Classifying concrete defects during a bridge inspection remains a subjective and laborious task. The risk of getting a false result is approximately 50% if different inspectors assess the same ...concrete defect. This is significant in the light of an over-aging bridge stock, decreasing infrastructure maintenance budgets and catastrophic bridge collapses as happened in 2018 in Genoa, Italy. To support an automated inspection and an objective bridge defect classification, we propose a three-staged concrete defect classifier that can multi-classify potentially unhealthy bridge areas into their specific defect type in conformity with existing bridge inspection guidelines. Three separate deep neural pre-trained networks are fine-tuned based on a multi-source dataset consisting of self-collected image samples plus several Departments of Transportation inspection databases. We show that this approach can reliably classify multiple defect types with an average mean score of 85%. Our presented multi-classifier is a contribution towards developing a mostly or fully inspection schema for a more cost-effective and more objective bridge inspection.
•The presented method can automatically multi-classify concrete bridge defects on image patches in accordance with existing inspection guidelines.•The cross-learning strategy of using a pre-trained network and refine this to domain-specific knowledge can be successfully applied for concrete bridge surface defects.•The multi-classifier can adapt to local variations and consider possible (and impossible) defect combinations.
In the current investigation is presented the prospective substitution of cement and fine aggregates with fine slag material (Alccofine 1203) and coal bottom ash, respectively. The investigation was ...carried out in two steps, viz. Phase I and Phase II. In Phase I, a control mix was designed with basic ingredients of concrete, and then fine aggregates were partially replaced with five percentages (10%, 20%, 30%, 40% and 50%) of coal bottom ash (CBA). To improve the characteristics of coal bottom ash concrete mixtures, ultra-fine slag material, i.e., Alccofine 1203 (an innovative ultra-fine slag material, low calcium silicate, which offers reduced water demand depending upon the concrete performance) was used as a partial replacement of cement. In Phase II, the inspected effect of replacing 5%, 10%, 15% and 20% cement with Alccofine, a concrete mix containing 40% coal bottom ash, on concrete properties such as workability, compressive strength, split tensile strength, flexural strength, pulse velocity, rapid chloride penetration along with a microstructural analysis using SEM was studied. It was concluded from cost analysis that the 15% replacement of cement with ultra-fine material Alccofine in 40% coal bottom ash concrete achieved the properties of high-strength concrete, with an 8.14% increase in cost compared to the control increase. The significance of this work lies in the fact that we achieved a high-strength concrete by using 40% industrial waste, i.e., coal bottom ash, as a partial replacement of fine aggregates in combination with the 15% Alccofine inclusion as a partial replacement of cement. About 58% improvement in compressive strength was recorded for 40% coal bottom ash and 15% Alccofine mix.
This work presents the numerical application of the diffuse cohesive interface model introduced in the Part I paper to the failure analysis of plain and reinforced concrete structures, subjected to ...complex loading conditions, inducing mixed‐mode fracture initiation and propagation. With the aim of capturing the interaction between concrete and steel reinforcements, the adopted fracture model is incorporated in a novel, more general numerical framework for the nonlinear analysis of reinforced concrete structures. Such a framework includes a newly proposed embedded truss model for the reinforcing bars, allowing them to be crossed by the neighboring propagating cracks. Comparisons with available experimental results are provided, assessing the reliability and the numerical accuracy of the proposed concrete model, with reference to plain specimens subjected to single‐crack propagation as well as to reinforced elements subjected to multiple cracking.
Highlights
An integrated fracture model is proposed to simulate failure in concrete structures
Interaction between cracks and rebars is accounted for via an embedded truss model
Mesh dependency and mode‐II cohesive parameter sensitivity issues are investigated
Comparisons with experiments assess the reliable application to RC structures
This article discusses the utilization of palm oil fuel ash (POFA) in normal and geopolymer concrete. Malaysia, one of the world's largest producers of palm oil, produces more than 10Mt/year of palm ...waste as ash, which is called POFA. Since 1989, extensive research has been conducted on its utilization in concrete. Several published studies have noted POFA's enormous potential as a partial replacement of cement in concrete. This paper describes the effects of using POFA on different fresh and hardened properties of concrete. The latest studies on the use of ground POFA revealed that concrete made from this material possesses better fresh properties and medium to higher strength than ordinary Portland cement (OPC) concrete. One of the major findings is that concrete that incorporates 20% fine POFA by weight of cement showed better durability properties than OPC concrete. Because limiting CO2 emissions has become a matter of increasing importance in the construction industry, concrete that uses less cement in its production and utilizes an increased amount of waste, such as POFA, offers an environmentally viable solution. Moreover, 100% cement-free geopolymer concrete can be produced using blended ash, such as POFA and fly ash.
