Polymer Bars Research Articles

Data-driven machine learning methodology for designing slender FRP-RC columns

Current design guidelines for reinforced concrete (RC) with fiber-reinforced polymers (FRP) bars lack provisions for designing slender columns. Limited attempts were made to modify the moment magnification procedure to accommodate FRP-RC columns. This study proposes a novel approach for designing FRP-RC slender columns based on suggesting a simplified slenderness reduction factor to account for the slenderness (ϕslender). The novel reduction factor has been developed using data-driven machine learning, where the available experimental database of short and slender FRP-RC columns has been employed to train a robust generalized artificial neural network (ANN) model. The ANN model is then utilized to generate reduction-factor curves, facilitating a straightforward approach to designing slender FRP-RC columns. For design practice purposes, genetic expression programming (GEP) was used to generate a mathematical equation for calculating ϕslender. The proposed ϕslender is a function of concrete compressive strength, reinforcement ratio, eccentricity, and column slenderness ratio. Statistical correlation analysis indicated that implementing the ϕslender eliminates the axial capacity correlation to the slenderness ratio, indicating a very good representation of the slenderness effect on the FRP-RC columns. The proposed approach revealed higher accuracy and consistent conservatism compared to the moment magnification procedure in predicting the strength of the slender FRP-RC columns.

Fatigue Behaviour of CFRP Bar-Reinforced Seawater Sea Sand Concrete Beams: Deformation Analysis and Prediction

The new composite application of seawater sea sand concrete (SSC) and fibre-reinforced polymer (FRP) bars had broad development prospects. In this paper, the load levels and stirrup spacing were the main research parameters. The fatigue behaviour of carbon fibre-reinforced polymer (CFRP) bar-reinforced SSC beams was studied by four-point bending tests, and the development laws of fatigue crack width and fatigue deflection were deeply discussed. Results revealed that excessive stirrup spacing might change static failure modes of CFRP bar-reinforced SSC beams, resulting in a reduction in mechanical behaviour. This paper preliminarily suggested that the maximum stirrup spacing should be 200 mm. The fatigue failure mode of CFRP bar-reinforced SSC beams in this paper was mainly shear fatigue failure. The fatigue crack width and fatigue deflection increased with the cycle number. When the cycle number reached 80% of fatigue life, the fatigue crack width increased by about 100%. When the beam specimens were close to fatigue failure, the increase in fatigue deflection ranged from 166.5% to 188.9%. Load levels had a significant impact on fatigue life, and a fatigue limit of 0.5 was proposed as a threshold. In addition, the larger the stirrup spacing, the greater the growth rate of fatigue crack width and fatigue deflection. Therefore, based on the calculation equation for the maximum crack width in the code, the influence of stirrup spacing, load levels and n/N was further considered in this paper. Considering the influence of stirrup spacing and load levels, a calculation equation for fatigue deflection was proposed. Finally, the fatigue design concept was improved, and the fatigue life was further subdivided into the fatigue life on bearing capacity and normal service.

Shear performance degradation of basalt fiber‐reinforced polymer bars in seawater environments: Coupled effects of seawater sea‐sand geopolymer mortar coatings and sustained loading

AbstractGeopolymers, as a promising substitute for ordinary cement, exhibit different coating effects with regard to the durability of basalt fiber‐reinforced polymer (BFRP) bars. In this study, a comparative investigation was carried out on the shear performance of prestressed BFRP bars coated with seawater sea‐sand geopolymer mortar (SSGM). The alkaline content of the SSGM was 4% or 6%. The prestress level was 20% of the ultimate tensile strength at room temperature. The immersion temperatures were room temperature (RT), 40, or 60°C. Interlaminar shear tests and transverse shear tests were conducted at each period (30, 60, 120, and 240 days). The results showed that BFRP bar coated with 6% alkaline content exhibited a slightly higher degradation of shear strength. Furthermore, the prestress developed microcracks in the bars and weakened the interface between the fiber and resin matrix, particular at the elevated temperature. This led to further degradation of the BFRP bars. Additionally, a comparison was made between the shear strength results of BFRP bars coated with SSGM and those coated with ordinary portland concrete or seawater sea‐sand concrete, revealing that the long‐term shear performance of BFRP bars was less negatively impacted by the SSGM coating.Highlights Coupled effects of SSGM coatings and sustained loading on the degradation of BFRP bars are investigated. SSGM provides better protection for BFRP bars than cement‐base concrete. Alkaline content of activator in SSGM has insignificant impact on the BFRP degradation.

