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GFRP-concrete-steel composite columns (GCS) are formed by combining different components with excellent mechanical properties. The GCS exhibits good corrosion resistance and can serve as a pile foundation platform for offshore wind turbines. An Artificial Neural Network (ANN) is utilized to swiftly predict the loading capacity of GCS columns with various geometrical parameters. The prediction error is primarily controlled within 10%. The thickness of GFRP tubes (tG), the inner diameter of GFRP tubes (DG,i), the thickness of steel tubes (ts), the outer diameter of steel tubes (DS,o), the strength of GFRP tubes (fG), the strength of concrete (fC), and the strength of steel tubes (fS) were used as independent variables to determine the key factors affecting the loading capacity of GCS columns. The impact of the number of input variables on the final prediction accuracy is analyzed. The proportional influence of different parameters on the loading capacity of GCS column is investigated using the Garson algorithm, among which, the thickness of the GFRP tube (tG) accounts for the largest proportion, approximately 24.57%. The suitability of the artificial neural network for predicting the loading capacity of GCS columns with various geometries is revealed. The results indicate that the ANN can be utilized for high-precision compressive strength prediction, and the thickness of the GFRP tube (tG) is the most influential factor on the loading capacity of GCS columns. [ABSTRACT FROM AUTHOR]

Because the cement content is inexorably growing, CO2 emissions from the cement industry are becoming unavoidable. The use of rice husk ash (RHA) makes the system environmentally benign. This paper investigates the effect of RHA and manufactured sand (M-Sand) on the axial capacity of circular Concrete Filled Steel Tube (CFST) specimens subjected to axial compression. Thirty-two CFST specimens infilled with self-compacting concrete (SCC) with a replacement of RHA and M-Sand to cement and fine aggregate in 0%, 15%, 20% and 25% proportions are subjected to axial compression. Results show that use of RHA beyond 20% decreased the compressive strength of concrete and eventually decreased the axial capacity of CFST and occurred higher local buckling irrespective of their L/D ratios. Failure modes, strength index, confinement along with steel and concrete contribution on axial capacities of CFST specimens are studied. The axial capacities of the specimens were compared with various design code results such as: American concrete institute, Australian Standards, Chinese code, Eurocode, and Japanese code. Among all the codes, Chinese code overestimated the test results and hence, the axial capacity equation is altered and compared the results with test data along with 278 circular CFST data available from literature and found the results to be accurate. [ABSTRACT FROM AUTHOR]

Abstract Steel construction is increasingly using thin-walled profiles to achieve lighter, more cost-effective structures. However, analyzing the behavior of these elements becomes very complex due to the combined effects of local buckling in the thin walls and overall global buckling of the entire column. These factors make traditional analytical methods difficult to apply. Hence, in this research work, the strength of bi-axially loaded track and channel cold formed composite column has been estimated by applying three AI-based symbolic regression techniques namely (GP), (EPR) and (GMDH-NN). These techniques were selected because their output models are closed form equations that could be manually used. The methodology began with collecting a 90 records database from previous researches and conducting statistical, correlation and sensitivity analysis, and then the database was used to train and validate the three models. All the models used local and global slenderness ratios (λ, λc, λt) and relative eccentricities (ex/D, ey/B) as inputs and (F/Fy) as output. The performances of the developed models were compared with the predicted capacities from two design codes (AISI and EC3). The results showed that both design codes have prediction error of 33% while the three developed models showed better performance with error percent of 6%, and the (EPR) model is the simplest one. Also, both correlation and sensitivity analysis showed that the global slenderness ratio (λ) has the main influence on the strength, then the relative eccentricities (ex/D, ey/B) and finally the local slenderness ratios (λc, λt).

The deterioration of reinforced concrete (RC) structures is a significant global concern. Demolishing degraded structures is costly, time-consuming, and impacts the integrity of connected members. Implementing jackets, including fiber-reinforced polymer (FRP), fiber-reinforced cementitious matrix (FRCM), and ferro-cement, for the retrofitting and rehabilitation of existing structural members presents an advanced alternative to the deteriorated RC structures. As compared to FRP and FRCM, the ferro-cement is an economical solution that improves the mechanical strength of the structural members, service life, and offers fire resistance, durability, and versatility. This research evaluated the axial load-carrying capacity (ALCC) of ferro-cement confined RC columns using existing analytical models and machine learning (ML) algorithms. A database of 151 RC column specimens from literature was utilized. Four ML models (Artificial Neural Network, Decision Tree, Linear Regression, and Support Vector Machine) were developed to predict the axial capacity of ferro-cement confined RC columns. The ANN model performed the best out of all the ML models. The developed model was precise, user-friendly, and cost-effective. The ANN-based mathematical model can be easily used by structural engineers and ferro-cement jacketing designers to estimate the axial capacity of the ferro-cement strengthened RC columns. [ABSTRACT FROM AUTHOR]

The concrete industry is increasingly adopting the production of environmentally sustainable green concrete. Using recycled coarse aggregate (RCA) produced from demolished concrete infrastructures and waste tire-derived crumb rubber (CR) in the concrete mixture provides a sustainable construction practice and can enhance structural performance. This study investigates the uniaxial compressive behavior of concrete columns composed of RCA, CR, and polypropylene (PP) fiber. A total of 26 columns 150 x 150 x 950 mm in size were tested under uniaxial compression loading. Test parameters included longitudinal reinforcement ratio (0, 1.4, and 2.0%), tie spacing (75 and 150 mm), CR content (0, 5, 10, and 15% of the volume of natural fine aggregate), and percentage of PP fiber (0 and 0.5% of the volume of the total mixture) with 30% RCA replacement (by weight of natural coarse aggregate). The compressive behavior, failure mechanism, influence of longitudinal and transverse reinforcement, dilation, ductility, and toughness were examined. This study demonstrated that incorporating fiber into the concrete made with RCA and CR waste materials improved the axial capacity, resulting in fiber-reinforced rubberized recycled concrete (FRRC) columns with enhanced ductility and toughness. These findings support the development of sustainable concrete for structural columns, justifying their applicability to existing design codes. [ABSTRACT FROM AUTHOR]

