Health monitoring of civil infrastructures, in particular, old bridges that are still in service, has become more than necessary, given the risk that a possible degradation or failure of these infrastructures can induce on the safety of users in addition to the resulting commercial and economic impact. Bridge integrity assessment has attracted significant research efforts over the past forty years with the aim of developing new damage identification methods applicable to real structures. The bridge of Ouled Mimoun (Tlemcen, Algeria) is one of the oldest railway structure in the country. It was built in 1889. This bridge, which is too low with respect to the level of the road, has suffered multiple shocks from various machines that caused considerable damage to its central part. The present work aims to analyze the stability of this bridge by identifying damages and evaluating the damage rate in different parts of the structure on the basis of a finite element model. The applied method is based on an inverse analysis of the normal stress responses that were calculated from the corresponding recorded strains, during the passage of a real train, by means of a set of strain gauges placed on certain elements of the bridge. The results obtained from the inverse analysis made it possible to successfully locate areas that were really damaged and to estimate the damage rate. These results were also used to detect an excessive rigidity in certain elements due to the presence of plates, which were neglected in the numerical reference model. In the case of the continuous bridge monitoring, this developed method will be a very powerful tool as a smart health monitoring system, allowing engineers to take in time decisions in the event of bridge damage.
Mohamed AbuGazia;Ashraf El Damatty;Kaoshan Dai;Wensheng Lu;Nima Ezami
Wind and Structures
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v.37
no.6
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pp.413-423
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2023
Wind turbines are usually steel hollow structures that can be vulnerable to dramatic failures due to high-intensity wind (HIW) events, which are classified as a category of localized windstorms that includes tornadoes and downbursts. Analyzing Wind Turbines (WT) under tornadoes is a challenging-to-achieve task because tornadoes are much more complicated wind fields compared with the synoptic boundary layer wind fields, considering that the tornado's 3-D velocity components vary largely in space. As a result, the supporting tower of the wind turbine and the blades will experience different velocities depending on the location of the event. Wind farms also extend over a large area so that the probability of a localized windstorm event impacting one or more towers is relatively high. Therefore, the built-in-house numerical code "HIW-WT" has been developed to predict the straining actions on the blades considering the variability of the tornado's location and the blades' pitch angle. The developed HIWWT numerical model incorporates different wind fields that were generated from developed CFD models. The developed numerical model was applied on an actual wind turbine under three different tornadoes that have different tornadic structure. It is found that F2 tornado wind fields present significant hazard for the wind turbine blades and have to be taken into account if the hazardous impact of this type of unexpected load is to be avoided.
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.
In this research, the study of the thermoelastic flexural analysis of silicon carbide/Aluminum graded (FG) sandwich 2D uniform structure (plate) under harmonic sinusoidal temperature load over time is presented. The plate is modeled using a simple two dimensional integral shear deformation plate theory. The current formulation contains an integral terms whose aim is to reduce a number of variables compared to others similar solutions and therefore minimize the computation time. The transverse shear stresses vary according to parabolic distribution and vanish at the free surfaces of the structure without any use of correction factors. The external load is applied on the upper face and varying in the thickness of the plates. The structure is supposed to be composed of "three layers" and resting on nonlinear visco-Pasternak's-foundations. The governing equations of the system are deduced and solved via Hamilton's principle and general solution. The computed results are compared with those existing in the literature to validate the current formulation. The impacts of the parameters (material index, temperature exponent, geometry ratio, time, top/bottom temperature ratio, elastic foundation type, and damping coefficient) on the dynamic flexural response are studied.