Ensemble machine learning-based approach with genetic algorithm optimization for predicting bond strength and failure mode in concrete-GFRP mat anchorage interface

Glass fiber-reinforced polymer (GFRP) bar reinforced concrete structures are susceptible to bonding failure because of the low bond strength between GFRP bars and concrete. In this study, four tree-based machine learning models have been used to predict the flexural bond strength and failure mode of mat anchorage between concrete and sand-coated GFRP bars. Machine learning models are Decision Tree, Random Forest, AdaBoost, and XGBoost; except for Decision Tree, the models were inspired by collective learning. After applying these models to the dataset, the R2 score of the test scores for AdaBoost, Random Forest, XGBoost, and Decision Tree models were 0.91, 0.88, 0.90 and 0.88, respectively. Then, to improve the performance of these models, genetic algorithm was used to optimize the hyperparameters, XGBoost, Decision Tree, Random Forest, and AdaBoost which led to an increase in R2 score by 2, 3, 4, and 3 percent, respectively. Also, XGBoost classification model was used to predict the failure mode, and all the test data (70%) were correctly predicted. In the end, the SHapley value technique was used to determine each feature’s effect on the best machine learning model for predicting adhesion stress and the classifier model for predicting failure mode.

Behaviour of reinforced concrete corbels strengthened by FRP composites and steel bars: a critical review

In reinforced concrete (RC) structures, corbels that extend from the faces of reinforced concrete columns are commonly employed to support primary beams and girders. Frequently, the use of corbels is limited to cantilevers with a shear span-depth ratio that is often less than 2. Because of this relatively low ratio, corbel strength is normally dominated by shear, which is comparable to deep beams. However, owing to some reasons (e.g., design and/or construction faults, modification of facility use, deterioration, and aging), strengthening of existing corbels is becoming of prime importance. The aim of the present paper is to conduct a critical review of commonly proposed techniques that have been implemented to strengthen RC corbels. These techniques comprised near surface mounted (NSM) steel bars, NSM fibre reinforced polymer (FRP) bars, and FRP sheets. The latter strategy included carbon (CFRP) and glass (GFRP) sheets. Hybrid strengthening (combining FRP sheets and FRP/steel bars) was also highlighted in this paper. The strengthened (upgraded) RC corbels were evaluated considering several parameters, including shear span to depth ratio (a/d), quantity and configuration of reinforcement, FRP type, and levels of damage in the tested specimens.

Flexural–shear deformation theory (FSDT) for modeling of mechanical responses of RC beams strengthened in shear with ETS-FRP bars

The flexural–shear deformation theory (FSDT) approach for simulating the shear behavior of reinforced concrete (RC) beams strengthened in shear with embedded-through section fiber-reinforced polymer (ETS-FRP) bars is developed in this study. The key feature of the FSDT approach is to mix both flexural and shear deformation parameters constituted in the beam into an algorithm, which is able to simplify the analysis and shorten the computation time. Most of the formulations adopted in the model are built on the basis of mechanics by applying a few common theories involved in stress and strain fields. Particularly, to couple the participation of the ETS-FRP strengthening system into the developed FSDT, the newly developed bonding-based mechanism between the ETS-FRP bar and concrete is used. The calculation outcome produces the vertical strain (εv), which is the main parameter used to determine the resistance of shear reinforcement. The shear contribution of concrete is derived via the concrete principal tensile strain (ε1). Then, the minimized discrepancy between shear forces induced by flexural (VT) and shear actions (Vtotal) is the condition for termination of the calculation. Through the broad corroboration of the developed model to the experimental data with respect to structural responses, excellent agreement and high accuracy are found. To offer prospects for the design practice of ETS-strengthened beams, a parametric study on the effects of important design variables is implemented against the results assessed by a guideline released by the American Concrete Institute (ACI). Consequently, the proposed FSDT approach provides more insight into the responses of ETS-strengthened beams than the ACI guideline, which is helpful for practitioners.

