An innovative approach for modeling of hysteretic energy demand in steel moment resisting frames

Gandomi, Amir H.; Alavi, Amir H.; Asghari, Abazar; Niroomand, Hadi; Nazar, Ali Matin

doi:10.1007/s00521-013-1342-x

Cited by 22 publications

(8 citation statements)

References 24 publications

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“…However, modern civil infrastructure systems are designed to achieve advanced functionalities for multipurpose applications under critical conditions such as earthquakes, storms and typhoons [ 127 ]. There are serious concerns about the integrity of such complex structural systems.…”

Section: Discussion: Piezoelectric Sensing Techniques For Smart Anmentioning

confidence: 99%

Piezoelectric Sensing Techniques in Structural Health Monitoring: A State-of-the-Art Review

Jiao

Egbe

Xie

et al. 2020

Sensors

137

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Recently, there has been a growing interest in deploying smart materials as sensing components of structural health monitoring systems. In this arena, piezoelectric materials offer great promise for researchers to rapidly expand their many potential applications. The main goal of this study is to review the state-of-the-art piezoelectric-based sensing techniques that are currently used in the structural health monitoring area. These techniques range from piezoelectric electromechanical impedance and ultrasonic Lamb wave methods to a class of cutting-edge self-powered sensing systems. We present the principle of the piezoelectric effect and the underlying mechanisms used by the piezoelectric sensing methods to detect the structural response. Furthermore, the pros and cons of the current methodologies are discussed. In the end, we envision a role of the piezoelectric-based techniques in developing the next-generation self-monitoring and self-powering health monitoring systems.

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Section: Discussion: Piezoelectric Sensing Techniques For Smart Anmentioning

confidence: 99%

Piezoelectric Sensing Techniques in Structural Health Monitoring: A State-of-the-Art Review

Jiao

Egbe

Xie

et al. 2020

Sensors

137

View full text Add to dashboard Cite

show abstract

“…The use of fog computing with the network's decentralization allows for wider geographical distribution than traditional networking or cloud computing. It will lead to better quality service for the end user [48][49][50][51]. Fourth is analysis instantaneously.…”

Section: Related Workmentioning

confidence: 99%

DMTC: Optimize Energy Consumption in Dynamic Wireless Sensor Network Based on Fog Computing and Fuzzy Multiple Attribute Decision‐Making

Varmaghani

Nazar

Ahmadi

et al. 2021

Wireless Communications and Mobile Computing

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Advances in wireless technologies and small computing devices, wireless sensor networks can be superior technology in many applications. Energy supply constraints are one of the most critical measures because they limit the operation of the sensor network; therefore, the optimal use of node energy has always been one of the biggest challenges in wireless sensor networks. Moreover, due to the limited lifespan of nodes in WSN and energy management, increasing network life is one of the most critical challenges in WSN. In this investigation, two computational distributions are presented for a dynamic wireless sensor network; in this fog-based system, computing load was distributed using the optimistic and blind method between fog networks. The presented method with the main four steps is called Distribution-Map-Transfer-Combination (DMTC) method. Also, Fuzzy Multiple Attribute Decision-Making (Fuzzy MADM) is used for clustering and routing network based on the presented distribution methods. Results show that the optimistic method outperformed the blind one and reduced energy consumption, especially in extensive networks; however, in small WSNs, the blind scheme resulted in an energy efficiency network. Furthermore, network growth leads optimistic WSN to save higher energy in comparison with blinded ones. Based on the results of complexity analysis, the presented optimal and blind methods are improved by 28% and 48%, respectively.

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“…By using genetic operators, population evolution occurs upon the selection of a population consisting of individuals (Gandomi et al 2014a). The algorithm, shown in Figure 2, is terminated if an acceptable fitness level is achieved.…”

Section: Gene Expression Programmingmentioning

confidence: 99%

Force–Displacement Relationship of the Butterfly-Shaped Beams Based on Gene Expression Programming

et al. 2020

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Structural steel plates with engineered cut-outs to exhibit controlled yielding mechanism is recently proposed for desirable structural performance compared to conventional systems.Butterfly-shaped beams with hexagonal cut-outs inside of the beam's web is implemented to better align the bending strength diagram along the link length with the corresponding demand shape of the applied moment diagram. In previous studies, it has been reported that these links have a substantial energy dissipation capability and sufficient ductility which necessities further investigations and structural behavior prediction studies. In this study, a set of 240 nonlinear finite element models are developed for creation of a database and subsequently calibrated with finite element software packages. The capability of the gene expression programming (GEP) is explored for prediction of force-displacement relationship of a butterfly-shaped beam. Two new models are developed based on the reliable generated database. Subsequently, the proposed models are validated with several conducted analysis and statistical parameters, for which the comparisons are shown in details. The results represent that the proposed models are able to predict the forcedisplacement relationship of a butterfly-shaped beam with satisfactory accuracy.

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An innovative approach for modeling of hysteretic energy demand in steel moment resisting frames

Cited by 22 publications

References 24 publications

Piezoelectric Sensing Techniques in Structural Health Monitoring: A State-of-the-Art Review

Piezoelectric Sensing Techniques in Structural Health Monitoring: A State-of-the-Art Review

DMTC: Optimize Energy Consumption in Dynamic Wireless Sensor Network Based on Fog Computing and Fuzzy Multiple Attribute Decision‐Making

Force–Displacement Relationship of the Butterfly-Shaped Beams Based on Gene Expression Programming

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