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Conference paperFang Q, Grosman S, Macorini L, et al., 2024,
Application of Digital Image Correlation to Field Monitoring of Masonry Arch Bridges
, SMAR 2024 – 7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures -
Journal articleRavasini S, Belletti B, Izzuddin BA, et al., 2024,
A robustness-oriented procedure for the design of tying reinforcement in precast concrete hollow-core floors
, STRUCTURES, Vol: 63, ISSN: 2352-0124 -
Journal articleVicencio F, Alexander NA, MálagaChuquitaype C, 2024,
Seismic Structure‐Soil‐Structure Interaction between inelastic structures
, Earthquake Engineering and Structural Dynamics, Vol: 53, Pages: 1417-1675, ISSN: 0098-8847Frequently, buildings in urban areas are designed by considering their stand-alone response, that is, as single structures with no neighboring buildings. Nevertheless, the existence of a high density of buildings in large metropolitan areas inevitably results in the likelihood of an important seismic interaction between adjacent buildings through the underlying soil. This paper explores the effects of Structure-Soil-Structure Interaction (SSSI) on the seismic response of two yielding structures embedded in a linear elastic soil. A simple two-dimensional nonlinear reduced-order parametric model is proposed, where different building parameters are considered. A nonlinear phenomenological Bouc–Wen model is assumed for the buildings. A database of 15 strong ground motion records and an additional spectrally matched seismic ground motion are considered. An extensive parametric study comprising over two million nonlinear cases is conducted. The results show important differences between nonlinear SSSI and nonlinear SSI for particular parameter configurations. Nevertheless, due to energy dissipation and increases in damping in the nonlinear case, the effects of SSSI are less relevant compared with the linear case.
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Journal articleSadowski AJ, Wong WJ, Li SCS, et al., 2024,
Dataset on the tested and simulated response of thick cold-formed circular hollow sections under cyclic loading
, Data in Brief, Vol: 53, ISSN: 2352-3409This article describes a dataset used to calibrate a finite element model of a thick circular hollow section (CHS) with varying d/t (diameter to thickness) ratio under cyclic loading which may be used as a computational model validation benchmark by researchers working on similar problems in structural and mechanical engineering. The test data consists of seven cold-formed S335J2H steel CHS tube specimens tested to buckling failure in low-cycle fatigue under a three-point bending arrangement, instrumented with discrete strain gauges, displacement transducers and string potentiometers together with continuous surface deformation fields obtained by two pairs of digital image correlation (DIC) cameras. ‘Half-cycle’ material data from the uniaxial tensile testing of dog-bone coupons is also provided. Comparisons between measured and simulated entities such as midspan forces, moments, displacements and mean curvatures can be obtained with MATLAB processing scripts. Complete ABAQUS model input files are also provided to aid in benchmarking.
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Journal articleWalport F, Zhu Y, Yun X, et al., 2024,
Experimental and numerical datasets for benchmark tests on high strength steel I-section frames
, Data in Brief, Vol: 53, ISSN: 2352-3409This data article presents experimental and numerical datasets for eight fixed-base, single storey, unbraced high strength steel welded I-section frames subjected to in-plane horizontal and vertical loading. A detailed description of the full-scale frame testing programme is provided in the related research article ‘Benchmark tests on high strength steel frames’. The experimental dataset can be used to steer future research in full-scale structural testing and provide benchmark results that are suitable for the validation of finite element models and the development of system-level design approaches. In addition to the benchmark experimental frame data, all necessary details and data for shell finite element (FE) model validation using geometrically and materially nonlinear analysis (GMNIA) is presented. The general purpose FE software Abaqus was used. The dataset can be used as an illustrative example of GMNIA validation in accordance with EN 1993–1–14 with all relevant data for reproducibility provided.
