• Steel and Composite Structures
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• 제33권4호
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• pp.509-523
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• 2019

In the present work, the buckling analysis of micro sandwich plate with an isotropic/orthotropic cores and piezoelectric/polymeric nanocomposite face sheets is studied. In this research, two cases for core of micro sandwich plate is considered that involve five isotropic Devineycell materials (H30, H45, H60, H100 and H200) and an orthotropic material also two cases for facesheets of micro sandwich plate is illustrated that include piezoelectric layers reinforced by carbon and boron-nitride nanotubes and polymeric matrix reinforced by carbon nanotubes under temperature-dependent and hydro material properties on the elastic foundations. The first order shear deformation theory (FSDT) is adopted to model micro sandwich plate and to apply size dependent effects from modified strain gradient theory. The governing equations are derived using the minimum total potential energy principle and then solved by analytical method. Also, the effects of different parameters such as size dependent, side ratio, volume fraction, various material properties for cores and facesheets and temperature and humidity changes on the dimensionless critical buckling load are investigated. It is shown from the results that the dimensionless critical buckling load for boron nitride nanotube is lower than that of for carbon nanotube. It is illustrated that the dimensionless critical buckling load for Devineycell H200 is highest and lowest for H30. Also, the obtained results for micro sandwich plate with piezoelectric facesheets reinforced by carbon nanotubes (case b) is higher than other states (cases a and c).The results of this research can be used in aircraft, automotive, shipbuilding industries and biomedicine.

• Ocean Systems Engineering
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• 제8권4호
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• pp.381-407
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• 2018

This paper presents a hybrid numerical approach, which combines a two-phase Navier-Stokes model (NS) and the fully nonlinear potential theory (FNPT), for modelling wave-structure interaction. The former governs the computational domain near the structure, where the viscous and turbulent effects are significant, and is solved by OpenFOAM/InterDyMFoam which utilising the finite volume method (FVM) with a Volume of Fluid (VOF) for the phase identification. The latter covers the rest of the domain, where the fluid may be considered as incompressible, inviscid and irrotational, and solved by using the Quasi Arbitrary Lagrangian-Eulerian finite element method (QALE-FEM). These two models are weakly coupled using a zonal (spatially hierarchical) approach. Considering the inconsistence of the solutions at the boundaries between two different sub-domains governed by two fundamentally different models, a relaxation (transitional) zone is introduced, where the velocity, pressure and surface elevations are taken as the weighted summation of the solutions by two models. In order to tackle the challenges associated and maximise the computational efficiency, further developments of the QALE-FEM have been made. These include the derivation of an arbitrary Lagrangian-Eulerian FNPT and application of a robust gradient calculation scheme for estimating the velocity. The present hybrid model is applied to the numerical simulation of a fixed horizontal cylinder subjected to a unidirectional wave with or without following current. The convergence property, the optimisation of the relaxation zone, the accuracy and the computational efficiency are discussed. Although the idea of the weakly coupling using the zonal approach is not new, the present hybrid model is the first one to couple the QALE-FEM with OpenFOAM solver and/or to be applied to numerical simulate the wave-structure interaction with presence of current.

• Advances in nano research
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• 제7권4호
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• pp.233-240
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• 2019

The present research work reports in-vitro anti-cancer activity of biologically synthesized ZnO nanoparticles (ZnO NPs) against human carcinoma cells viz SCC-40, SK-MEL-2 and SCC-29B using Sulforhodamine-B (SRB) Assay. ZnO NPs were synthesized by a unique and novel biological route using Temperature-gradient phenomenon where the extract of combination of Catharanthus roseus (L.) G. Don (C. roseus), Azadirachta indica (A. indica), Ficus religiosa (F. religiosa) and NaOH solution were used as synthesis medium. The morphology of the ZnO NPs was characterized by Transmission Electron Microscopy (TEM). TEM images reveal that particle size of the samples reduces from 76 nm to 53 nm with the increase in reaction temperature and 68 nm to 38 nm with the increase in molar concentration of NaOH respectively. XRD study confirms the presence of elements and reduction in crystallite size with increase in reaction temperature and NaOH concentration. The diffraction peaks show broadening and a slight shift towards lower Bragg angle ($2{\theta}$) which represents the reduction in crystallite size as well as presence of uniform strain. The FTIR spectra of the extract show transmittance peak fingerprint of Zn-O bond and presence of bioactive molecules These NPs exhibit inhibition greater than 50% for SCC-40, SK-MEL-2 and SCC-29B cell lines and more than 50% cell kill for SCC-29B cells at concentrations < $80{\mu}g/ml$. Nanoparticles with smallest size have shown better anti-cancer activity and peculiar cell-selectivity. The combination of extracts of these plants with ZnO NPs can be used in targeted drug delivery as an effective anti-cancer agent, a potential application in cancer treatment.

