The point load test (PLT) is a widely-used alternative method in the field to determine the uniaxial compressive strength due to its simple testing machine and procedure. The point load test index can estimate the uniaxial compressive strength through conversion factors based on the rock types. However, the mechanism correlating these two parameters and the influence of the mechanical properties on PLT results are still not well understood. This study proposed a theoretical model to understand the mechanism of PLT serving as an alternative to the UCS test based on laboratory observation and literature survey. This model found that the point load test is a self-confined compression test. There is a compressive ellipsoid near the loading axis, whose dilation forms a tensile ring that provides confinement on this ellipsoid. The peak load of a point load test is linearly positive correlated to the tensile strength and negatively correlated to the Poisson ratio. The model was then verified using numerical and experimental approaches. In numerical verification, the PLT discs were simulated using flat-joint BPM of PFC3D to model the force distribution, crack propagation and BPM properties' effect with calibrated micro-parameters from laboratory UCS test and point load test of Berea sandstones. It further verified the mechanism experimentally by conducting a uniaxial compressive test, Brazilian test, and point load test on four different rocks. The findings from this study can explain the mechanism and improve the understanding of point load in determining uniaxial compressive strength.
Seonhyeok Kim;Taegeon Kil;Sangmin Shin;Daeik Jang;H.N. Yoon;Jin-Ho Bae;Joonho Seo;Beomjoo Yang
Computers and Concrete
/
v.32
no.5
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pp.487-498
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2023
The present study investigated the flexural behavior of reinforced concrete (RC) beams strengthened with an ultrahigh performance concrete (UHPC) panel having various thicknesses. Two fabrication methods were introduced in this study; one was the direct casting of UHPC onto the bottom surface of the RC beams (I-series), and the other was the attachment of a prefabricated UHPC panel using an adhesive (E-series). UHPC panels having thicknesses of 10, 30, 50, and 70 mm were applied to RC beams, and these specimens were subjected to four-point loading to assess the effect of the UHPC thickness on the flexural strengthening of RC beams. The test results indicated that the peak strength and initial stiffness were vastly enhanced with an increase in the thickness of the UHPC panel, showing an improved energy dissipation capacity. In particular, the peak strength of the E-series specimens was higher than that of I-series specimens, showing high compatibility between the RC beam and the UHPC panel. The experimental test results were comparatively explored with a discussion of numerical analysis. Numerical analysis results showed that the predictions are in fair agreement with experimental results.
Engineered cementitious composites with calcined clay limestone cement (LC3-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC3-ECC compressive strength makes the prediction of LC3-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC3-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC3-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC3-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R2) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC3-ECC materials and further apply to such low-carbon, sustainable cement-based materials.
Reducing the self-weight of reinforced concrete structures problem is discussed in this paper by using two types of self-weight reduction, the first is by using lightweight coarse aggregate (crushed brick) and the second is by using styropor block. Experimental and Numerical studies are conducted on (LWAC) lightweight aggregate reinforced concrete slabs, having styropor blocks with various sizes of blocks and the ratio of shear span to the effective depth (a/d). The experimental part included testing eleven lightweight concrete one-way simply supported slabs, comprising three as reference slabs (solid slabs) and eight as styropor block slabs (SBS) with a total reduction in cross-sectional area of (43.3% and 49.7%) were considered. The holes were formed by placing styropor at the ineffective concrete zones in resisting the tensile stresses. The length, width, and thickness of specimen dimensions were 1.1 m, 0.6 m, and 0.12 m respectively, except one specimen had a depth of 85 mm (which has a cross-sectional area equal to styropor block slab with a weight reduction of 49.7%). Two shear spans to effective depth ratios (a/d) of (3.125) for load case (A) and (a/d) of (2) for load case (B), (two-line monotonic loads) are considered. The test results showed under loading cases A and B (using minimum shear reinforcement and the reduction in cross-sectional area of styropor block slab by 29.1%) caused an increase in strength capacity by 60.4% and 54.6 % compared to the lightweight reference slab. Also, the best percentage of reduction in cross-sectional area is found to be 49.7%. Numerically, the computer program named (ANSYS) was used to study the behavior of these reinforced concrete slabs by using the finite element method. The results show acceptable agreement with the experimental test results. The average difference between experimental and numerical results is found to be (11.06%) in ultimate strength and (5.33%) in ultimate deflection.
Researchers have embarked on an active investigation into the feasibility of adopting alternative materials as a solution to the mounting environmental and economic challenges associated with traditional concrete-based construction materials, such as reinforced concrete. The examination of concrete's mechanical properties using laboratory methods is a complex, time-consuming, and costly endeavor. Consequently, the need for models that can overcome these drawbacks is urgent. Fortunately, the ever-increasing availability of data has paved the way for the utilization of machine learning methods, which can provide powerful, efficient, and cost-effective models. This study aims to explore the potential of twelve machine learning algorithms in predicting the tensile strength of geopolymer concrete (GPC) under various curing conditions. To fulfill this objective, 221 datasets, comprising tensile strength test results of GPC with diverse mix ratios and curing conditions, were employed. Additionally, a number of unseen datasets were used to assess the overall performance of the machine learning models. Through a comprehensive analysis of statistical indices and a comparison of the models' behavior with laboratory tests, it was determined that nearly all the models exhibited satisfactory potential in estimating the tensile strength of GPC. Nevertheless, the artificial neural networks and support vector regression models demonstrated the highest robustness. Both the laboratory tests and machine learning outcomes revealed that GPC composed of 30% fly ash and 70% ground granulated blast slag, mixed with 14 mol of NaOH, and cured in an oven at 300°F for 28 days exhibited superior tensile strength.
