• Smart Structures and Systems
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• v.19 no.1
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• pp.39-46
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• 2017

Finite element model updating is very effective procedure to determine the uncertainty parameters in structural model and minimize the differences between experimentally and numerically identified dynamic characteristics. This procedure can be practiced with manual and automatic model updating procedures. The manual model updating involves manual changes of geometry and analyses parameters by trial and error, guided by engineering judgement. Besides, the automated updating is performed by constructing a series of loops based on optimization procedures. This paper addresses the ambient vibration based finite element model updating of long span reinforced concrete highway bridges using manual model updating procedure. Birecik Highway Bridge located on the $81^{st}km$ of Şanliurfa-Gaziantep state highway over Firat River in Turkey is selected as a case study. The structural carrier system of the bridge consists of two main parts: Arch and Beam Compartments. In this part of the paper, the arch compartment is investigated. Three dimensional finite element model of the arch compartment of the bridge is constructed using SAP2000 software to determine the dynamic characteristics, numerically. Operational Modal Analysis method is used to extract dynamic characteristics using Enhanced Frequency Domain Decomposition method. Numerically and experimentally identified dynamic characteristics are compared with each other and finite element model of the arch compartment of the bridge is updated manually by changing some uncertain parameters such as section properties, damages, boundary conditions and material properties to reduce the difference between the results. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of long span highway bridges. Maximum differences between the natural frequencies are reduced averagely from %49.1 to %0.6 by model updating. Also, a good harmony is found between mode shapes after finite element model updating.

• Journal of ILASS-Korea
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• v.27 no.2
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• pp.57-65
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• 2022

The purpose of this study is to use machine learning to build a model capable of predicting the flash boiling spray characteristics. In this study, the flash boiling spray was visualized using Shadowgraph visualization technology, and then the spray image was processed with MATLAB to obtain quantitative data of spray characteristics. The experimental conditions were used as input, and the spray characteristics were used as output to train the machine learning model. For the machine learning model, the XGB (extreme gradient boosting) algorithm was used. Finally, the performance of machine learning model was evaluated using R² and RMSE (root mean square error). In order to have enough data to train the machine learning model, this study used 12 injectors with different design parameters, and set various fuel temperatures and ambient pressures, resulting in about 12,000 data. By comparing the performance of the model with different amounts of training data, it was found that the number of training data must reach at least 7,000 before the model can show optimal performance. The model showed different prediction performances for different spray characteristics. Compared with the upstream spray angle and the downstream spray angle, the model had the best prediction performance for the spray tip penetration. In addition, the prediction performance of the model showed a relatively poor trend in the initial stage of injection and the final stage of injection. The model performance is expired to be further enhanced by optimizing the hyper-parameters input into the model.

• Steel and Composite Structures
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• v.10 no.6
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• pp.541-561
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• 2010

This paper presents finite element analyses, experimental measurements and finite element model updating of an arch type steel laboratory bridge model using semi-rigid connections. The laboratory bridge model is a single span and fixed base structure with a length of 6.1 m and width of 1.1m. The height of the bridge column is 0.85 m and the maximum arch height is 0.95 m. Firstly, a finite element model of the bridge is created in SAP2000 program and analytical dynamic characteristics such as natural frequencies and mode shapes are determined. Then, experimental measurements using ambient vibration tests are performed and dynamic characteristics (natural frequencies, mode shapes and damping ratios) are obtained. Ambient vibration tests are performed under natural excitations such as wind and small impact effects. The Enhanced Frequency Domain Decomposition method in the frequency domain and the Stochastic Subspace Identification method in the time domain are used to extract the dynamic characteristics. Then the finite element model of the bridge is updated using linear elastic rotational springs in the supports and structural element connections to minimize the differences between analytically and experimentally estimated dynamic characteristics. At the end of the study, maximum differences in the natural frequencies are reduced on average from 47% to 2.6%. It is seen that there is a good agreement between analytical and experimental results after finite element model updating. Also, connection percentages of the all structural elements to joints are determined depending on the rotational spring stiffness.

