• 한국축산식품학회지
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• 제44권4호
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• pp.873-884
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• 2024

Flunixin is a veterinary nonsteroidal anti-inflammatory agent whose residues have been investigated in their original form within tissues such as muscle and liver. However, flunixin remains in milk as a metabolite, and 5-hydroxy flunixin has been used as the primary marker for its surveillance. This study aimed to develop a quantitative method for detecting flunixin and 5-hydroxy flunixin in milk and to strengthen the monitoring system by applying to other livestock and fishery products. Two different methods were compared, and the target compounds were extracted from milk using an organic solvent, purified with C₁₈, concentrated, and reconstituted using a methanol-based solvent. Following filtering, the final sample was analyzed using liquid chromatography-tandem mass spectrometry. Method 1 is environmentally friendly due to the low use of reagents and is based on a multi-residue, multi-class analysis method approved by the Ministry of Food and Drug Safety. The accuracy and precision of both methods were 84.6%-115% and 0.7%-9.3%, respectively. Owing to the low matrix effect in milk and its convenience, Method 1 was evaluated for other matrices (beef, chicken, egg, flatfish, and shrimp) and its recovery and coefficient of variation are sufficient according to the Codex criteria (CAC/GL 71-2009). The limits of detection and quantification were 2-8 and 5-27 ㎍/kg for flunixin and 2-10 and 6-33 ㎍/kg for 5-hydroxy flunixin, respectively. This study can be used as a monitoring method for a positive list system that regulates veterinary drug residues for all livestock and fisheries products.

• Computers and Concrete
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• 제33권4호
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• pp.399-407
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• 2024

This study nondestructively examined the evolution of crack density in ultra-high performance concrete (UHPC) upon cyclic loading. Uniaxial compression was repeatedly applied to the cylindrical specimens at levels corresponding to 32% and 53% of the maximum load-bearing capacity, each at a steady strain rate. At each stage, both P-wave and S-wave velocities were measured in the absence of the applied load. In particular, the continuous monitoring of P-wave velocity from the first loading prior to the second loading allowed real-time observation of the strengthening effect during loading and the recovery effect afterwards. Increasing the number of cycles resulted in the reduction of both elastic wave velocities and Young's modulus, along with a slight rise in Poisson's ratio in both tested cases. The computed crack density showed a monotonically increasing trend with repeated loading, more significant at 53% than at 32% loading. Furthermore, the spatial distribution of the crack density along the height was achieved, validating the directional dependency of microcracking development. This study demonstrated the capability of the crack density to capture the evolution of microcracks in UHPC under cyclic loading condition, as an early-stage damage indicator.

• Computers and Concrete
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• 제33권4호
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• pp.341-348
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• 2024

Ultra-high-performance concrete (UHPC) has received remarkable attentions in civil infrastructure due to its unique mechanical characteristics and durability. UHPC gains increasingly dominant in essential structural elements, while its unique properties pose challenges for traditional inspection methods, as damage may not always manifest visibly on the surface. As such, the need for robust inspection techniques for detecting cracks in UHPC members has become imperative as traditional methods often fall short in providing comprehensive and timely evaluations. In the era of artificial intelligence, computer vision has gained considerable interest as a powerful tool to enhance infrastructure condition assessment with image and video data collected from sensors, cameras, and unmanned aerial vehicles. This paper presents a computer vision-based approach employing deep learning to detect cracks in UHPC beams, with the aim of addressing the inherent limitations of traditional inspection methods. This work leverages computer vision to discern intricate patterns and anomalies. Particularly, a convolutional neural network architecture employing transfer learning is adopted to identify the presence of cracks in the beams. The proposed approach is evaluated with image data collected from full-scale experiments conducted on UHPC beams subjected to flexural and shear loadings. The results of this study indicate the applicability of computer vision and deep learning as intelligent methods to detect major and minor cracks and recognize various damage mechanisms in UHPC members with better efficiency compared to conventional monitoring methods. Findings from this work pave the way for the development of autonomous infrastructure health monitoring and condition assessment, ensuring early detection in response to evolving structural challenges. By leveraging computer vision, this paper contributes to usher in a new era of effectiveness in autonomous crack detection, enhancing the resilience and sustainability of UHPC civil infrastructure.