Ilyas Aidyngaliyev;Dichuan Zhang;Robert Fleischman;Chang-Seon Shon;Jong Kim
Computers and Concrete
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v.33
no.2
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pp.195-204
/
2024
Floor inertial forces are transferred to lateral force resisting systems through a diaphragm action during earthquakes. The diaphragm action requires floor slabs to carry in-plane forces. In precast concrete diaphragms, these forces must be carried across the joints between precast floor units as they represent planes of weakness. Therefore, diaphragm reinforcement with sufficient strength and deformability is necessary to ensure the diaphragm action for the floor inertial force transfer. In a shake table test for a three-story precast concrete structure, an unexpected local failure in the diaphragm flexural reinforcement occurred. This failure caused loss of the diaphragm action but did not trigger collapse of the structure due to a possible alternative path for the floor inertial force transfer. This paper investigates this failure event and its impact on structural seismic responses based on the shake table test and simulation results. The simulations were conducted on a structural model with discrete diaphragm elements. The structural model was also validated from the test results. The investigation indicates that additional floor inertial force will be transferred into the gravity columns after loss of the diaphragm action which can further result in the increase of seismic demands in the gravity column and diaphragms in adjacent floors.
The purpose of this study is to propose new hysteretic characteristics of medium- to low-rise RC structures controlled by both shear and flexure. Through previous study, the dual lateral force-resisting system composed of shear and flexural failure members has a new failure mechanism that cooperates to enhance the flexural capacity of the flexural failure member even after the failure of the shear member, and the existing theoretical equation significantly underestimates the ultimate strength. In this study, the residual lateral strength mechanism of the dual lateral force-resisting system was analyzed, and, as a result, an equation for estimating the residual flexural strength of each shear-failure member was proposed. The residual flexural strength of each shear-failure member was verified in comparison with the structural testing results obtained in previous study, and the proposed residual flexural strength equation for shear-failure members was tested for reliability using FEA, and its applicable range was also determined. In addition, restoring-force characteristics for evaluating the seismic performance of the dual lateral force-resisting system (nonlinear dynamic analysis), reflecting the proposed residual flexural strength equation, were proposed. Finally, the validity of the restoring-force characteristics of RC buildings equipped with the dual lateral force-resisting system proposed in the present study was verified by performing pseudo-dynamic testing and nonlinear dynamic analysis based on the proposed restoring-force characteristics. Based on this comparative analysis, the applicability of the proposed restoring-force characteristics was verified.
In this paper, the non-linear behavior of masonry-infill and bare steel frames using different beam-column connections under monotonic static loading was investigated through a parametric study. Numerical models were carried out using one- and two-dimensional modelling to validate the experimental results. After validating the experimental results by using these models, a parametric study was carried out to model the behavior of these frames using flushed, extended, and welded connections. The results showed that using the welded or extended connection is more efficient than using the flushed type in masonry-infilled steel frames, since the lateral capacities, initial stiffness, and toughness have been increased by 155%, 601%, and 165%, respectively in the case of using welded connections compared with those used in bare frames. The FE investigation was broadened to study the influence of the variation of the uniaxial column loads on the lateral capacities of the bare/infill steel frames. As the results showed when increasing the amount of uniaxial loading on the columns, whether in tension or compression, causes the lateral load capacity of the columns to decrease by 26% for welded infilled steel frames. Finally, the influence of using different types of beam-to-column connections on the vertical capacities of the bare/infill steel frames under settlement effect was also studied. As a result, it was found that, the vertical load capacity of all types of frames and with using any type of connections is severely reduced, and this decrease may reach 62% for welded infilled frames. Furthermore, the flushed masonry-infilled steel frame has a higher resistance to the vertical loads than the flushed bare steel frame by 133%.
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.
Problems of under-sized dams (small dams with large basin area) could get worse under the global warming condition. This study evaluates the possible change of these problems with the Namgang Dam, an under-sized dam in Korea. For this purpose, first, this study simulates the dam inflow data using a rainfall-runoff model, which are then used as input for the reservoir operation. As a result, daily dam storage, dam release, and dam water supply are derived and compared for both past observed period (1973~2022) and future simulated period (2006~2099) based on the global warming scenarios. Summarizing the results are as follows. First, the inflow rate in the future is expected to be increased significantly. The maximum inflow could be twice of that observed in the past. As a result, it is also expected that the frequency of the water level reaching the high level is increasing. Also, the amount and frequency of dam release are to be increased in the future period. More seriously, this increase is expected to be concentrated on rather extreme cases with large dam release volume. Simply, the condition for flood protection in the downstream of the Namgang Dam is becoming worse and worse. Ironically, the severity of water shortage problem is also expected to become much worse. As the most extreme case, the frequency of no water supply was zero in the observed period, but in the future period, it becomes once every five years. Both the maximum consecutive shortage days and the total shortage volume are expected to become more than twice in the future period. To prevent or mitigate this coming problem of an under-sized dam, the only countermeasure at this moment seems to be its redevelopment. Simply a bigger dam with larger dam reservoir can handle this adverse effect more easily.
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