• Steel and Composite Structures
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• v.35 no.1
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• pp.93-109
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• 2020

Developed from conventional concrete filled steel tubular (CFST) members, concrete-encased CFST has attracted growing attention in building and bridge practices. In actual construction, the inner CFST is erected prior to the casting of the outer reinforced concrete part to support the construction preload, after which the whole composite member is under sustained service load. The complex loading sequence leads to highly nonlinear material interaction and consequently complicated structural performance. This paper studies the full-range behaviour of concrete-encased CFST columns with initial preload on inner CFST followed by sustained service load over the whole composite section. Validated against the reported data obtained from specifically designed tests, a finite element analysis model is developed to investigate the detailed structural behaviour in terms of ultimate strength, load distribution, material interaction and strain development. Parametric analysis is then carried out to evaluate the impact of significant factors on the structural behaviour of the composite columns. Finally, a simplified design method for estimating the sectional capacity of concrete-encased CFST is proposed, with the combined influences of construction preload and sustained service load being taken into account. The feasibility of the developed method is validated against both the test data and the simulation results.

• 한국연소학회:학술대회논문집
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• 2006.04a
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• pp.213-217
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• 2006

Recent advances in energetic materials modeling and high-resolution hydrocode simulation enable enhanced computational analysis of bio-medical treatments that utilize high-pressure shock waves. Of particular interest is in designing devices that use such technology in medical treatments. For example, the generated micro shock waves with peak pressure on orders of 10 GPa can be used for treatments such as kidney stone removal, trans-dermal micro-particle delivery. and cancer cell removal. In this work, we present a new computational methodology for applying the high explosive dynamics to bio-medical treatments by making use of high pressure shock physics and multi-material wave interactions. The preliminary calculations conducted by the in-house code, GIBBS2D, captures various features that are observed from the actual experiments under the similar test conditions. We expect to gain novel insights in applying explosive shock wave physics to the bio-medical science involving drug injection. Our forthcoming papers will illustrate the quantitative comparison of the modeled results against the experimental data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5392-5418
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• 2017

The primary aim of this paper is to propose a non-linear regression based technique for mapping different network Quality of Service (QoS) factors to an integrated end-user Quality of Experience (QoE) or Mean Opinion Score (MOS) value for an online video streaming service on a mobile phone. We use six network QoS factors for finding out the user QoE. The contribution of this paper is threefold. First, we investigate the impact of the network QoS factors on the perceived video quality. Next, we perform an individual mapping of the significant network QoS parameters obtained in stage 1 to the user QoE based upon a non-linear regression method. The optimal QoS to QoE mapping function is chosen based upon a decision variable. In the final stage, we evaluate the integrated QoE of the system by taking the combined effect of all the QoS factors considered. Extensive subjective tests comprising of over 50 people across a wide variety of video contents encoded with H.265/HEVC and VP9 codec have been conducted in order to gather the actual MOS data for the purpose of QoS to QoE mapping. Our proposed hybrid model has been validated against unseen data and reveals good prediction accuracy.

• Journal of ILASS-Korea
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• v.15 no.4
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• pp.195-201
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• 2010

Due to its carbon-neutral nature, biogas generated from anaerobic digestion or fermentation of biodegradable wastes is one of the important renewable energy sources to reduce global warming. It is mainly composed of methane and various inert gases such as $CO_2$ and $N_2$, and the actual composition of biogas significantly varies depending on the origin of anaerobic digestion process. Therefore, in order to effectively utilize this fuel as an energy source for electricity, it is important to develop power generation engines which can successfully apply biogas with significant composition variations. In this study, efforts have been made to develop a diesel-biogas duel fuel engine as a way to achieve such a stable power generation. The effects of diesel fuel injection quantity and pressure on stable combustion and engine performance were investigated, and an impact of diesel fuel atomization was discussed. The engine test results show that there exists a 2 stage combustion which consists of diesel pilot fuel burning and premixed biogas/air mixture burning in dual fuel engine operation and optimum diesel injection parameters were suggested for biogases with various compositions and heating values.

