ABSTRACT This study investigates a sustainable high-performance cementitious composite incorporating polypropylene fibers and a high volume of ground granulated blast furnace slag (GGBFS) to reduce clinker content and environmental impact. High-volume slag systems typically exhibit delayed hydration and reduced early-age strength. To address these limitations, nano-calcium carbonate (NCC) and nano-silica (NS) were incorporated as performance-enhancing additives. Although nano-materials are widely studied in ordinary Portland cement systems, their comparative performance in high-slag fiber-reinforced cementitious composites (FRCC) remains insufficiently clarified. The influence of NS and NCC on rheological behavior and age-dependent mechanical performance was systematically evaluated under identical mixture conditions. Fresh-state properties were assessed using slump flow, while compressive strength, flexural strength, mid-span deflection, ductility index, and energy absorption were measured at 7, 28, and 90 days. Both nano-additives enhanced mechanical performance at all ages. Nano-silica demonstrated superior long-term effectiveness, increasing 90-day compressive strength by up to 24% relative to the fiber-reinforced control. However, NS reduced slump flow from 80 mm to 70 mm (12.5%), compared to 74 mm for NCC, highlighting the trade-off between mechanical enhancement and workability in low water-to-cement ratio, high-slag FRCC systems.

ABSTRACT This study aims to evaluate the mechanical properties of M30 grade concrete using both destructive and nondestructive methods. Ultrasonic pulse velocity (UPV) testing assesses concrete integrity, whereas compressive strength tests and machine learning models are used to predict strain and assess structural health. Machine learning models such as Elastic net, Lasso, Ridge, and Support vector regression (SVR) were used on a dataset of 472 samples with corresponding values of UPV, stress, and strain. Among all the regression algorithms, the Elastic net had the highest accuracy in training, with an R2 of 0.967, and the testing accuracy of R2 was 0.923. The results of this study revealed that UPVs greater than 3000 m/s corresponded to high-quality concrete, whereas UPVs less than this value corresponded to microcracks and a reduction in the strength of the concrete. This value replicates the IS 13,311 (Part 1- NDT- Methods of Test) parameters, which describe the methodology used to calculate the nondestructive testing parameters. This study demonstrates the effectiveness of machine learning, particularly Elastic Net, in predicting structural strain and health. The integration of UPVs with ML provides a reliable assessment of concrete quality, although short curing times, limited data, and no environmental variation limit the use of UPVs.

ABSTRACT Reinforced shear masonry (RSM) walls are critical for resisting lateral loads, but accurately estimating their displacement capacity is challenging due to single reinforcement layer. This study addresses this issue by developing and comparing three machine learning algorithms: Convolutional Neural Network (CNN), Gene Expression Programming (GEP), and Tree-Structured Parzen Estimator-Extreme Gradient Boosting (TPE-XGB), to predict the lateral displacement of fully grouted RSM walls. A database of 152 experimental instances was compiled, incorporating variables like masonry strength, reinforcement ratios, axial load ratio, and shear stress demand. The TPE-XGB model demonstrated the highest predictive accuracy (R² = 0.995), followed by CNN, while GEP provided a less accurate but interpretable empirical equation (R² = 0.884). Comparisons with simpler regression models confirmed the efficiency of the machine learning approaches. To enhance transparency, Shapley Additive (SHAP) and Individual Conditional Expectation (ICE) analyses were conducted, identifying aspect ratio, shear stress demand, and grouted masonry strength as key factors influencing displacement. An explainable computational tool was also created to facilitate practical implementation, enabling engineers to accurately predict the lateral displacement behavior of RSM walls.

ABSTRACT The seismic analysis of high-rise buildings (HRBs) with rafted pile foundations is strongly influenced by soil-pile-structure interaction (SPSI). This numerical and experimental investigation utilized five earthquake records to evaluate the seismic response of 12-story RC HRBs, considering SPSI. The adopted methodology employed piled raft foundations for the HRBs with various pile configurations (i.e., arrangements of piles in the following shapes: square, diamond, rectangular, H-shaped, and circular), incorporating SPSI. The results were compared to assess how the different pile configurations impact the seismic response and resistance of HRBs. Distinct effects were observed in the maximum displacements and accelerations of the HRBs, as well as in the raft shears, raft moments, base shears, base moments, and axial forces, under five earthquake scenarios. The numerical results were validated by the experimental findings. Results showed that the HRB with the circular pile configuration experienced significantly reduced lateral displacements in both the X- and Y-directions compared to other pile arrangements, as confirmed by experimental testing and numerical analyses under five earthquake records. This circular pile configuration enhanced the seismic response of the HRB and is also favored from both economic and construction perspectives, making it a highly effective design choice for HRBs in seismic regions.

ABSTRACT The present study investigates the mechanical properties of composite sandwich panels with a novel truss-shaped core under three-point bending, utilizing both experimental and numerical methods. The panels were produced using a hand lay-up technique involving epoxy resin and glass fibers, with meticulous efforts to reduce manufacturing flaws. The truss-shaped core, demonstrating a distinctive structural design, was constructed using laser-cutting and mechanically joining composite panels. Halloysite Nanotubes (HNTs) were integrated into the epoxy matrix at weight fractions of 2%, 4%, and 6% to improve mechanical qualities. Tensile testing on specimens demonstrated that the composite containing 2% HNTs achieved the maximum tensile strength and elastic modulus. Three-point bending tests were performed to assess the flexural performance of the sandwich panels. The results were verified by finite element models in Abaqus/CAE, showing a 12% discrepancy in maximum load relative to experimental data, showing good agreement. The simulation utilized mechanical properties of a 2% HNT-reinforced composite, exhibiting superior mechanical performance. Furthermore, comparisons with a panel devoid of nanoparticles demonstrated that HNT reinforcement resulted in a 13% enhancement in bending resistance. This study illustrates the efficacy of integrating a truss-shaped core design with nanoparticle-reinforced composites to considerably enhance structural performance in lightweight sandwich panels.