• Journal of Ecology and Environment
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• 제45권1호
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• pp.1-9
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• 2021

Background: Abandoned coal piles after the closure of mines have a potential negative influence on the environment, such as soil acidification and heavy metal contamination. Therefore, revegetation by efficient species is required. For this, we wanted to identify the role of Silene acaulis in the succession of coal piles as a pioneer and a nurse plant. S. acaulis is a well-studied cushion plant living in the Arctic and alpine environments in the northern hemisphere. It has a highly compact cushion-like form and hosts more plant species under its canopy by ameliorating stressful microhabitats. In this research, we surveyed vegetation cover on open plots and co-occurring species within S. acaulis cushions in coal piles with different slope aspects and a control site where no coal was found. The plant cover and the similarity of communities among sites were compared. Also, the interaction effects of S. acaulis were assessed by rarefaction curves. Results: S. acaulis was a dominant species with the highest cover (6.7%) on the coal piles and occurred with other well-known pioneer species. Plant communities on the coal piles were significantly different from the control site. We found that the pioneer species S. acaulis showed facilitation, neutral, and competition effect in the north-east facing slope, the south-east facing slope, and the flat ground, respectively. This result was consistent with the stress gradient hypothesis because the facilitation only occurred on the north-east facing slope, which was the most stressed condition, although all the interactions observed were not statistically significant. Conclusions: S. acaulis was a dominant pioneer plant in the succession of coal piles. The interaction effect of S. acaulis on other species depended on the slope and its direction on the coal piles. Overall, it plays an important role in the succession of coal piles in the High Arctic, Svalbard.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• 한국지구과학회지
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• 제44권2호
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• pp.119-134
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• 2023

본 연구는 2021년 3월 1일부터 2일까지 영동지역에 강설이 발생했던 사례의 종관적, 열역학적, 역학적 특성을 분석한 것이다. 분석에 사용한 자료는 AWS 관측자료, 지상일기도, ERA5 재분석 자료, 레윈존데, 천리안 2A 위성 자료, WISSDOM 자료 등이다. 사례 기간 영동지역 4개소에서 관측된 적설은 10 cm 이상으로 나타났으며, 북강릉(37.4 cm)에서는 가장 많은 적설을 보였다. 종관 분석결과, 동해상 및 영동지역 주변으로 중·상층 대기의 매우 차고 건조한 대기와 상대적으로 따뜻한 하층 대기의 온도 차이로 대류 불안정이 형성되어 북강릉 지역으로 대류운의 발달과 함께 강설이 나타났다. 특히 열역학적 및 운동학적 연직 분석에서, 하층에서 온위의 연직 경도에 의한 강한 바람과 한랭이류에 의한 대류 불안정이 영동지역의 강설 발생에 큰 역할을 한 것으로 판단된다. 이러한 결과는 레윈존데의 연직 분석에서도 확인할 수 있었다.

• Ocean and Polar Research
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• 제45권2호
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• pp.57-69
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• 2023

Growth responses along the gradient of water temperature, salinity, and light intensity and cytotoxicity against Artemia nauplii were explored using Ostreopsis sp. and Coolia canariensis strains, representing the two potentially toxic epiphytic dinoflagellate (EPD) species from Jeju coastal waters of Korea. Variation in maximum growth rate (GRmax) and maximum biomass yield (Ymax) along the environmental gradients was quite contrasting between the two strains, which appears to be reflected in the in situ abundance distribution of the corresponding genera. The more eurythermal characteristics of Ostreopsis sp. strain were in good agreement with the relative distribution of Ostreopsis spp. and Coolia spp. in 520 macroalgal samples collected from 6 stations. The more stenohaline C. canariensis strain was well matched by a markedly narrower range of salinities in the in situ distribution of Coolia spp. than the salinity range for Ostreopsis species. The differences in light adaptation between the high light-preferring Ostreopsis sp. strain and the more euryphotic C. canariensis strain were remarkably consistent with the distinct vertical profiles of Ostreopsis spp. and Coolia spp. abundance in the red alga Amphiroa sp. off Moom-seom. Cytotoxicity against Artemia nauplii in the Ostreopsis sp. preparation with 1000 cells ml^-1 was similar to that in C. canariensis preparation with 12000 cells ml^-1, which is noteworthy. Thus, the new potential cytotoxicity risks from C. canariensis along with the well-known toxic genus Ostreopsis may be introduced to Jeju coasts, which necessitates further exploration into the contrasting ecological niches occupied by EPD species in relation to their cytotoxicity.

