Test and Numerical Simulation of Partially Encased Composite Columns Subject to Axial and Cyclic Horizontal Loads

Yiyi Chen,Tuo Wang,Jing Yang,Xianzhong Zhao 한국강구조학회 2010 International Journal of Steel Structures Vol.10 No.4

Partial encased composite (PEC) members with thin steel plates and three types of constructional detailing are studied. Six pieces of PEC column specimens were tested under constant vertical load and cyclic horizontal loads. A numerical FE model is established. In the model, the in-filled concrete is decomposed as transverse and longitudinal springs, considering the functions and the properties of the concrete in two directions. This model simplifies the numerical computation with high efficiency, and acquires a satisfied agreement with test results in both capacity and deformability of the PEC member. The parametrical study by the FE model is performed. By tests and numerical analysis, it is found that though local buckling of thin plate of H steel is a crucial factor, when the compressively axial load does not surpass the encased steel capacity, the PEC could behave quite well under cyclic horizontal loads. No distinguished difference in three kind details was observed, so that PEC member could be built in a simple way.

A New Support Vector Machine Model Based on Improved Imperialist Competitive Algorithm for Fault Diagnosis of Oil-immersed Transformers

Yiyi Zhang,Hua Wei,Ruijin Liao,Youyuan Wang,Lijun Yang,Chunyu Yan 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.2

Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.

A New Support Vector Machine Model Based on Improved Imperialist Competitive Algorithm for Fault Diagnosis of Oil-immersed Transformers

Zhang, Yiyi,Wei, Hua,Liao, Ruijin,Wang, Youyuan,Yang, Lijun,Yan, Chunyu The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.12 No.2

Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.

Socioeconomic inequality in precautions compliance and health behavior changes during COVID-19 outbreak: analysis of the Korean Community Health Survey 2020

이가빈,Jung Sun Jae,YANG YIYI,양재원,Hoang Thang Manh,Kim Hyeon Chang 한국역학회 2022 Epidemiology and Health Vol.44 No.-

OBJECTIVES: This study examined socioeconomic inequalities in compliance with precautions and health behavior changes during the coronavirus disease 2019 (COVID-19) outbreak using a representative Korean sample. METHODS: This exploratory study utilized around 210,000 participants aged ≥ 25 years in the Korean Community Health Survey 2020. Socioeconomic status was measured with educational attainment and household income. Outcomes included non-compliance with 8 precaution measures and deterioration in 6 health behaviors. The relative inequality index (RII) was calculated to quantify the degree of inequality by education and income level. RII values > 1.0 indicate that deprived people have a higher frequency of health problems, and RII values < 1.0 conversely indicate a higher frequency of health problems in more advantaged groups. RESULTS: People with lower education or income levels tended to have higher rates of non-compliance with COVID-19 safety precautions (RII range, 1.20 to 3.05). Lower education and income levels were associated with an increased smoking amount (RII= 2.10 and 1.67, respectively) and sleep duration changes (RII= 1.21 and 1.36, respectively). On the contrary, higher education and income levels were associated with decreased physical activity (RII= 0.59 and 0.77, respectively) and increased delivery food consumption (RII= 0.27 and 0.37, respectively). However, increased alcohol drinking was associated with lower education and income levels in younger men (RII= 1.73 and 1.31, respectively), but with higher levels in younger women (RII= 0.73 and 0.68, respectively). CONCLUSIONS: Our findings suggest the need to develop customized strategies, considering the characteristics of the target population, to decrease the burden and impact of the COVID-19 outbreak.

Study on Effects of Blending Fiber Type and Ratio on Antibacterial Properties of Chitosan Blended Yarns and Fabrics

Xiao Tian,Tszyin Poon,Yiyi Yang,Hong Hu,Jimin Fu,Jianhui Li,Ben Niu 한국섬유공학회 2022 Fibers and polymers Vol.23 No.9

Chitosan fiber possesses inherent advantages, such as excellent biocompatibility, nontoxicity as well asantibacterial property. However, there is no systematic study on the chitosan fiber blending effect with other fibers, and onthat basis, there is no suitable fiber blending technology for yarn and fabric production, which results in the incorrectproportion of chitosan fiber blended with other fiber type and thus lowers the fabric functionality as well as increases thematerial cost. In this study, thirteen chitosan blended yarns were designed and developed. Blending yarn structure wasexamined and the effects of blending fiber type and ratio on the antibacterial and physical property were firstly investigated. The experimental results show that the inhibition rate rises with the increase of the chitosan blending ratio. The polyester/cotton/chitosan and tencel/chitosan yarns have a better inhibition rate of Staphylococcus than that of the cotton/chitosan yarn,indicating that the blending fiber type has an impact on antibacterial properties. Moreover, various chitosan blended knittedfabrics were produced by using the chitosan blended yarns developed and their antibacterial, physical properties and comfortas well as anti-mite activity were evaluated. The results illustrate that the knitted fabrics with a small amount of chitosanfibers exhibit excellent antibacterial properties and desirable comfort. Furthermore, the chitosan blended fabrics present theanti-mites effect. This work would contribute to lowering the material cost of functional yarns and promoting thedevelopment of antibacterial textiles.