Shireen T. Saadullah;James H. Haido;Yaman S.S. Al-Kamaki
Advances in concrete construction
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v.16
no.1
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pp.35-57
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2023
Majority of the plastic produced each year is being disposed in land after single-use, which becomes waste and takes up a lot of storage space. Therefore, there is an urgent need to find alternative solutions instead of disposal. Recycling and reusing the PET plastic waste as aggregate replacement and fiber in concrete production can be one of the eco- friendly methods as there is a great demand for concrete around the world, especially in developing countries by raising human awareness of the environment, the economy, and Carbon dioxide (CO2) emissions. Self-compacting concrete (SCC) is a key development in concrete technology that offers a number of attractive features over traditional concrete applications. Recently, in order to improve its durability and prevent such plastics from directly contacting the environment, various kinds of plastics have been added. This review article summarizes the latest evident on the performance of SCC containing recycled PET as eco-friendly aggregates and fiber. Moreover, it highlights the influence of substitution content, shape, length, and size on the fresh and properties of SCC incorporating PET plastic. Based on the findings of the articles that were reviewed for this study, it is observed that SCC made of PET plastic (PETSCC) can be employed in construction era owing to its acceptable mechanical and fresh properties. On the other hand, it is concluded that owing to the lightweight nature of plastic aggregate, Reusing PET waste in the construction application is an effective approach to reduces the earthquake risk of a building.
Objectives : The aim of this study is to analyze the news articles related to Korean Medicine(KM) and compare trends in news reports from 2018 to 2022. Method : News articles related to KM were collected through the BigKinds, the news bigdata service of the Korea Press Foundation. News reports from 1 January 2018 to 31 December 2022 were searched. 2,950 news articles out of a total of 12,497 met the inclusion criteria. First, quantitative changes in media coverage were analyzed by year, media outlet, and month. For qualitative analysis, two authors independently coded the content of news articles, discussed them until consensus, and consulted with a third researcher to classify them. In addition, keywords extracted by the BigKind's Topic Rank algorithm were compared and analyzed in each year. Results : The number of news articles on KM decreased by 42% in 2022 compared to 2018. Over a fiveyear period, the Naeil Shinmun reported the most on KM among newspapers, while the Hankyoreh did the least. Among broadcasters, YTN reported the most and SBS did the least. When analyzing the reports by category, the most common was 'treatment', followed by 'prevention' and 'scientification'. As a result of extracting keywords with high weight and frequency, 'immunity' and 'immune system' ranked the first and second in 2018, while 'COVID 19' and 'medical law violation' did in 2022. Conclusion : The decrease in media reports on KM during the COVID-19 epidemic period seems to be due to the limited role of KM in responding to infectious diseases, and efforts to expand the scope of KM can induce increased media reports and social interest.
Rocks undergoing repeated loading and unloading over an extended period, such as due to earthquakes, human excavation, and blasting, may result in the gradual accumulation of stress and deformation within the rock mass, eventually reaching an unstable state. In this study, a CNN-CCM is proposed to address the mechanical behavior. The structure and hyperparameters of CNN-CCM include Conv2D layers × 5; Max pooling2D layers × 4; Dense layers × 4; learning rate=0.001; Epoch=50; Batch size=64; Dropout=0.5. Training and validation data for deep learning include 71 rock samples and 122,152 data points. The AI Rock Constitutive Model learned by CNN-CCM can predict strain values(ε1) using Mass (M), Axial stress (σ1), Density (ρ), Cyclic number (N), Confining pressure (σ3), and Young's modulus (E). Five evaluation indicators R2, MAPE, RMSE, MSE, and MAE yield respective values of 0.929, 16.44%, 0.954, 0.913, and 0.542, illustrating good predictive performance and generalization ability of model. Finally, interpreting the AI Rock Constitutive Model using the SHAP explaining method reveals that feature importance follows the order N > M > σ1 > E > ρ > σ3.Positive SHAP values indicate positive effects on predicting strain ε1 for N, M, σ1, and σ3, while negative SHAP values have negative effects. For E, a positive value has a negative effect on predicting strain ε1, consistent with the influence patterns of conventional physical rock constitutive equations. The present study offers a novel approach to the investigation of the mechanical constitutive model of rocks under cyclic loading and unloading conditions.
