Prediction of axial capacity of corrosion-affected RC columns strengthened with inclusive FRP.

The primary cause behind the degradation of reinforced concrete (RC) structures is the propagation of corrosion in the steel-RC structures. Nowadays, numerous retrofitting techniques are available in the construction sector. Fiber-reinforced polymer (FRP) is one of the efficient rehabilitation measures that can be implemented on corroded structures to enhance structural capacities.

The influence of nanosunflower ash and nanowalnut shell ash on sustainable lightweight self-compacting concrete characteristics.

The absence of biodegradability exhibited by plastics is a matter of significant concern among environmentalists and scientists on a global scale. Therefore, it is essential to figure out potential pathways for the use of recycled plastics. The prospective applications of its utilisation in concrete are noteworthy.

Ensemble learning based compressive strength prediction of concrete structures through real-time non-destructive testing.

This study conducts an extensive comparative analysis of computational intelligence approaches aimed at predicting the compressive strength (CS) of concrete, utilizing two non-destructive testing (NDT) methods: the rebound hammer (RH) and the ultrasonic pulse velocity (UPV) test. In the ensemble learning approach, the six most popular algorithms (Adaboost, CatBoost, gradient boosting tree (GBT), random forest (RF), stacking, and extreme gradient boosting (XGB)) have been used to develop the prediction models of CS of concrete based on NDT. The ML models have been developed using a total of 721 samples, of which 111 were cast in the laboratory, 134 were obtained from in-situ testing, and the other samples were gathered from the literature.

Application of Machine Learning in Modeling the Relationship between Catchment Attributes and Instream Water Quality in Data-Scarce Regions.

This research delves into the efficacy of machine learning models in predicting water quality parameters within a catchment area, focusing on unraveling the significance of individual input variables. In order to manage water quality, it is necessary to determine the relationship between the physical attributes of the catchment, such as geological permeability and hydrologic soil groups, and in-stream water quality parameters. Water quality data were acquired from the Iran Water Resource Management Company (WRMC) through monthly sampling.

Crack Size and Undermatching Effects on Fracture Behavior of a Welded Joint.

Crack size and undermatching effects on fracture behavior of undermatched welded joints are presented and analyzed. Experimental and numerical analysis of the fracture behavior of high-strength low-alloyed (HSLA) steel welded joints with so-called small and large crack in undermatched weld metal and the base metal was performed, as a part of more extensive research previously conducted. J integral was determined by direct measurement using special instrumentation including strain gauges and a CMOD measuring device.

Effect of Shielding Gas Arc Welding Process on Cavitation Resistance of Welded Joints of AlMg4.5Mn Alloy.

The effect of the shielding gas arc welding process on the cavitation resistance of the three-component aluminum alloy AlMg4.5Mn and its welded joints was investigated. Welding was performed using the GTAW and GMAW processes in a shielded atmosphere of pure argon.

Modeling the Thermoelastic Bending of Ferric Oxide (FeO) Nanoparticles-Enhanced RC Slabs.

Nanoparticles, by virtue of their amorphous nature and high specific surface area, exhibit ideal pozzolanic activity which leads to the formation of additional C-S-H gel by reacting with calcium hydroxide, resulting in a denser matrix. The proportions of ferric oxide (FeO), silicon dioxide (SiO), and aluminum oxide (AlO) in the clay, which interact chemically with the calcium oxide (CaO) during the clinkering reactions, influence the final properties of the cement and, therefore, of the concrete. Through the phases of this article, a refined trigonometric shear deformation theory (RTSDT), taking into account transverse shear deformation effects, is presented for the thermoelastic bending analysis of concrete slabs reinforced with ferric oxide (FeO) nanoparticles.

A Brief Overview on Crack Patterns, Repair and Strengthening of Historical Masonry Structures.

Given that a significant fraction of buildings and architectural heritage in Europe's historical centers are masonry structures, the selection of proper diagnosis, technological surveys, non-destructive testing, and interpretations of crack and decay patterns is paramount for a risk assessment of possible damage. Identifying the possible crack patterns, discontinuities, and associated brittle failure mechanisms within unreinforced masonry under seismic and gravity actions allows for reliable retrofitting interventions. Traditional and modern materials and strengthening techniques create a wide range of compatible, removable, and sustainable conservation strategies.

Machine learning intelligence to assess the shear capacity of corroded reinforced concrete beams.

The ability of machine learning (ML) techniques to forecast the shear strength of corroded reinforced concrete beams (CRCBs) is examined in the present study. These ML techniques include artificial neural networks (ANN), adaptive-neuro fuzzy inference systems (ANFIS), decision tree (DT) and extreme gradient boosting (XGBoost). A thorough databank with 140 data points about the shear capacity of CRCBs with various degrees of corrosion was compiled after a review of the literature.

Numerical and Experimental Investigations of Fracture Behaviour of Welded Joints with Multiple Defects.

Current standards related to welded joint defects (EN ISO 5817) only consider individual cases (i.e., single defect in a welded joint).