• Computers and Concrete
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• 제33권4호
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• pp.425-443
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• 2024

Floods are among the most common natural hazards in urban areas. To mitigate the problems caused by flooding, unstructured data such as images and videos collected from closed circuit televisions (CCTVs) or unmanned aerial vehicles (UAVs) have been examined for flood management (FM). Many computer vision (CV) techniques have been widely adopted to analyze imagery data. Although some papers have reviewed recent CV approaches that utilize UAV images or remote sensing data, less effort has been devoted to studies that have focused on CCTV data. In addition, few studies have distinguished between the main research objectives of CV techniques (e.g., flood depth and flooded area) for a comprehensive understanding of the current status and trends of CV applications for each FM research topic. Thus, this paper provides a comprehensive review of the literature that proposes CV techniques for aspects of FM using ground camera (e.g., CCTV) data. Research topics are classified into four categories: flood depth, flood detection, flooded area, and surface water velocity. These application areas are subdivided into three types: urban, river and stream, and experimental. The adopted CV techniques are summarized for each research topic and application area. The primary goal of this review is to provide guidance for researchers who plan to design a CV model for specific purposes such as flood-depth estimation. Researchers should be able to draw on this review to construct an appropriate CV model for any FM purpose.

• Computers and Concrete
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• 제33권6호
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• pp.689-706
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• 2024

This study is aimed at identifying structural element stiffness influence on vertical earthquake response of mid-rise R/C frame buildings. To this aim, a mid-rise RC building structure is designed as per the new Turkish Seismic Code for Buildings-2018, and 3D FE model of the building is established. Based on the established FE model, a total number of six buildings are considered depending on certain percentage increase in beam, slab, and column. The time-history response analyses (THA) are performed separately for only horizontal (H) and horizontal +vertical (H+V) earthquake motions to make a comparison between the load cases. The analysis results are presented comparatively in terms of the monitoring parameters of the base overturning moment (M_o), the top-story lateral displacement (d_L) and the top-story vertical displacement (d_V). The obtained results reveal that the base overturning moment and the top-story vertical displacement are affected by vertical earthquake motion regardless of the increase in the dimension of beam, slab, and column. However, vertical earthquake motion is not effective on the top-story lateral displacement due to no change between H and H+V load. The dimensional increase in either slab or beam leads to a considerable increase in the base overturning moment and the top-story vertical displacement while causing decrease in the top-story lateral displacement. In addition, the dimensional increase in column has a positive effect on the decrease in the monitoring parameters of the base overturning moment (M_o), the top-story lateral displacement (d_L) and the top-story vertical displacement (d_V).

• Computers and Concrete
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• 제33권6호
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• pp.707-724
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• 2024

This paper proposes a study of cement replacement with rice husk ash (RHA) and eggshell ash (ESA) for enhanced mechanical properties of geopolymer (GP) concrete with and without admixture. The main objective is to investigate the mechanical properties of GP with various replacement levels of Pozzolana Portland cement by RHA and ESA. The GP resistance to durability is examined and impact of ash materials on concrete's durability performance is determined. The environmental benefits of using agricultural waste materials in GP manufacturing minimize cement usage and CO2 emissions. The goal is to assess value of RHA-ESA of building material, paving stones for structures to lessen environmental impact. The novelty lies in use of ESA and RHA as partial replacements for cement and investigation of admixtures to enhance concrete properties, and reduce environmental impact. The research contributes by introducing a novel approach to reducing cement consumption by using ESA and RHA to address environmental concerns. It also explores the potential benefits of admixtures improving concrete performance and reducing environmental pollution. A study is carried with and without impacts of admixture to find compressive strength of GP cubes. The cement has been replaced by RHA and ESA in the range of (2.5%+7.5%, 5%+5%, 7.5%+2.5) by weight of cement for M20 mix. The compressive strength (CS) and split tensile strength (STS) at 7days, 14 days and 28 days is obtained as 21 N/mm2 at 7.5%RHA+2.5%ESA and 2.3 at 7.5%RHA+2.5%ESA, 24 N/mm2 at 7.5%RHA+2.5%ESA and 2.3 at 7.5%RHA+2.5%ESA, 28 N/mm2 at 7.5%RHA+2.5%ESA and 2.8 at 7.5%ESA respectively with normal curing condition.

• Computers and Concrete
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• 제34권1호
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• pp.93-122
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• 2024

One well-known reason for using Fiber Reinforced Polymer (FRP) composites is to improve concrete strength and strain capacity via external confinement. Hence, various studies have been undertaken to offer a good illustration of the response of FRP-wrapped concrete for practical design intents. However, in such studies, the strength and strain of the confined concrete were predicted using regression analysis based on a limited number of test data. This study presents an approach based on artificial neural networks (ANNs) to develop models to predict the strength and strain at maximum stress enhancement of circular concrete cross-sections confined with different FRP types (Carbone, Glass, Aramid). To achieve this goal, a large test database comprising 493 axial compression experiments on FRP-confined concrete samples was compiled based on an extensive review of the published literature and used to validate the predicted artificial intelligence techniques. The ANN approach is currently thought to be the preferred learning technique because of its strong prediction effectiveness, interpretability, adaptability, and generalization. The accuracy of the developed ANN model for predicting the behavior of FRP-confined concrete is commensurate with the experimental database compiled from published literature. Statistical measures values, which indicate a better fit, were observed in all of the ANN models. Therefore, compared to existing models, it should be highlighted that the newly developed models based on FRP type are remarkably accurate.

