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Box-Wilson Experimental Design-based Optimal Design Method of High Strength Self Compacting Concrete

Box-willson 실험계획법 기반 고강도 자기충전형 콘크리트의 최적설계방법

  • Received : 2015.05.19
  • Accepted : 2015.08.17
  • Published : 2015.09.01

Abstract

Box-Wilson experimental design method, known as central composite design, is the design of any information-gathering exercises where variation is present. This method was devised to gather as much data as possible in spite of the low design cost. This method was employed to model the effect of mixing factors on several performances of 60 MPa high strength self compacting concrete and to numerically calculate the optimal mix proportion. The nonlinear relations between factors and responses of HSSCC were approximated in the form of second order polynomial equation. In order to characterize five performances like compressive strength, passing ability, segregation resistance, manufacturing cost and density depending on five factors like water-binder ratio, cement content, fine aggregate percentage, fly ash content and superplasticizer content, the experiments were made at the total 52 experimental points composed of 32 factorial points, 10 axial points and 10 center points. The study results showed that Box-Wilson experimental design was really effective in designing the experiments and analyzing the relation between factor and response.

Box-Wilson 실험계획법은 보통 중심합성계획법으로 알려져 있으며, 변동성이 존재하는 정보를 실험 계획적 방법으로 수집하는 설계 기법이다. 이 방법은 최소의 설계비용으로 가능한 많은 정보를 얻는 목적으로 고안되었다. 본 연구에서는 60 MPa급 고강도 자기충전형 콘크리트(HSSCC)를 대상으로 다양한 성능에 대한 여러 배합인자들의 효과를 효율적으로 파악하고 최적배합을 찾는 과정에 이 방법을 적용하였다. HSSCC의 배합인자(요인)와 물리적 성능(반응) 사이의 비선형적 관계는 2차 다항식으로 반응표면을 근사화 모델링하였으며, 요인점=25=32개, 축점=2k=10개, 중심점은 각 축에서 2번 씩 10개, 총 52개의 실험점에서 물시멘트비, 단위시멘트량, 잔골재비, 단위플라이애쉬량, 단위고성능감수량의 총 5개의 인자에 따른 압축강도, 통과능력, 재료분리저항성, 제조비용, 밀도 등의 총 5개의 반응을 파악하기 위한 실험이 실시되었다. 연구의 결과 Box-Wilson 실험계획법은 배합인자와 반응 사이의 관계를 과학적인 방법으로 계획하고 객관적으로 해석하는 데 매우 효과적이었으며, 수치해석적인 방법으로 최적배합을 계산할 수 있었다.

Keywords

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Cited by

  1. Experimental Optimization of High-Strength Self-Compacting Concrete Based on D-Optimal Design vol.143, pp.4, 2017, https://doi.org/10.1061/(ASCE)CO.1943-7862.0001230