• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.27-42
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• 2019

It is not easy to evacuate when people face with emergency situation in deep underground space because space perception and synthetic judgement are readily lowered. In stead of evacuating safely outside within the given time, evacuation safety zone is required to be designed and installed. In this study, PATS (Pedestrian movement based Assessment Toolkit for Simulation) is applied to build a comprehensive and analytic framework for seeking the optimal (or proper) numbers and locations of evacuation safety zone. With two scenarios of emergency situation at intermodal transfer center with the 6 floor in underground, the problematic location on the evacuation path has been identified and the proper locations has been presented.

• Journal of Ocean Engineering and Technology
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• v.35 no.1
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• pp.50-58
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• 2021

The demand for eco-friendly energy is expected to increase due to the recently strengthened environmental regulations. In particular, the flow inside the pipe used in a cargo handling system (CHS) or fuel gas supply system (FGSS) of hydrogen transport ships and hydrogen-powered ships exhibits a very complex pattern of multiphase-thermal flow, including the boiling phenomenon and high accuracy analysis is required concerning safety. In this study, a feasibility study applying the boiling model was conducted to analyze the multiphase-thermal flow in the pipe considering the phase change. Two types of boiling models were employed and compared to implement the subcooled boiling phenomenon in nucleate boiling numerically. One was the "Rohsenow boiling model", which is the most commonly used one among the VOF (Volume-of-Fluid) boiling models under the Eulerian-Eulerian framework. The other was the "wall boiling model", which is suitable for nucleate boiling among the Eulerian multiphase models. Moreover, a comparative study was conducted by combining the nucleate site density and bubble departure diameter model that could influence the accuracy of the wall boiling model. A comparison of the Rohsenow boiling and the wall boiling models showed that the wall boiling model relatively well represented the process of bubble formation and development, even though more computation time was consumed. Among the combination of models used in the wall boiling model, the simulation results were affected significantly by the bubble departure diameter model, which had a very close relationship with the grid size. The present results are expected to provide useful information for identifying the characteristics of various parameters of the boiling model used in CFD simulations of multiphase-thermalflow, including phase change and selecting the appropriate parameters.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.168-177
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• 2020

In recent years, importance of blockchain systems has been grown after success of bitcoin. Distributed consensus algorithm is used to achieve an agreement, which means the same information is recorded in all nodes participating in blockchain network. Various algorithms were suggested to resolve blockchain trilemma, which refers conflict between decentralization, scalability, security. An algorithm based on Byzantine Agreement among Decentralized Agents (BADA) were designed for the same manner, and it used limited committee that enables an efficient consensus among considerable number of nodes. In addition, election of committee based on Proof-of-Nonce guarantees decentralization and security. In spite of such prominence, application of BADA in actual blockchain system requires further researches about performance and essential features affecting on the performance. However, performance assessment committed in real systems takes a long time and costs a great deal of budget. Based on this motivation, we designed and implemented a simulator for measuring performance of BADA. Specifically, we defined a simulation framework including three components named simulator Command Line Interface, transaction generator, BADA nodes. Furthermore, we carried out response surface analysis for revealing latent relationship between performance measure and design parameters. By using obtained response surface models, we could find an optimal configuration of design parameters for achieving a given desirable performance level.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.47-53
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• 2021

In this paper, we propose a quadtree-based optimization technique that enables fast Super-resolution(SR) computation by efficiently classifying and dividing physics-based simulation data required to calculate SR. The proposed method reduces the time required for quadtree computation by downscaling the smoke simulation data used as input data. By binarizing the density of the smoke in this process, a quadtree is constructed while mitigating the problem of numerical loss of density in the downscaling process. The data used for training is the COCO 2017 Dataset, and the artificial neural network uses a VGG19-based network. In order to prevent data loss when passing through the convolutional layer, similar to the residual method, the output value of the previous layer is added and learned. In the case of smoke, the proposed method achieved a speed improvement of about 15 to 18 times compared to the previous approach.

• Structural Engineering and Mechanics
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• v.80 no.6
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• pp.645-655
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• 2021

Performance-based reliability analysis is a practical approach to investigate the seismic performance and stochastic nonlinear response of structures considering a random process. This is significant due to the uncertainties involved in every aspect of the analysis. Therefore, the present study aims to evaluate the performance-based reliability within a stochastic finite element (FE) framework for reinforced concrete (RC) shear walls that are considered as one of the most essential elements of structures. To accomplish this purpose, deterministic FE analyses are conducted for both squat and slender shear walls to validate numerical models through experimental results. The presented numerical analysis is performed by using the ABAQUS FE program. Afterwards, a random-effects investigation is carried out to consider the influence of different random variables on the lateral load-top displacement behavior of RC members. Using these results and through utilizing the Monte-Carlo simulation method, stochastic nonlinear analyses are also performed to generate random FE models based on input parameters and their probabilistic distributions. In order to evaluate the reliability of RC walls, failure probabilities and corresponding reliability indices are calculated at life safety and collapse prevention levels of performance as suggested by FEMA 356. Moreover, based on reliability indices, capacity reduction factors are determined subjected to shear for all specimens that are designed according to the ACI 318 Building Code. Obtained results show that the lateral load and the compressive strength of concrete have the highest effects on load-displacement responses compared to those of other random variables. It is also found that the probability of shear failure for the squat wall is slightly lower than that for slender walls. This implies that 𝛽 values are higher in a non-ductile mode of failure. Besides, the reliability of both squat and slender shear walls does not change significantly in the case of varying capacity reduction factors.