• Geomechanics and Engineering
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• v.37 no.2
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• pp.97-107
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• 2024

The accurate prediction of grouting upward diffusion height is crucial for estimating the bearing capacity of tip-grouted piles. Borehole construction during the installation of bored piles induces soil unloading, resulting in both radial stress loss in the surrounding soil and an impact on grouting fluid diffusion. In this study, a modified model is developed for predicting grout diffusion height. This model incorporates the classical rheological equation of power-law cement grout and the cavity reverse expansion model to account for different degrees of unloading. A series of single-pile tip grouting and static load tests are conducted with varying initial grouting pressures. The test results demonstrate a significant effect of vertical grout diffusion on improving pile lateral friction resistance and bearing capacity. Increasing the grouting pressure leads to an increase in the vertical height of the grout. A comparison between the predicted values using the proposed model and the actual measured results reveals a model error ranging from -12.3% to 8.0%. Parametric analysis shows that grout diffusion height increases with an increase in the degree of unloading, with a more pronounced effect observed at higher grouting pressures. Two case studies are presented to verify the applicability of the proposed model. Field measurements of grout diffusion height correspond to unloading ratios of 0.68 and 0.71, respectively, as predicted by the model. Neglecting the unloading effect would result in a conservative estimate.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4102-4111
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• 2023

In order to better perform thermal hydraulic calculation and analysis of supercritical water reactor, based on the experimental data of supercritical water, the model training and predictive analysis of the heat transfer coefficient of supercritical water were carried out by using the support vector machine (SVM) algorithm. The changes in the prediction accuracy of the supercritical water heat transfer coefficient are analyzed by the changes of the regularization penalty parameter C, the slack variable epsilon and the Gaussian kernel function parameter gamma. The predicted value of the SVM model obtained after parameter optimization and the actual experimental test data are analyzed for data verification. The research results show that: the normalization of the data has a great influence on the prediction results. The slack variable has a relatively small influence on the accuracy change range of the predicted heat transfer coefficient. The change of gamma has the greatest impact on the accuracy of the heat transfer coefficient. Compared with the calculation results of traditional empirical formula methods, the trained algorithm model using SVM has smaller average error and standard deviations. Using the SVM trained algorithm model, the heat transfer coefficient of supercritical water can be effectively predicted and analyzed.

• Journal of Smart Tourism
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• v.4 no.2
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• pp.25-33
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• 2024

This study examines the factors influencing the use of mobile food ordering applications and their impact on consumption behavior amidst recent societal changes. It re-evaluates the relevance of factors from the UTAUT2 theory in predicting customers' behavioral intentions. Additionally, the study explores the moderating effect of confidence in food safety measures (CFSM). Quantitative research methods are employed. A structured questionnaire that measures the psychological factors, behavioral intention, and actual usage of mobile food ordering applications was used to collect customer data. Regression and moderation analyses are conducted to test the hypotheses and examine the moderating role of CFSM. The findings reveal that performance expectation, effort expectation, and habit significantly predict customers' intention to use mobile food ordering applications. Moreover, for customers with high CFSM, social influence, facilitating conditions, and hedonic motivation add additional contributions to their behavioral intention. This study extends the UTAUT2 theory by applying it to mobile food ordering applications and examining the influence of CFSM. It identifies the specific factors that drive customers' intention to use these applications and highlights the importance of CFSM as a moderating factor. The findings offer theoretical insights and practical implications for researchers and practitioners in the mobile food ordering industry.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.401-407
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• 2005

Simulations are currently an essential tool to develop and test wireless sensor networks (WSNs) protocols and to analyze future WSNs applications performance. Researchers often simulate their proposals rather than deploying high-cost test-beds or develop complex mathematical analysis. However, simulation results rely on physical layer assumptions, which are not usually accurate enough to capture the real behavior of a WSN. Such an issue can lead to mistaken or questionable results. Besides, most of the envisioned applications for WSNs consider the nodes to be at the ground level. However, there is a lack of radio propagation characterization and validation by measurements with nodes at ground level for actual sensor hardware. In this paper, we propose to use a low-computational cost, two slope, log-normal path­loss near ground outdoor channel model at 868 MHz in WSN simulations. The model is validated by extensive real hardware measurements obtained in different scenarios. In addition, accurate model parameters are provided. This model is compared with the well-known one slope path-loss model. We demonstrate that the two slope log-normal model provides more accurate WSN simulations at almost the same computational cost as the single slope one. It is also shown that the radio propagation characterization heavily depends on the adjusted model parameters for a target deployment scenario: The model parameters have a considerable impact on the average number of neighbors and on the network connectivity.

