Piles of a bridge pier are connected with the column through the pile cap (footing). Behavior of the pile foundation can be different according to the connection method between piles and the pile cap. Connection methods between pile heads and the pile cap are divided into two groups : rigid connections and hinge connections. Domestic design code has been specified to use rigid connection method for the highway bridge. In the rigid connection method, maximum bending moment of a pile occurs at the pile head and this helps the pile to prevent the excessive displacement. Rigid methods are also good to improve the seismic performance. However, some specifications prescribe that conservative results through investigations of both the fixed-head condition and the free-head condition should be reflected in the design. This statement may induce an over-estimated design for the bridge which has high-quality structures with casing covered drilled shafts and the PC-house contained pile cap. Because the assumption of free-head conditions (hinge connections) is unreal for the elevated pile cap system with multiple piles of the long span sea-crossing bridges. On the other hand, elastic displacement method to evaluate the pile reactions under the pile cap is not suitable for this type of bridges due to impractical assumptions. So, full modeling techniques which analyze the superstructure and the substructure simultaneously should be performed. Loads and stress state of the large diameter drilled shaft and the pile cap for Incheon Bridge which will be the longest bridge of Korea were investigated through the full modeling for rigid connection conditions.
Pa, Pa Win Aung;Lee, Donghwan;Park, Jooyoung;Cho, Mingeon;Park, Seunghee
KSCE Journal of Civil and Environmental Engineering Research
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v.42
no.2
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pp.249-256
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2022
Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.
Jung, In Kyun;Lee, Mi Seon;Park, Jong Yoon;Kim, Seong Joon
KSCE Journal of Civil and Environmental Engineering Research
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v.28
no.6B
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pp.697-707
/
2008
The grid-based KIneMatic wave STOrm Runoff Model (KIMSTORM) by Kim (1998) predicts the temporal variation and spatial distribution of overland flow, subsurface flow and stream flow in a watershed. The model programmed with C++ language on Unix operating system adopts single flowpath algorithm for water balance simulation of flow at each grid element. In this study, we attempted to improve the model by converting the code into FORTRAN 90 on MS Windows operating system and named as ModKIMSTORM. The improved functions are the addition of GAML (Green-Ampt & Mein-Larson) infiltration model, control of paddy runoff rate by flow depth and Manning's roughness coefficient, addition of baseflow layer, treatment of both spatial and point rainfall data, development of the pre- and post-processor, and development of automatic model evaluation function using five evaluation criteria (Pearson's coefficient of determination, Nash and Sutcliffe model efficiency, the deviation of runoff volume, relative error of the peak runoff rate, and absolute error of the time to peak runoff). The modified model adopts Shell Sort algorithm to enhance the computational performance. Input data formats are accepted as raster and MS Excel, and model outputs viz. soil moisture, discharge, flow depth and velocity are generated as BSQ, ASCII grid, binary grid and raster formats.
This study conducted preliminary study to identify effective ways to use ChatGPT in traffic policing by analyzing ChatGPT's responses to the driver's license test and the road traffic accident appraiser test. I collected ChatGPT responses for the driver's license test item pool and the road traffic accident appraiser test using the OpenAI API with Python code for 30 iterative experiments, and analyzed the percentage of correct answers by test, year, section, and consistency. First, the average correct answer rate for the driver's license test and the for road traffic accident appraisers test was 44.60% and 35.45%, respectively, which was lower than the pass criteria, and the correct answer rate after 2022 was lower than the average correct answer rate. Second, the percentage of correct answers by section ranged from 29.69% to 56.80%, showing a significant difference. Third, it consistently produced the same response more than 95% of the time when the answer was correct. To effectively utilize ChatGPT, it is necessary to have user expertise, evaluation data and analysis methods, design a quality traffic law corpus and periodic learning.
A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High-Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next-generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds-averaged Navier-Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.
Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.