Steel construction is increasingly using thin-walled profiles to achieve lighter, more cost-effective structures. However, analyzing the behavior of these elements becomes very complex due to the combined effects of local buckling in the thin walls and overall global buckling of the entire column. These factors make traditional analytical methods difficult to apply. Hence, in this research work, the strength of bi-axially loaded track and channel cold formed composite column has been estimated by applying three AI-based symbolic regression techniques namely (GP), (EPR) and (GMDH-NN). These techniques were selected because their output models are closed form equations that could be manually used. The methodology began with collecting a 90 records database from previous researches and conducting statistical, correlation and sensitivity analysis, and then the database was used to train and validate the three models. All the models used local and global slenderness ratios (λ, λc, λt) and relative eccentricities (ex/D, ey/B) as inputs and (F/Fy) as output. The performances of the developed models were compared with the predicted capacities from two design codes (AISI and EC3). The results showed that both design codes have prediction error of 33% while the three developed models showed better performance with error percent of 6%, and the (EPR) model is the simplest one. Also, both correlation and sensitivity analysis showed that the global slenderness ratio (λ) has the main influence on the strength, then the relative eccentricities (ex/D, ey/B) and finally the local slenderness ratios (λc, λt). [ABSTRACT FROM AUTHOR]

Secant pile walls (SPWs) are frequently employed as temporary excavation support systems in urban areas; thus, they are useless once permanent foundations and basements have been constructed. Recently, attempts have been made to employ these walls to bear axial loads and lateral earth pressure, which may have significant potential benefits. Unfortunately, the shortage of research that recognizes them as bearing elements, especially numerical studies, has prevented this approach from reaching the final design and implementation stage. Thus, the primary objective of this research was to calibrate a finite element model to depict the performance of axially loaded SPW and extend the finite element analysis by including key factors and additional trials that may impact the performance of the axially loaded SPW. This research investigated various aspects to describe SPW behavior, including the maximum axial capacity of the SPW (Pmax), normalized horizontal deflection (δh/Ht%), normalized ground settlement (δvg/Ht%), the normalized vertical deflection of the SPW (δvw/Ht%), the normalized pivot point location (ε′/He) and settlement influence zone (Do). Several parameters, such as normalized penetration depth (He/Hc), sand relative density (Dr), surcharge load density (Wsur), and wall rigidity (Ht/Dp), were studied and examined in relation to these aspects. Additionally, 224 axially loaded SPW trails were performed as part of a parametric study. The findings demonstrated that the proposed FEM could depict the performance of the experimental model with fair accuracy under the effect of the axial and lateral loads. The effects of the investigated aspects on the Pmax were also discussed in detail. Also, using linear and non-linear regression analysis, the data from the parametric analysis was utilized to create rational relations between the various parameters. The best-achieved mathematical models for predicting the Pmax were also represented in graphical forms. Moreover, these graphs can be a useful and fast tool for civil and geotechnical engineers to predict the maximum axial capacity of an SPW according to the different variables. [ABSTRACT FROM AUTHOR]

This paper describes research into the poorly understood axial behaviour of piles driven in chalk. Comprehensive dynamic and monotonic axial testing on 27, mostly instrumented, piles undertaken for the ALPACA joint industry projects is reported and interpreted covering: diameters between 139 mm and 1·8 m; lengths from 3 to 18 m; different pile material types; tip and groundwater conditions; and ages after driving. The experiments show the factors that influence resistance most strongly are: (a) pile end conditions; (b) slenderness ratio and flexibility; (c) shaft material; (d) age after driving; (e) relative water table depth; and (f) whether loading is compressive or tensile. Varying the factors systematically identified a remarkable average long-term shaft resistance range from below 11 kPa to more than 200 kPa for piles driven at the same low- to medium-density chalk test site in Kent (UK). Dynamic and static analyses demonstrate that soil resistances to driving were generally well predicted by the Chalk ICP-18 short-term formulation. Considering the piles' long-term behaviour, the Chalk ICP-18 approach over-predicted capacity, while the widely used CIRIA approach proved over-conservative for most cases. The research enabled the development of a revised 'ALPACA-SNW' long-term capacity assessment method that matches the test outcomes far more faithfully. [ABSTRACT FROM AUTHOR]

This study investigates the axial capacity of round-cornered square high-strength steel tube confined UHPC (HSSTCU) columns with the load primarily borne by the inner concrete. 9 round-corned square HSSTCU specimens with different steel strength grades and thicknesses were tested under axial compression, and compared with the same cross-sectional concrete-filled steel tube (CFST). Additionally, a finite element model (FEM) and parametric analysis were employed to examine the axial compression behavior, load bearing analysis, material utilization, and stress distribution. The results show that the round-cornered HSSTCU columns usually exhibit buckling damage failure at both ends, and the three typical load-displacement curve types are closely linked to the confinement index. The HSSTCU columns generally show smaller ultimate bearing load compared to the CFST columns with same cross-sectional parameters, but more superior ductility with higher residual bearing capacity after peak-load and better deformation capacity. The confinement index shows almost linear correlations on axial bearing capacity and material efficiency, up to 84.7% and 141% improvements with increasing confinement index from 0.717 to 2.386, respectively. The confined stress on the core concrete diffuses from the centre of the section towards the corners, intensifying near the corners. To accurately predict the bearing capacity of HSSTCU columns, a simplified formula was derived and validated using experimental results, literature data, and FEM simulations.

