TechnoRep - Faculty of Technology and Metallurgy Repository
University of Belgrade - Faculty of Technology and Metallurgy
    • English
    • Српски
    • Српски (Serbia)
  • English 
    • English
    • Serbian (Cyrillic)
    • Serbian (Latin)
  • Login
View Item 
  •   TechnoRep
  • Tehnološko-metalurški fakultet
  • Radovi istraživača / Researchers’ publications (TMF)
  • View Item
  •   TechnoRep
  • Tehnološko-metalurški fakultet
  • Radovi istraživača / Researchers’ publications (TMF)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation

No Thumbnail
Authors
Kostić, Srdan
Vasović, Nebojša
Marinković, Boban
Article (Published version)
Metadata
Show full item record
Abstract
A new approach is proposed for the robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation. The essence of the suggested procedure lies in the reliable prediction of concrete strength as a simple function of unit mass, water/cement ratio, age and superplasticizer content. The derived model provides sufficiently accurate results for the calibration and verification phases, the latter of which is conducted using data that were not used for model development. The results of additional analysis indicate that residuals in the calibration and verification stages have a normal distribution. Is its also shown that the uncertainty of estimated coefficient values has a statistically insignificant effect on concrete strength, confirming the reliability of the proposed model. Moreover, analysis of the effect of laboratory measurement errors indicates the robustness of concrete compressive strength against the variation in measured parameter... values.

Keywords:
Concrete compressive strength / response surface methodology (RSM) / historical data / prediction model / Monte Carlo simulation
Source:
Engineering Optimization, 2017, 49, 5, 864-877
Publisher:
  • Taylor & Francis Ltd, Abingdon
Funding / projects:
  • Magmatism and geodynamics of the Balkan Peninsula from Mesozoic to present day: significance for the formation of metallic and non-metallic mineral deposits (RS-176016)
  • Modeling and Numerical Simulations of Complex Many-Body Systems (RS-171017)

DOI: 10.1080/0305215X.2016.1211432

ISSN: 0305-215X

WoS: 000396745600009

Scopus: 2-s2.0-84981164273
[ Google Scholar ]
9
8
URI
http://TechnoRep.tmf.bg.ac.rs/handle/123456789/3690
Collections
  • Radovi istraživača / Researchers’ publications (TMF)
Institution/Community
Tehnološko-metalurški fakultet
TY  - JOUR
AU  - Kostić, Srdan
AU  - Vasović, Nebojša
AU  - Marinković, Boban
PY  - 2017
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/3690
AB  - A new approach is proposed for the robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation. The essence of the suggested procedure lies in the reliable prediction of concrete strength as a simple function of unit mass, water/cement ratio, age and superplasticizer content. The derived model provides sufficiently accurate results for the calibration and verification phases, the latter of which is conducted using data that were not used for model development. The results of additional analysis indicate that residuals in the calibration and verification stages have a normal distribution. Is its also shown that the uncertainty of estimated coefficient values has a statistically insignificant effect on concrete strength, confirming the reliability of the proposed model. Moreover, analysis of the effect of laboratory measurement errors indicates the robustness of concrete compressive strength against the variation in measured parameter values.
PB  - Taylor & Francis Ltd, Abingdon
T2  - Engineering Optimization
T1  - Robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation
EP  - 877
IS  - 5
SP  - 864
VL  - 49
DO  - 10.1080/0305215X.2016.1211432
ER  - 
@article{
author = "Kostić, Srdan and Vasović, Nebojša and Marinković, Boban",
year = "2017",
abstract = "A new approach is proposed for the robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation. The essence of the suggested procedure lies in the reliable prediction of concrete strength as a simple function of unit mass, water/cement ratio, age and superplasticizer content. The derived model provides sufficiently accurate results for the calibration and verification phases, the latter of which is conducted using data that were not used for model development. The results of additional analysis indicate that residuals in the calibration and verification stages have a normal distribution. Is its also shown that the uncertainty of estimated coefficient values has a statistically insignificant effect on concrete strength, confirming the reliability of the proposed model. Moreover, analysis of the effect of laboratory measurement errors indicates the robustness of concrete compressive strength against the variation in measured parameter values.",
publisher = "Taylor & Francis Ltd, Abingdon",
journal = "Engineering Optimization",
title = "Robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation",
pages = "877-864",
number = "5",
volume = "49",
doi = "10.1080/0305215X.2016.1211432"
}
Kostić, S., Vasović, N.,& Marinković, B.. (2017). Robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation. in Engineering Optimization
Taylor & Francis Ltd, Abingdon., 49(5), 864-877.
https://doi.org/10.1080/0305215X.2016.1211432
Kostić S, Vasović N, Marinković B. Robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation. in Engineering Optimization. 2017;49(5):864-877.
doi:10.1080/0305215X.2016.1211432 .
Kostić, Srdan, Vasović, Nebojša, Marinković, Boban, "Robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation" in Engineering Optimization, 49, no. 5 (2017):864-877,
https://doi.org/10.1080/0305215X.2016.1211432 . .

DSpace software copyright © 2002-2015  DuraSpace
About TechnoRep | Send Feedback

OpenAIRERCUB
 

 

All of DSpaceInstitutions/communitiesAuthorsTitlesSubjectsThis institutionAuthorsTitlesSubjects

Statistics

View Usage Statistics

DSpace software copyright © 2002-2015  DuraSpace
About TechnoRep | Send Feedback

OpenAIRERCUB