• Structural Engineering and Mechanics
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• 제87권2호
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• pp.137-149
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• 2023

In this study, to explore the working performance of the CFST split spherical node wind power tower, two groups of CFST split spherical joint plane towers with different web wall thicknesses and a set of space systems were analyzed. The tower was subjected to a low-cycle repeated load test, and the hysteresis and skeleton curves were analyzed. ABAQUS finite element simulation was used for verification and comparison, and on this basis parameter expansion analysis was carried out. The results show that the failure mode of the wind power tower was divided into weld tear damage between belly bar, high strength bolt thread damage and belly rod flexion damage. In addition, increasing the wall thickness of the web member could render the hysteresis curve fuller. Finally, the bearing capacity of the separated spherical node wind power tower was high, but its plastic deformation ability was poor. The ultimate bearing capacity and ductility coefficient of the simulated specimens are positively correlated with web diameter ratio and web column stiffness ratio. When the diameter ratio of the web member was greater than 0.13, or the stiffness ratio γ of the web member to the column was greater than 0.022, the increase of the ultimate bearing capacity and ductility coefficient decreased significantly. In order to maximize the overall mechanical performance of the tower and improve its economy, it was suggested that the diameter ratio of the ventral rod be 0.11-0.13, while the stiffness ratio γ should be 0.02-0.022.

• Steel and Composite Structures
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• 제49권3호
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• pp.337-348
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• 2023

Successive wetting and drying cycles of concrete due to weather changes can endanger the safety of engineering structures over time. Considering wetting and drying cycles in concrete tests can lead to a more correct and reliable design of engineering structures. This study aims to provide a model that can be used to estimate the resistance properties of concrete under different wetting and drying cycles. Complex sample preparation methods, the necessity for highly accurate and sensitive instruments, early sample failure, and brittle samples all contribute to the difficulty of measuring the strength of concrete in the laboratory. To address these problems, in this study, the potential ability of six machine learning techniques, including ANN, SVM, RF, KNN, XGBoost, and NB, to predict the concrete's tensile strength was investigated by applying 240 datasets obtained using the Brazilian test (80% for training and 20% for test). In conducting the test, the effect of additives such as glass and polypropylene, as well as the effect of wetting and drying cycles on the tensile strength of concrete, was investigated. Finally, the statistical analysis results revealed that the XGBoost model was the most robust one with R2 = 0.9155, mean absolute error (MAE) = 0.1080 Mpa, and variance accounted for (VAF) = 91.54% to predict the concrete tensile strength. This work's significance is that it allows civil engineers to accurately estimate the tensile strength of different types of concrete. In this way, the high time and cost required for the laboratory tests can be eliminated.

• 항공우주시스템공학회지
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• 제18권2호
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• pp.21-28
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• 2024

최근 뉴스페이스 시대라고 불릴 만큼 우주 산업 분야는 점점 커져가고 있으며, 초소형 위성의 중요성도 또한 커지는 추세이다. 초소형 위성은 주로 COTS 부품을 사용하며 우주급 부품에 비해 낮은 신뢰도를 가지고 있지만 개발 기간, 비용, 성능 측면에서 장점을 가지고 있어 사용성이 확대되고 있다. COTS(Commercial Off-The-Shelf)는 상용으로 판매되는 제품을 가리키며, 이는 특정 조직이나 프로젝트에서 직접 제작하는 대신 시장에서 구입하여 사용되는 것을 의미한다. 위성은 발사되는 순간부터 수리가 불가능 하기 때문에 신뢰도 예측의 중요성은 크게 작용한다. 근래에는 신뢰도 예측 시 부품에 대한 인자 뿐만 아니라 시스템 level에서의 신뢰도를 예측하는 것이 더 중요하게 적용되고 있다. 따라서 본 연구에서는 신뢰도 예측 규격인 MIL-HDBK-217F와 업데이트된 RiAC-HDBK-217Plus와 FIDES를 비교해 본다. 그리고 FIDES 예측 기준에서 다양한 산업 분야에 적용될 수 있도록 구성한 제조업체의 품질 보증 요소를 세분화하여 우주 산업에 적합한 점수가 반영될 수 있도록 하였다.