Three-dimensional discrete element method (DEM) is employed to model the published calibration chamber test of a closed-ended displacement pile driven in sand. To achieve large chamber-to-pile and pile-to-particle size ratios for unbiased predictions, a high-performance graphics processing unit-powered DEM code is utilised in conjunction with the axisymmetric assumption and particle refinement method. The DEM parameters are first calibrated against the drained triaxial compression test data on Fontainebleau sand. Then, the DEM modelling of pile driving demonstrates quantitative agreement with the experimental counterpart in terms of cone resistance, stress contours, and distributions. [ABSTRACT FROM AUTHOR]

Hollow concrete compressive members (HCCs) are lightweight and stiff structural members. The main focus of the study described is to create a model using nonlinear finite element analysis that can precisely forecast how well HCCs are when reinforced with non-corrosive glass fiberreinforced polymer (GFRP) bars and subjected to axial compressive loads. The researchers successfully achieved their objective by using the ABAQUS finite element package to develop the finite element model (FEM), which was then compared to experimental outcomes from previous studies. The FEM's predictions and the experimental findings were found to be very compatible. [ABSTRACT FROM AUTHOR]

This study presents experimental and analytical investigations on the axial capacity of 12 heat-damaged glass fiber-reinforced polymer reinforced concrete columns. The columns were prepared with dimensions of 200 × 200 × 1000 mm and 3 replacement ratios of seawater for concrete mixing and curing (0%, 50%, and 100%). At the age of 3 months, the columns were subjected to an elevated temperature of 500 °C for 30, 60, and 90 min and subsequently cooled and tested. The experimental results demonstrated that the compressive strength of concrete increased by 35% and 45% at seawater replacement ratios of 50% and 100%, respectively. In addition, seawater-concrete mixes exhibited a lower rate of strength development compared to the reference mix. Moreover, 100% seawater concrete columns reported an increase of 28% in the cracking and ultimate loads. However, columns at seawater replacement ratios of 0%, 50%, and 100% exhibited a drop of 27%, 53%, and 50% in the cracking load after being exposed to 500 °C for 90 min. Additionally, the columns exposed to elevated temperatures showed a reduction of 5%–20% in the ultimate load. Furthermore, the analytical models of ACI 440.11–22 and CAN/CSA-S806-12 significantly underestimated the axial capacity of all columns. The most accurate prediction for the columns’ axial capacity was associated with the analytical model of Mohamed et al. with mean, standard deviation, and coefficient of variance of experimental-to-predicted ratios of 1.17, 0.12, and 9.98%, respectively.

Concrete Filled Tube (CFT) columns represent an effective alternative to conventional reinforced concrete columns. Recently, there have been trials to replace steel encasing tubes with Polyvinyl-Chloride (PVC) tubes for the enhancement of columns performance. The use of fibrous concrete as the core of such columns still needs more focus. In this study, glass fibrous concrete was used to fabricate PVC CFT (PCFT) short columns. PVC tubes thickness, tube roughness and lateral PVC supporting ties were the adopted parameters herein. These columns were tested in compression and their vertical and lateral deformations were monitored during loading. It was concluded that PCFT columns have generally shown higher axial capacity and ductility in comparison to concrete core. The best performance was related to PCFT columns with rough interface which showed axial capacity of about two thirds and ductility of about three folds higher than concrete core. Also, the use of lateral ties along the column height showed reasonable results, but the installation method of these ties needs to be modified to reach better results. Based on the experimental program, a design formula was deduced to predict short PCFT columns capacity with an error of about 8%.

The aim in this study is to experimentally and numerically evaluate the effectiveness of the fiber-reinforced polymer (FRP) rehabilitation technique on postblast piers. Firstly, contact explosion, carbon FRP (CFRP) rehabilitation, and axial compression tests were successively conducted on half-scale RC pier specimens. The incident overpressure time histories and damage profiles of specimens in the explosion test, as well as the axial force–displacement curves, strain time histories of FRP, and specimen damage modes in the axial compression test were recorded. Secondly, a finite-element (FE) analysis approach was proposed and experimentally validated to reproduce the blast wave–pier interactions and dynamic behaviors of RC piers under explosions, as well as the axial compressive performance of the intact, unrehabilitated, and FRP-rehabilitated RC piers. Furthermore, three typical explosion threats specified by the Federal Emergency Management Agency were selected, and the damage profiles and residual axial capacities of the seismically designed prototype bridge piers were further examined. An FRP rehabilitation scheme, covering FRP type, rehabilitation height, and number of rehabilitation layers, for restoring the axial capacities of postblast prototype piers is recommended. It indicates the following. (1) FRP rehabilitation effectively improves the axial capacity and ductility of postblast piers, but slightly affects the axial stiffness. (2) The residual axial capacities of the presented prototype piers reduced to 92% and 58% of the intact value under contact explosion from a suicide belt or suicide vest, and increased to 99% and 84% after two-layer CFRP rehabilitation. (3) Compared with glass FRP and aramid FRP, CFRP rehabilitation along the overall pier height is more strongly recommended. (4) Increasing the number of rehabilitation layers to four could prominently improve the axial capacity. This work could provide a supportive reference on the FRP rehabilitation of a RC bridge pier after explosions. [ABSTRACT FROM AUTHOR]

Concrete-Filled Double Skin Tubular (CFDST) compression members have become a major thrust area of research over the last few decades to take advantage of the confinement effect as well as higher stiffness. In the present investigation, an unconventional confining material of Unplasticized Poly Vinyl Chloride (UPVC) pipe has been utilized in the form of double-skin tubular format with concrete as filler material so as to make the structural member more cost-effective and environment friendly. A total of 36 cylindrical specimens with diameter of 200 mm and 90 mm for outer and inner confining pipe respectively, having 300 mm length have been cast with three different pipe thicknesses and two different grades of infilled concrete and subsequently tested. Results have shown a promising response for such CFDST specimens particularly in terms of improved load-carrying capacity, energy absorption capacity, and ductility and thereby emphasizing the applicability of the UPVC tube-Concrete hybrid system. An attempt has also been made to estimate the ultimate load-carrying capacity in the form of a generalized equation for such configuration in line with stipulations available with current codes of practice and literature, which is in excellent agreement with the experimental data. [ABSTRACT FROM AUTHOR]

