• Smart Structures and Systems
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• v.18 no.4
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• pp.787-800
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• 2016

The aim of the paper is to analyze nonlinear transverse vibration of an embedded piezoelectric plate reinforced with single walled carbon nanotubes (SWCNTs). The system in rested in a Pasternak foundation. The micro-electro-mechanical model is employed to calculate mechanical and electrical properties of nanocomposite. Using nonlinear strain-displacement relations and considering charge equation for coupling between electrical and mechanical fields, the motion equations are derived based on energy method and Hamilton's principle. These equations can't be solved analytically due to their nonlinear terms. Hence, differential quadrature method (DQM) is employed to solve the governing differential equations for the case when all four ends are clamped supported and free electrical boundary condition. The influences of the elastic medium, volume fraction and orientation angle of the SWCNTs reinforcement and aspect ratio are shown on frequency of structure. The results indicate that with increasing volume fraction of SWCNTs, the frequency increases. This study might be useful for the design and smart control of nano/micro devices such as MEMS and NEMS.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.517-520
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• 2008

In this study, corrosion resistance of steel in cracked-reinforced concrete was performed according to experimental method. Mixed design is OPC, 30% PFA, 60% GGBS and 10% SF, respectively. Moreover, corrosion resistance test was measured using ultra testing machine for 0.3mm crack induction. The corrosion resistance of blended concrete shows the results following OPC > 10%SF > 30% PFA > 60% GGBS after 60days curing. In case of mass loss test, embedded reinforcement in OPC concrete surveyed the minimum corrosion and appeared better corrosion resistance than blended concrete. As a result, corrosion resistance of sound concrete is higher than cracked concrete. Moreover, corrosion resistance of binary concrete is lower than OPC.

• Steel and Composite Structures
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• v.23 no.6
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• pp.691-714
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• 2017

Rotating fluid induced vibration and instability of embedded piezoelectric nano-composite separators subjected to magnetic and electric fields is the main contribution of present work. The separator is modeled with cylindrical shell element and the structural damping effects are considered by Kelvin-Voigt model. Single-walled carbon nanotubes (SWCNTs) are used as reinforcement and effective material properties are obtained by mixture rule. The perturbation velocity potential in conjunction with the linearized Bernoulli formula is used for describing the rotating fluid motion. The orthotropic surrounding elastic medium is considered by spring, damper and shear constants. The governing equations are derived on the bases of classical shell theory (CST), first order shear deformation theory (FSDT) and sinusoidal shear deformation theory (SSDT). The nonlinear frequency and critical angular fluid velocity are calculated by differential quadrature method (DQM). The detailed parametric study is conducted, focusing on the combined effects of the external voltage, magnetic field, visco-Pasternak foundation, structural damping and volume percent of SWCNTs on the stability of structure. The numerical results are validated with other published works as well as comparing results obtained by three theories. Numerical results indicate that with increasing volume fraction of SWCNTs, the frequency and critical angular fluid velocity are increased.

• Smart Structures and Systems
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• v.17 no.1
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• pp.31-43
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• 2016

Applications of ultrasonic tomography to concrete structures have been reported for many years. However, practical and effective application of this tool for nondestructive assessment of internal concrete condition is hampered by time consuming transducer coupling that limits the amount of ultrasonic data that can be collected. This research aims to deploy recent developments in air-coupled ultrasonic measurements of solids, described in Part 1 of this paper set, to concrete in order to image internal inclusions. Ultrasonic signals are collected from concrete samples using a fully air-coupled (contactless) test configuration. These air coupled data are compared to those collected using partial semi-contact and full-contact test configurations. Two samples are considered: a 150 mm diameter cylinder with an internal circular void and a prism with $300mm{\times}300mm$ square cross-section that contains internal damaged regions and embedded reinforcement. The heterogeneous nature of concrete material structure complicates the application and interpretation of ultrasonic measurements and imaging. Volumetric inclusions within the concrete specimens are identified in the constructed velocity tomograms, but wave scattering at internal interfaces of the concrete disrupts the images. This disruption reduces defect detection accuracy as compared with tomograms built up of data collected from homogeneous solid samples (PVC) that are described in Part 1 of this paper set. Semi-contact measurements provide some improvement in accuracy through higher signal-to-noise ratio while still allowing for reasonably rapid data collection.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.2
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• pp.267-270
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• 2021

Long-term experiments have been conducted on two important safety issues: long-term durability of a concrete barrier with the steel reinforcements and gas generation from low-and intermediate-level wastes in an underground research tunnel of a radioactive waste disposal facility. The gas generation and microbial communities were monitored from waste packages (200 L and 320 L) containing simulated dry active wastes. In the concrete experiment, corrosion sensors were installed on the steel reinforcements which were embedded 10 cm below the surface of concrete in a concrete mock-up, and groundwater was fed into the mock-up at a pressure of 2.1 bars to accelerate groundwater infiltration. No clear evidence was observed with respect to corrosion initiation of the steel reinforcement for 4 years of operation. This is attributed to the high integrity and low hydraulic conductivity of the concrete. In the gas generation experiment, significant levels of gas generation were not measured for 4 years. These experiments are expected to be conducted for a period of more than 10 years.