• 산업경영시스템학회지
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• 제46권1호
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• pp.23-31
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• 2023

Research and interest in sustainable printing are increasing in the packaging printing industry. Currently, predicting the amount of ink required for each work is based on the experience and intuition of field workers. Suppose the amount of ink produced is more than necessary. In this case, the rest of the ink cannot be reused and is discarded, adversely affecting the company's productivity and environment. Nowadays, machine learning models can be used to figure out this problem. This study compares the ink usage prediction machine learning models. A simple linear regression model, Multiple Regression Analysis, cannot reflect the nonlinear relationship between the variables required for packaging printing, so there is a limit to accurately predicting the amount of ink needed. This study has established various prediction models which are based on CART (Classification and Regression Tree), such as Decision Tree, Random Forest, Gradient Boosting Machine, and XGBoost. The accuracy of the models is determined by the K-fold cross-validation. Error metrics such as root mean squared error, mean absolute error, and R-squared are employed to evaluate estimation models' correctness. Among these models, XGBoost model has the highest prediction accuracy and can reduce 2134 (g) of wasted ink for each work. Thus, this study motivates machine learning's potential to help advance productivity and protect the environment.

• Geomechanics and Engineering
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• 제31권3호
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• pp.237-248
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• 2022

Nowadays, more and more subway tunnels were planed and constructed underneath the ground of urban cities to relieve the congested traffic. Potential damage may occur in existing tunnel if the new tunnel is constructed too close. So far, previous studies mainly focused on the tunnel-tunnel interactions with circular shape. The difference between circular and horseshoe shaped tunnel in terms of deformation mechanism is not fully investigated. In this study, three-dimensional numerical parametric studies were carried out to explore the effect of different tunnel shapes on the complicated tunnel-tunnel interaction problem. Parameters considered include volume loss, tunnel stiffness and relative density. It is found that the value of volume loss play the most important role in the multi-tunnel interactions. For a typical condition in this study, the maximum invert settlement and gradient along longitudinal direction of horseshoe shaped tunnel was 50% and 96% larger than those in circular case, respectively. This is because of the larger vertical soil displacement underneath existing tunnel. Due to the discontinuous hoop axial stress in horseshoe shaped tunnel, significant shear stress was mobilized around the axillary angles. This resulted in substantial bending moment at the bottom plate and side walls of horseshoe shaped tunnel. Consequently, vertical elongation and horizontal compression in circular existing tunnel were 45% and 33% smaller than those in horseshoe case (at monitored section X/D = 0), which in latter case was mainly attributed to the bending induced deflection. The radial deformation stiffness of circular tunnel is more sensitive to the Young's modulus compared with horseshoe shaped tunnel. This is because of that circular tunnel resisted the radial deformation mainly by its hoop axial stress while horseshoe shaped tunnel do so mainly by its flexural rigidity. In addition, the reduction of soil stiffness beneath the circular tunnel was larger than that in horseshoe shaped tunnel at each level of relative density, indicating that large portion of tunneling effect were undertaken by the ground itself in circular tunnel case.

• 한국지하수토양환경학회지:지하수토양환경
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• 제28권5호
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• pp.12-24
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• 2023

The Songji lagoon is brackish environment with a mixture of saline and fresh water, and the interaction of groundwater-lagoon water creates a physicochemical gradient. Although some studies have been conducted on the hydrological and geochemical characteristics of the Songji lagoon, microbial ecological studies have not yet been conducted. In this study, we investigated the effect of groundwater and surface water interaction on water quality as well as microbial community changes in the Songji Lagoon using 16S rRNA gene sequencing. Hydrochemical analyses show that samples were classified as 5 hydrochemical facies (HF) and hydrochemical facies evolution (HFE) revealed the intrusion phase was more dominant (57.9%) than the freshening phase (42.1%). Higher microbial diversity was found in freshwater in comparison to saline water samples. The microbial community at the phylum level shows the most dominance of Proteobacteria with an average of 37.3%, followed by Bacteroidota, Actinobacteria, and Patescibacteria. Heat map analyses of the top 18 genera showed that samples were clustered into 5 groups based on type, and Pseudoalteromonas could be used potential indicator for seawater intrusion.