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Journal articleCaceres-Vilca G, Copa-Pineda J, Copa-Pineda F, et al., 2024,
Experimental assessment of sillar masonry barrel vaults retrofitted with reinforced concrete elements
, Structures, Vol: 62, ISSN: 2352-0124The historic centre of the city of Arequipa (Peru) has been an UNESCO’s World Heritage Site since 2000. This is a testament to the exceptional architectural beauty of its many historical buildings most of which are built from a distinctive white volcanic stone, known as Sillar, and date back to the 18th and 19th centuries. Nevertheless, Arequipa is in a region of extreme seismic activity that demands the provision of practical retrofitting solutions to preserve these historical structures. One of the most popular seismic rehabilitation methods in the region is the addition of concrete elements to enhance the seismic response of seismically damaged structures. However, to date there is no detailed study on the benefits provided by these measures; particularly when applied to historical sillar barrel vaults which are a common architectural feature in Arequipa’s historic building stock. In this paper we shed light on this issue by presenting, for the first time, the results of an experimental study on retrofitted historical sillar barrel vaults with inserted reinforced concrete frame elements. To this end, three vault specimens of 1/10 scale were built and tested until failure. These specimens were subsequently repaired, retrofitted with concrete elements, and tested again to failure under monotonic lateral loading. Our experimental results allow the quantification of the beneficial effects of the retrofit strategy in the lateral displacement capacity, ductility, and seismic resistance of sillar masonry barrel vaults. It is shown that the addition of concrete frames leads to a better control of plastic deformations, increasing the ductility of the original structures in up to 4.87 times and improving their lateral strength in 6.22 to 8.12 times the original resistance of the unreinforced structures.
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Journal articleSio J, Izzuddin BA, 2024,
Enhanced rational horizontal tying force method for practical robustness design of building structures
, ENGINEERING STRUCTURES, Vol: 301, ISSN: 0141-0296 -
Journal articleSio J, Khalid H, Izzuddin BA, 2024,
Objective modelling of reinforced concrete planar frame sub-systems under extreme loading
, STRUCTURES, Vol: 60, ISSN: 2352-0124 -
Journal articleZahra F, Macedo J, Malaga Chuquitaype C, 2024,
The importance of hazard-consistency when estimating seismic residual drifts in steel moment frames
, Journal of Building Engineering, ISSN: 2352-7102Residual drifts are routinely used to assess the post-earthquake safety of buildings. Despite their importance, studies on the probabilistic assessment of residual drifts in multi-storey buildings with Steel Moment Resisting Frames (SMRF) are far less common than those dealing with their transient peak drift counterpart. More seriously, although residual drift prediction models have been developed with a particular broad ground-motion type or soil condition in mind, all models proposed to date remain oblivious to the central issue of hazard consistency. Hence, missing the causal connection between the seismic hazard level and the ground-motion suite used and potentially compromising the meaningfulness of their results. This oversight is expected to introduce a bias in the estimation of residual drifts but its magnitude has not yet been properly evaluated. In this paper, we evaluate and quantify the significance of these effects. To this end, we use the Conditional Scenario Spectra framework, which provides a set of realistic earthquake spectra with assigned rates of occurrences based on their spectral shape and intensity, thus preserving the critical relationship of hazard consistency. Nonlinear response history analyses (NRHA) of 24 deteriorating SMRFs under 816 ground-motion records are performed to construct a database of residual drift demands. These NRHA results are used to examine the residual drift trends and to construct benchmark residual drift hazard curves. An extensive feature selection process employing several Machine Learning (ML) algorithms precedes the development of hybrid data-driven predictive models. Finally, we compare our hazard-consistent predictions with currently available models and quantify the massive under- and overestimations associated with previously proposed non-hazard-consistent assumptions.
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Journal articleShen S, Malaga Chuquitaype C, 2024,
Physics-informed artificial intelligence models for the seismic response prediction of rocking structures
, Data-Centric Engineering, Vol: 5, ISSN: 2632-6736The seismic response of a wide variety of structures, from small but irreplaceable museum exhibits to large bridge systems, is characterized by rocking. Besides, rocking motion is increasingly being used as a seismic protective strategy to limit the amount of seismic actions (moments) developed at the base of structures. However, rocking is a highly nonlinear phenomenon governed by non-smooth dynamic phases that make its prediction difficult. This study presents an alternative approach to rocking estimation based on a Physics-informed Convolutional Neural Network (PICNN). By training a PICNN framework using limited datasets obtained from numerical simulations and encoding the known physics into the PICNNs, important predictive benefits are obtained relieving difficulties associated with over-fitting and minimizing the requirement for large training database. Two models are created depending on the validation of the deep PICNN: the first model assumes that state variables including rotations and angular velocities are available, while the second model is useful when only acceleration measurements are known. The analysis is initiated by implementing K-means clustering. This is followed by a detailed statistical assessment and a comparative analysis of the response-histories of a rocking block. It is observed that the deep PICNN is capable of effectively estimating the seismic rocking response history when the rigid block does not overturn.
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