The statistical study of the glued-in rod splice connection for Mengkulang glulam timber is presented in this research. This type of connection is used in many applications, such as bridge construction and wide hall, besides becoming increasingly popular due to its cost-effectiveness and ease of installation. Using statistical analysis to evaluate the performance of glued-in rod splice connections is relatively new. Statistical analysis can assess the connection’s performance by examining the glued-in rod splice connection’s strength, stiffness, and durability. Glued-in rods have several advantages over traditional mechanical connections generally used in beam design, such as higher stiffness, more uniform stress distribution, fewer rod corrosion problems and better appearance. Due to this limitation, the standard design for glued-in rods using glulam is the estimated extrapolation for solid timber guidelines. The main objectives of this research were to develop the pull-out model and validate the effectiveness of the model equation for glued-in rods parallel (GRPS0^°) and perpendicular (GRPS90^°) to the grain directions using a statistical package for the social sciences (SPSS). The variables examined were the number of rods, diameter, length, spacing, the kind of glue utilised, and the number of adhesive layers. In conclusion, the model development clearly shows that most of the parameters achieved the R² more than 80% accurate for both parallel (GRPS0^°) and perpendicular (GRPS90^°) to the grain directions.

There is no direct measurement of tensile strength have been determined for Malaysian tropical hardwood. The usual approach is to consider the tensile strength of timber as 60% of the small clear specimen's bending strength values, as specified in MS 544: Part 2:2001. However, this method proves inadequate for engineering applications as it fails to provide precise and accurate values. Therefore, in this study, nine (9) species of Malaysian tropical hardwoods were selected namely Balau (Shorea spp.), Kempas (Koompassia Malaccensis), Kelat (Syzygium spp.) Kapur (Dryobalanops spp.), Resak (Vatica spp.), Keruing (Dipterocarpus spp.), Mengkulang (Heritiera spp.), Light Red Meranti (Shorea spp.) and Geronggang (Cratoxylum spp.). The specimens were tested in structural sizes and subjected to tensile strength testing in accordance with BS EN 408:2010. Subsequently, the results were transformed into grade stresses following the guidelines of MS 544: Part 3. The lowest mean tensile strength (42.23N/mm2) and Modulus of Elasticity (11972N/mm2) was obtained by the lowest density timber Light Red Meranti while the highest mean tensile strength (84.46N/mm2) and highest Modulus of Elasticity (21329N/mm2) was obtained by the high density Kempas species although not excelled by the highest density of the investigated species. The evaluation also indicated that the grade stresses of the structural specimens in this study surpass those published in MS 544: Part 3.

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Strength losses and poor compatibility between recycled crumb rubber (CR) and cement paste constrain the use of waste-tire polymers in concrete. This study investigated the combined use of corn straw ash (CSA) and KH570-treated crumb rubber (CR) through mechanical testing, microstructural characterization, and compressive strength prediction. Fifteen mixtures were examined, with compressive strength measured at 3, 7, and 28 d and flexural strength at 28 d. Among the investigated CSA replacement levels at 10% CR, 8% CSA produced the highest 28 d compressive and flexural strengths of 39.28 and 7.1 MPa, respectively. These values were 15.1% and 20.3% higher than those of the corresponding rubberized concrete without CSA, and 15.2% and 16.4% higher than those of the untreated-rubber mixture. The combined treatment therefore partially compensated for rubber-induced strength losses. X-ray diffraction, scanning electron microscopy, and Fourier-transform infrared spectroscopy provided complementary evidence consistent with matrix refinement and improved rubber–paste interfacial compatibility. Backpropagation (BP), genetic-algorithm-optimized BP, and particle-swarm-optimized BP (PSO-BP) models were compared using 135 experimental records. PSO-BP yielded the lowest test-set root-mean-square error of 2.1713 MPa under the adopted data partition. These findings demonstrate the potential of combining agricultural ash incorporation with waste-rubber surface treatment to improve the strength performance of rubberized concrete and provide an experimental basis for composition selection.

Purpose: The purpose of this study is to develop and validate a temperature-indexed Concrete Damage Plasticity (CDP) model to analyze the thermo-mechanical behavior of reinforced concrete beams, slabs and columns under fire exposure. By integrating temperature-dependent material properties, this research aims to provide a comprehensive approach for evaluating the degradation of mechanical properties, including damage and strain, at elevated temperatures. The findings contribute to enhancing fire safety design practices, supporting Sustainable Development Goal (SDG) 9 (industry, innovation and infrastructure) and SDG 11 (sustainable cities and communities), by improving structural resilience to fire hazards. Design/methodology/approach: This study employs a temperature-indexed CDP model to simulate the thermo-mechanical behavior of reinforced concrete beams, slabs and columns exposed to fire. Numerical simulations are conducted using finite element analysis to assess the degradation of mechanical properties such as stress, strain and damage evolution under varying temperature conditions up to 800°C. Experimental data are used to validate the model's predictions. The approach integrates temperature-dependent material properties, providing a comprehensive framework for understanding the structural response to fire and offering insights for enhancing fire-resistant design in concrete structures. Findings: The findings of this study demonstrate that the temperature-indexed CDP model accurately predicts the thermo-mechanical behavior of reinforced concrete beams, slabs and columns under fire exposure. The model effectively captures the degradation of mechanical properties, including damage and plastic strain, at temperatures up to 800°C. Numerical simulations align well with experimental data, showing strong predictive capability, although minor discrepancies are observed at higher temperatures, particularly in deflection and strain. The research underscores the importance of refining temperature-dependent material properties for more accurate simulations of concrete behavior in extreme fire conditions. Originality/value: This study provides a novel approach by developing and validating a temperature-indexed CDP model for assessing the thermo-mechanical behavior of reinforced concrete under fire exposure. The model integrates temperature-dependent material properties, offering a comprehensive framework for simulating the degradation of concrete's mechanical properties across various structural elements. The originality lies in the model's ability to accurately predict damage, strain and stress evolution at elevated temperatures, filling a critical gap in structural fire safety design. This research advances fire-resistant infrastructure design, supporting more resilient and sustainable urban structures, contributing to SDG 9 and SDG 11.