• Advances in concrete construction
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• v.7 no.4
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• pp.211-218
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• 2019

Predictions about shrinkage and creep of concrete are very important for evaluating time-dependent effects on structural performance. Some prediction models and formulas of concrete shrinkage and creep have been proposed with diversity. However, the influence of reinforcement ratio on shrinkage and creep of concrete has been ignored in most prediction models and formulas. In this paper, the concrete shrinkage and creep with different ratios of reinforcement were studied. Firstly, the shrinkage performance was tested by the 10 reinforced concrete beams specimens with different reinforcement ratios for 200 days. Meanwhile, the creep performance was tested by the 5 reinforced concrete beams specimens with different ratios of reinforcement under sustained load for 200 days. Then, the test results were compared with the prediction models and formulas of CEB-FIP 90, ACI 209, GL 2000 and JTG D 62-2004. At last, based on ACI 209, an improved prediction models and formulas of concrete shrinkage and creep considering reinforcement ratio was derived. The results from improved prediction models and formulas of concrete shrinkage and creep are in good agreement with the experimental results.

• International Journal of Concrete Structures and Materials
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• v.6 no.4
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• pp.221-230
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• 2012

Cracking of repair material due to restraint of shrinkage could hinder the intended extension of serviceability of repaired concrete structure. The availability of model to predict shrinkage stress under restraint condition will be useful to assess whether repair material with particular deformation properties is resistance to cracking or not. The accuracy in the prediction will depend upon reliability of the model, input parameters, testing methods used to characterize the input parameters, etc. This paper reviews a variety of models to predict shrinkage stress in patch repair system. Effect of creep and composite action to release shrinkage stress in the patch repair system are quantified and discussed. Accuracy of the models is examined by comparing predicted and measured shrinkage stress. Simplified model to estimate shrinkage stress is proposed which requires only shrinkage property of repair material as an input parameter.

• Computers and Concrete
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• v.12 no.2
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• pp.109-129
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• 2013

This work presents an approach to model concrete shrinkage. The goal is to permit the concrete industry's experts to develop independent prediction models based on a reduced number of experimental data. The proposed approach combines fuzzy logic and genetic algorithm to optimize the fuzzy decision-making, thereby reducing data collection time. Such an approach was implemented for an experimental data set related to self-compacting concrete. The obtained prediction model was compared against published experimental data (not used in model development) and well-known shrinkage prediction models. The predicted results were verified by statistical analysis, which confirmed the reliability of the developed model. Although the range of application of the developed model is limited, the genetic-fuzzy approach introduced in this work proved suitable for adjusting the prediction model once additional training data are provided. This can be highly inviting for the concrete industry's experts, since they would be able to fine-tune their models depending on the boundary conditions of their production processes.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.1
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• pp.125-132
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• 2020

The causes of concrete shrinkage are very diverse, in particular, aggregates impact the characteristics of shrinkage in concrete by constraining the shrinkage of cement paste. Meanwhile, owing to the lack of natural aggregate, various alternative aggregates are being developed, and their application in concrete also becomes more diverse. This study aimed to experimentally evaluate the drying and autogenous shrinkage in concrete that was composed of electric arc furnace slag as coarse aggregates. And, the results were compared with prediction models. From the results, the application of electric arc furnace slag can reduce the drying and autogenous shrinkage. In particular, autogenous shrinkage is greatly decreased. The predictions using GL2000 for drying shrinkage and Tazawa model for autogenous shrinkage were similar to the experimental results. However, the most prediction models do not consider the impact of aggregates, hence, the new prediction model should be developed or improved.

• Journal of the Korea Concrete Institute
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• v.11 no.3
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• pp.23-34
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• 1999

In designing PSC box girder bridge, the dead load, prestressing force, creep and shrinkage of concrete are the main factors which influence the camber and deflection of segmental concrete structure under construction. Among these factors the creep and shrinkage are the functions of the time-dependent property which, therefore, must considered with time. The prediction model for estimating creep and shrinkage of concrete has been suggested by ACI, CEB/FIP, JSCE and KSCE design code. In this study the creep and shrinkage test were carried out for four curing ages of concrete which was applied to the pretressed concrete box-girder bridge at a construction site, and the results of test were compared to the values of prediction by the design code. Shrinkage test shows that the test results are similar to KSCE-96 and JSCE-96 but very higher than other prediction model and creep test results are generally similar to ACI-209 and DSCE-96 but lower than other prediction models in contrast to shrinkage test.

• Computers and Concrete
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• v.28 no.5
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• pp.441-450
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• 2021

This study presents the first analysis system and fast-access cloud database for shrinkage and creep of concrete in the world, named "shrinkage and creep database in Taiwan", SCDT. SCDT not only has the most comprehensive experimental data, including NU, JSCE, Europe, and TW databases, but provides a design tool for researchers and engineers. It can further facilitate the development of prediction models for localized concrete. Users can obtain the shrinkage and creep curves based on their selected prediction models in SCDT. Comparisons of the predicted results of selected models and test results in the chosen database can be generated in seconds. One example of the development of basic creep prediction model in Taiwan based on model B4 by using SCDT to reflect concrete characteristics in Taiwan is also presented in this study. Users anywhere in the world can easily access SCDT to browse and upload data, receive predictive results, or develop predictive models.

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

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05b
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• pp.529-532
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• 2006

This paper presents results from creep and shrinkage tests performed on different High Strength Concrete (HSC) mixes (with compressive strengths up to 90 MPa). Results were compared with those from various Code prediction models. The effects of pozzolanic materials on the creep and shrinkage were also investigated. Results show that while fly ash increases the compressive creep of concrete, silica fume decreases it. Moreover, current creep and shrinkage prediction models need to be revised for the HSC mixture.

• Computers and Concrete
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• v.33 no.4
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• pp.349-359
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• 2024

This study aims to investigate the effect of restraint configuration on crack formation due to shrinkage-and-creep-induced volumetric change in unbonded post-tensioned slabs. The first part of this study focuses on the comparison of existing shrinkage and creep calculation models that are used to predict the volume-changing behavior of concrete. The second part of this study presents the finite element analysis of a series of architectural configuration prototypes subjected to shrinkage and creep, which comprise unbonded post-tensioned slabs with various restraint configurations. The shrinkage and creep effects were simulated in the analysis by imposing strains obtained from one selected calculation model. The results suggest that a slab up to 300 ft. (90 m) in length does not require a closure strip if it is unrestrained by perimeter walls, and that the most effective restraint crack mitigation strategy for a slab restrained by perimeter walls is a partial wall release.

• Structural Engineering and Mechanics
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• v.39 no.2
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• pp.267-285
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• 2011

There can be a significant amount of moment redistribution in composite frames consisting of steel columns and composite beams, due to cracking, creep and shrinkage of concrete. Considerable amount of computational effort is required for taking into account these effects for large composite frames. A methodology has been presented in this paper for taking into account these effects. In the methodology that has been demonstrated for moderately high frames, neural network models are developed for rapid prediction of the inelastic moments (typically for 20 years, considering instantaneous cracking, and time effects, i.e., creep and shrinkage, in concrete) at a joint in a frame from the elastic moments (neglecting instantaneous cracking and time effects). The proposed models predict the inelastic moment ratios (ratio of elastic moment to inelastic moment) using eleven input parameters for interior joints and seven input parameters for exterior joints. The training and testing data sets are generated using a hybrid procedure developed by the authors. The neural network models have been validated for frames of different number of spans and storeys. The models drastically reduce the computational effort and predict the inelastic moments, with reasonable accuracy for practical purposes, from the elastic moments, that can be obtained from any of the readily available software.