• Journal of the Korea Concrete Institute
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• v.17 no.6 s.90
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• pp.1075-1084
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• 2005

The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network(PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Improved probabilistic neural network was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment (DDA) algorithm. The conventional PNN and the PNN with DDA algorithm(IPNN) were applied to predict the compressive strength of concrete using actual test data of two concrete companies. IPNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

• Structural Engineering and Mechanics
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• v.91 no.6
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• pp.583-589
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• 2024

Accurately predicting the strength of concrete is vital for ensuring the safety and durability of structures, thereby contributing to time and cost savings throughout the design and construction phases. The compressive strength of concrete is determined by various material factors, including the type of cement, composition ratios of concrete mixtures, curing time, and environmental conditions. While mix design establishes the proportions of each material for concrete, predicting strength before experimental measurement remains a challenging task. In this study, Abrams's law was chosen as a representative investigative approach to estimating concrete compressive strength. Abrams asserted that concrete compressive strength depends solely on the water-cement ratio and proposed a logarithmic linear relationship. However, Abrams's law is only applicable to concrete using cement as the sole binding material and may not be suitable for modern concrete mixtures. Therefore, this research aims to predict concrete compressive strength by applying various conventional regression analyses and machine learning methods. Six models were selected based on performance experiment data collected from various literature sources on different concrete mixtures. The models were assessed using Root Mean Squared Error (RMSE) and coefficient of determination (R²) to identify the optimal model.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.3
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• pp.40-47
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• 2021

This study investigates the influence of hooked-end steel fiber volume fraction and aspect ratio on the mechanical properties, such as compressive and flexural performance, of concrete with specified compressive strength of 30MPa. Three types of hooked-end steel fibers with aspect ratios of 64, 67 and 80 were selected. The flexural tests of steel fiber reinforced concrete (SFRC) prismatic specimens were conducted according to EN 14651. The compressive performance of SFRC with different volume fractions (0.25, 0.50 and 0.75%) were evaluated through standard compressive strength test method (KS F 2405). Experimental results indicated that the flexural strength, flexural toughness, fracture energy of concrete were improved as steel fiber volume fraction increases but there is no unique relationship between steel fiber volume fraction and compressive performance. The flexural and compressive properties of concrete incorporating hooked-end steel fiber with aspect ratio of 64 and 80 are a little better than those of SFRC with aspect ratio of 67. For each SFRC mixture used in the study, the residual flexural tensile strength ratio defined in Model Code 2010 was more than the limit value to be able to substitute rebar or welded mesh in structural members with the fiber reinforcement.

• Smart Structures and Systems
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• v.20 no.1
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• pp.35-42
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• 2017

Recently, compressive sensing based data loss recovery techniques have become popular for Structural Health Monitoring (SHM) applications. These techniques involve an encoding process which is onerous to sensor node because of random sensing matrices used in compressive sensing. In this paper, we are presenting a model where the sampled raw acceleration data is directly transmitted to base station/receiver without performing any type of encoding at transmitter. The received incomplete acceleration data after data losses can be reconstructed faithfully using compressive sensing based reconstruction techniques. An in-depth simulated analysis is presented on how random losses and continuous losses affects the reconstruction of acceleration signals (obtained from a real bridge). Along with performance analysis for different simulated data losses (from 10 to 50%), advantages of performing interleaving before transmission are also presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1024-1031
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• 2015

Compressive sensing is a new data acquisition method enabling the reconstruction of sparse or compressible signals from a smaller number of measurements than Nyquist rate, as long as the signal is sparse and the measurement is incoherent. In this paper, we consider a simple hypothesis testing in target detection and estimation problems using compressive sensing, where the performance depends on the sparsity level of the signals being detected. We provide theoretical analysis results along with some experiment results.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.1
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• pp.19-27
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• 2014

Compressive sensing is an emerging sampling technique which enables sampling a signal at a much lower rate than the Nyquist rate. In this paper, we propose a novel framework based on Kronecker compressive sensing that provides multi-resolution image reconstruction capability. By exploiting the relationship of the sensing matrices between low and high resolution images, the proposed method can reconstruct both high and low resolution images from a single measurement vector. Furthermore, post-processing using BM3D improves its recovery performance. The experimental results showed that the proposed scheme provides significant gains over the conventional framework with respect to the objective and subjective qualities.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.04a
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• pp.375-380
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• 2000

Experimental and numerical studies were done to investigate seismic performance of slender sheat wall with no boundary confinement. 1/3 scale-specimens that model the plastic region of long slender shear walls subjected to combined axial load and bending moment were rested to investigate strength, ductility, capacity of energy dissipation and strain distribution. The experimental results show that the slender walls fail due to early crushing in the compressive boundary, and then have very low ductility. The measured maximum compressive strain is 0.0021, which is much less then 0.004 being commonly used for estimation of ductility. The experimental results indicates that the maximum compressive strain is not a fixed value but is affected by moment gradient along the shear wall height and distance from neutral axis to the extreme compressive fiber.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.54-55
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• 2018

Reinforced concrete is a building material that is generally used in modern society. Securing the performance of reinforced concrete is directly connected to the durability and longevity of the building. One of the major factors that deteriorate the durability of concrete is harmful ion. Recently, the quality and improvement method of reinforced concrete for penetration of harmful ion has been studied. In this study, the bead type ion exchange resin is substituted for 0%, 3%, and 6% of the fine aggregate volume in the mortar. The speciments underwent underwater curing and were checked for compressive strengths of 3 days and 28 days. From the results of compressive strength, it can be seen that the higher the substitution ratio of the ion exchange resin, the lower the early strength and long-term strength development, especially the early strength development.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.953-956
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• 2008

The purpose of this study is to ascertain the void ratio, permeability coefficient and compressive strength of porous polymer concretes with unsaturated polyester. The porous polymer concretes using unsaturated polyester with polymer binder contents of 3.5, 4.0, 4.5 and 5.5% are prepared, and tested for void ratio, permeability coefficient and compressive strength. As a result, void ratio and permeability coefficient of porous polymer concrete decrease with increasing polymer binder content. However, the compressive strength of porous polymer concrete increase with increasing polymer binder content. The compressive strength of porous polymer concrete decrease with increasing permeability coefficient.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.78-79
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• 2015

For estimating compressive strength of concrete, non-destructive test has conducted generally. It used experimental equation to calculate compressive strength from construction. This study investigated experiment to apply non-destructive test, based on fresh property, compressive strength and ultrasonic pulse velocity of high performance concrete. And it conducted to compare various proposed equation.