Unconventional Use of Tracer Technology Provides Flow Insights for EOR, IOR

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 207431, “Advanced Research and Development in Unconventional Use of Tracer Technology for EOR and IOR: What Lies Beyond?” by Monalisa Chatterjee and Sean Toh, Tracerco, and Ahmed Alshmakhy, SPE, ADNOC, et al. The paper has not been peer reviewed. _ In recent decades, tracers have provided crucial insight into fluid-flow behavior in assessing reservoir connectivity. While advancements in versatility of tracer molecules have been published before in the literature, to the best of the authors’ knowledge, no work has been published to date that discusses the latest advances in unconventional uses of tracer molecules aiding enhanced oil recovery (EOR) and improved oil recovery (IOR) processes. This work is meant to address that gap by exploring four unconventional uses of tracers that hold significant potential. Microencapsulation of Solid Tracers: Enhancing Intelligent Tracers Previous research specified that factors affecting the current technology of solid tracers include physical space restrictions, temperature, tracer-loading capacity, initial surge, release of the tracer into fluid, and target-tracer concentrations. While the first two factors often are dictated by project conditions, advances in the other factors have been largely attributed to the tracer-polymer composition. For the tracers to be released in a controlled manner across a designated period, polymer structure plays a pivotal role in achieving longevity. The complete paper discusses a technique that is an application revolving around microencapsulation of chemical tracers in a solid shell before the addition of polymer material. Encapsulation vs. Microencapsulation. The encapsulation technique is a complex process involving selection of compatible molecular carriers, understanding their effects, and building the appropriate encapsulation (usually molecular encapsulation) to ensure that the capsules meet the desired outcome of each study. In this paper, an advanced subset of encapsulation—microencapsulation—is presented and its applications in inflow chemical tracing are discussed. Microencapsulation involves a particle, usually of micrometer dimensions, comprising a core material surrounded by a wall material significantly different from that of the core. The difference between them mainly arises from the morphology and the internal structure. The process allows the active ingredient to be protected from adverse external environmental conditions by the encapsulating coating agent. By applying the microencapsulation technique, the release profiles of tracers can be further controlled by changing the thickness, material, and morphology of the encapsulating agent. When applied onto tracers, this changes the tracer-release mechanism to a two-step, instead of the typical one-step, process. Oil tracers that generally are oleophilic will be released when in contact with oil; similarly, water tracers that are hydrophilic will be released when in contact with water. The tracers will remain dormant until the phase of interest encounters the polymer bars, and the two-step process allows the encapsulating agent to further improve the longevity of the tracers.

Deflection Control Methodologies for Curvilinear Concrete Members Reinforced with Glass Fiber-Reinforced Polymer Bars

Deflection Control Methodologies for Curvilinear Concrete Members Reinforced with Glass Fiber-Reinforced Polymer Bars

Tensile property analysis of carbon/glass hybrid fibers-reinforced graphene-modified polymer bars

The application of single-type fiber-reinforced polymer (single-FRP) bar in civil engineering is restricted due to the brittle failure and low tensile modulus. In this work, the carbon/glass hybrid fibers-reinforced polymer (C/G-HFRP) bars were designed to realize tensile ductility and improve tensile modulus. Also, graphene nanosheets (GNPs) were used to modify the fracture toughness of polymer matrix between fibers, which can resist the energy release rate during the failure of carbon fibers and the crack initiation and development inside the modified C/G-HFRP bars. The experimental results indicated that GNPs increased the cooperative ability between fibers and reduced the separation degree of glass fibers after the failure of carbon fibers. The tensile strength and strain of the modified C/G-HFRP bars at the initial failure of carbon fibers were averagely improved by 6.9% and 4.3% relative to those of the unmodified ones, while their ultimate tensile strength and strain were averagely increased by 7.1% and 7.1%, respectively. Meanwhile, four evaluation indicators were proposed to reflect the superior performance of the modified C/G-HFRP bars. Additionally, the experiments verified that the contribution of carbon fibers to the secondary stiffness at the strain hardening stage in the tensile stress–strain response of the modified C/G-HFRP bars can be omitted.

