ABSTRACT Older bridges were designed and constructed with pre-1970 design guidelines with design shortcomings (e.g. shorter lap splices located in the potential plastic hinge zone at the bottom of the column, and inadequate lateral confinement). For older bridge columns, the potential of having a catastrophic collapse can only be assessed by conducting realistic simulations of deficient lap-spliced RC columns against seismic loading. This study proposes a numerical model to realistically simulate the nonlinear behaviour of bar-slip in circular lap-spliced RC columns through model calibration and regression and applies the model to existing older non-ductile bridges to assess their seismic vulnerability. An experimental database consisting of 17 circular specimens exhibiting lap-splice failure before yielding of longitudinal reinforcement is constructed and used to calibrate the proposed numerical model to optimise the model parameters. The proposed model correlates strongly with the existing experimental data. Fragility curves are developed to determine the seismic damage potential of non-ductile bridges. Single-frame concrete box-girder bridge models having two-span, three-span, and four-span with and without lap splices in the plastic hinge zone were selected. Fragility results indicate that the older bridges having deficient lap splices in RC columns in the plastic hinge zone have a higher probability of failure.

ABSTRACT To produce RA of good quality, this research proposed a new three-step processing method. First, soak the raw material in a moderate acetic acid solution. The second step is to grind the aggregate physically using an LA abrasion machine. Finally, the third step is to coat the aggregate with a cement silica fume slurry to seal any pores. There are seven distinct types of triple processed recycled aggregates (TPRAs): TPRA(0RVNs), TPRA(100RVNs), TPRA(200RVNs), TPRA(300RVNs), TPRA(400RVNs), TPRA(500RVNs), and TPRA(600RVNs). This study examined the effects of TPRAs by varying the amounts of TPRAs added to an M40 grade control mix in place of NA (0%, 20%, 40%, 60%, 80%, and 100%). Experiments were conducted to investigate the properties of TPRA-created concrete, including its workability, strength, and durability. Under conditions where TPRA (500 RVNs) replaces 60% of the NA in the mix, the compressive strength drops by 12.84%, but the RCPT value rises by 34%. This means that structural concrete should have TPRA (500 RVNs) replaced with 60% NA. Additionally, for the best results while making TPRA, it is recommended to soak it for 24 h in a moderate acetic acid solution, then run it through 500 revolutions per minute (RPM) on the LA abrasion machine. Finally, cover it with a layer of cement silica fume slurry.

ABSTRACT The study evaluates the mechanical performance of cementitious matrix-based strengthening composites through tensile and bond tests for masonry reinforcement. Two composite systems were tested: the first, a glass fabric embedded in a 1:3 cement mortar matrix (GF-RCM), and the second, short hybrid fibres in an engineered cementitious composite matrix (SF-ECC). Both systems were chosen for their potential to improve masonry’s tensile strength and bond properties. Experimental results indicated that both composites showed promising tensile and bond strengths, confirming their suitability for masonry strengthening. The GF-RCM composite outperformed the SF-ECC system, exhibiting significantly higher tensile and bond strengths. This enhanced performance is attributed to the strong interaction between the glass fabric reinforcement and the cement mortar matrix. Additionally, the GF-RCM composite proved to be more practical for field applications due to its simpler preparation and application process. The study highlights the effectiveness of the GF-RCM composite as an efficient and user-friendly solution for strengthening masonry structures, providing superior mechanical properties and ease of use. However, both composites demonstrate potential for various strengthening applications, depending on project-specific needs.

ABSTRACT This study utilises Exploratory 10.6, a coding-free machine learning (ML) platform, to predict the interface shear strength of concrete interfaces, offering a coding-free AutoML solution to a data-driven approach in structural engineering. A dataset of 200 push-off samples was analysed, incorporating six input parameters: volume fraction of steel fibres, concrete compressive strength, yield strength of interface reinforcement, strength ratio, interface shear reinforcement area, and interface shear plane area. The single output parameter is the interface shear strength. The study employed machine learning models, including XGBoost, decision tree (DT), random forest (RF), and linear regression (LR), to develop predictive models. XGBoost emerged as the most effective model, achieving an R2 of 0.924 and RMSE of 1.032, significantly outperforming traditional empirical models, such as those in AASHTO LRFD and ACI codes, which demonstrated poor generalisation across varying experimental conditions. The random forest and decision tree models achieved R2 values of 0.812 and 0.728, respectively, with RMSEs of 1.895 and 1.962, while the linear regression model showed the lowest performance with an R2 of 0.768 and an RMSE of 1.458. Data preprocessing techniques, including correlation plots and principal component analysis, highlighted strength ratio as the dominant factor influencing interface shear strength. This study also revealed that ML-based models performed better during training than testing, highlighting their reliance on training data. The findings underscore the superiority of advanced ML approaches, particularly XGBoost, over traditional empirical methods, and demonstrate the potential of coding-free platforms for enhancing predictive modelling in structural engineering.

ABSTRACT The use of recycled aggregates (RA) is promising in concrete production for construction projects. Therefore, accurately predicting the compressive strength (CS) of this concrete is crucial for understanding the behaviour of such concrete. This study marks an inaugural effort to evaluate the AutoGluon framework for predicting CS for RA concrete. In this novel framework, categorical boosting (CatBoost), light gradient boosting machine (LightGBM), weighted ensemble (WeightENS) and extreme gradient boosting (XGBoost) were considered. The variables used for the modelling were curing days, quantity of cement, water, recycled aggregate, coarse aggregate and fine aggregate. Various statistical and graphical tools were used to evaluate the effectiveness of the proposed models. The findings showed that the CatBoost model achieved the highest prediction performance with a minimal root mean squared error (RMSE) of 1.45. The feature importance evaluation indicated that cement is the most influential variable for CS models. Overall, the study highlights that AutoGluon provides a reliable and robust framework for modelling in structural engineering. Additionally, AutoGluon eliminates the need for an exhaustive and time-intensive process of hyperparameter optimisation.

