• International Journal of Concrete Structures and Materials
• /
• v.9 no.3
• /
• pp.337-343
• /
• 2015

Previous studies have shown that the drying shrinkage of recycled aggregate concrete (RAC) is greater than that of natural aggregate concrete (NAC). Drying shrinkage is the fundamental reason for the cracking of concrete, and tensile creep caused by the restraint of drying shrinkage plays a significant role in the cracking because it can relieve the tensile stress and results in the delay of cracking occurrence. However, up till now, all research has been focusing on the compressive creep of RAC. Therefore, in this study, a uniaxial restrained shrinkage cracking test was executed to investigate the tensile creep properties caused by the restraint of drying shrinkage of RAC. The mechanical properties, such as compressive strength, tensile splitting strength, and Young's modulus of RAC were also investigated in this study. The results confirmed that the tensile creep of RAC caused by the restraint of shrinkage was about 20-30 % larger than that of NAC.

• Structural Engineering and Mechanics
• /
• v.52 no.1
• /
• pp.97-113
• /
• 2014

In the present work appropriate concrete material models have been proposed to predict drying shrinkage and specific creep of High-performance concrete (HPC) using Artificial Neural Network (ANN). The ANN models are trained, tested and validated using 106 different experimental measured set of data collected from different literatures. The developed models consist of 12 input parameters which include quantities of ingredients namely ordinary Portland cement, fly ash, silica fume, ground granulated blast-furnace slag, water, and other aggregate to cement ratio, volume to surface area ratio, compressive strength at age of loading, relative humidity, age of drying commencement and age of concrete. The Feed-forward backpropagation networks with Levenberg-Marquardt training function are chosen for proposed ANN models and same implemented on MATLAB platform. The results shows that the proposed ANN models are more rational as well as computationally more efficient to predict time-dependent properties of drying shrinkage and specific creep of HPC with high level accuracy.

• Journal of the Korea Concrete Institute
• /
• v.16 no.3 s.81
• /
• pp.425-431
• /
• 2004

This paper describes an experimental investigation of how time-dependent deformations of high strength concretes are affected by maximum size of coarse aggregate, curing time, and relatively low sustained stress level. A set of high strength concrete mixes, mainly containing two different maximum sizes of coarse aggregate, have been used to investigate drying shrinkage and creep strain of high strength concrete for 7 and 28-day moist cured cylinder specimens. Based upon one-year experimental results, drying shrinkage of high strength concrete was significantly affected by the maximum size of coarse aggregate at early age, and become gradually decreased at late age. The larger the maximum size of coarse aggregate in high strength concrete shows the lower the creep strain. The prediction equations for drying shrinkage and creep coefficient were developed on the basis of the experimental results, and compared with existing prediction models.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2003.05a
• /
• pp.457-462
• /
• 2003

It studies the non-structural crack factors that are produced in Steel Box Girder Bridge concrete floor plate using analytical method. It mainly studies humidity and design standard of concrete strength. It used MIDAS CIVIL Ver 5.4.0, a general structure analysis program that applies drying shrinkage rate of domestic road bridge design standard and standard value of creep coefficient, CEF-FIP standard equation and ACI standard equation from the aspect of creep, drying shrinkage and hydration heat to see the effect of the two factors on concrete crack and found the following result. The analytical results of this study showed that the initial stress, which was obtained by ACI standard, exceeds the allowable tensile stress between 5 to 18 days. This result means that even if a bridge is designed and constructed according to design standard, the bridge can have cracks due to various variables such as drying shrinkage, hydration heat and creep that produce stress in slab.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2021.05a
• /
• pp.199-200
• /
• 2021

In the study, creep and dry shrinkage characteristics were evaluated to determine the material properties necessary for structural analysis such as column shortening and differential drying shrinkage. All the experiments were conducted in an constant temperature and humidity room. The mechanical properties as well as the specific creep and ultimate dry shrinkage values were derived. In addition the characteristics of the physical value of the high-strength fiber reinforced concrete were considered.

