• Structural Engineering and Mechanics
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• 제84권6호
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• pp.823-829
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• 2022

This study considered the experimental parameters (Nano-graphene oxide reinforced polycarbonate, GFRP) under low-velocity impact load and vibration analysis. The effect of nano-graphene oxide (NGO) on a polycarbonate-based composite was studied. Two test procedures were adopted to obtain experimental results, vibration analysis. The mechanical tests were performed on damaged and non-damaged specimens to determine the damaging effect on the composite specimens. After the test was carried out, the effect of NGO was measured and damping factors were ascertained experimentally. 0. 2 wt% NGO was determined as the optimum amount that best affected the Vibration Analysis. The experiments revealed that the composite's damping properties were increased by adding the nanoparticles to 0.25 wt% and decreased slightly for the specimens with the highest nanoparticles content. Cyclic sinus loading was applied at a frequency of 3.5 Hz. This paper study the frequency effect of 3.5khz frequency damage on mechanical results. Found that high frequency will worthlessly affect the fatigue life in NGO/polycarbonate composite. In 3.5 Hz frequency, it was chosen to decrease the heat by frequency. Transmission electron microscopy (TEM) micrographs were used to investigate the distribution of NGO on the polycarbonate matrix and revealed a homogeneous mixture of nano-composites and strong bonding between NGO and the polycarbonate which increased the damping properties and decreased vibration. Finally, experimental modal analysis was conducted after the high-velocity impact damage process to investigate the defect on the NGO polycarbonate composites.

• 대한약침학회지
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• 제26권1호
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• pp.53-59
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• 2023

Objectives: The most prominent microorganisms that cause hospital infections and acquire antibiotic resistance are Staphylococcus aureus and Pseudomonas aeruginosa. The present study aimed to compare the phenolic and flavonoid compounds of various Allium ampeloprasum and Allium porrum extracts and evaluate the antibacterial effects of these extracts against these two microorganisms. Methods: The total phenolic and flavonoid contents of the acetone, methanol, aqueous, and hexane leeks extracts from A. ampeloprasum and A. porrum were measured. The antibacterial activity of these extracts against S. aureus and P. aeruginosa was tested using the disk diffusion method for 24, 48, and 72 hours. Further, the minimum inhibitory concentrations and the minimum bactericidal concentrations of these extracts for these two bacteria were evaluated and compared with those of common antibiotics. Results: The aqueous extracts showed the highest phenolic and flavonoid contents and at concentrations of 35 and 40 mg per disk, showed the most antibacterial activity against S. aureus and P. aeruginosa; P. aeruginosa showed more sensitivity to the aqueous extracts than S. aureus. Conclusion: Aqueous A. ampeloprasum and A. porrum extracts may prevent the growth of hospital pathogens, especially P. aeruginosa; our findings will aid the discovery of new antimicrobial substances against antibiotic-resistant bacteria.

• Geomechanics and Engineering
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• 제30권6호
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• pp.551-564
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• 2022

Fragmenting the rock mass is considered as the most important work in open-pit mines. Ground vibration is the most hazardous issue of blasting which can cause critical damage to the surrounding structures. This paper focuses on developing an explicit model to predict the ground vibration through an multi objective evolutionary polynomial regression (MOGA-EPR). To this end, a database including 79 sets of data related to a quarry site in Malaysia were used. In addition, a gene expression programming (GEP) model and several empirical equations were employed to predict ground vibration, and their performances were then compared with the MOGA-EPR model using the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R²) and a20-index. Comparing the results, it was found that the MOGA-EPR model predicted the ground vibration more precisely than the GEP model and the empirical equations, where the MOGA-EPR scored lower MAE and RMSE, 𝜇 and 𝜎 closer to the optimum value, and higher R² and a20-index. Accordingly, the proposed MOGA-EPR model can be introduced as a useful method to predict ground vibration and has the capacity to be generalized to predict other blasting effects.

