• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2011.10a
• /
• pp.488-493
• /
• 2011

Authors previously suggested the design sensitivity analysis based on transmissibility function and identified the sensitivity of measured point over the small modification of system dynamics. On the other hand, the acceleration data will not reveal the strain information at the same location and authors suggested energy isoclines that successfully predict the fatigue damage on the interesting location to overcome the drawback of acceleration over fatigue society. Both of methodologies, sensitivity analysis and fatigue damage prediction, commonly use the response acceleration response as main indicator. In this paper, authors investigate the advanced method of vibration fatigue prediction using design sensitivity analysis to enhance the accuracy of predicted accumulated fatigue. Uni-axial vibration testing is performed with finite element model of a simple notched specimen and the prediction of fatigue damage at notched location is conducted for accelerations at different measurement locations that show different sensitivity contribution, either.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.22 no.2
• /
• pp.123-129
• /
• 2012

It was previously suggested the design sensitivity analysis based on transmissibility function to identify the most sensitive response location over a small design modification. On the other hand, energy isoclines were used to predict the fatigue damage with acceleration response only. Both of previous studies commonly tackle the engineering problem using the acceleration response alone such that it may be possible to investigate the relationship between sensitivity analysis and accumulated fatigue damage. In this paper, it is suggested the novel method of vibration fatigue prediction using design sensitivity analysis to enhance the accuracy of predicted accumulated fatigue. Uni-axial vibration testing is performed with a simple notched specimen and the prediction of fatigue damage is conducted using accelerations measured at different locations. It can be concluded that the accuracy of predicted fatigue damage is proportional to the sensitivity index of the responsible location.

• Journal of Ocean Engineering and Technology
• /
• v.36 no.5
• /
• pp.295-302
• /
• 2022

The initial response to a marine accident can play a key role to minimize the accident. Therefore, various decision support systems have been developed using sensors, simulations, and active response equipment. In this study, we developed an algorithm to predict damage locations using ship motion data with bidirectional long short-term memory (BiLSTM), a type of recurrent neural network. To reflect the low frequency ship motion characteristics, 200 time-series data collected for 100 s were considered as input values. Heave, roll, and pitch were used as features for the prediction model. The F1-score of the BiLSTM model was 0.92; this was an improvement over the F1-score of 0.90 of a prior model. Furthermore, 53 of 75 locations of damage had an F1-score above 0.90. The model predicted the damage location with high accuracy, allowing for a quick initial response even if the ship did not have flood sensors. The model can be used as input data with high accuracy for a real-time progressive flooding simulator on board.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.1
• /
• pp.91-98
• /
• 2023

With the increasing flood damage by frequently localized heavy rains, flood prediction research are being conducted to prevent flooding damage in advance. In this paper, we present a machine-learning scheme for developing a flooding depth and location prediction model using real-time rainfall data. This scheme proposes a dataset configuration method using the data as input, which can robustly configure various rainfall distribution patterns and train the model with less memory. These data are composed of two: valid total data and valid local. The one data that has a significant effect on flooding predicted the flooding location well but tended to have different values for predicting specific rainfall patterns. The other data that means the flood area partially affects flooding refers to valid local data. The valid local data was well learned for the fixed point method, but the flooding location was not accurately indicated for the arbitrary point method. Through this study, it is expected that a lot of damage can be prevented by predicting the depth and location of flooding in a real-time manner.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.321-324
• /
• 2007

It is commonly believed that a gigantic earthquake (Tokai Earthquake) could occur in Shizuoka Prefecture in the near future. The Shizuoka Prefecture Government made the prediction report of Tokai Earthquake disaster damage. But this report does not pay attention to the ground conditions. The authors make a prediction map using GIS of Tokai Earthquake disaster damage in Asada-cho and Hirosawa Ni-chome in the central Hamamatsu City and revealed the location of dangerous houses and dangerous points in road networks in each town. These information could be useful when people try to find escape routes in an earthquake.