• KCI Concrete Journal
• /
• v.14 no.1
• /
• pp.15-22
• /
• 2002

Stresses that develop due to differential shrinkage between polymer modified cement mortar (PM) and Portland cement concrete (PCC) in a repaired concrete beam at early ages were investigated. Interface delamination or debonding of the newly cast repair material from the base is often observed in the field when the drying shrinkage of the repair material is relatively large. This study presents results of both experimental and analytical works. In the experimental part of the study, development of the material properties such as compressive strength, elastic modulus, interface bond strength, creep constant, and drying shrinkage was investigated by testing cylinders and beams for a three-week period in a constant-temperature chamber. Development of shrinkage-induced strains in a PM-PCC composite beam was determined. In the analytical part of the study, two analytical solutions were used to compare the experimental results with the analytically predicted values. One analysis method was of an exact type but could not consider the effect of creep. The other analysis method was rather approximate in nature but the creep effect was included. Comparison between the analytical and the experimental results showed that both analytical procedures resulted in stresses that were in fair agreement with the experimentally determined values. It may be important to consider the creep effect to estimate shrinkage-induced stresses at early ages.

• Structural Engineering and Mechanics
• /
• v.50 no.5
• /
• pp.635-652
• /
• 2014

Creep and shrinkage behaviour of an ultra lightweight cement composite (ULCC) up to 450 days was evaluated in comparison with those of a normal weight aggregate concrete (NWAC) and a lightweight aggregate concrete (LWAC) with similar 28-day compressive strength. The ULCC is characterized by low density < 1500 $kg/m^3$ and high compressive strength about 60 MPa. Autogenous shrinkage increased rapidly in the ULCC at early-age and almost 95% occurred prior to the start of creep test at 28 days. Hence, majority of shrinkage of the ULCC during creep test was drying shrinkage. Total shrinkage of the ULCC during the 450-day creep test was the lowest compared to the NWAC and LWAC. However, corresponding total creep in the ULCC was the highest with high proportion attributed to basic creep (${\geq}$ ~90%) and limited drying creep. The high creep of the ULCC is likely due to its low elastic modulus. Specific creep of the ULCC was similar to that of the NWAC, but more than 80% higher than the LWAC. Creep coefficient of the ULCC was about 47% lower than that of the NWAC but about 18% higher than that of the LWAC. Among five creep models evaluated which tend to over-estimate the creep coefficient of the ULCC, EC2 model gives acceptable prediction within +25% deviations. The EC2 model may be used as a first approximate for the creep of ULCC in the designs of steel-concrete composites or sandwich structures in the absence of other relevant creep data.

• Magazine of the Korea Concrete Institute
• /
• v.9 no.2
• /
• pp.153-161
• /
• 1997

In the concrete st~uctures exposed to the environmental condition, the water movement is occurred by thc moisture difilsion, and the rnoisturrt distribution in concwt.c is nonunifhrm. Such a non-unif'orm moisture distribution causes tht. diflbrent.ia1 drying shrinkage in concrete structures. From this typc. of' dif'fercntial drying shrinkagr' tensiit-1 stress is occurred in exposure surface of concrete structures. and may result in crack formation. This residual stress is significantly affected by the creep of concrete, and the differential creep is also occurred at the cross section of concrete structures due to moisture difference at each locations. In this study, based on the moisture diffusion theory, a finite element program which is capable of simulating the moisture distribution in concrete was developed. And the analysis method for the differential drying shrinkage was suggested, in which the differential creep was considered. The differential drying shrinkage strain was also measured at various positions of concrete. Finally the validity of analysis method was proved by comparing test results with analytical results.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2004.05a
• /
• pp.612-615
• /
• 2004

The objective of this experimental study was to understand inelastic strain of concrete incorporating hwangtoh or combination of hwangtoh and slag. Main variables were replacement level of admixtures, hwangtoh and slag. We studied the properties of concrete such as heat of hydration, drying shrinkage and creep according to the replacement level of hwangtoh and slag. Test results showed that the heat of hydration of concrete decrease with increasing hwangtoh and slag replacement. Also drying shrinkage and creep of concrete increase with increasing hwangtoh replacement.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2006.05a
• /
• pp.494-497
• /
• 2006

The objectives of this study are to develop and evaluate the Neural Network algorithm which can predict the inelastic shortening such as the creep strain and the drying shrinkage strain of reinforced concrete members using the previous test data. New learning algorithms for the prediction of creep strain and the drying shrinkage strain are proposed focusing on input layer components and a normalization method for input data and their validity is examined through several test data. In Neural Network algorithm, the main input data to be trained are the compressive strength of the concrete, volume to surface ratio, curing condition, relative humidity, and the applied load. The results show that the new algorithms proposed herein successfully predict creep strain and the drying shrinkage strain.