• Journal of Powder Materials
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• v.28 no.5
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• pp.429-434
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• 2021

Magnetic nanoparticles have a significant impact on the development of basic sciences and nanomedical, electronic, optical, and biotech industries. The development of magnetic structures with size homogeneity, magnetization, and particle dispersibility due to high-quality process development can broaden their utilization for separation analysis, structural color optics using surface modification, and energy/catalysts. In addition, magnetic nanoparticles simultaneously exhibit two properties: magnetic and plasmon resonance, which can be self-assembled and can improve signal sensitivity through plasmon resonance. This paper reports typical examples of the synthesis and properties of various magnetic nanoparticles, especially magnetoplasmonic nanoparticles developed in our laboratory over the past decade, and their optical, electrochemical, energy/catalytic, and bio-applications. In addition, the future value of magnetoplasmonic nanoparticles can be reevaluated by comparing them with that reported in the literature.

• Journal of the Korean GEO-environmental Society
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• v.20 no.12
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• pp.41-47
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• 2019

This paper deals with the reliability analysis of foundation for an offshore wind turbine system. Reliability analyses were carried out for suction bucket foundation considering the uncertainties in soil and structural parameters. In reliability analysis, the vertical and lateral resistances are defined as base limit states. The case studies were carried out using the preliminarily designed foundations at western-south mainland sea of Korea. From reliability analyses, vertical resistance for free-slip condition has overall lower reliability index, and submerged unit weight and internal friction angle of seabed soil are governing factors in vertical and lateral resistance in this case.

• Structural Engineering and Mechanics
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• v.77 no.2
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• pp.231-243
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• 2021

In this paper, a dynamic response mapping model of the wheel-rail system is established by using the support vector regression (SVR) method, and the hierarchical safety thresholds of the subgrade void are proposed based on the reliability theory. Firstly, the vehicle-track coupling dynamic model considering the subgrade void is constructed. Secondly, the subgrade void area, the subgrade compaction index K30 and the fastener stiffness are selected as random variables, and the mapping model between these three random parameters and the dynamic response of the wheel-rail system is built by using the orthogonal test and the SVR. The sensitivity analysis is carried out by the range analysis method. Finally, the hierarchical safety thresholds for the subgrade void are proposed. The results show that the subgrade void has the most significant influence on the carbody vertical acceleration, the rail vertical displacement, the vertical displacement and the slab tensile stress. From the range analysis, the subgrade void area has the largest effect on the dynamic response of the wheel-rail system, followed by the fastener stiffness and the subgrade compaction index K30. The recommended safety thresholds for the subgrade void of level I, II and III are 4.01㎡, 6.81㎡ and 9.79㎡, respectively.

• Steel and Composite Structures
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• v.39 no.1
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• pp.81-93
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• 2021

Splitting tensile strength (STS) is an important mechanical parameter of concrete. This study offers novel methodologies for the early prediction of this parameter. Artificial neural network (ANN), which is a leading predictive method, is synthesized with two metaheuristic algorithms, namely atom search optimization (ASO) and equilibrium optimizer (EO) to achieve an optimal tuning of the weights and biases. The models are applied to data collected from the published literature. The sensitivity of the ASO and EO to the population size is first investigated, and then, proper configurations of the ASO-NN and EO-NN are compared to the conventional ANN. Evaluating the prediction results revealed the excellent efficiency of EO in optimizing the ANN. Accuracy improvements attained by this algorithm were 13.26 and 11.41% in terms of root mean square error and mean absolute error, respectively. Moreover, it raised the correlation from 0.89958 to 0.92722. This is while the results of the conventional ANN were slightly better than ASO-NN. The EO was also a faster optimizer than ASO. Based on these findings, the combination of the ANN and EO can be an efficient non-destructive tool for predicting the STS.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.363-375
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• 2022