• Magazine of the Korea Concrete Institute
• /
• v.6 no.6
• /
• pp.180-189
• /
• 1994

A practical methodology to detect and localm da~nagc in rcinforced concrete structures by utilizing modal response parameters of as built and tiamaged states is presented. First, a damage detection algorithm which yields information on the, location of damage directly from changes in mode shapes of structures is outlined. Next, the algorithm is implemented to detec and localize damage in a real, 1 1/3 scale, reinforced concrete structure. A set of pre-damage and post damage modal parameters are used for I he damage detection exercise. The results of the damage prediction show that the proposed algorithm can correctly locate the damage inflicted in the test structure.

• Journal of Ocean Engineering and Technology
• /
• v.37 no.4
• /
• pp.158-163
• /
• 2023

Objects adrift can cause considerable damage to coastal infrastructure and property during tsunami and storm surge events. Despite the potential for harm, the drifting behavior of these objects remains poorly understood, thereby hindering effective prediction and mitigation of collision damage. To address this gap, this study employed a motion analysis program to track a drifting container's location using images from an existing laboratory experiment. The container's trajectory and velocity were calculated based on the positions of five markers strategically placed at its four corners and center. Our findings indicate that the container's maximum drift velocity and distance are directly influenced by the scale of the solitary wave and inversely related to the container's weight. Specifically, heavier containers are less likely to be displaced by solitary waves, while larger waves can damage coastal structures more. This study offers new insights into container drift behavior induced by solitary waves, with implications for enhancing coastal infrastructure design and devising mitigation strategies to minimize the risk of collision damage.

• Asia pacific journal of information systems
• /
• v.34 no.2
• /
• pp.565-584
• /
• 2024

More than 1 million automobile insurance repairs occur per year globally, and the related repair costs add up to astronomical amounts. Insurance companies and repair shops are spending a great deal of money on manpower every year to claim reasonable insurance repair costs. For this reason, promptly predicting insurance claims for vehicles in accidents can help reduce social costs related to auto insurance. Several recent studies have been conducted in auto insurance repair prediction using variables such as photos of vehicle damage. We propose a new model that reflects auto insurance repair characteristics to predict auto insurance repair claims through an association rule method that combines gradient descent and location information. This method searches for the appropriate number of rules by applying the gradient descent method to results generated by association rules and eventually extracting main rules with a distance filter that reflects automobile part location information to find items suitable for insurance repair claims. According to our results, predictive performance could be improved by applying the rule set extracted by the proposed method. Therefore, a model combining the gradient descent method and a location-based association rule method is suitable for predicting auto insurance repair claims.

• Structural Monitoring and Maintenance
• /
• v.5 no.3
• /
• pp.379-390
• /
• 2018

In this paper, a novel and effective damage diagnosis algorithm is proposed to detect and estimate damage using two stages least squares support vector machine (LS-SVM) and limited number of attached sensors on structures. In the first stage, LS-SVM1 is used to predict the unmeasured mode shapes data based on limited measured modal data and in the second stage, LS-SVM2 is used to predicting the damage location and severity using the complete modal data from the first-stage LS-SVM1. The presented methods are applied to a three story irregular frame and cantilever plate. To investigate the noise effects and modeling errors, two uncertainty levels have been considered. Moreover, the performance of the proposed methods has been verified through using experimental modal data of a mass-stiffness system. The obtained damage identification results show the suitable performance of the proposed damage identification method for structures in spite of different uncertainty levels.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.13 no.6
• /
• pp.56-62
• /
• 2005

The fatigue analysis and lifetime evaluation are very important in design procedure to assure the safety and reliability of the rubber components. Fatigue lifetime prediction methodology of the rubber component was proposed by incorporating the finite element analysis and fatigue damage parameter from fatigue test. Finite element analysis of 3D dumbbell specimen and rubber component were performed based on a hyper-elastic material model determined from material test. The Green-Lagrange strain at the critical location determined from the FEM was used for evaluating the fatigue damaged parameter of the natural rubber. Fatigue life of the rubber component are predicted by using the fatigue damage parameter at the critical location. Predicted fatigue lifes of the rubber component agreed fairly well the experimental fatigue lives.