This research aimed at investigating the possibility of using glass fiber-reinforced polymer (GFRP) reinforcement in concrete piles submerged in marine environments. In addition, the validity of the available design provisions in the codes in predicting the nominal axial capacity of submerged GFRP-reinforced concrete (RC) piles in marine environments was investigated. The experimental program aimed at assessing the durability and structural response of RC square piles entirely reinforced with GFRP bars and spirals (or ties) exposed to laboratory-simulated marine environments. Fifteen laboratory-scale square concrete piles, including 10 conditioned and five unconditioned specimens, with a cross section of 300 mm (12 in.) and 1000 mm (40 in.) in length and reinforced with GFRP bars and spirals, were fabricated and tested. The structural parameters included longitudinal reinforcement ratio, diameter of GFRP bars, and configuration of the GFRP spirals or ties. The 10 specimens were submerged in two different marine environments for 365 days and then tested under concentric loading. Marine environments in tropical and hot regions were simulated by submerging the specimens in saline solution (3.5% NaCl) at 22°C (72°F) and in a heatwave chamber at 60°C (140°F), respectively. Microstructural analyses--including glass transition temperature, optical microscopy (OM), and scanning electronic microscopy (SEM)--were conducted on GFRP reinforcement extracted from the submerged pile specimens to assess the possible degradation of GFRP reinforcement and changes in its bonding to concrete and microstructure. The microstructure analysis results confirm that the GFRP reinforcement was well-bonded to the concrete and did not show any sign of microstructural deterioration. The structural test results indicate that axial capacities of the submerged GFRP-RC pile specimens increased up to 22% compared to the unconditioned counterpart specimens due to the increase in concrete compressive strength. Moreover, the test results have shown that increasing the GFRP reinforcement ratio and using GFRP spirals improved the post-peak response of the GFRP-RC piles. [ABSTRACT FROM AUTHOR]

One of the most common retrofitting processes for columns is reinforced concrete (RC) jacketing. This process enhances the ductility, stiffness, flexural capacity, and shear capacity of columns, and increases the axial load-carrying capacity of the RC column when subjected to an axial load. According to previous research, the most typical way to improve the lateral capacity of a column in composite action is column retrofitting with RC jacketing. The lateral strength of a single RC column and a single bay, single-story RC frame (retrofitted with concrete jacketing) is numerically analyzed in this work. To obtain a complete overview, an RC frame analysis is conducted even though a single column represents the column in the frame. Finally, parametric analysis is performed to assess the influence of reinforcement ratio, compressive strength of jacket concrete, and yield strength of reinforcement. The axial load carrying capacity and flexural capacity of retrofitted columns increase with the increase in RC jacket compressive strength, reinforcement percentage, and yield strength of the reinforcement. If the compressive strength of the jacket concrete stays constant, 1% reinforcement increment leads to a 10% to 20% increase in the axial capacity of the column. The parametric study reveals that retrofitted columns and frames exhibit a substantial increase in lateral capacity (10 to 12 times) compared to existing columns.

Many masonry structures are constructed with cement clay interlocking brick (CCIB) due to its added benefits. Recent research has demonstrated the vulnerability of brick masonry walls against seismic loading. Various strengthening materials and techniques are extensively used to improve the structural behavior of brick walls. Carbon fiber-reinforced polymer (CFRP) composites are the most popular strengthening material due to their advantages of easy application, lightweight qualities, and superior tensile strength. The current research work aimed to explore the cost-effective solutions and feasibility of CFRP composite-based strengthening techniques to improve the load-bearing capacity of CCIB walls. Various configurations and combinations of strengthening materials were investigated to customize the cost of repair and strengthening. The experimental results indicated that CFRP composites in combination with cement-sand (CS) mortar are an efficient strengthening material to enhance the strength and ultimate deflection of CCIB walls. The ultimate load-bearing capacity and axial deformation of the strengthened CCIB wall (using two layers of CFRP strips and CS mortar of 10 mm thickness) remained 171% and 190% larger than the unstrengthened CCIB wall. The conclusions of this study are expected to enhance the seismic performance of masonry buildings in developing countries. It should be noted that due to the reduced number of tested specimens, the results to be assumed as general considerations need a wider experimental campaign and a large numbers of tests for each strengthening typology. [ABSTRACT FROM AUTHOR]

This study investigates the distortional buckling strength of a partially closed cold-formed steel (CFS) channel section with intermediate web stiffeners and outward lips under axial compression. Generally, a closed CFS cross section has higher torsional resistance when compared to an open cross section. However, an open cross section is more popular in the construction industry. Despite the popularity of CFS open sections, distortional buckling can reduce the load-carrying capacity of such open cross sections. To improve the distortional buckling strength of the proposed selected section, a simple spacer plate is added externally to the channel section in the transverse direction. Initially, a numerical model is developed using the finite element software ANSYS, which is then validated against the experimental results available in the literature. A detailed parametric study was also conducted to investigate the influence of thickness, depth, and spacing of spacer plates on the distortional buckling strength of stiffened CFS channel sections. From the results of the parametric study, it was found that the presence of spacer plates can increase the axial capacity of stiffened CFS channel sections by as much as 32%. Finite element results were compared with the design strengths calculated in accordance with the direct strength method (DSM). [ABSTRACT FROM AUTHOR]

Previous studies on machine-learning (ML) prediction of axial capacity of composite concrete-filled steel tubular (CFST) columns under axial loading relate mainly to only one cross-section shape, meaning that they are limited to only one given application. In this paper, a ML model—namely support vector machine (SVM)—is proposed for the prediction of CFST columns with different cross-section shapes: circular, elliptical, square and rectangular, because they are the most widely used in engineering structures. A database consisting of 1093 tests was gathered from the available literature and used to train and validate the SVM model. The model's performance was quantified by various performance indicators: coefficient of determination (R2), root mean squared error, mean absolute error, Willmott's index of agreement, and mean absolute percentage error. Based on the SVM model, sensitivity analysis, influence of different factors, parametric study and comparison with the literature are presented. A graphic user interface of the proposed model was also implemented. The model could be extended to study the effect of other cross-sectional shapes, making for wider applicability. [ABSTRACT FROM AUTHOR]

This paper deals with the numerical analysis aimed at study the bearing capacity of pinended steel built-up columns under axial compression. Finite element (FE) models were performed for the columns presented in the literature. The main problem discussed in the article is the shape and magnitude of geometric imperfections introduced into the numerical FE model, necessary to obtain the load capacity consistent with the experimental strength tests. Three types of numerical analysis that can be used inAbaqus program to calculate the load bearing capacity have been described. The imperfections possible to introduce for built-up columns were presented and an equivalent imperfection corresponding to both imperfections recommended by Eurocode 3 (global of the entire column and local of the chord) for built-up members was proposed. The results of the geometrically and materially nonlinear static analysis were compared with the calculations according to the code procedures (Eurocode 3 and PN-B- 03200:1990) and the results of experimental tests.