• Wind and Structures
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• v.35 no.6
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• pp.405-418
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• 2022

The aerodynamic behaviour of a CRH high-speed train under three infrastructure scenarios (flat ground, embankment, and viaduct) in the presence of a crosswind was simulated using a 1/8th scaled train model with three cars and the IDDES framework. The time-averaged and instantaneous flow field around the model were examined. The employed numerical algorithm was verified through a wind tunnel test, and the grid and timestep resolution analyses were conducted to ensure the reliability of the data. It was noted that the flow around the rail line was different under different infrastructure scenarios, especially in the case of the embankment, which degraded the aerodynamic performance of the train under the crosswind. The flow around the train on the flat ground and viaduct was different, although the aerodynamic performance of the train was similar in both cases. Moreover, the viaduct accidents were noted to have the most critical consequences, thereby requiring the most attention. The aerodynamic performance of the train on the windward track of the embankment under the crosswind was worse than that of the train on the leeward track. But for the other two infrastructure scenarios, the aerodynamic performance of the train on the windward track is relatively dangerous, which is mainly caused by the head car. These observations suggest that the aerodynamic behaviour of the train on an embankment under a crosswind must be carefully considered and that certain wind protection measures must be adopted around rail lines in windy areas.

• Journal of the Korean Geotechnical Society
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• v.24 no.8
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• pp.111-123
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• 2008

Geotechnical engineering problems are characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for a probabilistic analysis that considers the spatial variability of soil properties is presented to study the response of spatially random soil. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two-dimensional non-Gaussian random fields are generated based on a Karhunen-$Lo{\grave{e}}ve$ expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to study the effects of uncertainty due to the spatial heterogeneity on the settlement and bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to the geotechnical problem and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.443-449
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• 2022

With climate change and the global population growth, the frequency and scope of wildfires are constantly increasing, which threatened people's lives and property. For example, according to California Department of Forestry and Fire Protection, in 2020, a total of 9,917 incidents related to wildfires were reported in California, with an estimated burned area of 4,257,863 acres, resulting in 33 fatalities and 10,488 structures damaged or destroyed. At the same time, the ongoing development of technology provides new tools to simulate and analyze the spread of wildfires. How to use new technology to reduce the losses caused by wildfire is an important research topic. A potentially feasible strategy is to simulate and analyze the spread of wildfires through computing technology to explore the impact of different factors (such as weather, terrain, etc.) on the spread of wildfires, figure out how to take preemptive/responsive measures to minimize potential losses caused by wildfires, and as a result achieve better management support of wildfires. In preparation for pursuing these goals, the authors used a powerful computing framework, Spark, developed by the Commonwealth Scientific and Industrial Research Organization (CSIRO), to study the effects of different weather factors (wind speed, wind direction, air temperature, and relative humidity) on the spread of wildfires. The test results showed that wind is a key factor in determining the spread of wildfires. A stable weather condition (stable wind and air conditions) is beneficial to limit the spread of wildfires. Joint consideration of weather factors and environmental obstacles can help limit the threat of wildfires.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.510-519
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• 2020

Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.163-168
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• 2013

A construction workspace is considered as a critical factor to secure constructability and safety of a project. Specially, optimized size of each workspace helps to minimize any conflicts between workspaces, works and resources within a workspace in the construction site. However, since an existing method for making a decision workspace's size depends on generally experiences of managers and work conditions of activity, it is difficult to perform safe works considering feasible workspace size. The workspace size is changed according to the quantity of resources allocated into each activity as time progresses. Accordingly, it is desirable that optimized workspace size considering input size of resources is determined. To solve these issues, this study configures an optimized model for deciding standard size of workspaces by simple regression analysis and develops a visualized scenario model for simulating the optimized workspace shape in order to support BIM (Building Information Modeling) environment. For this, this study determines an optimized resource shape size considering maximum working radius of each resource and constructs its visual model. Subsequently, input size of resources for each activity is estimated considering safety execution area of resources and workspaces. Based on this, an optimized 3D workspace shape is generated as a VR simulation model of a BIM system based on the suggested methodologies. Moreover, operational feasibility of the developed system is evaluated through a case study for a bride project. Therefore, this study provides a visualized framework so that project managers can establish an efficient workspace planning in BIM environment. Besides, it is expected that constructability, productivity and safety of the project will be improved by minimizing conflicts between workspace and congestions between resources within a workspace in the construction phase.