• Journal of Chest Surgery
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• 제57권1호
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• pp.36-43
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• 2024

Background: Coronavirus disease 2019 (COVID-19) can lead to acute respiratory failure, which frequently necessitates invasive mechanical ventilation and extracorporeal membrane oxygenation (ECMO). However, the limited availability of ECMO resources poses challenges to patient selection and associated decision-making. Consequently, this retrospective single-center study was undertaken to evaluate the characteristics and clinical outcomes of patients with COVID-19 receiving ECMO. Methods: Between March 2020 and July 2022, 65 patients with COVID-19 were treated with ECMO and were subsequently reviewed. Patient demographics, laboratory data, and clinical outcomes were examined, and statistical analyses were performed to identify risk factors associated with mortality. Results: Of the patients studied, 15 (23.1%) survived and were discharged from the hospital, while 50 (76.9%) died during their hospitalization. The survival group had a significantly lower median age, at 52 years (interquartile range [IQR], 47.5-61.5 years), compared to 64 years (IQR, 60.0-68.0 years) among mortality group (p=0.016). However, no significant differences were observed in other underlying conditions or in factors related to intervention timing. Multivariable analysis revealed that the requirement of a change in ECMO mode (odds ratio [OR], 366.77; 95% confidence interval [CI], 1.92-69911.92; p=0.0275) and the initiation of continuous renal replacement therapy (CRRT) (OR, 139.15; 95% CI, 1.95-9,910.14; p=0.0233) were independent predictors of mortality. Conclusion: Changes in ECMO mode and the initiation of CRRT during management were associated with mortality in patients with COVID-19 who were supported by ECMO. Patients exhibiting these factors require careful monitoring due to the potential for adverse outcomes.

• Earthquakes and Structures
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• 제26권1호
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• pp.77-86
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• 2024

To investigate the seismic performance of steel pipe-aeolian sand recycled concrete columns, this study designed and produced five specimens. Low-cycle repeated load tests were conducted while maintaining a constant axial compression ratio. The experiment aimed to examine the impact of different aeolian sand replacement rates on the seismic performance of these columns. The test results revealed that the mechanical failure modes of the steel pipe-recycled concrete column and the steel pipe-aeolian sand recycled concrete column were similar. Plastic hinges formed and developed at the column foot, and severe local buckling occurred at the bottom of the steel pipe. Interestingly, the bulging height of the damaged steel pipe was reduced for the specimen mixed with an appropriate amount of wind-deposited sand under the same lateral displacement. The hysteresis curves of all five specimens tested were relatively full, with no significant pinching phenomenon observed. Moreover, compared to steel tube-recycled concrete columns, the steel tube-aeolian sand recycled concrete columns exhibited improved seismic energy dissipation capacity and ductility. However, it was noted that as the aeolian sand replacement rate increased, the bearing capacity of the specimen increased first and then decreased. The seismic performance of the specimen was relatively optimal when the aeolian sand replacement rate was 30%. Upon analysis and comparison, the damage analysis model based on stiffness and energy consumption showed good agreement with the test results and proved suitable for evaluating the damage degree of steel pipe-wind-sand recycled concrete structures.

• Steel and Composite Structures
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• 제51권5호
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• pp.509-527
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• 2024

Bonding carbon fiber-reinforced polymer (CFRP) laminates have been extensively employed in the restoration of steel constructions. In addition to the mechanical properties of the CFRP, the bond strength (P_U) between the CFRP and steel is often important in the eventual strengthened performance. Nonetheless, the bond behavior of the CFRP-steel (CS) interface is exceedingly complicated, with multiple failure causes, giving the P_U challenging to forecast, and the CFRP-enhanced steel structure is unsteady. In just this case, appropriate methods were established by hybridized Random Forests (RF) and support vector regression (SVR) approaches on assembled CS single-shear experiment data to foresee the P_U of CS, in which a recently established optimization algorithm named Aquila optimizer (AO) was used to tune the RF and SVR hyperparameters. In summary, the practical novelty of the article lies in its development of a reliable and efficient method for predicting bond strength at the CS interface, which has significant implications for structural rehabilitation, design optimization, risk mitigation, cost savings, and decision support in engineering practice. Moreover, the Fourier Amplitude Sensitivity Test was performed to depict each parameter's impact on the target. The order of parameter importance was t_c> L_c > E_A > t_A > E_c > b_c > f_c > f_A from largest to smallest by 0.9345 > 0.8562 > 0.79354 > 0.7289 > 0.6531 > 0.5718 > 0.4307 > 0.3657. In three training, testing, and all data phases, the superiority of AO - RF with respect to AO - SVR and MARS was obvious. In the training stage, the values of R² and VAF were slightly similar with a tiny superiority of AO - RF compared to AO - SVR with R² equal to 0.9977 and VAF equal to 99.772, but large differences with results of MARS.