• The Journal of Fisheries Business Administration
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• v.54 no.1
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• pp.37-49
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• 2023

Climate change is a major global problem. Oysters, one of the most representative farmed fish in Korea, are attracting attention as candidates for blue carbon, an alternative to carbon neutrality. This study is analyzed by the SSP scenarios to determine the impact of oyster aquaculture production according to climate change. Based on the analysis, future productions of oysters are predicted by the SSP scenario. Significant differences by the SSP scenario are confirmed through predictive power tests among scenarios. Regression analysis was conducted from January 2001 to December 2014. As a result of the analysis, water temperature, water temperature quadratic term, salinity, salinity quadratic term, and month × water temperature cross term were estimated as significant variables. Oyster production which is predicted by the SSP scenario based on the significant variables from 2015 to 2022 was compared with actual production. The model with the highest predictive power was selected by RMSE and MAPE criteria. The predictive power was compared with the MDM test to determine which model was superior. As a result, based on RMSE and MAPE, the SSP1-2.6 scenario was selected as the best model and the SSP1-2.6, SSP2-4.5, and SSP3-7.0 scenarios all showed the same predictive power based on the MDM test. In conculusion, this study predicted oyster aquaculture production by 2030, not the distant future, due to the short duration of the analytical model. This study was found that oyster aquaculture production increased in all scenarios and there was no significant difference in predictive power by the SSP scenario.

• Journal of Distribution Science
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• v.11 no.8
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• pp.25-30
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• 2013

Purpose - Foodservices have grown to over 60% of the franchise industry. However, despite reaching this high level, the foodservice franchise industry is experiencing severe ups and downs. While factors such as expansion by franchises and the entry of large multinational firms are causing this imbalance, the more serious problem faced by franchisees is the lack of know-how and correct operating procedures. Franchise headquarters should advise franchisees on important matters such as food ingredients, interior design, tableware, and fixtures. However, even though franchise headquarters have the ability to impart such management know-how, this is often a neglected area. Research design, data and methodology - This study was conducted in an industrial environment to present suitable competitive alternatives for foodservice franchises. Empirical analysis was conducted using a sample of 232 people with experience in targeting customers. The main purpose of this study is not to identify and analyze the factors affecting customer satisfaction. Customers of the Food Service Industry to invite contacts until departure for the service flow by identifying the expectations and allow this area by analyzing the resulting measures to enhance the competitiveness has presented. Results - Actual results contact factors affecting the quality of service on customer satisfaction was a significant influence. However, the end of this analysis, the actual customer satisfaction directly affects the quality of service that is only important factor can commit mistakes. Relatively large impact on customer satisfaction, which is relatively independent of the quality factor should be a review of zone of tolerance. In this study, eating phase relative to contact the service customer satisfaction was the most influential. The results, however, zone of tolerance for an area in the waiting and ordering dissatisfaction factors are appearing. And in the course of these services outside the zone of tolerance area is unsatisfactory evaluation is being done. Conclusions - After all, Foodservice, the contact service management for zone of tolerance the top priority should be can be seen. Foodservice contact first in the case of service quality factors caused by the continuous flow of services, so this step-by-step identification needs to be clearer. This, of course, to distinguish between the actual per unit of activity appears to be more difficult to follow, for it seems to need a lot of future complementary. Next is the assessment of customer service quality. Customers remember the experience for the services of a real contact through the assessment and service evaluation clearly emerge as the expected level can be difficult. However, this situation is controlled by the test method cannot be avoided unless there is no limit to the number of leave. Despite these limitations, the next step to contact a service evaluation and analysis have to continue to refine and thereby franchisees for the operation of the store in terms of practical know-how required to provide to the office believe.