• Steel and Composite Structures
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• v.48 no.2
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• pp.131-143
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• 2023

The CFRP bar was used to achieve more ductile and durable headed-stud shear connectors in composite components. Three series of push-out tests were firstly conducted, including specimens reinforced with pure steel fibers, steel and CFRP bars. The distributed stress was measured by the commercial PPP-BOTDA (Pre-Pump-Pulse Brillouin optical time domain analysis) optical fiber sensor with high spatial resolution. A series of numerical analyses using non-linear FE models were also made to study the shear force transfer mechanism and crack response based on the test results. Test results show that the CFRP bar increases the shear strength and stiffness of the large diameter headed-stud shear connection, and it has equivalent reinforcing effects on the stud shear capacity as the commonly used steel bar. The embedded CFRP bar can also largely improve the shear force transfer mechanism and decrease the tensile stress in the transverse direction. The parametric study shows that low content steel fibers could delay the crack initiation of slab around the large diameter stud, and the CFRP bar with normal elastic modulus and the standard reinforcement ratio has good resistance to splitting crack growth in headed stud shear connectors.

• Advances in concrete construction
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• v.15 no.1
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• pp.1-10
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• 2023

Concrete is one of the most widely used structure materials. Concrete is like the motor of the construction industry. The remarkable feature of this Concrete is its cheapness and low energy consumption. Concrete alone does not show resistance against any force but only against compressive forces. Therefore, steel rebar product is used as a reinforcement and increase the strength of Concrete. It can be done by putting rebar in Concrete in different ways. Rebar rusting is one of the crucial symptoms that cause swift destruction in reinforced structures-factors such as moisture in concrete increase the steel corrosion rate. In most cases, it is difficult to compensate for the damage caused by the corrosion of base metals, so preventing corrosion will be much more cost-effective. Coatings made with nanotechnology can protect Concrete against external degradation factors to prevent water and humidity from penetrating the Concrete and prevent rusting and corrosion of the rebar inside. It prevents water penetration and contamination into the Concrete and increases the Concrete's quality and structural efficiency. In this research, silica and titanium dioxide nanoparticle coatings have been used due to their suitable electrical and thermal properties, resistance to oxidation, corrosion, and wear to prevent the corrosion of rebars in Concrete. The results of this method show that these nanoparticles significantly improve the corrosion resistance of rebars.

• Steel and Composite Structures
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• v.49 no.1
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• pp.109-123
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• 2023

Headed studs welded to steel beams and embedded within the concrete of deck slabs are vital components of modern composite floor systems, where safety and economy depend on the accurate predictions of the stud shear resistance. The multitude of existing deck profiles and the complex behavior of studs in deck slab ribs makes developing accurate and reliable mechanical or empirical design models challenging. The paper addresses this issue by presenting a machine learning (ML) model developed from the natural gradient boosting (NGBoost) algorithm capable of producing probabilistic predictions and a database of 464 push-out tests, which is considerably larger than the databases used for developing existing design models. The proposed model outperforms models based on other ML algorithms and existing descriptive equations, including those in EC4 and AISC 360, while offering probabilistic predictions unavailable from other models and producing higher shear resistances for many cases. The present study also showed that the stud shear resistance is insensitive to the concrete elastic modulus, stud welding type, location of slab reinforcement, and other parameters considered important by existing models. The NGBoost model was interpreted by evaluating the feature importance and dependence determined with the SHapley Additive exPlanations (SHAP) method. The model was calibrated via reliability analyses in accordance with the Eurocodes to ensure that its predictions meet the required reliability level and facilitate its use in design. An interactive open-source web application was created and deployed to the cloud to allow for convenient and rapid stud shear resistance predictions with the developed model.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.143-151
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• 2006

This paper presents the comparison of the goodness-of-fit test of analytical bond models between concrete and steel or GFRP reinforcements. Bond test specimens were prepared in accordance with the CSA codes and the rebars used in the test were steel and two types of commercial GFRP rebar products. Using the test data, a bond model was proposed, and comparison of goodness-of-fit test for existing bond models and proposed bond model was carried out by the least squares method. The result indicates that the proposed bond model has better goodness-of-fit test than the existing ones.

• Smart Structures and Systems
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• v.33 no.5
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• pp.333-347
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• 2024

There has been an increasing interest in the construction of smart buildings that can actively monitor and react to their surroundings. The capacity of these intelligent structures to precisely predict and respond to deflection is a crucial feature that guarantees both their structural soundness and efficiency. Conventional techniques for determining deflection often depend on intricate mathematical models and computational simulations, which may be time- and resource-consuming. Artificial intelligence (AI) algorithms have become a potent tool for anticipating and controlling deflection in intelligent structures in response to these difficulties. The term "deflection-aware smart structures" in this sense refers to constructions that have AI algorithms installed that continually monitor and analyses deflection data in order to proactively detect any problems and take appropriate action. These structures anticipate deflection across a range of operating circumstances and environmental factors by using cutting-edge AI approaches including deep learning, reinforcement learning, and neural networks. AI systems are able to predict real-time deflection with high accuracy by using data from embedded sensors and actuators. This capability enables the systems to identify intricate patterns and linkages. Intelligent buildings have the potential to self-correct in order to reduce deflection and maximize performance. In conclusion, the development of deflection-aware smart structures is a major stride forward for structural engineering and has enormous potential to enhance the performance, safety, and dependability of designed systems in a variety of industries.