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CONTENTS
Volume 30, Number 1, July 2022
 


Abstract
The basic purpose of the current study is to compute the numerical analysis of heat source/sink for Darcy- Forchheimer three dimensional nanofluid flow with gyrotactic microorganism by rotatable disk via porous media under the slip conditions. Due to nanoparticles, random and thermophoretic motion phenomenon occurs. The governing mathematical model is handled numerically by shooting method. Additionally, the characteristics of velocities, mass, heat, motile microorganisms and associated parameters are thoroughly analyzed via plots and tables. Different physical parameters like Forchheimer number, slip parameters like velocity, porosity parameter, Prandtl number, Brownian number, thermophoresis parameter, heat sink/source parameter, bioconvected Rayleigh number, buoyancy parameteron dimensionless velocities, temperature. Approximate values of Sherwood microorganism are analyzed.

Key Words
dimensionless velocities; shooting method; thermophoresis parameter

Address
Muzamal Hussain: Department of Mathematics, Govt. College University Faisalabad, 38040, Faisalabad, Pakistan
Humaira Sharif: Department of Mathematics, Govt. College University Faisalabad, 38040, Faisalabad, Pakistan
Mohamed Amine Khadimallah: Civil Engineering Department, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, 16273, Saudi Arabia
Hamdi Ayed: Department of Civil Engineering, College of Engineering, King Khalid University, Abha, Kingdom of Saudi Arabia; Higher Institute of Transport and Logistics of Sousse, University Sousse, Tunisia
Essam Mohammed Banoqitah: Nuclear Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah P.O. Box 80204, Jeddah 21589, Saudi Arabia
Hassen Loukil: Department of Electrical Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia
Imam Ali: Civil Engineering Department, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, 16273, Saudi Arabia
S.R. Mahmoud: GRC Department, Applied College, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Abdelouahed Tounsi: FL (Yonsei Frontier Lab.), Yonsei University, Seoul, Korea; Department of Civil and Environmental Engineering, King Fahd University of Petroleum and Minerals, 31261 Dhahran, Eastern Province, Saudi Arabia

Abstract
This paper discusses the effect of high temperatures (Ts) on the compressive strength and stress-strain curve of recycled fine aggregate concrete (RFAC), based on the experimental results. A total of 90 prisms (100 mmx100 mmx300 mm) were tested. The results show that the compressive strength and elastic modulus of RFAC specimens decreased significantly with increasing T values. As T increased, the strain corresponding to peak stress decreased first when T<200oC and then increased afterwards. With increasing T values, the stress-strain curves became flat gradually, the peak stress dropped gradually, and ep decreased when T<200oC and increased in the T range of 400-800oC. A stress-strain relations for RFAC exposed to high Ts is proposed, which agree quite well with the test results and may be used to practical applications.

Key Words
compressive strength; concrete; recycled fine aggregate; stress-strain relationship; temperature

Address
Jiongfeng Liang: Jiangsu Province Key Laboratory of Structure Engineering, Suzhou, China; State Key Laboratory of Green Building in Western China, Xian University of Architecture & Technology, Xian, China; Faculty of Civil & Architecture Engineering, East China University of Technology, Nanchang, China
Liuhaoxiang Wang: Faculty of Civil & Architecture Engineering, East China University of Technology, Nanchang, China
Zhibin Ling, Wei Li: Jiangsu Province Key Laboratory of Structure Engineering, Suzhou, China
Wenrui Yang: College of Civil Engineering and Architecture, Wenzhou University, Wenzhou 325035, Zhejiang, China

Abstract
This paper presents an investigation into the failure of RC columns under impact loadings. A numerical simulation of 19 identical RC columns subjected to single and repeated impact loadings was performed. A free-falling hammer was dropped at midspan with the same total kinetic energy input but varying mass and momentum. The specimens under the repeated impact test were struck two times at the same location. The colliding index, defined as the impact energy-momentum ratio, was proposed to explain the different impact responses under equal-energy impacts. The increase of colliding index from low to high indicates the transition of the impact response from static to dynamic and failure mode from flexure to shear. This phenomenon was more evident when the column had a greater axial load and was impacted with a high colliding index. The existence of the axial load had an inhibitory effect on the crack development and increased the shear resistance. The second impact changes the failure mode from flexural to brittle shear as found in the specimen with 20% axial load subjected to high a colliding index. Moreover, a deflection prediction equation based on the impact energy and force was limited to the low colliding index impact.

Key Words
brittle shear failure; colliding index; concrete column; momentum; repeated impact loading

Address
Warakorn Tantrapongsaton: Department of Civil Engineering, Chiang Mai University, Thailand
Chayanon Hansapinyo, Piyapong Wongmatar: Excellence Center in Infrastructure Technology and Transportation Engineering, Department of Civil Engineering, Chiang Mai University,
Chiang Mai, Thailand
Suchart Limkatanyu: Department of Civil Engineering, Prince of Songkla University, Thailand
Hexin Zhang: School of Engineering and the Built Environment, Edinburgh Napier University, 10 Colinton Road, Edinburgh, Scotland EH10 5DT, UK
Bhuddarak Charatpangoon: Excellence Center in Infrastructure Technology and Transportation Engineering, Department of Civil Engineering, Chiang Mai University,
Chiang Mai, Thailand

Abstract
Experimentally predicting the compressive strength (CS) of concrete (for a mix design) is a time-consuming and laborious process. The present study aims to propose surrogate models based on Support Vector Machine (SVM) and Gaussian Process Regression (GPR) machine learning techniques, which can predict the CS of concrete containing nano-silica. Content of cement, aggregates, nano-silica and its fineness, water-binder ratio, and the days at which strength has to be predicted are the input variables. The efficiency of the models is compared in terms of Correlation Coefficient (CC), Root Mean Square Error (RMSE), Variance Account For (VAF), Nash-Sutcliffe Efficiency (NSE), and RMSE to observation's standard deviation ratio (RSR). It has been observed that the SVM outperforms GPR in predicting the CS of the concrete containing nano-silica.

