Construction Materials

Corrosion of steel structures remains a persistent challenge in construction, particularly in coastal and industrial environments where chloride-induced degradation accelerates structural failure. This study presents an eco-friendly approach to improve the corrosion protection of the steel by incorporating Lawsonia inermis (henna) leaf extract into zinc–aluminum silicate coatings. The henna extract was added at varying concentrations (0–12 wt%) to evaluate its influence on structure, adhesion, and electrochemical performance of the coating. Physicochemical characterizations including FTIR, XRD, XRF, and SEM revealed that a 5 wt% addition optimized pigment dispersion, resulting in a denser and more homogeneous coating microstructure. Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization tests after 35 days of immersion in 3.5 wt% NaCl solution demonstrated that this formulation achieved the highest impedance and polarization resistance, confirming enhanced corrosion resistance. The improvement was attributed to the dual action of the henna extract: (i) as a dispersant, promoting uniform Zn–Al pigment distribution and reducing porosity, and (ii) as a green corrosion inhibitor, forming an adsorbed protective film on the steel surface. This work highlights the potential of bio-derived additives to enhance the long-term durability of steel infrastructure and supports the development of sustainable protective materials for construction applications.

Cross-beam glued-laminated timber (glulam) floor systems offer material efficiency but pose a complex design challenge due to three-dimensional (3D) load interactions, and systematic optimization guidelines are lacking. This study implements a parametric optimization framework using a three-factor Design of Experiments (DOE) approach (beam spacing ratio, height-to-span ratio, width-to-height ratio). A total of 27 full-factorial finite element models (FEMs) were simulated in Dlubal RFEM. A second-order response surface methodology (RSM) model was developed to predict the load utilization factor (Y) in accordance with Eurocode 5. The predictive model demonstrated high statistical accuracy (R² > 0.98). A multi-criteria optimization using the Pareto frontier identified a balanced solution (x₁ = 0.250, x₂ = 0.042, x₃ = 0.5) that achieved 97.4% load utilization (Y = 0.974). This optimal configuration reduces the required timber volume by approximately 10% compared with other efficient designs and by over 60% compared with inefficient (Y ≈ 0.5) but safe designs within the experimental space. The resulting regression model provides a validated engineering tool for designing materially efficient glulam floor systems, allowing designers to balance structural safety with material economy.

The UPV technique has been widely employed to predict the hardened properties of Portland cement mixtures. This article assesses the hardened properties of alkali-activated blast furnace slag mortars by comparing UPV measurements with compressive strength and dry density and calculating the dynamic modulus of elasticity from UPV results. The mixtures were prepared varying the type of activator (sodium metasilicate and sodium silicate), the content of Na₂O in the activators (3.0, 4.5, 6.0, and 7.5%), and the water/binder ratio. The results showed that exponential models showed medium and high determination coefficients (R²), which explained the correlation between UPV and hardened properties. It was observed a limitation on the measurements of UPV, which did not surpass 4.4 km/s, which made it difficult to predict compressive strength value above 50 MPa. The dynamic modulus of elasticity calculated from UPV showed reliable results, even varying the Poisson’s coefficient between 0.15 and 0.25. Lastly, it was also observed that a correlation between the content of C-S-H and UPV suggested that this technique can also be used to predict the evolution of the hydration products in alkali-activated slag mixtures.