Due to the corrosion problem in reinforced concrete structures, the use of fiber-reinforced polymer (FRP) bars may be preferred in place of traditional reinforcing steel. FRP bars are used in concrete constructions to boost the strength of structural elements and retain their longevity. In this study, the axial load carrying capacity (ALCC) of the FRP-reinforced concrete columns has been evaluated using analytical, as well as machine learning, models. A total of fourteen popular analytical models and one proposed machine learning-based model were used to estimate the ALCC of the concrete columns. The proposed machine learning model is based on an artificial neural network (ANN) method. The performance of the ANN, as well as the analytical models, are assessed using six different performance indices. The R-value of the developed ANN model is 0.9758, followed by an NS value of 0.9513. It has been found that the mean absolute percentage error of the best-fitted analytical model is 328.71% higher than the ANN model, and the root-mean-square error value of the best-fitted analytical model is 211.97% higher than the ANN model. The evaluated data demonstrate that the proposed ANN model performs better than the other analytical models. The developed model is quick and easy-to-use to estimate the axial capacity of the FRP-reinforced concrete columns. [ABSTRACT FROM AUTHOR]

A few empirical models for the axial loading capacity (ALC) of circular normal strength concrete (NSC) columns wrapped by carbon fiber reinforced polymer (CFRP) sheets and interior transverse steel reinforcement (TSR) (CSC columns) are available in the literature. The deficiency of those models is that they were proposed based on a small number of tests by considering limited parameters of CSC columns. Therefore, the main aim of the current investigation is to propose the improved empirical models for the ALC of CSC columns by including the interaction mechanism between TSR and FRP confining behavior. To secure this aim, a general regression analysis technique and artificial neural networks (NNs) on the experimental outcomes of 76 CSC columns collected from the previous investigations were employed. The proposed NN model was adjusted for the different number of hidden layers and neurons to achieve an optimized model. The suggested NN and empirical models portrayed a close agreement with the testing database with R2 = 0.998 and R2 = 0.892, respectively. The NN model reported a higher accuracy than the theoretical model. The comparative investigation solidly authenticated the superiority and accuracy of the anticipated strength models for CSC columns. [ABSTRACT FROM AUTHOR]

The use of fiber-reinforced polymer (FRP) composites in compressive members is advantageous to reinforced concrete structures in order to alleviate the problem of corrosion of steel reinforcement and to produce a lightweight and efficient structural element. This investigation aims to propose the theoretical models for capturing the axial loading capacity (ALC) of hollow concrete columns (HCCs) having main FRP rebars and transverse FRP spirals. All the glass-FRP-reinforced HCCs portray two-peak load performance. The first peak is due to the gross cross-sectional area of concrete while the second peak is due to the core material laterally wrapped with FRP spirals. For the prediction of the first peak load of HCCs which is equal to the maximum capacity of solid concrete columns, a database of 279 FRP-reinforced columns was produced from the previous research and the ALC models were suggested; one for capturing the first peak and the other for estimating the second peak ALC of HCCs. The predictions of proposed models were compared with the test results from the literature. A close relationship was perceived between the theoretical and experimental results. [ABSTRACT FROM AUTHOR]

Numerous studies have indicated the existence of a size effect on the axial compressive behaviour of stirrup-confined concrete columns. However, most of these studies have focused on nominal compressive strength. Investigations of the size effect on the axial strain (at peak load) and of the descending branch are limited. In this study, the size effect behaviour of square stirrup-confined concrete columns under axial compression was explored, using a three-dimensional mesoscale simulation method. Based on the numerical and available experimental results, the influence of specimen size on peak axial stress (i.e. compressive strength), corresponding strain and softening rate was explored. Moreover, quantitative relationships between specimen size and peak axial stress, corresponding strain and softening rate for circular and square stirrup-confined concrete columns were derived. Finally, considering the size effect on the peak axial stress, corresponding strain and softening rate, a novel stress–strain model describing the axial compression behaviour of stirrup-confined concrete was developed. The proposed model was verified by comparison with the available experimental results and existing models. [ABSTRACT FROM AUTHOR]

One of the most common retrofitting processes for columns is reinforced concrete (RC) jacketing. This process enhances the ductility, stiffness, flexural capacity, and shear capacity of columns, and increases the axial load-carrying capacity of the RC column when subjected to an axial load. According to previous research, the most typical way to improve the lateral capacity of a column in composite action is column retrofitting with RC jacketing. The lateral strength of a single RC column and a single bay, single-story RC frame (retrofitted with concrete jacketing) is numerically analyzed in this work. To obtain a complete overview, an RC frame analysis is conducted even though a single column represents the column in the frame. Finally, parametric analysis is performed to assess the influence of reinforcement ratio, compressive strength of jacket concrete, and yield strength of reinforcement. The axial load carrying capacity and flexural capacity of retrofitted columns increase with the increase in RC jacket compressive strength, reinforcement percentage, and yield strength of the reinforcement. If the compressive strength of the jacket concrete stays constant, 1% reinforcement increment leads to a 10% to 20% increase in the axial capacity of the column. The parametric study reveals that retrofitted columns and frames exhibit a substantial increase in lateral capacity (10 to 12 times) compared to existing columns. [ABSTRACT FROM AUTHOR]

A pressure-grouted helical pile (PGHP) is a stiffened helical pile installed by using the simultaneous drilling and grouting technique. The formation of the soil-cement column surrounded by the helical pile is influenced by the multiple installation parameters, including helix number, helix size, and drilling speed. A series of small-scale model tests was carried out in clay to investigate the influence of installation parameters on axial behavior of PGHP and the load transfer mechanism. The model piles were pulled out after the loading tests, and the dimensions of the soil-cement columns were measured. The ultimate compressive bearing capacities of the PGHPs were 260% to 293% higher than the un-grouted helical piles. The ultimate bearing capacities of the PGHPs were proportional to the increase of the helix number and helix size and decreased with the drilling speed. The average bond diameter of the soil-cement column was 1.26 to 1.35 times the helix size. The adhesion between the soil-cement column and the surrounding clay was in the range of 0.8 to 1.2. The overall results examine the feasibility of the simultaneous drilling and grouting technique in clay and the improvement of the axial bearing performance compared to un-grouted helical piles. [ABSTRACT FROM AUTHOR]

