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CONTENTS
Volume 24, Number 2, February 2023
 

Abstract
The maximum drifts are important to the seismic evaluation of steel buildings and connections, but the information can hardly be obtained from the post-earthquake field investigation. This research studies the feasibility of using the loss rate of bolt pretension as an earthquake damage predictor. Full-scale tests were made on four steel connections using bolted-webwelded-flange details. One connection was unreinforced (UN), another was reinforced with double shear plates (DS), and the other two used reduced beam sections (RBS). The preinstalled strain gauges were used to control the pretensions and monitor the losses of the high-strength bolts. The results showed that the loss rate of bolt pretension was highly related to the damage of the connections. The pretensions lost up to 10% in all the connections at the yield drifts of 0.5% to 1%. After yielding of the connections, the pretensions lost significantly until fracture occurred. The UN and DS connections failed with a maximum drift of 4 %, and the two RBS connections showed better ductility and failed with a maximum drift of 6%. Under the far-field-type loading protocol, the loss rate grew to 60%. On the contrary, the rate for the specimen under near-fault-type loading protocol was about 40%. The loss rate of bolt pretension is therefore recommended to use as an earthquake damage predictor. Additionally, the 10% and 40% loss rates are recommended to predict the limit states of connection yielding and maximum strength, respectively, and to define the performance levels of serviceability and life-safety for the buildings.

Key Words
damage predictor; loading protocol; loss rate of bolt pretension; moment connections; steel buildings

Address
Chui-Hsin Chen: Department of Civil Engineering, National Yang Ming Chiao Tung University, 1001, University Rd, Hsinchu 300, Taiwan
Chi-Ming Lai: Department of Civil Engineering, National Cheng Kung University, 1, University Rd., Tainan 701, Taiwan
Ker-Chun Lin and Sheng-Jhih Jhuang: National Center for Research on Earthquake Engineering, National Applied Research Laboratories, 200, Sec. 3, HsinHai Rd., Taipei 106, Taiwan
Heui-Yung Chang: Department of Civil Engineering, National Chung Hsing University, 145, Xingda Rd, Taichung 402, Taiwan

Abstract
In this article, the vibration response of elastic nanocomposite beams with enhanced damping by nanoparticles is presented based on the mathematical model. Damp construction is considered by spring and damper elements based on the Kelvin model. Exponential shear deformation beam theory (ESDBT) has been used to model the structure. The mixed model model is used to obtain the effective properties of the structure including compaction effects. Using the energy method and Hamilton's principle, the equations of motion are calculated. The beam frequency is obtained by analytical method. The purpose of this work is to investigate the effect of volume percentage of nanoparticles and density, length and thickness of the beam on the frequency of the structure. The results show that the frequency increases with the increase in volume percentage of nanoparticles.

Key Words
beam; damping; ESDBT; frequency; numerical method

Address
A.A. Mosallaie Barzoki: Department of Mechanical Engineering, Kashan University, Iran
M. Saadantia: Department of Mechanical Engineering, University of Sydney
Hamed Karami: Department of Civil Engineering, Jasb Branch, Islamic Azad University, Jasb, Iran

Abstract
This experimental study investigates the effectiveness of applying carbon fiber reinforced polymer (CFRP) jackets for the retrofit of short reinforced concrete (RC) columns with inadequate transverse reinforcement and stirrup spacing to longitudinal rebar diameter equal to 12. RC columns scaled at 1/3, with round and square section, were subjected to axial compression up to failure. A damage scale is introduced for the assessment of the damage severity, which focusses on the extent of buckling of the longitudinal rebars. The damaged specimens were subsequently repaired with unidirectional CFRP jackets without any treatment of the buckled reinforcing bars and were finally re-tested to failure. Test results indicate that CFRP jackets may be effectively applied to rehabilitate RC columns (a) with inadequate transverse reinforcement constructed according to older practices so as to meet modern code requirements, and (b) with moderately buckled bars without the need of previously repairing the reinforcement bars, an application technique which may considerably facilitate the retrofit of earthquake damaged RC columns. Factors for the estimation of the reduced mechanical properties of the repaired specimens compared to the respective values for intact CFRP-jacketed specimens, in relation to the level of damage prior to retrofit, are proposed both for the compressive strength and the average modulus of elasticity. It was determined that the compressive strength of the retrofitted CFRP-jacketed columns is reduced by 90% to 65%, while the average modulus of elasticity is lower by 60% to 25% in respect to similar undamaged columns jacketed with the same layers of CFRP.