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•Increasing the fineness of palm oil fuel ash (POFA) as partial replacement of ordinary Portland cement (OPC) considerably improves the flexural and tensile strengths of concrete.•Increasing ultrafine POFA up to 40 wt.% leads to significant increase (14%) of compressive strength of POFA concrete compared to OPC concrete.•Concrete containing 20% fine POFA exhibited lower water permeability and higher resistance to chloride and sulphate attack than OPC concrete.•Geopolymer concrete containing blended fly ash:POFA (70:30) by mass resulted in similar compressive strength (25MPa) to OPC concrete after 28days.
This article presents the results of fatigue testing and assessment of the mechanical and physical properties of the concrete pavement of the A6 motorway, which was put in service in 1938. After 82 ...years of operation under heavy traffic loading conditions, the pavement was fully recycled by crushing of the existing concrete and reuse of the reclaimed material in the new courses of pavement placed as part of the motorway renewal project. The main objective of this research was to determine the properties of the tested concrete, including compressive strength, water absorption and freeze-thaw resistance after 150 cycles of alternate freezing and thawing. The resistance of the concrete to the action of de-icing products was also checked. The article also presents the results of petrographic analysis of the aggregates. Additionally, concrete sampled from the pavement was evaluated for freeze-thaw resistance in relation to the determined porosity characteristics. The tested concrete, which was subjected to over 80 years of traffic loading on the A6 motorway, was found to meet the highest requirements as currently applied for the extra heavy-duty pavements. With a compressive strength value in excess of 50 MPa, the tested concrete can be rated at least CC40, according to EN 13877-2:2013-08. The samples were found to satisfy the freeze-thaw resistance requirements of an F150 rating. The air void analysis showed that the analyzed concrete contained 1.6% of micropores, i.e., air voids smaller than 300 μm (A
). The spacing factor, in turn, was below 0.200 mm (
= 0.185 mm). The example of the A6 motorway renewal project served to demonstrate that reclaimed concrete aggregate, obtained by crushing the entire pavement, can be used for production of the new pavement courses.
•The load-deformation behaviors of HGSC are tested under monotonic and repeated loads.•The effect of rebar diameter, as well as the spliced length of rebar in the sleeve is discussed.•The bond-slip ...mechanism of spliced rebar in sleeve is revealed with pre-installed gauges.•The equivalent stress-strain models are proposed and preliminarily verified for HGSC under monotonic and repeated loads.
The half grouted sleeve connection (HGSC) is widely adopted in the construction of precast concrete (PC) structures. So far, a few studies have been developed on the mechanical behavior of HGSC, however, efficient load-deformation models of HGSC are still scarce, which limits the numerical analysis of PC structures. In this study, therefore, an experimental study is undertaken to propose equivalent stress-strain models of HGSC under monotonic and repeated loads. The effect of rebar diameter, as well as the spliced length of rebar in the sleeve on the load-deformation behavior of HGSC is investigated with 60 specimens. Based on the test results, the failure mode, load capacity and strain of the spliced rebar is discussed. The results show that the failure mode of HGSC is mainly related to the spliced length of rebar. The capacity of HGSC is affected by the failure mode rather than the loading type. Moreover, a non-uniform distribution of bond stress of the spliced rebar is observed from the measured strains in the rebar. Finally, equivalent stress-strain models are proposed for the HGSC under monotonic and repeated loads. The model is established by revising the bi-linear stress-strain model of bare rebar, thus can be applied in the numerical study of PC members with high computational efficiency. The parameters of the models are calibrated with the test data obtained in the current study. A numerical simulation of a PC column with HGSC is developed to preliminarily verify the proposed model. The results show that the prediction of member deformation can be greatly improved by using the proposed model.
3D concrete printing has tremendous potential for construction manufacturing; however, weak interface bonding between adjacent layers remains a well-known issue that affects the mechanical properties ...of printed structures. The layers introduce anisotropy and reduce the capacity to resist tensile and shear loads. Reinforcements, inserted perpendicular to the printed layers to traverse the interfaces, can improve these limitations, but the insertion of reinforcements is difficult to achieve in practice, and there are few published studies exploring appropriate methods. This study presents a promising approach using U-shaped nails inserted into concrete during the printing process. The bridging effect and dowel action of the applied U-nails are visualised and analysed to elucidate the toughness improvement. The ultimate tensile strength and shear strength of 3D printed concrete are significantly increased by 145.0% and 220.0%, respectively. U-nails with a filament thickness of 2–2.5 mm are recommended to yield optimal improvement in the interlayer strength.