• Computers and Concrete
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• 제34권1호
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• pp.1-14
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• 2024

The design of disturbed regions in reinforced concrete structures usually applies the well known Strut and Tie Method (STM). As an alternative, the Stringer-Panel Method (SPM), an intermediate model between STM and the Finite Element Method (FEM), consists in dividing a structure into two distinct elements: the stringers (which carry axial forces) and panels (which carry shear forces). SPM has already showed good applicability in manual calculations and computer implementations, and its most known application was SPanCAD, an AutoCAD plugin for linear and nonlinear analysis by SPM. Unfortunately, SPanCAD was discontinued by the developers, and it's not compatible with the most recent versions of AutoCAD. So, this paper aims to present a computer program that was developed as an upgrade to the latter: the Stringer Panel Modelling Tool (SPMTool), which is intended to be an auxiliary design tool and it presents improvements, in comparison to SPanCAD. It is possible to execute linear and nonlinear analysis by three distinct formulations: Modified Compression Field Theory (MCFT), Disturbed Stress Field Model (DSFM) and Softened Membrane Model (SMM). The nonlinear results were compared to experimental data of reinforced concrete elements that were not designed by SPM; these elements were also analyzed in SPanCAD. On overall, SPMTool made more realistic predictions to the behavior of the analyzed structures than SPanCAD. Except for DSFM predictions for corbels (1.24), in overall average, the ultimate load predictions were conservative (0.85 to 0.98), which is a good aspect for a design tool. On the other hand, the cracking load predictions presented overestimations (1.06 to 1.47) and higher variations (25.59% to 34.25%) and the post-cracking behavior could not be accurately predicted; for this use case, a more robust finite element software is recommended.

• Computers and Concrete
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• 제34권1호
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• pp.33-48
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• 2024

This paper presents the detailed experimental and analytical investigation on the evolution of static (E_s) and dynamic modulus of elasticity (E_d) of concrete having 0%, 35%, and 50% FA used as partial cement replacement. Destructive and non-destructive tests were conducted on cylindrical specimens to evaluate the compressive strength and MoE of concrete in compression at the age of 28, 56, 90, and 150 days for all mixes. Experimental results show that the concrete having 35% FA achieved compressive strength and MoE similar to plain concrete at the age of 90 days, while 50% FA concrete attained satisfactory compressive strength and MoE at the age of 150 days. The comprehensive statistical analysis has been carried out in two ways on the basis of the experimental results. Firstly, the 28-day crushing strength of plain concrete in compression was used to design the models for the prediction of E_s and E_d of fly ash concrete at any age and percentage replacement of FA. Secondly, using the values of UPV and RHN, models have been developed to predict the age or time-dependent E_s and E_d of fly ash concrete. These models will be helpful in assessing the E_s and E_d of fly ash concrete without knowing the 28-day crushing strength of plain concrete in compression in the laboratory. Hence, the suggested models in the present study will be beneficial in conducting the health assessment of fly ash based concrete structures.

• Computers and Concrete
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• 제34권4호
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• pp.379-391
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• 2024

The ultra-high performance concrete (UHPC) mixed with hybrid fibers has excellent mechanical properties and durability, and the hybrid fibers have a certain impact on the bearing capacity, deformation capacity, and crack propagation of beams. Many scholars have conducted a series of studies on the bending performance of prestressed UHPC beams, but there are few studies on prestressed UHPC beams mixed with hybrid fibers. In this study, five bonded post-tensioned partially prestressed UHPC beams mixed with steel fibers and macro-polyolefin fibers were poured and subjected to four-points symmetric loading bending tests. The effects of different prestressing degrees and prestressing levels on the load-deflection curves, crack propagation, failure modes and ultimate bearing capacity of beams were discussed. The results showed that flexural failure occurred in the prestressed UHPC beams with hybrid fibers, and the integrity of specimens was good. When the prestressing degree was the same, the higher the prestressing level, the better the crack resistance capacity of UHPC beams; When the prestressing level was 90%, increasing the prestressing degree was beneficial to improve the crack resistance and ultimate bearing capacity of UHPC beams. When the prestressing degree increased from 0.41 to 0.59, the cracking load and ultimate load increased by 66.0% and 41.4%, respectively, but the ductility decreased by 61.2%. Based on the plane section assumption and considering the bridging effect of short fibers, the cracking moment and ultimate bearing moment were calculated, with good agreement between the test and calculated values.