• Computers and Concrete
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• v.22 no.2
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• pp.227-237
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• 2018

Today, the modeling of concrete as a material within finite element simulations is predominantly done through nonlinear material models of concrete. In current sophisticated computational systems, there are a number of complex concrete material models which are based on theory of plasticity, damage mechanics, linear or nonlinear fracture mechanics or combinations of those theories. These models often include very complex constitutive relations which are suitable for the modeling of practically any continuum mechanics tasks. However, the usability of these models is very often limited by their parameters, whose values must be defined for the proper realization of appropriate constitutive relations. Determination of the material parameter values is very complicated in most material models. This is mainly due to the non-physical nature of most parameters, and also the large number of them that are frequently involved. In such cases, the designer cannot make practical use of the models without having to employ the complex inverse parameter identification process. In continuum mechanics, however, there are also constitutive relations that require the definition of a relatively small number of parameters which are predominantly of a physical nature and which describe the behavior of concrete very well within a particular task. This paper presents an example of such constitutive relations which have the potential for implementation and application in finite element systems. Specifically, constitutive relations for modeling the plane stress state of concrete are presented and subsequently tested and evaluated in this paper. The relations are based on the incremental theory of elastic strain-hardening plasticity in which a non-associated flow rule is used. The calculation result for the case of concrete under uniaxial compression is compared with the experimental data for the purpose of the validation of the constitutive relations used.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.127-137
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• 2024

Physical models, which are often used for water resource management, are difficult to build and operate with input data and may involve the subjective views of users. In recent years, research using data-driven models such as machine learning has been actively conducted to compensate for these problems in the field of water resources, and in this study, an artificial neural network was used to simulate long-term rainfall runoff in the Osipcheon watershed in Samcheok-si, Gangwon-do. For this purpose, three input data groups (meteorological observations, daily precipitation and potential evapotranspiration, and daily precipitation - potential evapotranspiration) were constructed from meteorological data, and the results of training the LSTM (Long Short-term Memory) artificial neural network model were compared and analyzed. As a result, the performance of LSTM-Model 1 using only meteorological observations was the highest, and six LSTM-MLP ensemble models with MLP artificial neural networks were built to simulate long-term runoff in the Fifty Thousand Watershed. The comparison between the LSTM and LSTM-MLP models showed that both models had generally similar results, but the MAE, MSE, and RMSE of LSTM-MLP were reduced compared to LSTM, especially in the low-flow part. As the results of LSTM-MLP show an improvement in the low-flow part, it is judged that in the future, in addition to the LSTM-MLP model, various ensemble models such as CNN can be used to build physical models and create sulfur curves in large basins that take a long time to run and unmeasured basins that lack input data.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.5
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• pp.33-41
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• 2000

Three dimensional flow fields around passenger car body was computed by PAM-FLOW, well-known and validated computer program for thermal and fluid analysis. Regarding the computational method, a Navier-Stokes solver based on finite element method with various turbulent models and adaptive grid technique (H-refinement)was adopted. The results were physically reasonable and compared with experimental data, giving good agreement. It was found that three dimensional flow simulation with H-refinement technique had potential for prediction of low fie이 around vehicle and the ability to predict vortex in the wake, which is vital for CFD to be used for automobile aerodynamic calculation.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.454-458
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• 2007

Nonpoint source (NPS) pollution is a serious problem causing the degradation of soil and water quality. Concentrated overland flow is the primary transport mechanism for a large amount of NPS pollutants from hillslope areas to downslope areas in a watershed. In this study, a soil erosion model, nLS model, to identify transitional overland flow regions (i.e., ephemeral gully head areas) was developed using the kinematic wave overland flow theory. Spatial data, including digital elevation models (DEMs), soil, and landcover, were used in the GIS-based model algorithm. The model was calibrated and validated using gully head locations in a large agricultural watershed, which were identified using 1-m aerial photography. The model performance was better than two previous approaches; the overall accuracy of the nLS model was 72 % to 87 % in one calibration subwatershed and the mean overall accuracy was 75 to 89 % in four validation subwatersheds, showing that the model well predicted potential transitional erosion areas at different watersheds. However, the user accuracy in calibration and validation was still low. To improve the user accuracy and study the effects of DEM resolution, finer resolution DEMs may be preferred because DEM grid is strongly sensitive to estimating model parameters. Information gained from this study can improve assessing soil erosion process due to concentrated overland flow as well as analyze the effect of microtopographic landscapes, such as riparian buffer areas, in NPS control.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.5
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• pp.545-565
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• 2018

A numerical code is developed based on potential flow theory to investigate nonlinear sloshing in rectangular Liquefied Natural Gas (LNG) tanks under forced excitation. Using this code, internal free-surface elevation and sloshing loads on liquid tanks can be obtained both in time domain and frequency domain. In the mathematical model, acceleration potential is solved in the calculation of pressure on tanks and the artificial damping model is adopted to account for energy dissipation during sloshing. The Boundary Element Method (BEM) is used to solve boundary value problems of both velocity potential and acceleration potential. Numerical calculation results are compared with published results to determine the efficiency and accuracy of the numerical code. Sloshing properties in partially filled rectangular and membrane tank under translational and rotational excitations are investigated. It is found that sloshing under horizontal and rotational excitations share similar properties. The first resonant mode and excitation frequency are the dominant response frequencies. Resonant sloshing will be excited when vertical excitation lies in the instability region. For liquid tank under rotational excitation, sloshing responses including amplitude and phase are sensitive to the location of the center of rotation. Moreover, experimental tests were conducted to analyze viscous effects on sloshing and to validate the feasibility of artificial damping models. The results show that the artificial damping model with modifying wall boundary conditions has better applicability in simulating sloshing under different fill levels and excitations.