• Advances in nano research
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• 제13권4호
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• pp.369-378
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• 2022

Dynamic study of concrete plates under impact load is presented in this article. The main objective of this work is presenting a mathematical model for the concrete plates under the impact load. The concrete plate is reinforced by carbon nanoparticles which the effective material proprieties are obtained by mixture's rule. Impacts are assumed to occur normally over the top layer of the plate and the interaction between the impactor and the structure is simulated using a new equivalent three-degree-of-freedom (TDOF) spring-mass-damper (SMD) model. The structure is assumed viscoelastic based on Kelvin-Voigt model. Based on the classical plate theory (CPT), energy method and Hamilton's principle, the motion equations are derived. Applying DQM, the dynamic deflection and contact force of the structure are calculated numerically so that the effects of mass, velocity and height of the impactor, volume percent of nanoparticles, structural damping and geometrical parameters of structure are shown on the dynamic deflection and contact force. Results show that considering structural damping leads to lower dynamic deflection and contact force. In addition, increasing the volume percent of nanoparticles yields to decreases in the deflection.

• Steel and Composite Structures
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• 제45권4호
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• pp.555-562
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• 2022

Improving the mechanical properties of concrete in the construction industry in order to increase resistance to dynamic and static loads is one of the essential topics for researchers. In this work, vibration analysis of elastic nanocomposite beams reinforced by nanoparticles based on mathematical model is presented. For modelling of the strucuture, sinusoidal shear deformation beam theory (SSDBT) is utilized. Mori-anak model model is utilized for obtaining the effective properties of the strucuture including agglomeration influences. Utilizing the energy method and Hamilton's principal, the motion equations are calculated. The frequency of the elastic nanocomposite beam is obtanied by analytical method. The aim of this work is investigating the effects of nanoparticles volume percent and agglomeration, length and thickness of the beam on the frequency of the structure. The results show that the with enhancing the nanoparticles volume percent, the frequency is increased. In addition, the water absorption of the concrete is presented in this article.

• Geomechanics and Engineering
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• 제37권1호
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• pp.21-29
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• 2024

The effective management of damage in tunnels is crucial for ensuring their safety, longevity, and operational efficiency. In this paper, we propose an educational management model tailored specifically for addressing damage in tunnels, utilizing numerical solution techniques. By leveraging advanced computational methods, we aim to develop a comprehensive understanding of the factors contributing to tunnel damage and to establish proactive measures for mitigation and repair. The proposed model integrates principles of tunnel engineering, structural mechanics, and numerical analysis to facilitate a systematic approach to damage assessment, diagnosis, and management. Through the application of numerical solution techniques, such as finite element analysis, we demonstrate the efficacy of the proposed model in simulating various damage scenarios and predicting their impact on tunnel performance. Additionally, the educational component of the model provides valuable insights and training opportunities for tunnel management personnel, empowering them to make informed decisions and implement effective strategies for ensuring the structural integrity and safety of tunnel infrastructure. Overall, the proposed educational management model represents a significant advancement in tunnel management practices, offering a proactive and knowledge-driven approach to addressing damage and enhancing the resilience of tunnel systems.

• Bulletin of the Korean Chemical Society
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• 제27권9호
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• pp.1439-1444
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• 2006

A $Cu^{2+}$ ion-selective membrane microelectrode has been fabricated from poly vinyl chloride (PVC) matrix membrane containing a new symmetrical hexadentate Schiff,s base 2-{1-(E)-2-((Z)-2-{(E)-2-[(Z)-1-(2-hydroxyphenyl)ethylidene]hydrazono}-1-methylpropylidene)hydrazono]ethyl}phenol (HDNOS) as a neutral carrier, Potassium tetrakis(4-chlorophenyl) borate (KTpClPB) as an anionic excluder and o-nitrophenyloctyl ether (NPOE) as a plasticizing solvent mediator. The microelectrode displays linear potential response in the concentration range of $1.0\;{\times}\;10^{-5}-1.0\;{\times}\;10^{-11}$ M of $Cu^{2+}$. The microelectrode exhibits a nice Nernstian slope of 25.9 ${\pm}$ 0.3 mV $decade^{-1}$ in the pH range of 3.1-8.1. The sensor has a relatively short response time in whole concentration ranges ($\sim$5 s). The detection limit of proposed sensor is $5.0\;{\times}\;10^{-12}$ M (320 pg/L), and it can be used over a period of eight weeks. The practical utility of the sensor has been demonstrated by using it as an indicator electrode in the potentiometric titration of $Cu^{2+}$ with EDTA. The proposed membrane electrode was used for the direct determining of $Cu^{2+}$ content in black and red pepper, and in waste water samples.