Prediction of shear behavior of glass FRP bars-reinforced ultra-highperformance concrete I-shaped beams using machine learning

This study focuses on using various machine learning (ML) models to evaluate the shear behaviors of ultra-high-performance concrete (UHPC) beams reinforced with glass fiber-reinforced polymer (GFRP) bars. The main objective of the study is to predict the shear strength of UHPC beams reinforced with GFRP bars using ML models. We use four different ML models: support vector machine (SVM), artificial neural network (ANN), random forest (R.F.), and extreme gradient boosting (XGBoost). The experimental database used in the study is acquired from various literature sources and comprises 54 test observations with 11 input features. These input features are likely parameters related to the composition, geometry, and properties of the UHPC beams and GFRP bars. To ensure the ML models' generalizability and scalability, random search methods are utilized to tune the hyperparameters of the algorithms. This tuning process helps improve the performance of the models when predicting the shear strength. The study uses the ACI318M-14 and Eurocode 2 standard building codes to predict the shear capacity behavior of GFRP bars-reinforced UHPC I-shaped beams. The ML models' predictions are compared to the results obtained from these building code standards. According to the findings, the XGBoost model demonstrates the highest predictive test performance among the investigated ML models. The study employs the SHAP (SHapley Additive exPlanations) analysis to assess the significance of each input parameter in the ML models' predictive capabilities. A Taylor diagram is used to statistically compare the accuracy of the ML models. This study concludes that ML models, particularly XGBoost, can effectively predict the shear capacity behavior of GFRP bars-reinforced UHPC I-shaped beams.

Bond behaviour between additional aluminium alloy ribs anchored CFRP bar and ultra-high ductile concrete

This study investigated the impact of incorporating additional aluminium ribs (ARs) on the bond behaviour of carbon fiber reinforced polymer (CFRP) bars in ultra-high ductile concrete (UHDC). The research conducted pull-out tests on 48 specimens with various parametric variables, including the number and location of ARs, the type of concrete material, and the depth of CFRP ribs. The outcomes revealed that the use of ARs significantly enhanced the bond performance of the CFRP bars in UHDC. The ultimate and residual bond strengths of both CFRP bars and AR anchored CFRP bars in UHDC surpassed those in ordinary concrete. The ARs also improved the rigidity of the bond-slip curve. Additionally, the bond performance of shallow-rib CFRP bars was substantially improved and comparable to that of deep-rib bars. The wave propagation method and wavelet packet analysis were employed to monitor the bond-slip process and to quantitatively analyze the degree of interface damage. The results suggested that increasing the extrusion length and number of ARs can improve the bond performance of the interface. Therefore, incorporating ARs can be considered as an effective approach to enhance the anchorage performance of FRP-reinforced concrete structures.

Experimental Study on the Bond Performance between Glass-Fiber-Reinforced Polymer (GFRP) Bars and Concrete

By investigating the bond performance between glass-fiber-reinforced polymer (GFRP) bars and concrete, GFRP bars can be better applied to concrete structures as a building material. This paper considered the effects of three different GFRP bar surface treatments, three bonding lengths, corrosive solution, and immersion time on the bonding strength. The test results indicated that the bond strength decreases with the increase in the diameter and bond length. The bonding between GFRP bars and concrete can be improved by treating the surface of the bars in different ways. Compared with the control group, the bond strength of the specimens in the saline solution decreased by 1.3–21.4%, and the bond strength of the specimens in the alkaline solution decreased by 26.5–38.8%. In the corrosive environment, the bond properties are degraded. A bond strength calculation formula considering the surface treatment method of the GFRP bars was proposed. The prediction formula of the bond strength retention rate between the GFRP bar and concrete in the corrosive environment was established. The formula was validated with the available research data and the calculated values agreed well with the test values. The MBPE model and CMR model are modified to establish the bond-slip model of the GFRP bars and concrete in the corrosive environment. The model curve is close to the test curve. This paper provides a theoretical basis for future research on the bond-slip performance of GFRP bars and concrete.