•An in-process interlayer reinforcement approach for 3D concrete printing was proposed through the concurrent deposition of U-nails.•Significant strength and toughness improvement was achieved for U-nail reinforced 3D-printed concrete.•The bridge linking effect and dowel action of U-nails were analysed.•Response surface method were utilised to quantify the effects of U-nails on the interlayer bonding behaviour.
In this paper, an extensive simulation program is conducted to find out the optimal ANN model to predict the shear strength of fiber-reinforced polymer (FRP) concrete beams containing both flexural ...and shear reinforcements. For acquiring this purpose, an experimental database containing 125 samples is collected from the literature and used to find the best architecture of ANN. In this database, the input variables consist of 9 inputs, such as the ratio of the beam width, the effective depth, the shear span to the effective depth, the compressive strength of concrete, the longitudinal FRP reinforcement ratio, the modulus of elasticity of longitudinal FRP reinforcement, the FRP shear reinforcement ratio, the tensile strength of FRP shear reinforcement, the modulus of elasticity of FRP shear reinforcement. Thereafter, the selection of the appropriate architecture of ANN model is performed and evaluated by common statistical measurements. The results show that the optimal ANN model is a highly efficient predictor of the shear strength of FRP concrete beams with a maximum R2 value of 0.9634 on the training part and an R2 of 0.9577 on the testing part, using the best architecture. In addition, a sensitivity analysis using the optimal ANN model over 500 Monte Carlo simulations is performed to interpret the influence of reinforcement type on the stability and accuracy of ANN model in predicting shear strength. The results of this investigation could facilitate and enhance the use of ANN model in different real-world problems in the field of civil engineering.
•The seismic behavior of concrete slender columns was investigated.•The main parameters include stirrup space, concrete strength and axial load ratio.•The yield, maximum and failure points obtained ...from ABAQUS analysis were shown.•Parameter analysis on deformation and load at different service states was conducted.
To investigate the influence of longitudinal reinforcement strength grade, stirrup spacing, concrete strength and axial load ratio (ALR) on seismic behavior of high-strength concrete (HSC) columns, seven full-scale square HSC columns reinforced with high-strength steel bars (HSSB) with nominal yield strength of 600 MPa or conventional steel bars were tested under constant axial load and cyclic lateral load. Furthermore, corresponding nonlinear finite element analysis was conducted in ABAQUS. The column top deformation and lateral load at different service states, stiffness degradation, bearing capacity degradation and strain of longitudinal and transverse reinforcement were discussed. The test result shows that using steel bars with nominal yield strength of 400 MPa as stirrup is a better choice for HSC columns and ALR is an important factor which determines whether the high-strength longitudinal reinforcement can reach its compressive or tensile yield strain before maximum point. Taking HSSB as longitudinal reinforcement (equivalent volume replacement) greatly improves the seismic behavior of HSC columns. After taking the influence of strain gradient on stress-strain relationship of compressive concrete into consideration, a confined strain gradient model (CSGM) which was suitable for finite element analysis (FEA) was established based on the model established by Razvi and Saatcioglu. Specific verification of finite element model (FEM) on deformation and lateral load at different service states were presented for further parameter analysis. The trend of displacement ductility factor were investigated in detail in numerical analysis part. With proper ALR and stirrup characteristic value, HSC columns reinforced with HSSB is able to present a displacement ductility of higher than 4, which is capable to meet the ductility demand of most codes.
Effective damage identification is paramount to evaluating safety conditions and preventing catastrophic failures of concrete structures. Although various methods have been introduced in the ...literature, developing robust and reliable structural health monitoring (SHM) procedures remains an open research challenge. This study proposes a new approach utilizing a 1-D convolution neural network to identify the formation of cracks from the raw electromechanical impedance (EMI) signature of externally bonded piezoelectric lead zirconate titanate (PZT) transducers. Externally bonded PZT transducers were used to determine the EMI signature of fiber-reinforced concrete specimens subjected to monotonous and repeatable compression loading. A leave-one-specimen-out cross-validation scenario was adopted for the proposed SHM approach for a stricter and more realistic validation procedure. The experimental study and the obtained results clearly demonstrate the capacity of the introduced approach to provide autonomous and reliable damage identification in a PZT-enabled SHM system, with a mean accuracy of 95.24% and a standard deviation of 5.64%.
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