ABSTRACT Recent developments in concrete technology, especially over the last decade, have enabled the commercial development of high-strength concrete (HSC). This study investigates the performance of HSC reinforced with single and hybrid fibers, specifically steel and coir fibers. The findings reveal a significant improvement in mechanical properties, particularly compressive and split tensile strengths, with optimal performance observed when hybridizing 2% steel fiber with 0.2% coir fiber. The study also evaluates the thermal performance of HSC under elevated temperatures, demonstrating that steel fibers help maintain structural integrity, while coir fibers contribute positively, especially in hybrid mixes. Additionally, the use of coir fiber, a renewable and biodegradable material, enhances sustainability by reducing reliance on synthetic fibers and promoting eco-friendly construction practices. Recommendations include incorporating coir fiber at a volume fraction of 0.1% to 0.2% to achieve optimal mechanical performance without compromising quality. This research provides valuable insights for advancing durable, cost-efficient, and environmentally friendly hybrid fiber-reinforced HSC.

ABSTRACT To predict the punching shear strength of recycled aggregate concrete (RAC) thin flat slabs, a model was constructed based on their failure mechanism under punching shear. For accurate predictions, a novel size effect factor was suggested for thin slabs. The proposed model was validated by comparing its predictions with RAC thin flat slabs’ experimental results. Additionally, a natural aggregate concrete (NAC) thin flat slab database was utilized to further evaluate the proposed model’s applicability. The model’s accuracy and reliability were rigorously assessed by comparing it with existing design equations. The comparison results demonstrated that the proposed model consistently aligned best with experimental results across all test parameters. It also outperformed the existing design equations, as evidenced by statistical parameters: a mean of 1.05, the lowest coefficient of variation (COV) of 0.148, the highest R2 at 0.90, and disparity rate reaching 100% in the range of 0 to 0.2. Moreover, the proposed model demonstrated a good fit for NAC thin flat slabs, with a mean value of 1.01 and a COV of 0.201. To provide insight into the design of RAC flat slabs, the influences of recycled aggregate (RA) content and key design parameters on punching shear strength were thoroughly analyzed.

ABSTRACT This study compares the fracture parameters of self-compacting lightweight concrete (SCLC) obtained from two-parameter model (TPM) and size effect method (SEM). Moreover, the influence of using silica fume and nano-silica on the fracture parameters and mechanical properties of SCLC was evaluated. For this purpose, eight mix designs were made by replacing 0, 1, 3, and 5% of the cement weight with nano-silica and using 0 and 10% of the cement weight with silica fume. The SCLC incorporating 3% nano-silica and 10% silica fume was the best mix design. This mix enhanced the compressive strength, tensile strength, and elasticity modulus of SCLC by about 36, 17, and 18%, respectively. Based on SEM, this mix increased the fracture energy and fracture toughness by about 32% and 25%, respectively. According to TPM, this mix improved the mentioned parameters by approximately 33 and 25%, respectively. The average value of differences in the fracture energy and fracture toughness attained from SEM and TPM were about 2% and 1%, respectively. The average difference in the critical crack tip opening displacement (CTODc) results was about 6%.

ABSTRACT In the present study, a 3D nonlinear finite element (FE) model has been developed to simulate reinforcement corrosion in RC beams under sustained load. The corrosion effects were modelled as bond deterioration at the rebar-concrete interface, damage in cover concrete and mechanical degradation of corroded rebars. A simplified temperature field-based methodology was proposed in the commercial program ABAQUS to simulate the evolution of corrosion degradation while a sustained load is maintained in the beam. The FE model was validated using available experimental results in terms of cracking behaviour and load-deflection response and found to be in good agreement. Parametric investigations were carried out to analyse the performance of beams under simultaneous corrosion and sustained loads. The findings demonstrated that pitting corrosion under simultaneous loading conditions can significantly compromise a beam’s structural integrity. Specifically, a scenario with 20% mass loss and 60% sustained load resulted in a 33.3% increase in concrete strain and a significant increase of 738% in the tensile steel strain leading to yielding. Furthermore, the influence of load and corrosion sequence on the behaviour of the beam was assessed by comparing its response when corroded under sustained load with a beam corroded and subsequently loaded.

ABSTRACT Thin lightly reinforced concrete wall (TLRCW) buildings are commonly used to mitigate the housing deficit in developing countries. The TLRCW system comprises slender walls with a thickness lower than 150 mm, a high aspect ratio, limited or no confinement at the edges of the walls, and web reinforcement with limited ductility. This paper describes and discusses the main geometric and mechanical characteristics of 207 TLRCW buildings constructed in intermediate- and high-seismicity regions. Variables considered in the study are the number of stories, wall-area index, axial load ratio, slenderness, aspect ratio, and the type of reinforcement at wall edges. Statistical analyses of the database and global performance indices are correlated with the expected seismic performance of TLRCW buildings. The results of the analyses aided at developing a useful toolbox for rapid assessment of design and structural configuration to prioritize intervention strategies for existing TLRCW buildings.