Enhancement of bond characteristics between sand-coated GFRP bar and normal weight and light-weight concrete using an innovative anchor

To prevent the concrete bar from slipping, a common approach is to ensure an adequate development length or bend it upwards. However, in the case of fiber reinforcement polymer (FRP) bars, on-site bending is not feasible. Therefore, employing a mechanical end-anchor offers an alternative solution to enhance the bond in reinforced concrete. This study investigates the influence of end-anchor shape on ribbed sand-coated glass fiber-reinforced polymer (GFRP) bars, utilizing four different types of mechanical end-anchors. Additionally, the effects of concrete type and compressive strength are evaluated by considering normal-weight concrete (NC) and light-weight concrete (LC) with compressive strengths ranging from 26 MPa to 38 MPa. The study involves the preparation and testing of 60 specimens using a direct pull-out test. The findings demonstrate that the utilization of the proposed mechanical end-anchors enhances the developed tensile stress of the GFRP bar by 10% to 50%, consequently significantly increasing the ultimate capacity of the reinforced concrete section. Furthermore, optimizing stress distribution and improving the bond behavior between the bar and concrete can be achieved by increasing the number of end-anchors and adjusting the distance between them, while maintaining the total length and diameter.

Size effect tests on shear strength of Basalt FRP-RC deep beams with different shear-span ratios

Basalt Fiber Reinforced Polymer (BFRP) bars appear effective in reducing corrosion-related damage and are gradually used as substitute for Steel bars in engineering practices. However, most of available efforts are focused on the size effect of BFRP-reinforced concrete (BFRP-RC) deep beams without web reinforcement, while less efforts have been studied on BFRP-RC deep beams with web reinforcement. Moreover, the quantitative influence of the shear-span ratio on the shear capacity of BFRP-RC deep beams is always in dispute. The purpose of the work is to investigate the quantitative influence of beam depth and shear-span ratio on the shear behavior of BFRP-RC deep beams with web reinforcement. A total of sixteen specimens were tested by considering the beam depth (i.e., 300 mm ∼ 1200 mm) and the shear-span ratio (i.e., 0.8, 1.3 and 1.8) as test variables. Twelve beams were reinforced with BFRP bars while the other four beams were reinforced with steel bars to act as controls. The corresponding size effect of BFRP-RC deep beams with web reinforcement was quantitatively studied, and the applicability of current design codes and scientific calculation methods were discussed. The results indicate that: 1) the increase of shear-span ratio reduces the nominal ultimate shear strength but has an ignorable influence on the size effect; 2) the nominal ultimate shear strength of BFRP-RC deep beams declinebyabout 46% as the beam depth increases from 300 mm to 1200 mm (both horizontal and vertical web reinforcement ratio are 0.51%); 3) the size effect of FRP-RC deep beams is not reasonably considered in current design codes, while, Jin’s theoretical model can scientificallyreflect the effect of beam depth and shear-span ratio on the nominal shear strength.

Predicting punching shear in RC interior flat slabs with steel and FRP reinforcements using Box-Cox and Yeo-Johnson transformations

This study presents a new approach for predicting the punching shear strength of reinforced concrete flat plates reinforced with steel and fiber-reinforced polymer (FRP) bars, using four machine learning regression models. A dataset of 505 interior flat plates from previous literature was used to develop the models. Input variables were transformed using Box-Cox and Yeo-Johnson transformations to improve predictive power by reducing white noise. The SHapley Additive exPlanations (SHAP) framework was utilized as the Explainable Artificial Intelligence (XAI) method to decipher model execution and feature the main info factors for anticipating the punching shear capacity. Additionally, design codes and equations from the literature are compared to the efficiency and accuracy of the power transformation featured XGBoost model. The findings demonstrate that the suggested prediction model performed very well and is appropriate for estimating the punching shear capacity of slab-column connections reinforced with steel and FRP bars. Moreover, the power transferred XGBoost model performed better than other numerical equations because it had the highest mean R2 (0.93) and lowest MAPE (0.20) for testing, which suggests that machine learning models may be able to offer an elective strategy to currently used mechanics-based models for configuration practice.