ABSTRACT This study focuses on resin-based concrete, a novel composite material in which resin replaces the traditional cementitious binder, forming a three-phase composite consisting of aggregate, resin matrix, and interfacial transition zones. Four random aggregate models were generated using the Monte Carlo method and their stability was verified. Subsequently, a two-dimensional micro-model was established, and the simulation results were compared with experimental data, yielding a maximum error of 8%, which validated the feasibility of the model. The findings indicate that circular aggregates exhibit lower load-bearing capacity, while irregular aggregates demonstrate higher capacity. Although the peak compressive strength is similar among different aggregate shapes, the crack propagation paths vary significantly. The load-bearing capacity of resin-based concrete increases with aggregate content up to an optimal value of approximately 80%, beyond which it decreases. At this optimal content, crack paths transition from branched to near-linear. In terms of aggregate grading, higher coarse aggregate proportions enhance load-bearing capacity and promote linear crack propagation, whereas higher fine aggregate proportions reduce capacity and result in multiple irregular crack paths. Finally, the numerical simulation results were used to guide macroscopic experiments, and orthogonal experiments were conducted to determine the optimal mixture proportions of different resin binders.

ABSTRACT A new double-deck steel truss arch bridge with a length of 408 meters is proposed for Qingshuitang Bridge. The upper deck serves as a six-lane highway in both directions, with a bridge deck width of 32 meters. The main arch ribs are constructed using steel box arches, equipped with lateral wind braces for enhanced stability. The main span employs a lightweight composite steel deck with double main girders and ultra-high-performance concrete to reduce self-weight and increase span length. The side spans and approach bridges utilize a double main girders + beam steel-concrete composite deck. The upper deck has a standard width of 24.5 meters, while the lower deck is designated for pedestrian and non-motorized traffic, with a width of 10 meters in the suspension area and 12 meters in the recreational area. Finite element analysis conducted using Midas software indicates that the static and dynamic performance of the bridge, as well as the forces acting on the bridge deck, meet the specified requirements.

ABSTRACT In building construction, starter bars are used in columns to ensure continuity after slabs and beams are completed. These exposed reinforcement bars are subjected to vibrations from wind, human activities, and machinery during concrete casting, which reduces the bond between steel reinforcements and surrounding concrete, especially near the free surface at the top of the column. This study aims to experimentally evaluate the impact of external vibrations on reinforcement bars in concrete columns. Reinforced Concrete (RC) columns, with dimensions of 150 mm x 150 mm, were cast with variations in concrete grade (20, 25, 30), steel bar diameter (12 mm, 16 mm), and column height (500 mm, 1000 mm). The columns were subjected to external lateral loads, simulating continuous vibration at the top. The gap between steel and concrete was measured using dial gauges with incremental loading. A pull-out test was performed to determine the bonding capacity. Results showed a 33% reduction in bond stress during the initial setting period and a 10% reduction at the final setting period.

ABSTRACT This paper presents experimental investigation of the axial behaviour of built-up (BU) (I-section) cold-formed steel doubly-symmetric channel with single-/double-layer sheathing on both sides configuration. Fifteen (15) monotonic concentric axial compression tests were performed on 7-BU sections with single-layer sheathing, 7-BU sections with double-layer sheathing, 1-BU section stud without sheathing. The experiments aim to enumerate ultimate axial strength, buckling interactions, failure pattern and strength enhancement due to sheathing for BU section stud members. The novelty of the study is that, for the first time an attempt is made to investigate the axial behaviour of single-/double-layer sheathed BU section panels using seven different sheathing boards. Results indicate large range of deformation behaviour, with local-global and distortional-global interaction buckling phenomena. Failure is also observed due to failing of screws in specimens with sheathing of thickness ≥ 9 mm and modulus of elasticity > 6400MPa. Also, for the first time, efficacies of four semi-analytical methods based on rational extension of direct strength method (DSM) are presented. Results suggest the insufficiency of current AISI design specifications, whereas predicted results obtained using the new modified DSM methodology are within the adequate variation range as the adopted methodology considers desired buckling interaction. The efficacy of the recommended design methodology is verified through reliability analysis.

ABSTRACT The impact of imperfection/flaws in axially compressed/externally pressurised stiffened cylindrical shells with various shapes was studied using finite element analysis (FE). The study examined imperfection methods such as the Single Perturbation Load Approach (SPLA) and Smooth Inward Dimple (SID) to validate them against existing experimental data. It also explored the influence of initial imperfections in terms of depth, magnitude, size, and location on the buckling strength of the shell. Both methods showed reasonable agreement with published experimental data, with differences ranging from 2% to 13%. The shells’ load-carrying capacity was affected by initial geometric imperfections, particularly in terms of depth, magnitude, size, and location. The study’s findings add to our understanding of how structural imperfections impact the initial phases of designing, fabricating, and analysing axially compressed or externally pressurised stiffened cylindrical shell structures in terms of their magnitude, size, and location.