earticle

논문검색

신경망 이론을 이용한 100MPa급 초고강도 콘크리트의 최적 배합설계모델에 관한 연구

원문정보

A Study on the Optimum Mix Design Model of 100MPa Class Ultra High Strength Concrete using Neural Network

김영수, 신상엽, 정의창

피인용수 : 0(자료제공 : 네이버학술정보)

초록

한국어

The purpose of this study is to suggest 100MPa class ultra high strength concrete mix design model applying neural network theory, in order to minimize an effort wasted by trials and errors method until now. Mix design model was applied to each of the 70 data using binary binder, ternary binder and quaternary binder. Then being repeatedly applied to back-propagation algorithm in neural network model, optimized connection weight was gained. The completed mix design model was proved, by analyzing and comparing to value predicted from mix design model and value measured from actual compressive strength test. According to the results of this study, more accurate value could be gained through the mix design model, if error rate decreases with the test condition and environment. Also if content of water and binder, slump flow, and air content of concrete apply to mix design model, more accurate and resonable mix design could be gained.

목차

Abstract
1. 서론
1.1 연구배경 및 목적
1.2 연구범위 및 방법
2. 초고강도 배합설계 시험
2.1 사전 배합실험 계획
2.2 사용재료
2.3 시험결과
3. 배합설계를 위한 모델링
3.1 신경망 모델링 방법
3.2 입력변수 및 출력변수의 결정
3.3 배합설계모델 최적화
3.4 학습검증
4. 모델 검증
4.1 배합 인자 수준 예측
4.2 검증실험
4.3 결과 분석
5. 결론
REFERENCES

저자정보

  • 김영수 Kim, Young-Soo. 부산대학교 건축공학과 교수 공학박사
  • 신상엽 Shin, Sang-Yeop. ING&ENG, 연구실장, 공학박사
  • 정의창 Jeong, Euy-Chang. ING&ENG, 기획실장, 공학박사

참고문헌

자료제공 : 네이버학술정보
  • 1The Effect of Ground Granulated Blast-Furnace Slag on the Control of Temperature Rising in High Strength Concrete네이버 원문 이동
  • 2Lee, S.U. (2008). The Effect of High Strength Concrete by Admixture Types and Mixture Condition [master's thesis]. Dae Jeon University. Korea.
  • 3Bae, S.K. (2003). Compressive Strength of High-Strength Concrete for the Mix Proportion [master’s thesis]. In Ha University. Korea.
  • 4Yoo, S.Y, Lee, S.L, Koo, J.S, Kang, S.H. (2010). High Strength Concrete Mix Design Program and Ultra High Strength Concrete Ready-mixed Concrete Manufacturing Technology Development. Journal of Korea Cement Association, 185(1), pp.28~35.
  • 5Kim, K.H., An, S.H., Cho, H.G. (2006). Comparison of the Accuracy between Cost Prediction Models based on Neural Network and Genetic Algorithm–Focused on Apartment Housing Project Cost. Journal of Architectural Institute of Korea, 22(3), pp.111~118.
  • 6Lee, Y.J. (2008). A study on the mix design model of 60MPa class high strength concrete using neural network theory [master's thesis]. Pusan National University. Korea.
  • 7Kim, S.Y., Ji, N.Y., Yoon, S.C. (2007). Compressive Strength of High-Strength Concrete using Fly Ash on the Basis of Statistical Analysis. Journal of Architectural Institute of Korea, 23(1), pp.113~121.
  • 8Kim, C.H. (2007). Study on the High-Strength of High Flowing Concrete using Fly Ash [master’s thesis], Dong Yang University. Korea.
  • 9Investigating mix proportions of high strength self compacting concrete by using Taguchi method네이버 원문 이동
  • 10Williams, P., Trefor, P. (1991). Predicting changes in construction cost indexes using neural networks. Journal of construction engineering and management, 117(4), pp. 606~625.

※ 기관로그인 시 무료 이용이 가능합니다.

  • 4,000원

0개의 논문이 장바구니에 담겼습니다.