Research on the Bonding Performance of BFRP Bars with Reactive Powder Concrete

In recent years, replacing steel bars with basalt fiber-reinforced polymer (BFRP) bars and replacing ordinary concrete with reactive powder concrete (RPC) are considered effective solutions to the corrosion problem of steel bars in ordinary reinforced concrete structures. In order to study the bonding performance between BFRP bars and RPC, a total of 27 bonding specimens were tested by pull-out test. The effects of steel fiber volume content (0%, 1.5%, 2%), protective layer thickness (25 mm, 40 mm, 55 mm, 69 mm), and bond anchorage length of bars (3 d, 4 d, 5 d; d is the diameter of the bars) on the bond performance were studied. The experimental results indicated that the BFRP bar and reactive powder (RPC) concrete interface exhibited better bonding performance, and the steel fibers mixed in RPC can play the role of crack-blocking enhancement in the specimen, which improves the shear and tensile properties of the concrete, thus improving the bond strength between BFRP bar and RPC. Three failure modes were observed in the pull-out tests: BFRP bar shear failure, splitting failure, and concrete shear failure. The bond strengths of BFRP bars and RPC with 0%, 1.5%, and 2% steel fiber content were 24.2 MPa, 32.1 MPa, and 34.5 MPa, respectively. With the increase in bond anchorage length, the ultimate bond strength tended to increase first and then decrease. There may be an optimal bonding length between BFRP bar and reactive powder concrete, and when the optimal bonding length is exceeded, the bond strength decreases with the increase in bonding length. With the increase in the protective layer thickness, the improvement in the bond strength of the BFRP bar and RPC was not very significant.

Flexural behavior and bond coefficient of BFRP bar reinforced normal and high strength concrete beams

Basalt fiber-reinforced polymer (BFRP) bars are emerging as potential non-metallic reinforcements for concrete structures due to the wide availability of their raw materials, their environmentally friendly manufacturing process, and their excellent mechanical and durability properties. This paper focuses on the flexural and deflection response of normal and high-strength concrete (HSC) beams reinforced with BFRP bars. A total of fifteen simply supported concrete beams were tested under four-point loading on a flexural span of 2.5 m. The study parameters were the reinforcement ratio, BFRP bar size, concrete strength and bar type (BFRP, GFRP and Steel). The experimental results were compared to ACI 440.1R-15 predictions. The prediction of ultimate moment capacity was in good agreement with the experimental result, while the cracking moment was overestimated. Furthermore, the mid-span deflection was significantly underestimated at service and ultimate loads. Modification in the empirical equations was proposed to enhance the predictions of mid-span deflection at service load. The bond coefficient kb used for predicting the crack width was estimated at 0.89 and 1.12 for BFRP-reinforced normal and high-strength beams.

Three-fold benefits of using CO2 to cure seawater sea sand concrete

Excessive CO2 curing of concrete may significantly increase the risk of steel corrosion, which limits the application of this technology in reinforced concrete. Considering the substantial potential advantages of seawater sea sand concrete (SWSSC) structures reinforced by fiber reinforced polymer (FRP) bars in coastal infrastructure, FRP-SWSSC is proposed to capture CO2 by means of carbonation curing in this study. The effects of long-term CO2 curing on the compressive strength, pore structure, interfacial transition zone, CO2 uptake and pH of SWSSC were examined. It is found that CO2 curing can achieve an increase of approximately 25% in both 28-d and 56-d compressive strengths of SWSSC. Additionally, the porosity experiences a reduction of approximately 3%. The increased carbonation depth and higher CO2 uptake in CO2-cured SWSSC lead to significantly greater CO2 storage. Even after 28 days of additional water curing, the pH of CO2-cured SWSSC remains below 9, thus preventing any damage caused by the high pH environment to the mechanical properties and microstructure of embedded FRP bars. Therefore, CO2 curing of FRP-SWSSC offers three-fold great benefits: (1) improved SWSSC performance, (2) increased CO2 storage amount, and (3) reduced adverse effects of high alkaline concrete pore solution on embedded FRP bars.

