this research uses the recently developed deep learning (DL) neural network BridgeNet to autonomously segment masonry bridge point clouds into different components. Due to the limited availability of 3D point clouds, BridgeNet is trained using a synthetic multi-span masonry arch bridge dataset; the network is then tested on real arch bridge point clouds. By fitting appropriate primitive shapes to bridge component point clouds using Random Consensus Sampling (RANSAC) techniques the bridge geometry is effectively characterised by a few parameters.Jing, Y.; Sheil, B.; Acikgoz, S. (2023). Extraction of key geometric parameters from segmented masonry arch bridge point clouds. Editorial Universitat Politècnica de València. 185-190. https://doi.org/10.4995/JISDM2022.2022.1381418519