• Ocean Systems Engineering
• /
• 제12권2호
• /
• pp.143-157
• /
• 2022

In this study, the nominal wake field of a semi-displacement type high-speed vessel was computed at full scale by using CFD (Computational Fluid Dynamics) and GEOSIM-based approaches. A scale effect investigation on nominal wake field of benchmark Athena vessel was performed with two models which have different model lengths. The members of the model family have the same Fr number but different Re numbers. The spatial components of nominal wake field have been analyzed by considering the axial, radial and tangential velocities for models at different scales. A linear feature has been found for radial and tangential components while a nonlinear change has been obtained for axial velocity. Taylor wake fraction formulation was also computed by using the axial wake velocities and an extrapolation technique was carried out to get the nonlinear fit of nominal wake fraction. This provides not only to observe the change of nominal wake fraction versus scale ratios but also to estimate accurately the wake fraction at full-scale. Extrapolated full-scale nominal wake fractions by GEOSIM-based approach were compared with the full-scale CFD result, and a very good agreement was achieved. It can be noted that the GEOSIM-based extrapolation method can be applied for estimation of the nominal wake fraction of semi-displacement type high-speed vessels.

• Wind and Structures
• /
• 제35권2호
• /
• pp.131-146
• /
• 2022

Tornadic wind flow is inherently turbulent. A turbulent wind flow is characterized by fluctuation of the velocity in the flow field with time, and it is a dynamic process that consists of eddy formation, eddy transportation, and eddy dissipation due to viscosity. Properly modeling turbulence significantly increases the accuracy of numerical simulations. The lack of a clear and detailed comparison between turbulence models used in tornadic wind flows and their effects on tornado induced pressure demonstrates a significant research gap. To bridge this research gap, in this study, two representative turbulence modeling approaches are applied in simulating real-world tornadoes to investigate how the selection of turbulence models affects the simulated tornadic wind flow and the induced pressure on structural surface. To be specific, LES with Smagorinsky-Lilly Subgrid and k-ω are chosen to simulate the 3D full-scale tornado and the tornado-structure interaction with a building present in the computational domain. To investigate the influence of turbulence modeling, comparisons are made of velocity field and pressure field of the simulated wind field and of the pressure distribution on building surface between the cases with different turbulence modeling.

• 대한의용생체공학회:의공학회지
• /
• 제43권4호
• /
• pp.259-270
• /
• 2022

Artificial intelligence (AI) has been studied in various fields of medical imaging. Currently, top-notch deep learning (DL) techniques have led to high diagnostic accuracy and fast computation. However, they are rarely used in real clinical practices because of a lack of reliability concerning their results. Most DL models can achieve high performance by extracting features from large volumes of data. However, increasing model complexity and nonlinearity turn such models into black boxes that are seldom accessible, interpretable, and transparent. As a result, scientific interest in the field of explainable artificial intelligence (XAI) is gradually emerging. This study aims to review diverse XAI approaches currently exploited in medical imaging. We identify the concepts of the methods, introduce studies applying them to imaging modalities such as computational tomography (CT), magnetic resonance imaging (MRI), and endoscopy, and lastly discuss limitations and challenges faced by XAI for future studies.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2023년도 학술발표회
• /
• pp.25-25
• /
• 2023

The ensemble optimal interpolation (EnOI) scheme is a sub-optimal alternative to the ensemble Kalman filter (EnKF) with a reduced computational demand making it potentially more suitable for operational applications. Since only one model is integrated forward instead of an ensemble of model realizations, online estimation of the background error covariance matrix is not possible in the EnOI scheme. In this study, we investigate two Gaussian noise based ensemble generation strategies to produce dynamic covariance matrices for assimilation of water level observations into a distributed hydrological model. In the first approach, spatially correlated noise, sampled from a normal distribution with a fixed fractional error parameter (which controls its standard deviation), is added to the model forecast state vector to prepare the ensembles. In the second method, we use an adaptive error estimation technique based on the innovation diagnostics to estimate this error parameter within the assimilation framework. The results from a real and a set of synthetic experiments indicate that the EnOI scheme can provide better results when an optimal EnKF is not identified, but performs worse than the ensemble filter when the true error characteristics are known. Furthermore, while the adaptive approach is able to reduce the sensitivity to the fractional error parameter affecting the first (non-adaptive) approach, results are usually worse at ungauged locations with the former.

• 국제학술발표논문집
• /
• The 3th International Conference on Construction Engineering and Project Management
• /
• pp.1414-1418
• /
• 2009

International construction projects typically manifest difficult, complex, and varied types of risk exposures; because of this, there is a need for accurate evaluation of risk-integrated performances during the timeframe of project execution. Given the financial crisis currently affecting the world economy recession, risk management has become a more crucial part for the success of international project management. However, the majority of risk management approaches, particularly for overseas projects, are focused primarily on simple forms of checklists, formalization of risk variables affecting project performance for a specific phase, or more complicated computational methods that restricting practical utilization in real-world projects; moreover, these methods lack the conceptual basis to broadly visualize the level of risk over all phases of a project. This study suggests an efficient, yet simple risk-integrated total index to successfully assess the risk levels of overseas construction projects. To this end, this paper first investigates the life cycles and key processes of decision-making for a given project and then derives formulas to represent the total risk index (TRI) along the key decision-making processes. In addition, the study examines the relationships between TRI and performance levels based on the analysis of 126 real-world project samples. Validations using the proposed TRI showed a high correlation to project performance, signifying the usefulness of the proposed approach for construction firms when investigating the level of risks and key areas for management focus.