To ensure the flutter stability of three-tower suspension bridges under skew wind, by using the computational procedure of 3D refined flutter analysis of long-span bridges under skew wind, in which structural nonlinearity, the static wind action(also known as the aerostatic effect) and the full-mode coupling effect etc., are fully considered, the flutter stability of a three-tower suspension bridge-the Taizhou Bridge over the Yangtze River in completion and during the deck erection is numerically investigated under the constant uniform skew wind, and the influences of skew wind and aerostatic effects on the flutter stability of the bridge under the service and construction conditions are assessed. The results show that the flutter critical wind speeds of three-tower suspension bridge under service and construction conditions fluctuate with the increase of wind yaw angle instead of a monotonous cosine rule as the decomposition method proposed, and reach the minimum mostly in the case of skew wind. Both the skew wind and aerostatic effects significantly reduce the flutter stability of three-tower suspension bridge under the service and construction conditions, and the combined skew wind and aerostatic effects further deteriorate the flutter stability. Both the skew wind and aerostatic effects do not change the evolution of flutter stability of the bridge during the deck erection, and compared to the service condition, they lead to a greater decrease of flutter critical wind speed of the bridge during deck erection, and the influence of the combined skew wind and aerostatic effects is more prominent. Therefore, the skew wind and aerostatic effects must be considered accurately in the flutter analysis of three-tower suspension bridges.
The penetrated chloride in concrete has different behavior with mix proportions and local exposure conditions, even in the same environments, so that it is very important to quantify surface chloride contents for durability design. As well known, the surface chloride content which is a key parameter like external loading in structural safety design increases with exposure period. In this study, concrete samples containing OPC (Ordinary Portland Cement), GGBFS (Ground Granulated Blast Furnace Slag), and FA (Fly Ash) had been exposed to submerged, tidal, and splash area for 5 years, then the surface chloride contents changing with exposure period were evaluated. The surface chloride contents were obtained from the chloride profile based on the Fick's 2nd Law, and the regression analysis for them was performed with exponential and square root function. After exposure period of 5 years in submerged and tidal area conditions, the surface chloride content of OPC concrete increased to 6.4 kg/m3 - 7.3 kg/m3, and the surface chloride content of GGBFS concrete was evaluated as 7.3 kg/m3 - 11.5 kg/m3. In the higher replacement ratio of GGBFS, the higher surface chloride contents were evaluated. The surface chloride content in FA concrete showed a range of 6.7 kg/m3 to 9.9 kg/m3, which was the intermediate level of OPC and GGBFS concrete. In the case of splash area, the surface chloride contents in all specimens were from 0.59 kg/m3 to 0.75 kg/m3, which was the lowest of all exposure conditions. Experimental constants available for durability design of chloride ingress were derived through regression analysis over exposure period. In the concrete with GGBFS replacement ratio of 50%, the increase rate of surface chloride contents decreased rapidly as the water to binder ratio increased.
Journal of the Korean Society for information Management
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v.41
no.1
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pp.107-132
/
2024
This study attempted to analyze newspaper articles related to May 18 through frequency analysis and network analysis using news data related to May 18 for about 30 years from 1990 to 2022 at the Korea Press Foundation's Big Kinds. Specifically, quantitative change trends were examined by analyzing the amount of articles by period and region, and the connection structure between major keywords by the regime was explored through network analysis by regime using co-appearance keywords. As a result of the analysis, it was found that 2019 had the largest amount of coverage, which had many social issues in time, and the Jeolla-do region had the largest amount of coverage in the region. And as a result of network analysis, there were differences in words related to May 18 in news data according to the perception and policy of the regime toward May 18. As a result of synthesizing the analysis of May 18 news data, it was confirmed that May 18 was becoming a democratic movement over time regardless of region, but at the same time, the distortion of May 18 was not resolved.
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