• Asian Oncology Nursing
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• v.2 no.1
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• pp.5-16
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• 2002

Purpose: This study was to develop a stress-adaptation model for family caregivers of cancer patients that could provide the basis of planning nursing intervention. Method: A hypothetical model was developed using the family adaptation model proposed by Haley et al. (1987). In the literature, the stressor was identified as patient's characteristics, caregiver's characteristics, duration of illness, and family life events. It affected stress appraisal, family resources, family coping and finally caregiver's adaptation. In this model, 18 paths were constructed. Data were collected from 241 caregivers, whose family members were in treatment between June and August 2000, at 3 university hospitals and were analyzed by SPSS and LISREL programs. Results: 1) The overall fitness indices of the hypothetical model were x 2=267.78 (P= .0), GFI= .92, AGFI= .87, NFI= .93, NNFI= .93, PNFI= .64, PGFI= .55, and RMR= .43. Ten of the eighteen paths proved to be significant. 2) To improve the model fitness, the hypothetical model was modified considering modification indices and the paths proved not significant. Final model excluded 3 paths demonstrated to be improved by x2=161.96 (P= .00), GFI= .95, AGFI= .91, NFI= .96, NNFI= .96, and RMR= .23. Twelve of fifteen paths proved to be significant. 3) Stress appraisal was influenced by disease related characteristics and duration of illness and was explained 22% of the variance. Family resources were influenced by stress appraisal and was explained 57% of variance. Family coping was influenced by disease related characteristics, caregiver's characteristics, duration of illness, family life event, and stress appraisal and was explained 57% of variance. Family caregiver adaptation was influenced by disease related characteristics, caregiver's characteristics, stress appraisal, and family coping and was explained 31% of variance. Twelve of fifteen paths were significant. Conclusion: Based on this study, to help family caregivers to adapt, individual intervention is necessary with consideration of disease related and caregiver's characteristics and duration of illness. The intervention should include efforts to raise the family resources and to identify positively the stress they encounter, and there is a need to establish an adaptation model that considers emotional aspects of family caregivers. Since there is a difference in emotional status depending on the disease stage, a study needs to be done to analyze the differences among the disease stages (diagnosis, treatment, recurrence, and terminal stages).

• The Journal of Information Systems
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• v.25 no.4
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• pp.87-104
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• 2016

Purpose As the smartphone market arrived at its saturation, from world leading information and communications technologies (ICT) businesses to startups, companies are competing to develop innovative wearable device products and suitable contents. Utility, technology, design, price, and various killer contents development targeting every customer's need should be considered for a success in the wearable device market. Design/methodology/approach Prior studies on innovation technology of ICT field have mainly focused on the innovation diffusion theory, expectation confirmation theory, and technology acceptance model, this study suggested the innovation resistance factors of adopting the smart wearable devices based on the innovation resistance model and theory of perceived risk. The model comprises the following two characteristics factors: 1) innovation characteristics which include perceived relative advantages, perceived compatability, perceived complexity, and perceived risk, 2) consumer characteristics which include attitudes towards innovation and existing products (i.e., mobile devices and analog watches). This study developed an extended innovation resistance model to explain the intention to acceptance of wearable devices consumers and collected 284 online survey responses from the non-consumers of the wearable devices. Findings The findings of this study suggest that perceived relative advantage, perceived compatibility, perceived complexity, perceived risk, attitudes towards innovation and attitudes towards existing analog watches affected the innovation resistance which has negative influence on the intention to adoption of wearable devices.

• Journal of Preventive Medicine and Public Health
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• v.18 no.1
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• pp.13-24
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• 1985