Key Words
compressive strength; concrete; GPR; machine learning; nano-silica; SVM

Address
Aman Garg: Department of Aerospace Engineering, Indian Institute of Technology Kanpur, Uttar Pradesh, 208016, India; Department of Civil and Environmental Engineering, The NorthCap University, Gurugram, Haryana, 122017, India
Paratibha Aggarwal, Yogesh Aggarwal: Department of Civil Engineering, National Institute of Technology Kurukshetra, Haryana, 136119, India
M.O. Belarbi: Laboratoire de Recherche en Génie Civil, LRGC. Université de Biskra B.P. 145, R.P. 07000, Biskra, Algeria
H.D. Chalak: Department of Civil Engineering, National Institute of Technology Kurukshetra, Haryana, 136119, India
Abdelouahed Tounsi: YFL (Yonsei Frontier Lab), Yonsei University, Seoul, Korea; Department of Civil and Environmental Engineering, King Fahd University of Petroleum & Minerals, 31261 Dhahran, Eastern Province, Saudi Arabia; Civil Engineering Department, Faculty of Technology, Material and Hydrology Laboratory, University of Sidi Bel Abbes, Algeria
Reeta Gulia: Department of Civil Engineering, DPG Institute of Technology and Management, Gurugram, Haryana, 122004, India

Abstract
Machine learning technique is recently opening new opportunities to identify the complex shear transfer mechanisms of reinforced concrete (RC) beam members. This study employed 1224 shear test specimens to train decision tree-based machine learning (ML) programs, by which strong correlations between shear capacity of RC beams and key input parameters were affirmed. In addition, shear contributions of concrete and shear reinforcement (the so-called Vc and Vs) were identified by establishing three independent ML models trained under different strategies with various combinations of datasets. Detailed parametric studies were then conducted by utilizing the well-trained ML models. It appeared that the presence of shear reinforcement can make the predicted shear contribution from concrete in RC beams larger than the pure shear contribution of concrete due to the intervention effect between shear reinforcement and concrete. On the other hand, the size effect also brought a significant impact on the shear contribution of concrete (Vc), whereas, the addition of shear reinforcements can effectively mitigate the size effect. It was also found that concrete tends to be the primary source of shear resistance when shear span-depth ratio a/d<1.0 while shear reinforcements become the primary source of shear resistance when a/d>2.0.

Key Words
deep beam; machine learning; mechanism; shear; slender beam

Address
Wei Zhang, Deuckhang Lee: Department of Architectural Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-gu, Cheongju, Chungbuk 28644, Republic of Korea
Hyunjin Ju: School of Architecture and Design Convergence, Hankyong National University, 327 Jungang-ro, Anseong, Gyeonggi 17579, Republic of Korea
Lei Wang: School of Civil Engineering, Changsha University of Science & Technology, 960 Wanjiali Road, Changsha, Hunan 410114, China

Abstract
This study introduced a post-tensioned precast concrete system that was developed and designed to improve the performance of joints by post-tensioning. Full-scaled specimens were tested to investigate flexural performances at the negative moment region, where the test variables were the presence of slabs, tendon types, and post-tensioned lengths. A specimen with slabs exhibited significantly higher stiffness and strength values than a specimen without slabs. Thus, it would be reasonable to consider the effects of a slab on the flexural strength for an economical design. A specimen with unbonded mono-tendons had slightly lower initial stiffness and flexural strength values than a specimen with bonded multi-tendons but showed greater flexural strength than the value specified in the design codes. The post-tensioned length was found to have no significant impact on the flexural behavior of the proposed post-tensioned precast concrete system. In addition, a finite element analysis was conducted on the proposed post-tensioned precast concrete system, and the tests and analysis results were compared in detail.

Key Words
flexural behavior; negative moment; post-tensioned method; prestressed concrete; tendon stress

Address
Seung-Ho Choi, Inwook Heo, Jae Hyun Kim: Department of Architectural Engineering, University of Seoul, 163 Siripdaero, Dongdaemun-gu, Seoul, 02504, Korea
Hoseong Jeong: Department of Architectural Engineering and Smart City Interdisciplinary Major Program, University of Seoul, 163 Siripdaero, Dongdaemun-gu, Seoul, 02504, Korea
Jae-Yeon Lee: Division of Architecture, Mokwon University, 88 Doanbuk-ro, Seo-gu, Daejeon, 35349, Korea
Kang Su Kim: Department of Architectural Engineering and Smart City Interdisciplinary Major Program, University of Seoul, 163 Siripdaero, Dongdaemun-gu, Seoul, 02504, Korea


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