• Structural Engineering and Mechanics
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• v.46 no.2
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• pp.197-212
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• 2013

With more and more high-rise building being constructed in recent decades, bluff body flow with high Reynolds number and large scale dimensions has become an important topic in theoretical researches and engineering applications. In view of mechanics, the key problems in such flow are high Reynolds number turbulence and fluid-solid interaction. Aiming at such problems, a parallel fluid-structure interaction method based on socket parallel architecture was established and combined with the methods and models of large eddy simulation developed by authors recently. The new method is validated by the full two-way FSI simulations of 1:375 CAARC building model with Re = 70000 and a full scale Taipei101 high-rise building with Re = 1e8, The results obtained show that the proposed method and models is potential to perform high-Reynolds number LES and high-efficiency two-way coupling between detailed fluid dynamics computing and solid structure dynamics computing so that the detailed wind induced responses for high-rise buildings can be resolved practically.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.873-879
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• 2024

A sodium-cooled fast reactor (SFR) core has a potential of prompt criticality due to a change of core material distribution during a severe accident, and the resultant energy release has been one of the safety issues of SFRs. In this study, the safety assessment of an unprotected loss-of-flow (ULOF) in a small SFR (SSFR) has been performed using the SIMMER-IV computer code, which couples the models of space- and time-dependent neutronics and multi-component, multi-field thermal hydraulics in three dimensions. The code, therefore, is applicable to the simulations of transient behaviors of extended disrupted core material motion and its reactivity effects during the transition phase (TP) of ULOF, including a potential of prompt-criticality power excursions driven by fuel compaction. Several conservative assumptions are used in the TP analysis by SIMMER-IV. It was found out that one of the important mechanisms that drives the reactivity-inserting fuel motion was sodium vapor pressure resulted from a fuel-coolant interaction (FCI), which itself was non-energetic local phenomenon. The uncertainties relating to FCI is also evaluated in much conservative way in the sensitivity analysis. From this study, the ULOF characteristics in an SSFR have been understood. Occurrence of recriticality events under conservative assumptions are plausible, but their energy releases are limited.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.29-34
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• 2023

The flow from developing a machine learning model to deploying it in a production environment suffers challenges. Efficient and reliable deployment is critical for realizing the true value of machine learning models. Bridging this gap between development and publication has become a pivotal concern in the machine learning community. FastAPI, a modern and fast web framework for building APIs with Python, has gained substantial popularity for its speed, ease of use, and asynchronous capabilities. This paper focused on leveraging FastAPI for deploying machine learning models, addressing the potentials associated with integration, scalability, and performance in a production setting. In this work, we explored the seamless integration of machine learning models into FastAPI applications, enabling real-time predictions and showing a possibility of scaling up for a more diverse range of use cases. We discussed the intricacies of integrating popular machine learning frameworks with FastAPI, ensuring smooth interactions between data processing, model inference, and API responses. This study focused on elucidating the integration of machine learning models into production environments using FastAPI, exploring its capabilities, features, and best practices. We delved into the potential of FastAPI in providing a robust and efficient solution for deploying machine learning systems, handling real-time predictions, managing input/output data, and ensuring optimal performance and reliability.

• Asia pacific journal of information systems
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• v.8 no.2
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• pp.69-83
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• 1998

Some simulation tools have been developed to support business process reengineering. These tools can be used to not only analyze an as-is model of the existing process but also assess the potential value and feasibility of to-be models. But most of them are restricted to analyzing and redesign of the workflow only. Little attention is paid to the organization of people and their roles. This paper Presents a new methodology for business process simulation modeling and analysis. The methodology is based on the concepts of roles and customer-supplier chains. So the proposed methodology allows for tracking people and their roles affected by reengineering the business process. It enables one to analyze and evaluate not only workflow, but roles that are part of the flow. This paper developed a simulator to systematically construct simulation models and conduct simulations easily and efficiently. A case study is also presented as an illustrative example.

• Current Research on Agriculture and Life Sciences
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• v.30 no.2
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• pp.97-104
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• 2012

Over the last century, drainage systems have become an integral component of agriculture. Climate observations and experiments using General circulation models suggest an intensification of the hydrologic cycle due to climate change. This study presents hydrologic simulations assessing the potential impact of climate change on subsurface drainage in Daegu, Republic of Korea. Historical and Long Ashton Research Station weather generator perturbed future climate data from 15 general circulation models for a field in Daegu were ran into a water management simulation model, DRAINMOD. The trends and variability in rainfall and Soil Excess Water ($SEW_{30}$) were assessed from 1960 to 2100. Rainfall amount and intensity were predicted to increase in the future. The predicted annual subsurface drainage flow varied from -35 to 40 % of the baseline value while the $SEW_{30}$ varied from -50 to 100%. The expected increases in subsurface drainage outflow require that more attention be given to soil and water conservation practices.