• Structural Engineering and Mechanics
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• 제65권5호
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• pp.587-600
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• 2018

Infill panel is the first element of a building subjected to blast loading activating its out-of-plane behavior. If the infill panel does not have enough ductility against the loading, it breaks and gets damaged before load transfer and energy dissipation. As steel infill panel has appropriate ductility before fracture, it can be used as an alternative to typical infill panels under blast loading. Also, it plays a pivotal role in maintaining sensitive main parts against blast loading. Concerning enough ductility of the infill panel out-of-plane behavior, the impact force enters the horizontal diaphragm and is distributed among the lateral elements. This article investigates the behavior of steel infill panels with different thicknesses and stiffeners. In order to precisely study steel infill panels, different ranges of blast loading are used and maximum displacement of steel infill under such various blast loading is studied. In this research, finite element analyses including geometric and material nonlinearities are used for optimization of the steel plate thickness and stiffener arrangement to obtain more efficient design for its better out-of-plane behavior. The results indicate that this type of infill with out-of-plane behavior shows a proper ductility especially in severe blast loadings. In the blasts with high intensity, maximum displacement of infill is more sensitive to change in the thickness of plate rather the change in number of stiffeners such that increasing the number of stiffeners and the plate thickness of infill panel would decrease energy dissipation by 20 and 77% respectively. The ductile behavior of steel infill panels shows that using infill panels with less thickness has more effect on energy dissipation. According to this study, the infill panel with 5 mm thickness works better if the criterion of steel infill panel design is the reduction of transmitted impulse to main structure. For example in steel infill panels with 5 stiffeners and blast loading with the reflected pressure of 375 kPa and duration of 50 milliseconds, the transmitted impulse has decreased from 41206 N.Sec in 20 mm infill to 37898 N.Sec in 5 mm infill panel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1624-1647
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• 2020

Vehicular network is one of the most important subjects for researchers in recent years. Anycast routing protocols have many applications in vehicular ad hoc networks. The aim of an anycast protocol is sending packets to at least one of the receivers among candidate receivers. Studies done on anycast protocols over vehicular networks, however, have capability of implementation on some applications; they are partial, and application specific. No need to say that the lack of a comprehensive study, having a strong analytical background, is felt. Mathematical modeling in vehicular networks is difficult because the topology of these networks is dynamic. In this paper, it has been demonstrated that vehicular networks can be modeled based on time-expanded networks. The focus of this article is on geographical anycast. Three different scenarios were proposed including sending geographic anycast packet to exactly-one-destination, to at-least-one-destination, and to K-anycast destination, which can cover important applications of geographical anycast routing protocols. As the proposed model is of MILP type, a decentralized heuristic algorithm was presented. The evaluation process of this study includes the production of numerical results by Branch and Bound algorithm in general algebraic modeling system (GAMS) software and simulation of the proposed protocol in OMNET++ simulator. The comprehension of the result of proposed protocol and model shows that the applicability of this proposed protocol and its reactive conformity with the presented models based on presented metrics.

• Journal of Animal Science and Technology
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• 제58권1호
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• pp.1.1-1.6
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• 2016

Background: Genotype imputation is an important process of predicting unknown genotypes, which uses reference population with dense genotypes to predict missing genotypes for both human and animal genetic variations at a low cost. Machine learning methods specially boosting methods have been used in genetic studies to explore the underlying genetic profile of disease and build models capable of predicting missing values of a marker. Methods: In this study strategies and factors affecting the imputation accuracy of parent-offspring trios compared from lower-density SNP panels (5 K) to high density (10 K) SNP panel using three different Boosting methods namely TotalBoost (TB), LogitBoost (LB) and AdaBoost (AB). The methods employed using simulated data to impute the un-typed SNPs in parent-offspring trios. Four different datasets of G1 (100 trios with 5 k SNPs), G2 (100 trios with 10 k SNPs), G3 (500 trios with 5 k SNPs), and G4 (500 trio with 10 k SNPs) were simulated. In four datasets all parents were genotyped completely, and offspring genotyped with a lower density panel. Results: Comparison of the three methods for imputation showed that the LB outperformed AB and TB for imputation accuracy. The time of computation were different between methods. The AB was the fastest algorithm. The higher SNP densities resulted the increase of the accuracy of imputation. Larger trios (i.e. 500) was better for performance of LB and TB. Conclusions: The conclusion is that the three methods do well in terms of imputation accuracy also the dense chip is recommended for imputation of parent-offspring trios.