• Geomechanics and Engineering
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• 제36권5호
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• pp.511-525
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• 2024

Underground openings significantly affect the mechanical stability of underground spaces and create damaged zones. This study investigated the acoustic emission (AE) characteristics associated with the formation of damaged zones around circular openings. Uniaxial compression experiments were conducted on three types of rock specimens, namely, granite (GN-1 and GN-2), gabbro (GB), and slate (SL), containing a circular opening. AE and digital image correlation (DIC) techniques were used to monitor and evaluate the damaged zones near the circular openings. The AE characteristics were evaluated using AE parameters, including count, energy, amplitude, average frequency, and RA value. The DIC results revealed that the estimated diameters of the damaged zones of GN-1, GN-2, GB, and SL were 1.66D, 1.53D, 1.49D, and 1.9D, respectively. The average displacements at the surface of the damaged zones for these specimens were 0.814, 0.786, 0.661, and 0.673 mm, respectively, thus demonstrating a strong correlation with Young's modulus. The AE analysis with DIC revealed that tensile failure occurred in the direction parallel to the maximum compression axis as the load increased. Thus, this study provides fundamental data for a comprehensive analysis of damaged zones in underground openings and will facilitate the optimization of rock engineering projects and safety assessments thereof.

• 대한영상의학회지
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• 제85권2호
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• pp.308-326
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• 2024

심장 기능의 포괄적인 결과는 심장박출량과 전신 정맥 환류로 표현된다. 심장의 4개의 방실은 각자 고유한 기계적 기능을 가진다. 심장방실과 판막, 폐순환 시스템은 전부하 또는 후부하의 형태로 상호 연관되어 있다. 심장 기능 장애는 전반적인 심장 기능의 실패로 전형적인 임상 증상을 나타낸다. 심장 기능 장애의 근본 원인을 조사하려면 심장 내 혈류 유동 경로에 대한 단계별 평가가 필요하다. 이러한 맥락에서, 심장의 세부 구조를 볼 수 있는 영상검사의 표지자는 심장 기능 평가에 중요한 역할을 한다. 영상기반 평가를 통해 개별 심장 구성 요소의 기능을 단계별로 조사할 수 있다. 심장 기능 평가를 위한 영상검사 중 최근 심장 CT가 포함되고 검증되었다. 본 종설에서는 포괄적 및 단계별 심장 기능 평가를 위한 심장 CT 기반 영상 표지자에 대해 논의하겠다.

• Steel and Composite Structures
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• 제51권4호
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• pp.351-361
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• 2024

Accurate measurement of K_IC values for gas pipeline steels is important for assessing pipe safety using failure assessment diagrams. As direct measurement of K_IC was impossible for the API X70 pipeline steel, multi-specimen fracture tests were conducted to measure J_IC using three-point bend geometry. The J values were calculated from load-displacement (F-δ) plots, and the associated crack extensions were measured from the fracture surface of test specimens. Valid data points were found for the constructed J-Δa plot resulting in J_IC=356kN/m. More data points were added analytically to the J-Δa plot to increase the number of data points without performing additional experiments for different J-Δa zones where test data was unavailable. Consequently, displacement (δ) and crack-growth (Δa) from multi-specimen tests (with small displacements) were used simultaneously, resulting in the variation of Δa-δ (crack growth law) and δ-Δa obtained for this steel. For new Δa values, corresponding δ values were first calculated from δ-Δa. Then, corresponding J values for the obtained δ values were calculated from the area under the F-δ record of a full-fractured specimen (with large displacement). Given Δa and J values for new data points, the developed J-Δa plot with extra data points yielded a satisfactory estimation of J_IC=345kN/m with only a -3.1% error. This is promising and showed that the developed technique could ease the estimation of J_IC significantly and reduce the time and cost of expensive extra fracture toughness tests.

• Nuclear Engineering and Technology
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• 제56권6호
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• pp.2220-2238
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• 2024

As a typical active equipment, pump machinery is widely used in nuclear power plants. Although the mechanism of pump machinery in nuclear power plants is similar to that of conventional pumps, the safety and reliability requirements of nuclear pumps are higher in complex operating environments. Once there is significant performance degradation or failure, it may cause huge security risks and economic losses. There are many pumps mechanical parameters, and it is very important to explore the correlation between multi-dimensional variables and condition. Therefore, a condition monitoring model based on Deep Denoising Autoencoder (DDAE) is constructed in this paper. This model not only ensures low false positive rate, but also realizes early abnormal monitoring and location. In order to alleviate the influence of parameter time-varying effect on the model in long-term monitoring, this paper combined equidistant sampling strategy and DDAE model to enhance the monitoring efficiency. By using the simulation data of reactor coolant pump and the actual centrifugal pump data, the monitoring and positioning capabilities of the proposed scheme under normal and abnormal conditions were verified. This paper has important reference significance for improving the intelligent operation and maintenance efficiency of nuclear power plants.