Reinforced concrete (RC) is well-recognized as a fire-resistant construction material. Even though, severe fire exposure can change the physical and chemical properties of concrete and steel, causing some level of damage to RC structures. As a practical solution to these problems, strain-hardening cementitious composites (SHCC) have been used in this study to repair the post-fire square RC columns. So far, a total of 13 specimens have been prepared and tested under axial compression. The full experimental program involved: (1) one non-damaged/non-repaired reference column; (2) five post-fire/non-repaired columns; and (3) seven post-fire/SHCC-repaired columns. The test variables included the fire exposure duration (1, 2, or 3 hrs.), temperature level (400 ºC, 600 ºC, or 800 ºC), and thickness of the SHCC jacket (20 mm, 30 mm, or 40 mm). The results indicated that using the SHCC jacket was effective in terms of the restorability of the load-carrying capacity, secant stiffness, and energy absorption of all tested post-fire RC columns even more than the reference specimen at ambient temperature (20 ºC). The enhancement percentages in the load-carrying capacity varied between 17 % and 151 %, depending on the test parameters. In addition, SHCC-repaired columns exhibited on average 16 % higher axial stiffness and a larger energy absorption capacity when compared to the reference non-damaged column. A three-dimensional (3D) non-linear finite element model (FEM) was carried out using ABAQUS software and validated against the experimental results in order to further evaluate the potential of the SHCC jacket to restore the efficiency of fire-damaged columns. Finally, test results were utilized to verify an engineer-friendly formula that was derived to predict the load-carrying capacity of post-fire/repaired RC columns to promote their evaluation in engineering practices. • 13 specimens were tested: 1 reference non-damaged/non-repaired, 5 post-fire/non-repaired, and 7 post-fire/SHCC-repaired. • Parameters: fire exposure duration, temperature level, and thickness of the SHCC jacket. • The adopted repair technique (SHCC jackets) manifested enhanced capacity and energy absorption. • A FE model agreed well with the experimental results. • An equation for estimating the load-carrying capacity of post-fire/repaired RC columns is proposed. [ABSTRACT FROM AUTHOR]

A genetic algorithm (GA) was used in this study to develop a standard penetration test (SPT)-based design method for the axial capacity of driven piles. A total of 72 pile load tests was collected from literature and divided into two groups based on their measurements. The first group had the load-transfer distribution measurements for extracting both the unit side and tip resistances. These unit resistances were correlated by the GA with soil measurements and pile properties to develop the design method. The second group, where only the total capacity measurements were available, were used to validate the new design method and compare its performance with three existing SPT-based design methods. The new GA-derived design method considers nonlinear relationships with the effective stress and pile length and provides an unbiased prediction with a low coefficient of variation (COV) of 40.0 %, while the three existing methods overestimate the capacity by a factor of 1.62 to 1.65 with a high COV of 40.3 % to 52.8 %, which could result in an under design of pile foundations. This study shows that the GA was able to obtain complex relationships with great accuracy and the new design method can be applied to new cases reasonably well.

Over the past decade, cold-formed steel (CFS) channel sections with edge-stiffened circular web holes have been developed and are now widely used in New Zealand. Previous studies on axial compression have demonstrated enhanced axial capacity when utilizing edge-stiffened web holes in these channel sections. Building on this, research has extended to include elongated web holes, but literature lacks investigations into the axial capacity of CFS channel sections with elongated edge-stiffened web holes (EEH). This study addresses this gap. Non-linear finite element (FE) analysis was employed to examine the axial capacity of CFS channel sections with both EEH and elongated unstiffened web holes (EUH). FE models were developed and validated against the experimental results available in the literature. Using the validated FE models, a comprehensive parametric study comprising 990 finite element analysis (FEA) results was conducted. These parametric study results were compared with design strengths calculated from the current design guidelines of the American Iron and Steel Institute (AISI 2016) and Australia/New Zealand Standards (AS/NZS 2018) for CFS channel sections with plain webs and EUH. Also, design equations in the form of capacity reduction and enhancement factors for effective width method (EWM) and modified direct strength method (DSM) equations were proposed to determine the axial capacity of CFS channel sections with EEH and EUH. Finally, a reliability analysis was performed, demonstrating that the proposed equations are reliable and can provide accurate predictions for the axial capacity of such sections. • The axial capacity of cold-formed steel (CFS) channel sections with elongated web holes was investigated numerically. • The results of a total of 990 new finite element analysis were reported. • The prediction accuracy of the current available design guidelines was evaluated. • Design equations in the form of effective width method (EWM) and the direct strength method (DSM) were proposed. [ABSTRACT FROM AUTHOR]

Several past studies have shown the use of glass fibre-reinforced polymer (GFRP) bars to alleviate the reinforced steel rusting issue in different concrete structures. However, the practise of GFRP bars in concrete columns has not yet achieved a sufficient confidence level due to the lack of a theoretical model found in the literature. The objective of the current study is to introduce a novel prediction model for the axial capability of concrete columns made with bars of GFRP. For this purpose, two different approaches, such as data envelopment analysis (DEA) and artificial neural networks (ANNs) modelling, are used on a collected dataset of 266 concrete column specimens made with GFRP bars from previous literature works. Eight parameters were used to predict the axial performance of GFRP-based RC columns. The proposed DEA and ANNs predictions demonstrated a good correlation with the testing dataset, having R2 values of 0.811 and 0.836, respectively. A comparative analysis of the DEA and ANNs models is undertaken, and it was found that the suggested models are capable of accurately forecasting the structural response of GFRP-made RC column structures. Then, a comprehensive parametric analysis of 266 GFRP-based columns was performed to study the effect of different materials and their geometrical shape. [ABSTRACT FROM AUTHOR]

