Prediction of Compressive Strength of Concrete from Early Age Test Result Using Design of Experiments (RSM)
Response Surface Methods (RSM) provide
statistically validated predictive models that can then be manipulated
for finding optimal process configurations. Variation transmitted to
responses from poorly controlled process factors can be accounted
for by the mathematical technique of propagation of error (POE),
which facilitates ‘finding the flats’ on the surfaces generated by
RSM. The dual response approach to RSM captures the standard
deviation of the output as well as the average. It accounts for
unknown sources of variation. Dual response plus propagation of
error (POE) provides a more useful model of overall response
variation. In our case, we implemented this technique in predicting
compressive strength of concrete of 28 days in age. Since 28 days is
quite time consuming, while it is important to ensure the quality
control process. This paper investigates the potential of using design
of experiments (DOE-RSM) to predict the compressive strength of
concrete at 28th day. Data used for this study was carried out from
experiment schemes at university of Benghazi, civil engineering
department. A total of 114 sets of data were implemented. ACI mix
design method was utilized for the mix design. No admixtures were
used, only the main concrete mix constituents such as cement, coarseaggregate,
fine aggregate and water were utilized in all mixes.
Different mix proportions of the ingredients and different water
cement ratio were used. The proposed mathematical models are
capable of predicting the required concrete compressive strength of
concrete from early ages.
[1] Hasan. M and Kabir, " Prediction of compressive strength of concrete
from early age test result",4th Annual Paper Meet and 1st Civil
Engineering Congress, 2011, 22-24, Dhaka, Bangladesh ISBN: 978-984-
33-4363-5.
[2] M. Sayed-Ahmed1, "Statistical Modeling and Prediction of Compressive
Strength of Concrete" Concrete Research Letters, 2012, Vol. 3(2).
[3] M. J. Simon, "Concrete Mixture Optimization Using Statistical
Methods: Final Report" FHWA Office of Infrastructure Research and
Development, 6300 Georgetown Pike, 2003, McLean, VA 22101.
[4] M. T. Cihan et al., "Response surfaces for compressive strength of
concrete", Construction and Building Materials 40, 2013, 763–7740.
[5] Murali. and Kandasamy, " Mix proportioning of high performance selfcompacting
concrete using response surface methodology", Journal of
Civil Engineering (IEB), 2009,37 (2) ,91-98.
[6] Myers, R. H., and Montgomery, D. C. "Response surface methodology",
1995, Wiley, New York.
[1] Hasan. M and Kabir, " Prediction of compressive strength of concrete
from early age test result",4th Annual Paper Meet and 1st Civil
Engineering Congress, 2011, 22-24, Dhaka, Bangladesh ISBN: 978-984-
33-4363-5.
[2] M. Sayed-Ahmed1, "Statistical Modeling and Prediction of Compressive
Strength of Concrete" Concrete Research Letters, 2012, Vol. 3(2).
[3] M. J. Simon, "Concrete Mixture Optimization Using Statistical
Methods: Final Report" FHWA Office of Infrastructure Research and
Development, 6300 Georgetown Pike, 2003, McLean, VA 22101.
[4] M. T. Cihan et al., "Response surfaces for compressive strength of
concrete", Construction and Building Materials 40, 2013, 763–7740.
[5] Murali. and Kandasamy, " Mix proportioning of high performance selfcompacting
concrete using response surface methodology", Journal of
Civil Engineering (IEB), 2009,37 (2) ,91-98.
[6] Myers, R. H., and Montgomery, D. C. "Response surface methodology",
1995, Wiley, New York.
@article{"International Journal of Architectural, Civil and Construction Sciences:71603", author = "Salem Alsanusi and Loubna Bentaher", title = "Prediction of Compressive Strength of Concrete from Early Age Test Result Using Design of Experiments (RSM)", abstract = "Response Surface Methods (RSM) provide
statistically validated predictive models that can then be manipulated
for finding optimal process configurations. Variation transmitted to
responses from poorly controlled process factors can be accounted
for by the mathematical technique of propagation of error (POE),
which facilitates ‘finding the flats’ on the surfaces generated by
RSM. The dual response approach to RSM captures the standard
deviation of the output as well as the average. It accounts for
unknown sources of variation. Dual response plus propagation of
error (POE) provides a more useful model of overall response
variation. In our case, we implemented this technique in predicting
compressive strength of concrete of 28 days in age. Since 28 days is
quite time consuming, while it is important to ensure the quality
control process. This paper investigates the potential of using design
of experiments (DOE-RSM) to predict the compressive strength of
concrete at 28th day. Data used for this study was carried out from
experiment schemes at university of Benghazi, civil engineering
department. A total of 114 sets of data were implemented. ACI mix
design method was utilized for the mix design. No admixtures were
used, only the main concrete mix constituents such as cement, coarseaggregate,
fine aggregate and water were utilized in all mixes.
Different mix proportions of the ingredients and different water
cement ratio were used. The proposed mathematical models are
capable of predicting the required concrete compressive strength of
concrete from early ages.", keywords = "Mix proportioning, response surface methodology,
compressive strength, optimal design.", volume = "9", number = "12", pages = "1567-5", }