Key Words
axial compressive strength; buckling of longitudinal bars; damage level; retrofit with CFRP jacket; short reinforced concrete column; stiffness and ductility

Address
Marina L. Moretti: School of Architecture, National Technical University of Athens, GR-106-82 Athens, Greece

Abstract
Highly reliable and versatile methods artificial intelligence (AI) have found multiple application in the different fields of science, engineering and health care system. In the present study, we aim to utilize AI method to investigated vibrations in the human leg bone. In this regard, the bone geometry is simplified as a thick cylindrical shell structure. The deep neural network (DNN) is selected for prediction of natural frequency and critical buckling load of the bone cylindrical model. Training of the network is conducted with results of the numerical solution of the governing equations of the bone structure. A suitable optimization algorithm is selected for minimizing the loss function of the DNN. Generalized differential quadrature method (GDQM), and Hamilton's principle are used for solving and obtaining the governing equations of the system. As well as this, in the results section, with the aid of AI some predictions for improving the behaviors of the various sport systems will be given in detail.

Key Words
artificial intelligence; GDQM; Hamilton's principle; machine learning; sport systems

Address
Yongyong Wang and Qixia Jia: Ministry of Sports, Chongqing Jiaotong University, Chongqing 400074, Chongqing, China
Tingting Deng: Second Foreign Language School of Sichuan Foreign Studies University, Chongqing 400074, Chongqing, China
H. Elhosiny Ali: 1) Research Center for Advanced Materials Science (RCAMS), King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia, 2) Department of Physics, Faculty of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia, 3) Physics Department, Faculty of Science, Zagazig University, Zagazig 44519, Egypt

Abstract
The vibration of microtubule in human cells is the source of electrical field around it and inside cell structure. The induction of electrical field is a direct result of the existence of dipoles on the surface of the microtubules. Measuring the electrical fields could be performed using nano-scale sensors and the data could be transformed to other computers using internet of things (IoT) technology. Processing these data is feasible by artificial intelligence-based methods. However, the first step in analyzing the vibrational behavior is to study the mechanics of microtubules. In this regard, the vibrational behavior of the microtubules is investigated in the present study. A shell model is utilized to represent the microtubules' structure. The displacement field is assumed to obey first order shear deformation theory and classical theory of elasticity for anisotropic homogenous materials is utilized. The governing equations obtained by Hamilton's principle are further solved using analytical method engaging Navier's solution procedure. The results of the analytical solution are used to train, validate and test of the deep neural network. The results of the present study are validated by comparing to other results in the literature. The results indicate that several geometrical and material factors affect the vibrational behavior of microtubules.

Key Words
artificial intelligence; dynamics; Internet of Things; microtubule; viscoelastic properties

Address
Chunping Wang and Keming Chen: Shanghai Technical Institute of Electronics & Information, Fengxian 201141, Shanghai, China
Abbas Yaseen Naser: Information Technology Unit, Al mustaqbal University College, Babylon 51001, Iraq
H. Elhosiny Ali: 1) Research Center for Advanced Materials Science (RCAMS), King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia, 2) Department of Physics, Faculty of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia, 3) Physics Department, Faculty of Science, Zagazig University, Zagazig 44519, Egypt

Abstract
The presented paper considers infill masonry walls' influence on the seismic reliability of precast concrete frames. The recent Bojnord earthquake on May 13th, 2017 in Iran (MW 5.4) illustrated that the infill masonry walls play a crucial role in the damage extent and life safety issues of inhabitants in the precast concrete buildings. The incremental dynamic analysis (IDA) approach was used to determine the fragility curves of the represented damaged precast frame. Then, by integrating site hazard and structural fragilities, the seismic reliability of the represented precast frame was evaluated in different damage limit states. Additionally, the static pushover analysis (SPA) approach was used to assess the seismic performance assessment of the precast frame. Bare and infilled frames were modeled as 2D frames employing the OpenSees software platform. The multi-strut macromodel method was employed for infill masonry simulation. Also, a relatively efficient and straightforward nonlinear model was used to simulate the nonlinear behavior of the precast beam-column joint. The outputs show that consideration of the masonry infilled wall effect in all spans of the structural frame leads to a decrease in the possibility of exceedance of specified damage limit states in the structures. In addition, variation of hazard curves for buildings with and without consideration of infilled walls leads to a decrease in the reliability of the building's frames with masonry infilled walls. Furthermore, the lack of infill walls in the first story significantly affects the precast concrete frame's seismic reliability and performance.

Key Words
beam-column connection; infill masonry wall; precast concrete frame; seismic reliability

Address
Mahdi Adibi: 1) Engineering Faculty, Department of Civil Engineering, University of Bojnord, Iran, 2) Civil Engineering Department, Faculty of Engineering, Antalya Bilim University, Antalya, Turkey
Roozbeh Talebkhah: School of Civil Engineering, College of Engineering, University of Bojnord, Iran
Hamid Farrokh Ghatte: Civil Engineering Department, Faculty of Engineering, Antalya Bilim University, Antalya, Turkey

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