Fiber-reinforced polymer (FRP) rebars are increasingly being used as an alternative to steel rebars in reinforced concrete (RC) members due to their excellent corrosion resistance capability and enhanced mechanical properties. Extensive research works have been performed in the last two decades to develop predictive models, codes, and guidelines to estimate the axial load-carrying capacity of FRP-RC columns. This study utilizes the power of artificial intelligence and develops an alternative approach to predict the axial capacity of FRP-RC columns more accurately using data-driven machine learning (ML) algorithms. A database of 117 tests of axially loaded FRP-RC columns is collected from the literature. The geometric and material properties, column shape and slenderness ratio, reinforcement details, and FRP types are used as the input variables, while the load-carrying capacity is used as the output response to develop the ML models. Furthermore, the input-output relationship of the ML model is explained through feature importance analysis and the SHapely Additive exPlanations (SHAP) approach. Eight ML models, namely, Kernel Ridge Regression, Lasso Regression, Support Vector Machine, Gradient Boosting Machine, Adaptive Boosting, Random Forest, Categorical Gradient Boosting, and Extreme Gradient Boosting, are used in this study for capacity prediction, and their relative performances are compared to identify the best-performing ML model. Finally, predictive equations are proposed using the harmony search optimization and the model interpretations obtained through the SHAP algorithm. [ABSTRACT FROM AUTHOR]

A simplified procedure to predict the residual axial capacity and stiffness of both rectangular and circular reinforced concrete (RC) columns after exposure to a standard fire provides the means to replace the current descriptive methods. The availability of such a procedure during the design phase provides engineers with the flexibility to come up with better designs that ensure safety. In this paper, finite difference heat transfer and sectional analysis models are combined to determine the axial behavior of RC columns with various end-restraint conditions at different standard fire durations. The influence of cooling phase on temperature distribution and residual mechanical properties is considered in the analysis. The ability of the model to predict the axial behavior of the damaged columns is validated in view of related experimental studies and shown to be in very good agreement. A parametric study is then conducted to assess the axial performance of fire-damaged RC columns. A procedure is proposed to determine the residual strength and stiffness of fire-damaged RC columns in typical frame structures. [ABSTRACT FROM AUTHOR]

This paper presents a study conducted on a multi-under-reamed pile having a small bulb size, but more than two in number. The proposed design is aimed to mobilize the side friction along the cylindrical surface formed between the bulbs to a greater extent and thereby enhance the load-carrying capacity with the minimum use of concrete. Pile load test was carried out on full-scale models of the conventional pile, and the proposed multi-tiny bulb pile. Finite-element analyses were performed to analyse the capacity of the proposed pile and to compare it with conventional bored cast-in-situ piles tested in the field. The validated model was then used to study the effect of various parameters on load-deformation behaviour and to understand the deformation contours of Multi-tiny bulb pile and to compare it with other existing pile geometries. It was found that Multi-tiny bulb piles of bulb diameter equal to the shaft diameter of conventional piles mobilize almost the same capacity as that of a solid conventional pile of uniform shaft diameter equal to that of bulb diameter of the former. The volume of material consumed by a Multi-tiny bulb pile to attain this was only 42% of a conventional pile considered for the study. The study suggests that Multi-tiny bulb piles if properly employed in the field with quality control can effectively replace the conventional piles in clayey stratum and also is a cost-effective option in terms of material input. [ABSTRACT FROM AUTHOR]

This experimental investigation reveals the projected benefits of concrete-filled double-skin tubular columns. These columns are made up of an outside steel tube, an interior UPVC pipe, and a sandwich of concrete among these tubes. The effect of the dimension ratio of the outer-to-inner tube, the thickness ratio of the outer tube, and the internal tube material (steel/UPVC) on the ultimate compressive strength of double-skin tubular columns samples filled with concrete are investigated. Finally, the experimental findings were compared to previously published design approaches in AISC (2010), GB50936 (2014), and EC4 (2004). The analysis revealed that GB50936 (2014) produces the best outcomes, followed by AISC (2010) and EC4 (2004). In addition, the samples were tested in elevated temperatures to study their post-fire axial capacity. It was discovered that the type of infilled concrete and interior tube material has no major impact on the performance of samples at elevated temperatures.

This paper analyzed the ultimate grout-to-soil bond strength based on a database of 40 full-scale static load tests conducted on micropiles in glacial deposits in the province of Ontario, Canada. The Décourt extrapolation method was used to extrapolate the field load–settlement curves to identify the ultimate limit state. The elastic length method was modified by considering the shear stress influence to more accurately predict the failure loads of micropiles. A set of the ultimate bond strengths were correlated with the field standard penetration test blow count for different types of micropiles in different soil conditions. The results were compared with existing design values recommended by the Federal Highway Administration manual. The findings will help to improve the design of micropiles in similar soil conditions and the development of a reliability-based design method for soil-bonded micropiles. [ABSTRACT FROM AUTHOR]

Nowadays, the improper disposal of electronic waste (E-waste) is creating environmental pollution and health problems in developing countries. Moreover, the corrosion of steel bars reduces the serviceability of reinforced concrete columns. Although many researchers studied the behavior of glass fiber reinforced polymer (GFRP) bars in concrete columns, none of the studies investigated the structural performance of structural fiber-reinforced E-waste concrete (SFEC) columns having GFRP reinforcement. The present study aims to examine the structural performance of GFRP reinforced concrete circular columns consisting of polypropylene structural fibers (GSFEC columns) under concentric and eccentric loading. Identical steel bars reinforced concrete columns (SSFEC columns) were also manufactured and tested to failure under the same loading conditions. The experimental program consisted of 18 circular columns (1200 mm × 300 mm) to measure the axial capacity (AC), axial deflections, failure modes, and cracking patterns under different eccentric loadings. The AC of SSFEC columns was larger while the ductility was lower than GSFEC columns. Both GSFEC and SSFEC columns illustrated similar damaging behavior. The eccentric loading led to similar decreases in AC for both GSFEC and SSFEC columns. [ABSTRACT FROM AUTHOR]