Flexural capacity prediction is a challenging problem for externally prestressed concrete beams (EPCBs) due to the unbonded phenomenon between the concrete beam and external tendons. Many prediction equations have been provided in previous research but typically ignored the differences in deformation mode between internal and external unbonded tendons. The availability of these equations for EPCBs is controversial due to the inconsistent deformation modes and ignored second-order effects. In this study, the deformation characteristics and collapse mechanism of EPCB are carefully considered, and the ultimate deflected shape curves are derived based on the simplified curvature distribution. With the compatible relation between external tendons and the concrete beam, the equations of tendon elongation and eccentricity loss at ultimate states are derived, and the geometric interpretation is clearly presented. Combined with the sectional equilibrium equations, a rational and simplified flexural capacity prediction method for EPCBs is proposed. The key parameter, plastic hinge length, is emphatically discussed and determined by the sensitivity analysis of 324 FE analysis results. With 94 collected laboratory-tested results, the effectiveness of the proposed method is confirmed, and comparisons with the previous formulas are made. The results show the better prediction accuracy of the proposed method for both stress increments and flexural capacity of EPCBs and the main reasons are discussed.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.4
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• pp.41-65
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• 2022

This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, 'Library' and 'Lifelong Learning Center' from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, 'reading' and 'book' were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.

• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.279-285
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• 2022

Recently, 3D printing technology has gained increased attention in the manufacturing industry because it allows the manufacturing of complex but sophisticated structures as well as moderate production speed. Owing to advantages of 3D printers, such as flexible design, customization, rapid prototyping, and ease of access, can also be advantageous to sensor developments, 3D printing demands have increased in various active device fields, including sensor manufacturing. In particular, 3D printing technology is of significant interest in tactile sensor development where piezoelectric materials are typically embedded to acquire voltage signals from external stimuli. In regard with piezoelectricity, researchers have worked with various piezoelectric materials to achieve high piezoelectric response, but the structural approach is limited because ceramics have been regarded as challenging materials for complex design owing to their limited manufacturing methods. If appropriate piezoelectric materials and approaches to design are used, sensors can be fabricated with the improved piezoelectric response and high sensitivity that cannot be found in common bulk materials. In this study, various 3D printing technologies, material combinations, and applications of various piezoelectric sensors using the 3D printing method are reviewed.

• Structural Engineering and Mechanics
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• v.84 no.3
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• pp.337-344
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• 2022

Due to corrosion defects on the surface of the oil pipe, the sealing performance of the annular blowout preventer (BOP) decreases, and the leakage of toxic and harmful gases such as H₂S and SO₂ will threaten the safety of operators on the well. Therefore, this paper establishes the FE model for evaluating the sealing performance of BOP-oil pipe corrosion defects, which is based on the rubber large deformation theory and rubber core sealing mechanism, and designs the experiment of BOP sealing performance to verify the accuracy of the FE model. The sealing performance of BOP sealing oil pipe with corrosion defects is studied. The research results show that the sealing performance of BOP is more sensitive to the axial size of corrosion defects. With the increase of oil pipe outer diameter, the critical size of defects increases continuously. The sensitivity of radial and depth dimensions is low, When for 88.9 mm outer diameter oil pipe, the axial critical size of corrosion defect is 20 mm, the radial critical size is 16 mm and the critical depth is 2 mm. Fit the formula between the outer diameter of oil pipe and the piston increment. According to the formula, the operator can calculate the piston stroke increment required by the BOP to complete the sealing when the oil pipe is corroded.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1507-1517
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• 2023

Centrifugal pumps are a crucial part of nuclear power plants, and their dependable and safe operation is crucial to the security of the entire facility. Cavitation will cause the centrifugal pump to violently vibration with the large number of vacuoles generated, which not only affect the hydraulic performance of the centrifugal pump but also cause structural damage to the impeller, seriously affecting the operational safety of nuclear power plants. A closed cavitation test bench of a centrifugal pump is constructed, and a method for precisely identifying the cavitation state is proposed based on Complementary Ensemble Empirical Mode Decomposition (CEEMD) and Deep Residual Shrinkage Network (DRSN). First, we compared the cavitation sensitivity of pressure fluctuation, vibration, and liquid-borne noise and decomposed the liquid-borne noise by CEEMD to capture cavitation characteristics. The decomposition results are sent into a 12-layer deep residual shrinkage network (DRSN) for cavitation identification training. The results demonstrate that the liquid-borne noise signal is the most cavitation-sensitive signal, and the accuracy of CEEMD-DRSN to identify cavitation at different stages of centrifugal pumps arrives at 94.61%

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.24-29
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• 1997

Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.