In structures with reinforced concrete walls, coupling beams join individual walls to produce a rigid assembly that withstands sideways forces. A precise forecasting of the critical shear capacity is essential to avoid early shear failure and attain the desired ductility performance of coupled shear wall systems in earthquake design. This paper examines the ability of Support Vector Regression (SVR) in predicting the shear performance of coupling beams. SVR is a distinguished machine learning regression method that has been positively utilized in former works to forecast the performance of several structural members. Nevertheless, the capability of this regression method deeply relies on picking its best hyperparameters. To handle this, a heuristic optimization procedure named Particle Swarm Optimization (PSO) was merged with SVR to select the optimal hyperparameters. The data of RC coupling beams collected from the previous works were utilized to build the proposed model. Several performance metrics, including RMSE, R2, and MAE, were employed to compare the performance of the optimized model against a baseline SVR model and previous approaches. Analytical results indicate that the new optimized prediction model can assist civil engineers in designing RC coupling beam structures more effectively and outperforms existing models in predicting the shear strength of such beams.

Cellulose, the most prevalent biopolymer on Earth, has proven to be an effective multifunctional material for enhancing the performance of concrete and other cement-based products. The current review analyzes recent developments in the application of cellulosic polymers in concrete and cement composites, including microcrystalline cellulose (MCC), cellulose nanofibrils (CNF/NFC), cellulose nanocrystals (CNC), carboxymethyl cellulose (CMC), and hydroxypropyl methylcellulose (HPMC). Special attention is paid to their interfacial interactions with cement hydration products, modes of incorporation, and impact on the properties of fresh concrete and performance of hardened materials (mechanical performance, transport properties, durability, etc.). According to published data, the addition of CNF in an amount of approximately 0.1 wt. % results in a 106% enhancement of flexural strength and a 184% increase in energy absorption capacity. Meanwhile, the flexural strength was enhanced by CNC (approximately 0.2 vol. %) by approximately 30%. Ultra-high-performance concrete containing nanocellulose experienced a 45-75% reduction in autogenous shrinkage in the initial 24 h. Nevertheless, the effects and signs of these improvements are strongly determined by the cellulose structure, dosage, surface chemistry, dispersion quality, consumption of water, cement formulation, and other parameters, which must be controlled because excessive amounts of cellulose and its improper dispersion could negatively influence the workability, hydration process, and strength development. In addition, potential drawbacks such as agglomeration, requirement for high energy input for dispersion, incompatibility with certain chemical admixtures, durability under aggressive environments, and other factors are considered in this review.