This study seeks to provide a framework for understanding differential access to medical care. The framework is provided by Anderson Model, a model of health services utilization which suggests a sequence of predisposing, enabling, illness-morbidity characteristics that determine the number of times people will visit a physician. The framework in this study is composed of two models, one is for Adults and the other is for Non-Adults. Models are operationalized using stepwise multiple regression analysis and path analysis. The data come from a national health survey conducted in 1983. The findings of the analysis can be summarized as follows : First, the causal models used in this study are able to explain only a small amount of the variance in medical care utilization(Adjusted $R^2$ is .144 in the Model for Adults and .243 in that for Non-Adults). This finding suggests that we reconsider the utility of such existing model using the predisposing, enabling, and illness-morbidity characteristics in light of their poor correspondence with these data. Second, while small amount of the valiance in medical care utilization is explained, most of the explained variance is due to the illness-morbidity characteristics. The path coefficients of study variables except illness-morbidity variables show these characteristics to be substantially unrelated to medical care utilization, and the indirect effects of the predisposing and edabling characteristics on medical care utilization are also negligible. This casts doubt on the importance of the predisposing and enabling characteristics in explaining medical care utilization. Third, among the predisposing and enabling characteristics, Medical Security variable is the only one having significant direct effect on medical care utilization in both models for Adults and for Non-Adults. Fourth, the amount of the variance explained in the Model for Non-Adults is more than in the Model for Adults. This suggests that medical care utilization of adults is more influenced by behavioral factors than that of children.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.40-45
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• 2008

This paper presents an optimal design of a permanent magnet actuator(PMA) using a parallel genetic algorithm. Dynamic characteristics of permanent magnet actuator model are analyzed by coupled electromagnetic-mechanical finite element method. Dynamic characteristics of PMA such as holding force, operating time, and peak current are obtained by no load test and compared with the analyzed results by coupled finite element method. The permanent magnet actuator model is optimized using a parallel genetic algorithm. Some design parameters of vertical length of permanent magnet, horizontal length of plunger, and depth of permanent magnet actuator are predefined for an optimal design of permanent magnet actuator model. Furthermore dynamic characteristics of the optimized permanent magnet actuator model are analyzed by coupled finite element method. A displacement of plunger, flowing current of the coil, force of plunger, and velocity of plunger of the optimized permanent magnet actuator model are compared with the results of a primary permanent magnet actuator model.

• Journal of Mechanical Science and Technology
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• v.17 no.11
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• pp.1812-1819
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• 2003

This paper presents the effect of injection pressure on the atomization characteristics of high-pressure injector in a direct injection gasoline engine both experimentally and numerically. The atomization characteristics such as mean droplet size, mean velocity, and velocity distribution were measured by phase Doppler particle analyzer. The spray development, spray penetration, and global spray structure were visualized using a laser sheet method. In order to investigate the atomization process in more detail, the calculations with the LISA-DDB hybrid model were performed. The results provide the effect of injection pressure on the macroscopic and microscopic behaviors such as spray development, spray penetration, mean droplet size, and mean velocity distribution. It is revealed that the accuracy of prediction is promoted by using the LISA-DDB hybrid breakup model, comparing to the original LISA model or TAB model alone. And the characteristics of the primary and secondary breakups have been investigated by numerical approach.

• Journal of Industrial Technology
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• v.34
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• pp.45-52
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• 2014

In this paper the settlement characteristic of shallow foundation on sandy soil overlained by rigid ground was investigated by analyzing results of model tests. For model experiments, model tests were performed with sandy soils sampled from the field, changing the relative density of sandy soil and the ratio of thickness of sandy layer(H) to the width of model strip footing(B). As result of tests, settlement of sandy soils increases as the value of H/B increases, whereas it increases with relative density of soil. Bearing capacity decreases as the thickness of the sand layer relative to the footing width increases. In order to analyze the settlement characteristics of sandy ground, the results of model tests were compared with the predicted values using the empirical formulas proposed by Terzaghi, De Beer and Schmertmann. The method by De Beer was found to be in good agreements with test results.

• Journal of Mechanical Science and Technology
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• v.17 no.5
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• pp.668-678
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• 2003

For the purpose to facilitate development of high-speed spindle units (SUs) running on rolling bearings, we have developed a beam element model, algorithms, and software for computer analysis of thermal characteristics of SUs. The thermal model incorporates a model of heat generation in rolling bearings, a model of heat transfer from bearings, and models for estimation of temperature and temperature deformations of SU elements. We have carried out experimental test and made quantitative evaluation of the effect of operation conditions on friction and thermal characteristics of the SUs of grinding and turning machines of typical structures. It is found out that the operation conditions make stronger effect on SU temperatures when rpm increases. A comparison between the results of analysis and experiment proves their good mutual correspondence and allows us to recommend application of the models and software developed for design and research of high-speed SUs running on rolling bearings.