Abstract
Self-compacting concrete (SCC), characterized by the high flowability and resistance to segregation, is due to the high amount of paste (including cement and mineral admixtures) in contrast with normal concrete (NC). However, the high amount of paste will limit the volume fractions of coarse aggregate,and reduce the tendency of coarse aggregate to suppress drying shrinkage deformations. For this reason, SCC tends to produce higher values of drying shrinkage than NC for the most part. In order to assess the drying shrinkage of SCC quantitatively for application to offshore caisson foundations, the formulas presented in the literatures (ACI 209 and CEB-FIP) are used to predict the values of drying shrinkage in SCC according to the corresponding mix proportions. Additionally, a finite element (FE) model, which assumes concrete to be a homogeneous and isotropic material and follows the actual size and environmental conditions of the caisson, is utilized to simulate stress distribution situations and deformations in the SCC caisson resulting from the drying shrinkage. The probability of cracking and the behavior of drying shrinkage of the SCC caisson are drawn from the analytic results calculated by the FE model proposed in this paper.
Key Words
self-compacting concrete; drying shrinkage; caisson foundation.
Address
How-Ji Chen and Te-Hung Liu : Department of Civil Engineering, National Chung-Hsing University, Taichung 402, Taiwan
Chao-Wei Tang : Department of Civil Engineering & Engineering Informatics, Cheng-Shiu University, Koahsiung 833, Taiwan
Abstract
This paper focuses on the application of two dimensional orthogonal polynomials in the regression analysis for the relationship of product parameters viz. compressive strength, bulk density and water absorption of fly ash cement bricks with other process parameters such as percentages of fly ash, sand and cement. The method has been validated by linear and non-linear two parameter regression models. The use of two dimensional orthogonal system makes the analysis computationally efficient, simple and straight forward. Corresponding co-efficient of determination and F-test are also reported to show the efficacy and reliability of the relationships. By applying the evolved relationships, the product parameters of fly ash cement bricks may be approximated for the use in construction sectors.
Abstract
The paper explores the potential of Support Vector Machines (SVM) approach in predicting 28-day compressive strength and slump flow of self-compacting concrete. Total of 80 data collected from the exiting literature were used in present work. To compare the performance of the technique, prediction was also done using a back propagation neural network model. For this data-set, RBF kernel worked well in comparison to polynomial kernel based support vector machines and provide a root mean square error of 4.688 (MPa) (correlation coefficient=0.942) for 28-day compressive strength prediction and a root mean square error of 7.825 cm (correlation coefficient=0.931) for slump flow. Results obtained for RMSE and correlation coefficient suggested a comparable performance by Support Vector Machine approach to neural network approach for both 28-day compressive strength and slump flow prediction.
Key Words
28-day compressive strength; slump flow; prediction; Support vector machines technique; neural network.
Address
Rafat Siddique : Department of Civil Engineering, Thapar University, Patiala, India
Paratibha Aggarwal, Yogesh Aggarwal and S. M. Gupta : Department of Civil Engineering, N.I.T. Kurukshetra, India
Abstract
The paper explores the potential of applicability of Genetic programming approach (GP), adopted in this investigation, to model the combined effects of five independent variables to predict the mini-slump, the plate cohesion meter, the induced bleeding test, the J-fiber penetration value, and the compressive strength at 7 and 28 days of self-compacting slurry infiltrated fiber concrete (SIFCON). The variables investigated were the proportions of limestone powder (LSP) and sand, the dosage rates of superplasticiser (SP) and viscosity modifying agent (VMA), and water-to-binder ratio (W/B). Twenty eight mixtures were made with 10-50% LSP as replacement of cement, 0.02-0.06% VMA by mass of cement, 0.6-1.2% SP and 50-150% sand (% mass of binder) and 0.42-0.48 W/B. The proposed genetic models of the self-compacting SIFCON offer useful modelling approach regarding the mix optimisation in predicting the fluidity, the cohesion, the bleeding, the penetration, and the compressive strength.
Address
Abdulkadir Cevik : Department of Civil Engineering, University of Gaziantep, Turkey
Mohammed Sonebi : School of Planning, Architecture, and Civil Engineering, Queen?s University Belfast Belfast BT7 1NN, Northern Ireland, UK
Abstract
The present study verifies compressive strength, ultrasonic pulse velocity, electrical resistance,permeable ratio, and shrinkage from waste glass controlled low strength materials (WGCLSM) and earlyhigh-strength WGCSLM specimens, by replacing the sand with waste glass percentages of 0%, 10%,20%, and 30%. This study reveals that increasing amounts of waste LCD glass incorporated into concrete increases WGCLSM fluidity and reduces the setting time, resulting in good working properties. By increasing the glass to sand replacement ratio, the compressive strength decreases to achieve low-strength effects. Furthermore, the electrical resistance also rises as a result of increasing the glass to sand replacement ratio. Early-high-strength WGCSLM aged 28 days has twice the electrical resistance compared to general WGCSLM. Early-high-strength WGCSLM aged 7 days has a higher ultrasonic pulse velocity similar to WGCSLM aged 28 days. The variation of length with age of different compositions is all within the tolerance range of 0.025%. This study demonstrates that the proper composition ratio of waste LCD glass to sand in early-high-strength WGCSLM can be determined by using different amounts of glass-sand. A mechanism for LCD optical waste glass usage can be established to achieve industrial waste minimization, resource recycling, and economic security.
Address
Mehmet Emiroglu and Servet Yildiz : Firat University, Technical Education Faculty, Department of Construction Education, Elazig, Turkey
M. Halidun Kelestemur : Firat University, Engineering Faculty, Department of Metallurgical and Materials Engineering Elazig, Turkey