지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국계산역학회 Computers and Concrete, An International Journal Computers and Concrete, An International Journal Vol.19 No.1
- 발행연도
- 2017.1
- 수록면
- 59 - 68 (10page)
이용수
초록· 키워드
오류제보하기
This study focused on modeling the behavior of the compressive stress using the average strain and ultrasonic test results in concrete. Feed-forward backpropagation artificial neural network (ANN) models were used to compare four types of concrete mixtures with varying water cement ratio (WC), ordinary concrete (ORC) and concrete with short steel fiber-reinforcement (FRC). Sixteen (16) 150 mm×150 mm×150 mm concrete cubes were used; each contained eighteen (18) data sets. Ultrasonic test with pitch-catch configuration was conducted at each loading state to record linear and nonlinear test response with multiple step loads. Statistical Spearman’s rank correlation was used to reduce the input parameters. Different types of concrete produced similar top five input parameters that had high correlation to compressive stress: average strain (ε), fundamental harmonic amplitude (A1), 2nd harmonic amplitude (A2), 3rd harmonic amplitude (A3), and peak to peak amplitude (PPA). Twenty-eight ANN models were trained, validated and tested. A model was chosen for each WC with the highest Pearson correlation coefficient (R) in testing, and the soundness of the behavior for the input parameters in relation to the compressive stress. The ANN model showed increasing WC produced delayed response to stress at initial stages, abruptly responding after 40%. This was due to the presence of more voids for high water cement ratio that activated Contact Acoustic Nonlinearity (CAN) at the latter stage of the loading path. FRC showed slow response to stress than ORC, indicating the resistance of short steel fiber that delayed stress increase against the loading path.
목차
등록된 정보가 없습니다.
참고문헌 (39)
참고문헌 신청
Alexandridis, A. / 2016 / A Fast and Efficient Method for Training Categorical Radial Basis Function Networks / IEEE Trans. Neural Networks Learn. Sys.
Alex Alexandridis / 2015 / Non-destructive assessment of the three-point-bending strength of mortar beams using radial basis function neural networks / Computers and Concrete, An International Journal 16(6):909~932
Atici, U. / 2011 / Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network / Expert Sys. Appl. 38(8):9609~9618
M. Bilgehan / 2010 / The use of neural networks in concrete compressive strength estimation / Computers and Concrete, An International Journal 7(3):271~283
Breysse, D. / 2012 / Nondestructive evaluation of concrete strength: An historical review and a new perspective by combining NDT methods / Constr. Build. Mater. 33:139~163
Alex Alexandridis / 2015 / Non-destructive assessment of the three-point-bending strength of mortar beams using radial basis function neural networks / Computers and Concrete, An International Journal 16(6):909~932
Atici, U. / 2011 / Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network / Expert Sys. Appl. 38(8):9609~9618
M. Bilgehan / 2010 / The use of neural networks in concrete compressive strength estimation / Computers and Concrete, An International Journal 7(3):271~283
Breysse, D. / 2012 / Nondestructive evaluation of concrete strength: An historical review and a new perspective by combining NDT methods / Constr. Build. Mater. 33:139~163
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Inverse model for pullout determination of steel fibers
Coupled systems mechanics
2018 .01
-
Traffic-load-induced dynamic stress accumulation in subgrade and subsoil using small scale model tests
Geomechanics & engineering
2018 .01
-
Experimental characterization of ultrasonic nonlinearity in concrete under cyclic change of prestressing force
Computers and Concrete, An International Journal
2017 .01
-
파이버모델을 이용한 RC벽체의 핀칭해석
대한건축학회 논문집 - 구조계
2017 .06
-
Application of Nonlinear Ultrasonic Method for Monitoring of Stress State in Concrete
비파괴검사학회지
2016 .04
-
섬유 조합 변화에 따른 FRC의 기초적 특성 분석
한국콘크리트학회 학술대회 논문집
2015 .05
-
Effects of temperature on the evolution of stresses at the stem cement interface
Advances in computational design
2019 .01
-
인공신경망을 사용한 섬유금속적층판의 온도에 따른 유동응력에 대한 수치해석적 예측
소성·가공
2018 .08
-
Experimental Toughness and Durability Evaluation of FRC Composite Reinforced with Steel–Polyester Fiber Combination
International Journal of Concrete Structures and Materials
2023 .09
-
적산온도에 의한 FRC 기층의 강도발현 성능 분석
한국도로학회논문집
2016 .01
-
Study on Early‑Age Elastic Modulus of FRC Using Electrical Resistivity and Resonance Frequency
International Journal of Concrete Structures and Materials
2023 .01
-
Effect of Mixing Method on Mechanical Properties of Fiber Reinforced Concrete
한국건축시공학회지
2015 .01
-
Numerical Study on Prediction of Flow Stress of Fiber Metal Laminate based on Self-Reinforced Polypropylene using Artificial Neural Network method
한국소성가공학회 학술대회 논문집
2017 .10
-
모르타르 시편의 재령에 따른 초음파를 이용한 내부탐사
한국건축시공학회 학술발표대회 논문집
2019 .01
-
Correlation between Ultrasonic Nonlinearity and Elastic Nonlinearity in Heat-Treated Aluminum Alloy
비파괴검사학회지
2017 .04
-
Influence of dynamic loading induced by free fall ball on high-performance concrete slabs with different steel fiber contents
Structural monitoring and maintenance
2019 .01
-
기공을 포함한 피로손상 알루미늄 6061-T6의 초음파 특성평가
한국가스학회지
2015 .10
-
Long-term quality control of self-compacting semi-lightweight concrete using short-term compressive strength and combinatorial artificial neural networks
Computers and Concrete, An International Journal
2020 .01
-
3차원 노즐로드 보수적 하중 조건 결정을 위한 하중 부호 결정 방법론
한국압력기기공학회 논문집
2023 .12
-
Predicting compressive strength of bended cement concrete with ANNs
Computers and Concrete, An International Journal
2017 .01
이 논문의 저자 정보
최근 본 자료
댓글(0)
0