• Journal of the Korea Society for Simulation
• /
• v.25 no.3
• /
• pp.41-51
• /
• 2016

In this study, we propose an improved Floor Field Model(FFM) that considers the physical characteristics of pedestrians, i.e., body size, shape, and posture. Also we analyse limits of FFM and features of improved model compared with existing evacuation simulation models. FFM is a typical microscopic pedestrian model using CA, but it does not reflect the physical characteristics of pedestrians. Because of this, FFM is difficult to modeling phenomena such as collision, friction between pedestrians. As a result, FFM calculates a very short evacuation time when compared with the other models. We performed a computational experiment to compare improved model with other models such as FFM, Simulex, Pathfinder in an actual campus building. We carried out a comparison of evacuation aspect according to the change in number of evacuees. Also we compared evacuation aspect by exit. Finally, we confirmed that improved model reflects physical phenomena which were not reflected in FFM. Especially, experimental results were very similar to the Simulex.

• Journal of the Korean Society for Railway
• /
• v.16 no.3
• /
• pp.169-174
• /
• 2013

The effect of modifying the shape of a high-performance EMU train on the aerodynamic drag is studied here using Computational Fluid Dynamics(CFD) based on three dimensional Steady-state Navier-Stokes equation and two equation turbulence modeling. FLUENT 12 and Gambit 2.4.6 are employed for a numerical simulation of the aerodynamic drag of a streamlined-shape train as well as a proto type train. The characteristics of the aerodynamic drag of trains in tunnels are analyzed in a comparison with these characteristics in an open space. The contribution of the aerodynamic drag of each case is also investigated to establish principal pertaining to drag reduction for urban trains in tunnels. The aerodynamic drag of a streamlined train was reduced to 9.8% relative to a proto-type train with a blunt nose and a protruding roof facility and underbody shape: the running resistance is expected to be reduced by as much as 4% at a running speed of 80km/h.

• Nuclear Engineering and Technology
• /
• v.53 no.12
• /
• pp.3902-3909
• /
• 2021

SACOS series of subchannel analysis codes have been developed by XJTU-NuTheL for many years and are being used for the thermal-hydraulic safety analysis of various reactor cores. To achieve fine whole core pin-level analysis, the input preprocessing and parallel capabilities of the code have been developed in this study. Preprocessing is suitable for modeling rectangular and hexagonal assemblies with less error-prone input; parallelization is established based on the domain decomposition method with the hybrid of MPI and OpenMP. For domain decomposition, a more flexible method has been proposed which can determine the appropriate task division of the core domain according to the number of processors of the server. By performing the calculation time evaluation for the several PWR assembly problems, the code parallelization has been successfully verified with different number of processors. Subsequent analysis results for rectangular- and hexagonal-assembly core imply that the code can be used to model and perform pin-level core safety analysis with acceptable computational efficiency.

• Advances in Computational Design
• /
• v.4 no.2
• /
• pp.155-177
• /
• 2019

Operation and Maintenance (O&M) phase is the main contributor to the total lifecycle cost of a building. Previous studies have described that Building Information Models (BIM), if available with detailed asset information and their properties, can enable rapid troubleshooting and execution of O&M tasks by providing the required information of the facility. Despite the potential benefits, there is still rarely BIM with Mechanical, Electrical and Plumbing (MEP) assets and properties that are available for O&M. BIM is usually not in possession for existing buildings and generating BIM manually is a time-consuming process. Hence, there is a need for an automated approach that can reconstruct the MEP systems in BIM. Previous studies investigated automatic reconstruction of BIM using architectural drawings, structural drawings, or the combination with photos. But most of the previous studies are limited to reconstruct the architectural and structural components. Note that mechanical components in the building typically require more frequent maintenance than architectural or structural components. However, the building mechanical drawings are relatively more complex due to various type of symbols that are used to represent the mechanical systems. In order to address this challenge, this paper proposed a symbol recognition framework that can automatically recognize the different type of symbols in the building mechanical drawings. This study applied vector-based computer vision techniques to recognize the symbols and their properties (e.g., location, type, etc.) in two vector-based input documents: 2D drawings and the symbol description document. The framework not only enables recognizing and locating the mechanical component of interest for BIM reconstruction purpose but opens the possibility of merging the updated information into the current BIM in the future reducing the time of repeated manual creation of BIM after every renovation project.

• Advances in Computational Design
• /
• v.4 no.1
• /
• pp.53-72
• /
• 2019

Safety measures for tower cranes are extremely important among the seismic countermeasures at high-rise building construction sites. In particular, the collapse of a tower crane from a high position is a very serious catastrophe. An example of such an accident due to an earthquake is the case of the Taipei 101 Building (the author was the project director), which occurred on March 31, 2002. Failure of the bolted joints of the tower-crane mast was the direct cause of the collapse. Therefore, it is necessary to design for this eventuality and to take the necessary measures on construction sites. This can only be done by understanding the precise dynamic behavior of mast joints during an earthquake. Consequently, we created a new hybrid-element model (using beam, shell, and solid elements) that not only expressed the detailed behavior of the site joints of a tower-crane mast during an earthquake but also suppressed any increase in the total calculation time and revealed its behavior through computer simulations. Using the proposed structural model and simulation method, effective information for designing safe joints during earthquakes can be provided by considering workability (control of the bolt pretension axial force and other factors) and less construction cost. Notably, this analysis showed that the joint behavior of the initial pretension axial force of a bolt is considerably reduced after the axial force of the bolt exceeds the yield strength. A maximum decrease of 50% in the initial pretension axial force under the El Centro N-S Wave ($v_{max}=100cm/s$) was observed. Furthermore, this method can be applied to analyze the seismic responses of general temporary structures in construction sites.