Nuclear accidents such as Fukushima Daiichi have highlighted the potential of passive safety systems to replace or complement active safety systems as part of the overall prevention and/or mitigation strategies. In addition, passive systems are key features of Small Modular Reactors (SMRs), for which they are becoming almost unavoidable and are part of the basic design of many reactors available in today's nuclear market. Nevertheless, their potential to significantly increase the safety of nuclear power plants still needs to be strengthened, in particular the ability of computer codes to determine their performance and reliability in industrial applications and support the safety demonstration. The PASTELS project (September 2020-February 2024), funded by the European Commission "Euratom H2020" programme, is devoted to the study of passive systems relying on natural circulation. The project focuses on two types, namely the SAfety COndenser (SACO) for the evacuation of the core residual power and the Containment Wall Condenser (CWC) for the reduction of heat and pressure in the containment vessel in case of accident. A specific design for each of these systems is being investigated in the project. Firstly, a straight vertical pool type of SACO has been implemented on the Framatome's PKL loop at Erlangen. It represents a tube bundle type heat exchanger that transfers heat from the secondary circuit to the water pool in which it is immersed by condensing the vapour generated in the steam generator. Secondly, the project relies on the CWC installed on the PASI test loop at LUT University in Finland. This facility reproduces the thermal-hydraulic behaviour of a Passive Containment Cooling System (PCCS) mainly composed of a CWC, a heat exchanger in the containment vessel connected to a water tank at atmospheric pressure outside the vessel which represents the ultimate heat sink. Several activities are carried out within the framework of the project. Different tests are conducted on these integral test facilities to produce new and relevant experimental data allowing to better characterize the physical behaviours and the performances of these systems for various thermo-hydraulic conditions. These test programmes are simulated by different codes acting at different scales, mainly system and CFD codes. New "system/CFD" coupling approaches are also considered to evaluate their potential to benefit both from the accuracy of CFD in regions where local 3D effects are dominant and system codes whose computational speed, robustness and general level of physical validation are particularly appreciated in industrial studies. In parallel, the project includes the study of single and two-phase natural circulation loops through a bibliographical study and the simulations of the PERSEO and HERO-2 experimental facilities. After a synthetic presentation of the project and its objectives, this article provides the reader with findings related to the physical analysis of the test results obtained on the PKL and PASI installations as well an overall evaluation of the capability of the different numerical tools to simulate passive systems.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.24
no.2
/
pp.139-145
/
2024
This paper presents the design of a voltage controlled oscillator (VCO) which is one of the key building blocks in modern wireless communication systems with small VCO gain (Kvco) variation. To compensate conventional large Kvco variation, a series varactor bank has been added to the conventional LC-tank with parallel capacitor bank array. And also, in order to achieve excellent phase noise performance while maintaining wide tuning range, a mixed coarse/fine tuning scheme(series varactor array and parallel capacitor array) is chosen. The switched varactor array bank is controlled by the same digital code for switched capacitor array without additional digital circuits. For use at a low voltage of 1.2V, the proposed current reference circuit in this paper used a current reference circuit for safety with the common gate removed more safely. Implemented in a TSMC 0.13㎛ CMOS RF technology, the proposed VCO can be tuned from 4.4GH to 5.3GHz with the Kvco (VCO gain ) variation of less than 9.6%. While consuming 3.1mA from a 1.2V supply, the VCO has -120dBc/Hz phase noise at 1MHz offset from the carrier of the 5.3 GHz.
Blanket is of vital importance for engineering application of the fusion reactor. Nuclear heat deposition in materials is the main heat source in blanket structure. In this paper, the three-dimensional method for thermal-hydraulics/neutronics coupling analysis is developed and applied for the full-scale module of the helium-cooled ceramic breeder tritium breeding blanket (HCCB TBB) designed for China Fusion Engineering Test Reactor (CFETR). The explicit coupling scheme is used to support data transfer for coupling analysis based on cell-to-cell mapping method. The coupling algorithm is realized by the user-defined function compiled in Fluent. The three-dimensional model is established, and then the coupling analysis is performed using the paralleled Coupling Analysis of Thermal-hydraulics and Neutronics Interface Code (CATNIC). The results reveal the relatively small influence of the coupling analysis compared to the traditional method using the radial fitting function of internal heat source. However, the coupling analysis method is quite important considering the nonuniform distribution of the neutron wall loading (NWL) along the poloidal direction. Finally, the structure optimization of the blanket is carried out using the coupling method to satisfy the thermal requirement of all materials. The nonlinear effect between thermal-hydraulics and neutronics is found during the blanket structure optimization, and the tritium production performance is slightly reduced after optimization. Such an adverse effect should be thoroughly evaluated in the future work.
Journal of The Korean Institute of Defense Technology
/
v.5
no.3
/
pp.8-17
/
2023
The current weapon system is operated as a complex weapon system with various standards and protocols applied, so there is a risk of failure in smooth information exchange during combined and joint operations on the battlefield. The interoperability of weapon systems to carry out precise strikes on key targets through rapid situational judgment between weapon systems is a key element in the conduct of war. Since the Korean military went into service, there has been a need to change the configuration and improve performance of a large number of software and hardware, but there is no verification system for the impact on interoperability, and there are no related test tools and facilities. In addition, during combined and joint training, errors frequently occur during use after arbitrarily changing the detailed operation method and software of the weapon/power support system. Therefore, periodic verification of interoperability between weapon systems is necessary. To solve this problem, rather than having people schedule an evaluation period and conduct the evaluation once, AI should continuously evaluate the interoperability between weapons and power support systems 24 hours a day to advance warfighting capabilities. To solve these problems, To this end, preliminary research was conducted to improve defense interoperability capabilities by applying natural language processing techniques (①Word2Vec model, ②FastText model, ③Swivel model) (using published algorithms and source code). Based on the results of this experiment, we would like to present a methodology (automated evaluation of interoperability requirements evaluation / level measurement through natural language processing model) to implement an automated defense interoperability evaluation tool without relying on humans.
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