• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.1
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• pp.9-20
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• 2018

Due to integrated stochastic wind and wave loads, the supporting platform of a Floating Offshore Wind Turbine (FOWT) has to bear six Degrees of Freedom (DOF) motion, which makes the random cyclic loads acting on the structural components, for instance the tower base, more complicated than those on bottom-fixed or land-based wind turbines. These cyclic loads may cause unexpected fatigue damages on a FOWT. This paper presents a study on short-term fatigue damage at the tower base of a 5 MW FOWT with a spar-type platform. Fully coupled time-domain simulations code FAST is used and realistic environment conditions are considered to obtain the loads and structural stresses at the tower base. Then the cumulative fatigue damage is calculated based on rainflow counting method and Miner's rule. Moreover, the effects of the simulation length, the wind-wave misalignment, the wind-only condition and the wave-only condition on the fatigue damage are investigated. It is found that the wind and wave induced loads affect the tower base's axial stress separately and in a decoupled way, and the wave-induced fatigue damage is greater than that induced by the wind loads. Under the environment conditions with rated wind speed, the tower base experiences the highest fatigue damage when the joint probability of the wind and wave is included in the calculation. Moreover, it is also found that 1 h simulation length is sufficient to give an appropriate fatigue damage estimated life for FOWT.

• Journal of Ocean Engineering and Technology
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• v.33 no.5
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• pp.435-446
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• 2019

Because offshore structures are affected by various environmental loads, the risk of damage is high. As a result of ever-changing ocean environmental loads, damage to offshore structures is expected to differ from year to year. However, in previous studies, it was assumed that a relatively short period of load acts repeatedly during the design life of a structure. In this study, the residual life of an offshore wind turbine support structure was evaluated in consideration of the timing uncertainty of the ocean environmental load. Sampling points for the wind velocity, wave height, and wave period were generated using a central composites design, and a transfer function was constructed from the numerical analysis results. A simulation was performed using the joint probability model of ocean environmental loads. The stress time history was calculated by entering the load samples generated by the simulation into the transfer function. The damage to the structure was calculated using the rain-flow counting method, Goodman equation, Miner's rule, and S-N curve. The results confirmed that the wind speed generated at a specific time could not represent the wind speed that could occur during the design life of the structure.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.4
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• pp.311-320
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• 2014

Rotor blades are important devices that affect the power performance, efficiency of energy conversion, and loading and dynamic stability of wind turbines. Therefore, considering the characteristics of a wind turbine system is important for achieving optimal blade design. When a design is complete, a design evaluation should be performed to verify the structural integrity of the proposed blade in accordance with international standards or guidelines. This paper presents a detailed exposition of the evaluation items and acceptance criteria required for the design certification of wind turbine blades. It also presents design evaluation results for a 2-MW blade (KR40.1b). Analyses of ultimate strength, buckling stability, and tip displacement were performed using FEM, and Miner's rule was applied to evaluate the fatigue life of the blade. The structural integrity of the KR40.1b blade was found to satisfy the design standards.

• Structural Engineering and Mechanics
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• v.65 no.3
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• pp.315-325
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• 2018

This paper predicts the flexural behaviour of reinforced concrete (RC) beams strengthened with a precast strip of ultra-high performance fiber-reinforced concrete (UHPFRC). In the first phase, ultimate load capacity of preloaded and strengthened RC beams by UHPFRC was predicted by using various analytical models available in the literature. RC beams were preloaded under static loading approximately to 70%, 80% and 90% of ultimate load of control beams. The models such as modified Kaar and sectional analysis predicted the ultimate load in close agreement to the corresponding experimental observations. In the second phase, the famous fatigue life models such as Papakonstantinou model and Ferrier model were employed to predict the number of cycles to failure and the corresponding deflection. The models were used to predict the life of the (i) strengthened RC beams after subjecting them to different pre-loadings (70%, 80% and 90% of ultimate load) under static loading and (ii) strengthened RC beams after subjecting them to different preloading cycles under fatigue loading. In both the cases precast UHPFRC strip of 10 mm thickness is attached on the tension face. It is found that both the models predicted the number of cycles to failure and the corresponding deflection very close to the experimental values. It can be concluded that the models are found to be robust and reliable for cement based strengthening systems also. Further, the Wang model which is based on Palmgren-Miner's rule is employed to predict the no. of cycles to failure and it is found that the predicted values are in very good agreement with the corresponding experimental observations.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.251-257
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• 2017

Purpose: A chisel mounted on working implement, such as agricultural machinery used in irregular farming conditions, is subjected to highly variable fatigue loading during work. To ensure the safety of the chisel on a working implement for the duration of its service life, fatigue testing must be performed with the proper fatigue test load conditions. In this study, working loads for a chisel were developed by reconstructing loads from strain gage data collected during field tests and used to conduct fatigue tests on the chisel component. Methods: FE analysis with nCode software was utilized to select the proper quantity and locations of strain gages for load measurements. A fatigue test was performed to experimentally verify the fatigue strength of the chisel and to evaluate the validity of the load history developed with the load reconstruction technique. Results: A strain history for the chisel was obtained from data collected during field tests. The data was filtered for the 14-16 km/h speed range, connected, and merged. The chisel load history was developed using the load reconstruction technique. The resulting load history was expressed as a load spectrum using the rain-flow counting method. Conclusions: A fatigue test was conducted on a chisel under a constant load condition with an equivalent load amplitude and number of cycles, as calculated by Miner's Rule for linear damage accumulation. During the fatigue test, there were no cracks at any position. It is concluded that the fatigue test method proposed in this study can be utilized successfully as a durability evaluation method for the chisel.

• 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 the Korean Institute of Gas
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• v.21 no.3
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• pp.39-45
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• 2017

The LNG storage tank as core facility of LNG industry is mainly composed of the inner tank of nikel 9% steel and the outer tank of prestressed concrete. To respond proactively increased risk of structure performance deterioration due to fatigue of the inner tank and durability reduction of the outer tank, life evaluation program for LNG storage tank is needed. In this study, life evaluation program for LNG storage tank was developed to assess fatigue of the inner tank and durability(carbonation and chloride attack) of the outer tank. By defining the main three scenarios in the inner tank, the fatigue life analysis is conducted from structural analysis and Miner's damage rule. Carbonation progress of the outer tank is predicted according to thickness of cover concrete by using carbon dioxide contents and data of penetration depth. To consider a variety of input conditions and a reliability in results of chloride attack, the evaluation of choride attack for the outer tank is constructed through Life-365 program of open source.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1147-1158
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• 2020

The purpose of this study was to measure the engine torque and rotational speed of a 67 kW class agricultural tractor according to tire type during plow tillage and to analyze the gear strength of the driving shift for the tractor. A field test was performed under the condition with a single tire (Test A) and dual tires (Test B) to increase the ground width of the rear tires. A load monitoring system was developed, and the engine torque and rotational speed were measured using controller area network (CAN) communication. The engine torque and rotational speed during plow tillage were calculated as the equivalent torque and speed using Palmgren Miner's rule. As a result, the equivalent torque and speed in Test A and Test B were 181.0 Nm and 1,913 rpm and 206.1 Nm and 2,130 rpm, respectively. As the ground width of the rear tire was increased, the bending stress in Test B was about 9.9 to 10.5% higher than that of the Test A, and the contact stress was about 4.6 to 4.9% higher than that of the Test A. Under all conditions, the safety factor for the bending and contact stress was 1 or more. Thus, the driving shift gears for the dual tire type are considered safe.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.