• 국제학술발표논문집
• /
• The 9th International Conference on Construction Engineering and Project Management
• /
• pp.1114-1121
• /
• 2022

Construction laborers and crews play a critical role in achieving a safe and productive construction site. Many past research studies used top-down approaches/perspectives for studying the impact of laborers' performance on overall construction site outputs with limited flexibility in accounting for laborers' various characteristics. However, the recent reap in computational advances allowed applications of bottom-up architectures, which can potentially incorporate heterogeneous characteristics of laborers' individual behavioral and decision-making features effectively. Accordingly, agent-based modeling (ABM), as a tool to leverage a bottom-up methodological approach, has been widely adopted by recent research. Existing literature investigated the influence of changes in laborers' behaviors and interactions on either construction sites' safety performance or productivity performance individually, leaving the tradeoff between safety and productivity in this context relatively unexplored. Accordingly, this study aims to develop an agent-based framework to study the tradeoff between project safety and productivity performances resulting from changes in laborers' behaviors after attending safety trainings. Our findings via simulations indicate that proper safety trainings can improve safety performance without negatively impacting productivity performance.

• Nuclear Engineering and Technology
• /
• 제55권5호
• /
• pp.1911-1923
• /
• 2023

The nuclear safety assessment involving large transient simulations is forcing the community to develop methods for coupling thermal-hydraulics and neutronic codes and three-dimensional (3D) Computational Fluid Dynamics (CFD) codes. In this paper a set of dynamic boundary conditions are implemented in OpenFOAM^Ⓡ in order to apply zero-dimensional (0D) approaches coupling with 3D thermal-hydraulic simulation in a single framework. This boundary conditions are applied to model pipelines, tanks, pumps, and heat exchangers. On a first stage, four tests are perform in order to assess the implementations. The results are compared with experimental data, full 3D CFD, and system code simulations, finding a general good agreement. The semi-implicit implementation nature of these boundary conditions has shown robustness and accuracy for large time steps. Finally, an application case, consisting of a simplified open pool with a cooling external circuit is solved to remark the capability of the tool to simulate thermal hydraulic systems commonly found in nuclear installations.

• Nuclear Engineering and Technology
• /
• 제55권5호
• /
• pp.1742-1756
• /
• 2023

The hydrogen behavior in a nuclear containment vessel is a significant issue when discussing the potential of hydrogen combustion during a severe accident. After the Fukushima-Daiichi accident in Japan, we have investigated in-depth the hydrogen transport mechanisms by utilizing experimental and numerical approaches. Computational fluid dynamics is a powerful tool for better understanding the transport behavior of gas mixtures, including hydrogen. This paper describes a Large-eddy simulation of gas mixing driven by a high-buoyancy flow. We focused on the interaction behavior of heat and mass transfers driven by the horizontal high-buoyant flow during density stratification. For validation, the experimental data of the Containment InteGral effects Measurement Apparatus (CIGMA) facility were used. With a high-power heater for the gas-injection line in the CIGMA facility, a high-temperature flow of approximately 390 ℃ was injected into the test vessel. By using the CIGMA facility, we can extend the experimental data to the high-temperature region. The phenomenological discussion in this paper helps understand the heat and mass transfer induced by the high-buoyancy flow in the containment vessel during a severe accident.

• International Journal of Computer Science & Network Security
• /
• 제23권6호
• /
• pp.193-201
• /
• 2023

In this paper, we consider the maximum scatter traveling salesman problem (MSTSP), a travelling salesman problem (TSP) variant. The problem aims to maximize the minimum length edge in a salesman's tour that travels each city only once in a network. It is a very complicated NP-hard problem, and hence, exact solutions can be found for small sized problems only. For large-sized problems, heuristic algorithms must be applied, and genetic algorithms (GAs) are found to be very successfully to deal with such problems. So, this paper develops a hybrid GA (HGA) for solving the problem. Our proposed HGA uses sequential sampling algorithm along with 2-opt search for initial population generation, sequential constructive crossover, adaptive mutation, randomly selected one of three local search approaches, and the partially mapped crossover along with swap mutation for perturbation procedure to find better quality solution to the MSTSP. Finally, the suggested HGA is compared with a state-of-art algorithm by solving some TSPLIB symmetric instances of many sizes. Our computational experience reveals that the suggested HGA is better. Further, we provide solutions to some asymmetric TSPLIB instances of many sizes.

• Genomics & Informatics
• /
• 제21권1호
• /
• pp.6.1-6.8
• /
• 2023

Glaucoma is the second leading cause of irreversible blindness, and primary open-angle glaucoma (POAG) is the most common type. Due to inadequate diagnosis, treatment is often not administered until symptoms occur. Hence, approaches enabling earlier prediction or diagnosis of POAG are necessary. We aimed to identify novel drugs for glaucoma through bioinformatics and network analysis. Data from 36 samples, obtained from the trabecular meshwork of healthy individuals and patients with POAG, were acquired from a dataset. Next, differentially expressed genes (DEGs) were identified to construct a protein-protein interaction (PPI) network. In both stages, the genes were enriched by studying the critical biological processes and pathways related to POAG. Finally, a drug-gene network was constructed, and novel drugs for POAG treatment were proposed. Genes with p < 0.01 and |log fold change| > 0.3 (1,350 genes) were considered DEGs and utilized to construct a PPI network. Enrichment analysis yielded several key pathways that were upregulated or downregulated. For example, extracellular matrix organization, the immune system, neutrophil degranulation, and cytokine signaling were upregulated among immune pathways, while signal transduction, the immune system, extracellular matrix organization, and receptor tyrosine kinase signaling were downregulated. Finally, novel drugs including metformin hydrochloride, ixazomib citrate, and cisplatin warrant further analysis of their potential roles in POAG treatment. The candidate drugs identified in this computational analysis require in vitro and in vivo validation to confirm their effectiveness in POAG treatment. This may pave the way for understanding life-threatening disorders such as cancer.