• Smart Structures and Systems
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• v.31 no.1
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• pp.57-68
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• 2023

Bridge hangers, such as those in suspension and cable-stayed bridges, suffer from cumulative fatigue damage caused by dynamic loads (e.g., cyclic traffic and wind loads) in their service condition. Thus, the identification of damage to hangers is important in preserving the service life of the bridge structure. This study develops a new method for condition assessment of bridge hangers. The tension force of the bridge and the damages in the element level can be identified using the Bayesian optimization method. To improve the number of observed data, the additional mass method is combined the Bayesian optimization method. Numerical studies are presented to verify the accuracy and efficiency of the proposed method. The influence of different acquisition functions, which include expected improvement (EI), probability-of-improvement (PI), lower confidence bound (LCB), and expected improvement per second (EIPC), on the identification of damage to the bridge hanger is studied. Results show that the errors identified by the EI acquisition function are smaller than those identified by the other acquisition functions. The identification of the damage to the bridge hanger with various types of boundary conditions and different levels of measurement noise are also studied. Results show that both the severity of the damage and the tension force can be identified via the proposed method, thereby verifying the robustness of the proposed method. Compared to the genetic algorithm (GA), particle swarm optimization (PSO), and nonlinear least-square method (NLS), the Bayesian optimization (BO) performs best in identifying the structural damage and tension force.

• Herbal Formula Science
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• v.15 no.2
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• pp.35-45
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• 2007

Objective : The purpose of this report was to provide the information activity and safety of Palmul-tang by analyzing domestic/international papers and theses about Palmul-tang, Methods: Domestic/international papers and theses related to Palmul-tang were reviewed and analyzed, These papers were then classified by year, experimental method and subject, Results: The following results were obtained in this study. 1. The study of Palmul-tang started from 1985 and was continuously increased. The study was mainly forcused on experimental model rather than clinical study. 2. As these studies were classified by subject, papers related to immune intensification were most abundant by 20 papers, Besides there were several papers related to cardiovascular activity, reproductive activity, anti-apoptotic activity and cerebral hemodynamics. 3. Among the papers related to immune intensification. the studies on recovery of fatigue were mostabundant by 10 papers and the studies of on immune cell and cytokine express were six. In addition to. several studies were associated with anti-cancer activity and anti-allergic activity. Recovery of fatigue was determined by measurement of fatigue markers in a living body such as lactate. CPK, pyruvate and triglyceride and assessment of exercise capability of animals such as swimming test. slopped plate test. Rota-rod test, and activity cage test after Palmul-tang treatment. 4. According to experimental data. it is supported that Palmul-tang has been used as Qi and Blood intensifier with immune intensification and recovery of fatigue. 5. The paper related to safety of Palmul-tang was only one paper which is studied on acute toxicity of Palmul-tang with experiment with ICR mouse. There was no study on evaluating safety by observing liver and kidney functions after Palmul-tang treatment Conclusion: Palmul-tang is being used in various ways associating with immune intensification. cardiovascular activity and reproductive activity. However. studies on efficacy and mechanism of Palmul-tang should be conducted at the molecular biology level and studies on safety of Palmul-tang need to be completed at the clinical level.

• Information Systems Review
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• v.17 no.2
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• pp.77-100
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• 2015

This study examined the factors that influence the smartphone user's decision to accept the personalized mobile advertisement. As a theoretical basis, we applied the privacy calculus model (PCM) that illustrates how consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. In particular, we investigated how smartphone users make a risk-benefit assessment under which personalized service as benefit-side factor and information privacy risks as a risk-side factor accompanying their acceptance of advertisements. Further, we extend the current PCM by considering advertisement fatigue as a new factor that may influence the user's acceptance. The research model with five (5) hypotheses was tested using data gathered from 215 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a mobile advertisement service was provided. The results showed that three (3) out of five (5) hypotheses were supported. First, we found that the intention to accept advertisements is positively and significantly influenced by the perceived value of personalization. Second, perceived advertisement fatigue was also found to be a strong predictor of the intention to accept advertisements. However, we did not find any evidence of direct influence of privacy risks. Finally, we found that the significant moderating effect between the perceived value of personalization and advertisement fatigue. This suggests that the firms should provide effective tailored advertisement that can increase the perceived value of personalization to mitigate the negative impacts of advertisement fatigue.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.1
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• pp.267-277
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• 2003

The purpose of this study makes a retrofit and rehabilitation practice trough the analysis and the improvement for the underlying problem of current retrofit and rehabilitation methods. Therefore, the deterioration process, the damage cause, the condition classification, the fatigue mechanism and the applied quantity of strengthening methods for slab bridge decks were analysed. Artificial neural networks are efficient computing techniqures that are widely used to solve complex problems in many fields. In this study, a back-propagation neural network model for estimating a management on existing slab bridge decks from damage cause, damage type, and integrity assessment at the initial stsge is need. The training and testing of the network were based on a database of 36. Four different network models werw used to study the ability of the neural network to predict the desirable output of increasing degree of accuracy. The neural networks is trained by modifying the weights of the neurons in response to the errors between the actual output values and the target output value. Training was done iteratively until the average sum squared errors over all the training patterms were minimized. This generally occurred after about 5,000 cycles of training.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.227-236
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• 2002

