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ABSTRACTThe absolute maximum response (AMR) of structures might occur posterior to the end of earthquake excitations, hence, extending the dynamic analysis to the post-shaking phase is required. This phenomenon was found to be more common for long-period and low-damping structures, which are prevailing in regions of low-to-moderate seismicity like Australia. In this article, the mechanism of the occurrence of AMR in the post-shaking phase is first explained using single-degree-of-freedom (SDOF) systems subjected to a simple sine wave. Further investigation on real earthquake ground motions reveals that whether an extended analysis is required depends greatly on the characteristics of the post-significant duration phase. Finally, suitable metrics for describing ground motions that require extended analysis (EAGMs) are identified based on the Kolmogorov–Smirnov test. Regression analyses are then conducted to predict the probability of EAGMs.

ABSTRACTBase isolation is a low-damage seismic design strategy that can be used for constructing resilient structures. Geotechnical seismic isolation (GSI) is a new category of emerging base isolation techniques that has attracted global interest in the past decade. Research on GSI based on rubber-soil mixtures (RSM) has focused on structural performance under earthquake actions, whilst there are concerns over the serviceability limit states (SLS) requirements in relation to (i) human comfort under strong winds and (ii) ground settlement under gravity, which may induce cracking and durability issues in structures. This article presents the first study on the serviceability performance of buildings constructed with the GSI-RSM system. The finite element model of a coupled soil-foundation-structure system has been validated by data recorded from geotechnical centrifuge testing. The numerical estimates of ground settlement have also been compared with analytical predictions. It is concluded that the GSI-RSM system can satisfactorily fulfill the SLS requirements.

Bitumen has been used in different forms and with various properties in pavement as a binder material. Meanwhile, the properties of soil-rubber mixtures (SRM) have been extensively examined for applications in geotechnical and highway engineering. These applications range from serving as a lightweight fill material, subgrade layers in pavement, and foundation materials for geotechnical seismic isolation (GSI). However, a research gap exists in understanding the effect of the interaction between bitumen and rubber granules on their mechanical properties under a range of confining pressures. In this paper, a series of unconfined compressive strength (UCS) and monotonic triaxial tests were conducted. The results show that a bitumen content as low as 3% of the total mass can significantly increase the shear strength and cohesion of SRM and reduce the deformability. Moreover, the increase in the elastic modulus due to a 3–5% bitumen content is notably less than the reduction obtained from 25% to 45% rubber replacement, which is favourable for GSI applications. The shear strength and elastic modulus in gravel-based mixtures were found to be more sensitive to changes in rubber and bitumen content compared to sand-based mixtures. Conversely, the effect of confining pressure was more pronounced in sandy soil than in gravelly soil.

ABSTRACTThis paper presents a statistical analysis of the actual mean material properties for typical grades of concrete and reinforcement available in Australia. The analysis was performed using a database of 3,447 concrete cylinder test results and 15,201 reinforcement tensile test results. The test results were taken over a period from 2009 to 2021. The paper provides a summary of the mean values and respective coefficient of variation values for the different grades of concrete and reinforcement that make up the database. Distinctive manufacturing trends and variability between suppliers were observed for reinforcement samples and appropriate recommendations have been proposed. Researchers or designers can adopt these values to undertake probabilistic assessments of RC structures. The paper also provides recommendations for mean material properties for the purpose of undertaking non-linear analysis of RC structures. The database of test results also includes early age strength data for concrete, which have been used to provide recommendations for predicting the early age strength of various standard grades of concrete available in Australia. The paper also presents an assessment of the theoretical characteristic values from the database for the various grades of reinforcement and concrete and how they compare to respective specified code requirements.

ABSTRACTDisplacement-based methods, such as a non-linear static pushover analysis (e.g. the capacity spectrum method), have many advantages compared to traditional force-based design methods. However, implementing a non-linear analysis and design method in accordance with the Australian Standard for concrete structures (AS 3600) introduces many difficult technical issues into the design, of which the standard provides little guidance. The aim of this study is to provide a framework and general guidance for designers who wish to perform non-linear displacement-based analysis methods for RC wall buildings. The paper will present how these methods can be used in accordance with the Australian Standard for earthquake actions (AS 1170.4) to assess seismic compliance and then provide recommendations for the requirements stipulated by AS 3600, which includes an experimentally validated tension stiffening model, nonlinear stress-strain material curves, mean material properties and material strain limits. The paper is concluded with a case study example of how a displacement-based seismic assessment can be performed using a typical case study building.