• Tunnel and Underground Space
• /
• v.32 no.2
• /
• pp.144-159
• /
• 2022

The present study developed a sequential approach-based numerical simulator for modeling coupled thermal-hydrological-mechanical (THM) processes in the ground and investigated the computational performance of the coupling analysis algorithm. The present sequential approach linked the two different solvers: an open-source numerical code, OpenGeoSys for solving the thermal and hydrological processes in porous media and a commercial code, FLAC3D for solving the geomechanical response of the ground. A benchmark test of the developed simulator was carried out using a THM problem where an analytical solution is given. The benchmark problem involves the coupled behavior (variations in temperature, pore pressure, stress, and deformation with time) of a fully saturated porous medium which is subject to a point heat source. The results of the analytical solution and numerical simulation were compared and the validity of the numerical simulator was investigated.

• Nuclear Engineering and Technology
• /
• v.54 no.1
• /
• pp.36-48
• /
• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Membrane and Water Treatment
• /
• v.13 no.5
• /
• pp.235-243
• /
• 2022

The paper presents the effect of operating temperatures and flow rates on the distillate flux that can be obtained from a hydrophobic membrane having the characteristics: pore size of 0.15 ㎛; thickness of 130 ㎛; and 85% porosity. That membrane in the present investigation could be the direct contact (DCMD) or the air-gap membrane distillation (AGMD). To model numerically the membrane distillation processes, the two-dimensional computational fluid dynamic (CFD) is used for the DCMD and AGMD cases here. In this work, DCMD and AGMD models have been validated with the experimental data using different flows (Parallel and Counter-current flows) in non-steady-state situations. A good agreement is obtained between the present results and those of the experimental data in the literature. The new approach in the present numerical modeling has allowed examining effects of the nature of materials (Polyvinylidene fluoride (PVDF) polymers, copolymers, and blends) used on thermal properties. Moreover, the effect of the area surface of the membrane (0.021 to 3.15 ㎡) is investigated to explore both the laminar and the turbulent flow regimes. The obtained results found that copolymer P(VDF-TrFE) (80/20) is more effective than the other materials of membrane distillation (MD). The mass flux and thermal efficiency reach 193.5 (g/㎡s), and 83.29 % using turbulent flow and an effective area of 3.1 ㎡, respectively. The increase of feed inlet temperatures and its flow rate, with the reduction of cold temperatures and its flow rate are very effective for increasing distillate water flow in MD applications.

• Smart Structures and Systems
• /
• v.28 no.6
• /
• pp.745-760
• /
• 2021

Dynamic buckling of structure is one of the failure modes that needs to be considered since it may result in catastrophic failure of the structure in a short period of time. For a thin fiber-reinforced polymer (FRP) plate under compression, buckling is an inherent hazard which will be intensified by the existence of defects like holes, cracks, and delamination. On the other hand, the growth of the delamination is another prime concern for thin FRP plates. In the current paper, reinforcing the plates against buckling is realized by using SMA wires in the form of stitches. A numerical framework is proposed to simulate the dynamic instability emphasizing the effect of the SMA stitches in suppressing delamination growth. The suggested algorithm is more accurate than the other methods when considering the transformation point of the SMA wires and the modeling of the cohesive zone using simple and yet reliable technique. The computational design of the method by producing the line by line orders leads to a simple algorithm for simulating the super-elastic behavior. The Lagoudas constitutive model of the SMA material is implemented in the form of user material subroutines (VUMAT). The normal bilinear spring model is used to reproduce the cohesive zone behavior. The nonlinear finite element formulation is programmed into FORTRAN using the Newmark-beta numerical time-integration approach. The obtained results are compared with the results obtained by the finite element method using ABAQUS/Explicit solver. The obtained results by the proposed algorithm and those by ABAQUS are in good agreement.

• Steel and Composite Structures
• /
• v.44 no.2
• /
• pp.241-254
• /
• 2022

The cables in a cable-stayed bridge are critical load-carrying parts. The potential damage to cables should be identified early to prevent disasters. In this study, an efficient deep learning model is proposed for the damage identification of cables using both a multi-layer perceptron (MLP) and a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), which is a robust program for modeling and analyzing bridge structures with low computational costs. The model based on the MLP and GNN can capture complex nonlinear correlations between the vibration characteristics in the input data and the cable system damage in the output data. Multiple hidden layers with an activation function are used in the MLP to expand the original input vector of the limited measurement data to obtain a complete output data vector that preserves sufficient information for constructing the graph in the GNN. Using the gated recurrent unit and set2set model, the GNN maps the formed graph feature to the output cable damage through several updating times and provides the damage results to both the classification and regression outputs. The model is fine-tuned with the original input data using Adam optimization for the final objective function. A case study of an actual cable-stayed bridge was considered to evaluate the model performance. The results demonstrate that the proposed model provides high accuracy (over 90%) in classification and satisfactory correlation coefficients (over 0.98) in regression and is a robust approach to obtain effective identification results with a limited quantity of input data.