The purpose of this study makes a retrofit and rehabilitation practice trough the analysis and the improvement for the underlying problem of current retrofit and rehabilitation methods. Therefore, the deterioration process, the damage cause, the condition classification, the fatigue mechanism and the applied quantity of strengthening methods for RC deck slabs were analyzed. Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this study, a back-propagation neural network model for estimating a management on existing reinforced concrete bridge decks from damage cause, damage type, and integrity assessment at the initial stage is need. The training and testing of the network were based on a database of 36. Four different network models were used to study the ability of the neural network to predict the desirable output of increasing degree of accuracy. The neural networks is trained by modifying the weights of the neurons in response to the errors between the actual output values and the target output value. Training was done iteratively until the average sum squared errors over all the training patterns were minimized. This generally occurred after about 5,000 cycles of training.

• Transactions of the KSME C: Technology and Education
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• v.5 no.2
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• pp.89-95
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• 2017

LCD robot vertical frame lets a arm assembly with glass substrate move up and down, so it must have high stiffness and strength. We applied new manufacturing process by using design optimization process such as topology and size optimization in order to satisfy the request of high stiffness and light weight. The proposed model should be evaluated for endurance strength. Therefore fatigue assessment for weak point of aluminum welding area of vertical frame studied with hot spot stress approach. And the actual stress measuring from test was compared and evaluated with the dynamic stress calculated from multi-body dynamics considering flexible body.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1185-1191
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• 2014

Gas turbine blades that have complex geometry of the cooling holes and cooling passages are usually subjected to cyclic and sustained thermal loads due to changes in the operating characteristic in combined power plants; these results in non-uniform temperature and stress distributions according to time to gas turbine blades. Those operation conditions cause creep or thermo-mechanical fatigue damage and reduce the lifetime of gas turbine blades. Thus, an accurate analysis of the stresses caused by various loading conditions is required to ensure the integrity and to ensure an accurate life assessment of the components of a gas turbine. It is well known that computational analysis such as cross-linking process including CFD, heat transfer and stress analysis is used as an alternative to demonstration test. In this paper, temperatures and stresses of gas turbine blade were calculated with fluid-structural analysis integrating fluid-thermal-solid analysis methodologies by considering actual operation conditions. Based on analysis results, additionally, the total lifetime was obtained using creep and thermo-mechanical damage model.

• Transactions of the KSME C: Technology and Education
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• v.5 no.2
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• pp.115-126
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• 2017

This paper proposes an accelerated life evaluation of drive shaft for the power train parts of special purpose vehicle. It is necessary the real load data of usage level driving load condition for life evaluation of power train parts, but we can't get the load spectrum data for evaluation in many case of special purpose vehicle. So, in this paper, the road load spectrum data for evaluation is created by modeling and simulation based on vehicle data and special road condition. The inverse power model is used for accelerated life test. The equivalent torque of load spectrum is achieved using the Miner's Rule. This paper also proposes the calibrated acceleration life test method for drive shaft. The fatigue test is performed through three stress levels. The lifetime at normal stress level is predicted by extrapolation, and is verified through comparison of experimental results and load spectrum data.

• Journal of Preventive Medicine and Public Health
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• v.56 no.2
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• pp.154-163
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• 2023

Objectives: Systemic lupus erythematosus (SLE) or lupus patients usually experience various physical and psychological challenges. Since the coronavirus disease 2019 pandemic, these challenges have become even harsher. Using the participatory action research approach, this study evaluated how an e-wellness program (eWP) impacted SLE-related knowledge and health behaviors, mental health, and quality of life among lupus patients in Thailand. Methods: A 1-group, pretest-posttest design study was conducted among a purposive sample of lupus patients who were members of Thai SLE Foundation. The 2 main intervention components were: (1) online social support, and (2) lifestyle and stress management workshops. Sixty-eight participants completed all the study requirements, including the Physical and Psychosocial Health Assessment questionnaire. Results: After being in the eWP for 3 months, participants' mean score for SLE-related knowledge increased significantly (t=5.3, p<0.001). The increase in sleep hours was statistically significant (Z=-3.1, p<0.01), with the percentage of participants who slept less than 7 hours decreasing from 52.9% to 29.0%. The percentage of participants reporting sun exposure decreased from 17.7% to 8.8%. The participants also reported significantly lower stress (t(66)=-4.4, p<0.001) and anxiety (t(67)=-2.9, p=0.005). The post-eWP quality of life scores for the pain, planning, intimate relationship, burden to others, emotional health, and fatigue domains also improved significantly (p<0.05). Conclusions: The overall outcomes showed promising results of improved self-care knowledge, health behaviors, mental health status, and quality of life. It is recommended that the SLE Foundation continues to use the eWP model to help the lupus patient community.