Prediction model of long-term tensile strength of glass fiber reinforced polymer bars exposed to alkaline solution based on Bayesian optimized artificial neural network

The present study presents a model for predicting the long-term tensile strength of glass reinforced thermoset polymer (GFRP) bars based on the artificial neural network (ANN) algorithm, for bars which were exposed to alkaline solutions with different temperatures, different chloride ions concentration, and different applied stress levels. 272 groups of durability data of GFRP bars were collected from the literature. The correlation coefficients between each input feature and the target variable were calculated to analyze their relationships. The principal component analysis (PCA) method was performed to identify possible opportunities to reduce the input dimensions. Bayesian optimized search and randomized search were used and compared to tune and optimize the hyperparameters of the ANN model. Once the optimal ANN model was built, permutation feature importance, partial dependence plot (PDP), and SHapley Additive exPlanations (SHAP) value methods were used to interpret the optimal model. Results indicate that only the ultimate tensile strength has a high potential of being linearly changing with the long-term tensile strength of GFRP bars. PCA results show that the input dimensions cannot be reduced if 99% explained variance needs to be retained. The optimal ANN model trained through the Bayesian optimized search method can achieve a determination coefficient R2 and a mean absolute percentage error of 0.941 and 7.11%. Permutation feature importance and SHAP importance both ranked the initial ultimate tensile strength of GFRP bars as the most important input feature, followed by temperature, ageing time, diameter, applied stress level, pH value, and chloride ions concentration based on their SHAP values. On average, the PDP result of the ageing time tended to show that there will be a certain residual tensile strength of GFRP bars after ageing for a long period.

Beyond time: Enhancing corrosion resistance of geopolymer concrete and BFRP bars in seawater

To improve the durability of Basalt fiber reinforced polymer (BFRP) bars reinforced geopolymer concrete (GPC), it is important to study the time-dependent variation of the corrosion resistance ability of GPC and BFRP in a seawater environment. This paper presents an experimental investigation to study the time-dependent mechanical properties and durability of BFRP bars and geopolymer materials synthesized by granulated blast furnace slag (GGBFS), fly ash, and silica fume. The resulting GPC and Portland cement (PC) concrete were exposed to artificial seawater. The mechanical properties of GPC were evaluated by analyzing and comparing the volume expansion and strength loss rates of GPC and PC concrete in an artificial seawater environment. The corrosion resistance of geopolymer (GP) mortar and PC mortar was evaluated by studying the migration ability and pore structure in corrosive ions attack (Cl−, SO42−, Mg2+) in artificial seawater. Moreover, the time-dependent tensile strength of BFRP was comparatively investigated by immersing in different solutions (tap water, artificial seawater, and alkaline simulated seawater). In addition, the dual interface transition zones (ITZs) characteristics of BFRP reinforced GPC under artificial seawater were also investigated by SEM and BSE tests. The results showed that the volume expansion rate and strength loss rate of GPC decreased by 77.6% and 8.7%, respectively, after 360 days of seawater corrosion compared with PC concrete. This enabled the development of a time-dependent strength model of GPC in marine environments. The coefficient of ions diffusion in GP mortar is much lower than that of PC mortar, and GP mortar shows excellent resistance to ion migration. In addition, the effect of seawater corrosion on the tensile strength of BFRP bars increases with the increase of bars' diameter, and the ultimate strengths of BFRP bars with diameters of 6 mm and 8 mm were 695 MPa and 663 MPa, respectively. The tensile strength degradation model of BFRP bars in geopolymer concrete under seawater corrosion was established. After 360 days of seawater immersion, the average porosity of the ITZ between geopolymer and aggregates, and the average porosity of the ITZ between geopolymer and BFRP bars increased insignificantly compared to that of PC concrete. This research can provide a theoretical basis for the service life prediction of BFRP reinforced geopolymer concrete within marine environments.