Despite the great promise of machine learning in the structural seismic analysis, the deployment of advanced neural networks has been limited in practical applications because of the high costs of data acquisition. This paper introduces a new framework that integrates the powerful learning ability of physics-informed neural networks (PINNs) with the effectiveness of pseudo-labelling in data augmentation to improve the accuracies of seismic response predictions of structures. The architecture of PINNs consists of two blocks of gated recurrent unit-fully connected neural networks (GRU-FCNNs) and one block of ordinary differential equation (ODE) that leverages the knowledge of structural dynamics. The first block of GRU-FCNNs serves as a generator of pseudo-labels when drawing upon the input of unlabelled datasets. The second block of GRU-FCNNs in combination with the ODE block is a selector of reliable pseudo-labels. The performance of PINNs trained on limited labelled data can be significantly improved by successively selecting reliable pseudo-labels from the generator and selector to supplement training datasets. The effectiveness of pseudo-labelling in PINNs is validated and compared with PINNs without pseudo-labelling through case studies with simulation datasets and real datasets from experiment. The results show that the proposed framework is effective and robust in improving prediction accuracies of structural seismic responses with limited labelled data.

ABSTRACTCollapse prevention is the primary objective of earthquake-resistant design of structures; hence, the probability of collapse should be taken as a crucial performance indicator for risk-based design of new structures or assessment of existing structures. One major challenge in collapse risk assessment is to reliably model the non-linear structural response behaviour. This study features the rocking response behaviour of precast reinforced concrete (RC) columns based on results from previous field testing on parts of a real building and supplemented with a study of their rocking behaviours through a series of shake-table tests. The effects of bidirectional earthquake actions on failure drift capacity of columns have also been incorporated, such that realistic estimates of displacement capacity were made for constructing collapse fragility functions, which were then combined with the ground motion recurrence relationships of Melbourne, Australia for the computation of collapse probability. A suite of typical soft-storey buildings was adopted, with considerations given to a diversity of site conditions. Deaggregation of the results reveals the range of return periods that controls the collapse risk, which could have important implications for the choice of earthquake scenarios for seismic analysis and design in regions of lower seismicity.

AbstractThis paper presents a refined site classification scheme and a design spectrum (DS) model for different site conditions, with site natural period as the key classification parameter. The refined model has a particular emphasis on the phenomenon of resonant-like amplification behaviour in soil sites, which have not been explicitly considered in any existing code models. The need to address the effects of soil resonance and increased displacement demand is particularly justified in regions of lower seismicity, where structures are typically of limited ductility with low energy dissipation capability. Significantly, the mitigating effects of a very flexible soil site resulting in reduction in the level of seismic demand on low-rise buildings is a distinctive feature of the model which has been well validated by comparison with results obtained from computational site response analysis of soil columns derived from real borehole records, as well as from strong motion data recorded in the 1994 Northridge earthquake.

A large quantity of end-of-life tire (ELT) rubber is being blended with thermoplastic polyurethane to provide a durable and ecologically friendly material for flexible surfaces, while a significant quantity of thermoplastic elastomeric waste (left-over and cut-outs) is also generated. These waste materials can be used efficiently for seismic isolation and vibration damping at a minimal cost, a process known as frugal innovation. In this regard, waste thermoplastic elastomeric (TPE) material, which is also known as polyurethane-coated rubber (PUcR), obtained from the tire rubber recycling industry, is explored in this study. Herein, we targeted to evaluate the stiffness and energy dissipation capabilities of waste TPE or PU-coated rubber, which, to the best of our knowledge, has never been reported before. To that end, a series of cyclic triaxial tests were carried out on PU-coated rubber-soil mixtures. In comparison to untreated rubber-soil mixtures, the shear modulus of PU-coated rubber-soil mixtures reduces by 5.5–12.7%, while the damping ratio increases by up to 12.6%.

Sand–tyre chip (STCh) mixtures can be used in many geotechnical applications as alternative backfill material. The reuse of scrap tyres in STCh mixtures can effectively address growing environmental concerns and, at the same time, provide solutions to geotechnical problems associated with low soil shear strength and high dilatancy. In this paper, the shear strength and dilatancy behaviour of STCh mixtures have been investigated. A series of monotonic triaxial tests has been carried out on sand mixed with various proportions of tyre chips. It has been found that tyre chips significantly influence the shear strength and the dilatancy behaviour of STCh mixtures. The effects of confinement and relative density on the shear strength, dilatancy and initial tangent modulus of the STCh mixtures have also been investigated. Moreover, a dilatancy model for STCh mixtures has been proposed and validated with the experimental results.