Statistical Models for Hardened Properties of Self-Compacting Concrete

Abstract

Problem statement: For predicting workability and hardened properties of SelfCompacting Concrete (SCC) no well known explicit formulation. Approach: Statistical models were carried out to model the influence of key mixture parameter (cement, water to powder ratio, fly ash and super plasticizer) on hardened properties affecting the performance of SCC. Such responses included compressive strength at 3, 7 and 28 days and modulus of elasticity. Thirty one mixtures were prepared to derive the numerical models and evaluate the accuracy. The models were valid for a wide range of mixture proportioning. Results: The research presented derived numerical models that can be useful to reduce the test procedures and trials needed for the proportioning of self-compacting concrete. The qualities of these models were evaluated based on several factors such as level prediction, residual error, residual mean square and correlation coefficients. Conclusion: Full quadratic models in all the response (compressive strength at 3,7 and 28 days and modulus of elasticity) showed high correlation coefficient (R 2 ), adjusted correlation coefficient, less level of significant and sum of square errors from the four predictions models (linear, interaction, full quadratic and pure quadratic) were developed.

Multifunctional computational models to predict the long‐term compressive strength of concrete incorporated with waste steel slag

“…The appropriateness of the entire quadratic model for projecting the compressive strength of concrete with steel slag substituted for typical coarse aggregate was evaluated; each parameter is shown in squared, interaction (product), linear, and constant terms; Equation 3a depicts the revealed model for data containing steel slag aggregate and Equation 3b indicates the model for steel slag absent. 51,52 There does not seem to be any evidence linking model predictions to mistaken words.…”

“…The appropriateness of the entire quadratic model for projecting the compressive strength of concrete with steel slag substituted for typical coarse aggregate was evaluated; each parameter is shown in squared, interaction (product), linear, and constant terms; Equation depicts the revealed model for data containing steel slag aggregate and Equation indicates the model for steel slag absent 51,52 . There does not seem to be any evidence linking model predictions to mistaken words. …”

Modeling of Elastic Modulus of Concrete Containing Fly Ash By Gene Expression Programming

“…The explicit formulations from these models were also presented. Besides, these formulations were validated with different experimental results gathered from the literature [Siddique 2003;Camões, Aguiar and Jalali 2005;Schindler, Barnes, Roberts and Rodriguez 2007;Qadi and Mustapha 2009]. These formulations results were compared with the experimental results and formulas results given by some national building codes.…”

“…To develop these models, among 137 experimental data presented with 81 different concrete containing FA mixtures collected from the eight different experimental studies [Siddique, 2004;Wee, Chin and Mansur 1996;Haque and Kayali 1998;Kim, Han, Park and Noh 1998;Nassif, Najm and Suksawang 2005;Mittal, Kaisare and Shetti 2005;Atiş 2009;Kou, Poon and Chan 2007], about 70% of the entire data (92 sets) was randomly separated as training set, and the remaining of the entire data (45 sets) was taken as testing set. Besides, the proposed equations used the explicit formulations obtained from training and testing sets in these models were validated with 122 experimental data presented with 51 different concrete containing FA mixtures collected from the four different experimental studies [Siddique 2003;Camões, Aguiar and Jalali 2005;Schindler, Barnes, Roberts and Rodriguez 2007;Qadi and Mustapha 2009] not used in the training and testing sets.…”

Use of Recycled Aggregate and Fly Ash in Concrete Pavement

“…However, the compressive strength of the HSC had increased from 71.8-79.0 MPa using 1.8% of BF while flexural strength had increased from 5.21-6.50 MPa. Qadi et al (2009) developed Statistical models to model the influence of key mixture parameter such as cement and fly ash on hardened properties affecting the performance of Self-Compacting Concrete (SCC). Their results presented numerical models that can be useful to reduce the test procedures and trials needed for the proportioning of self-compacting concrete.…”