Many masonry structures are constructed with cement clay interlocking brick (CCIB) due to its added benefits. Recent research has demonstrated the vulnerability of brick masonry walls against seismic loading. Various strengthening materials and techniques are extensively used to improve the structural behavior of brick walls. Carbon fiber-reinforced polymer (CFRP) composites are the most popular strengthening material due to their advantages of easy application, lightweight qualities, and superior tensile strength. The current research work aimed to explore the cost-effective solutions and feasibility of CFRP composite-based strengthening techniques to improve the load-bearing capacity of CCIB walls. Various configurations and combinations of strengthening materials were investigated to customize the cost of repair and strengthening. The experimental results indicated that CFRP composites in combination with cement-sand (CS) mortar are an efficient strengthening material to enhance the strength and ultimate deflection of CCIB walls. The ultimate load-bearing capacity and axial deformation of the strengthened CCIB wall (using two layers of CFRP strips and CS mortar of 10 mm thickness) remained 171% and 190% larger than the unstrengthened CCIB wall. The conclusions of this study are expected to enhance the seismic performance of masonry buildings in developing countries. It should be noted that due to the reduced number of tested specimens, the results to be assumed as general considerations need a wider experimental campaign and a large numbers of tests for each strengthening typology.

In this study, artificial neural network analysis is introduced to aid in estimating the axial capacity of concrete-filled steel tube stub columns. A wide range of experimental database of rectangular concrete-filled steel tube columns available in the literature is used here in order to construct and verify the model. The Levenberg-Marquardt algorithm is employed in this backpropagation training procedure. The present artificial neural network model has been created using six input neurons that have different geometric and material properties of the column including the length of the column, the width and the depth of the section, the thickness of the steel tube, the compressive strength of the concrete core, and the yield strength of the steel tube. Six hidden neurons have been employed, in addition to one output neuron that gives the ultimate capacity of the column. The verification process has showed that the present model is very accurate in predicting the ultimate capacities of the columns. This model is tested against other methods found in codes and standards and a method that has been previously proposed by the authors. With the limitations set by the codes and standards, the present model can be used safely and with sufficient accuracy. A parametric study using the artificial neural network model has been conducted to explore the effect of different parameters on axial capacities of the composite columns. The results have showed that careful optimizing techniques should be followed in order to get the most efficient sections. [ABSTRACT FROM AUTHOR]

Due to the corrosion problem in reinforced concrete structures, the use of fiber-reinforced polymer (FRP) bars may be preferred in place of traditional reinforcing steel. FRP bars are used in concrete constructions to boost the strength of structural elements and retain their longevity. In this study, the axial load carrying capacity (ALCC) of the FRP-reinforced concrete columns has been evaluated using analytical, as well as machine learning, models. A total of fourteen popular analytical models and one proposed machine learning-based model were used to estimate the ALCC of the concrete columns. The proposed machine learning model is based on an artificial neural network (ANN) method. The performance of the ANN, as well as the analytical models, are assessed using six different performance indices. The R-value of the developed ANN model is 0.9758, followed by an NS value of 0.9513. It has been found that the mean absolute percentage error of the best-fitted analytical model is 328.71% higher than the ANN model, and the root-mean-square error value of the best-fitted analytical model is 211.97% higher than the ANN model. The evaluated data demonstrate that the proposed ANN model performs better than the other analytical models. The developed model is quick and easy-to-use to estimate the axial capacity of the FRP-reinforced concrete columns.

A pressure-grouted helical pile (PGHP) is a stiffened helical pile installed by using the simultaneous drilling and grouting technique. The formation of the soil-cement column surrounded by the helical pile is influenced by the multiple installation parameters, including helix number, helix size, and drilling speed. A series of small-scale model tests was carried out in clay to investigate the influence of installation parameters on axial behavior of PGHP and the load transfer mechanism. The model piles were pulled out after the loading tests, and the dimensions of the soil-cement columns were measured. The ultimate compressive bearing capacities of the PGHPs were 260% to 293% higher than the un-grouted helical piles. The ultimate bearing capacities of the PGHPs were proportional to the increase of the helix number and helix size and decreased with the drilling speed. The average bond diameter of the soil-cement column was 1.26 to 1.35 times the helix size. The adhesion between the soil-cement column and the surrounding clay was in the range of 0.8 to 1.2. The overall results examine the feasibility of the simultaneous drilling and grouting technique in clay and the improvement of the axial bearing performance compared to un-grouted helical piles.

In recent years considerable attention has been given to estimating the strength of box concrete-filled steel tube (CFST) stub columns. The effect of confining pressures is one of the complexities in determining the ultimate strength of the CFST columns. An experimental database of 188 tested columns has been used to produce two types of formulae: modified and simplified, that can help to predict the ultimate strength of box CFST columns with a wide range of geometrical and material properties. Different code procedures and previous formulae given by other authors were used for verification purposes and to show reliability. The axial load-shortening behaviors of composite columns were plotted using a proposed model of confined concrete adopted in a finite element analysis and compared with the experimental results. It has been found that the present formulae and concrete model have given results that agree quite well with the results of the experimental tests. [ABSTRACT FROM AUTHOR]

Hollow bar micropiles (HBMP) have been popular for some time due to their fast installation and efficient load transfer mechanism. In the construction of HBMP, it is common practice to use a diameter ratio of drill bit/ hollow bar (Db/Dh) between 2 and 2.5. However, increasing the drill bit diameter should increase the micropile diameter and hence may enhance its performance and increase its capacity for a minimal increase in cost. In this study, a field testing program was conducted on six single HBMP with two different (Db/Dh) ratios installed in sand to investigate their performance. The ratio Db/Dh was increased from 2.25 to 3 by increasing the drill bit diameter for the same size hollow bar. The micropile length was 6 m, with 0.25 m free standing above ground. The micropiles were subjected to compression and tension load tests. The results demonstrated that increasing Db/Dh to 3 improved the micropiles performance and increased their compression and uplift capacities: the stiffness increased by 38% and 32% in compression and uplift, while the capacity increased by 17% and 22.5%, respectively. The compressive load–displacement response of micropiles was slightly stiffer than the uplift response and their ultimate compressive capacity was slightly higher than their uplift capacity. [ABSTRACT FROM AUTHOR]