• 한국BIM학회 논문집
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• 제12권4호
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• pp.61-69
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• 2022

Earthmoving operations account for approximately 25% of construction cost, generally executed prior to the construction of buildings and structures with heavy equipment. For the successful completion of earthwork projects, it is crucial to constantly monitor earthwork equipment (e.g., trucks), estimate productivity, and optimize the construction process and equipment on a construction site. Traditional methods however require time-consuming and painstaking tasks for the manual observations of the ongoing field operations. This study proposed the use of a GPS sensor embedded in a smartphone for the tracking and visualization of equipment locations, which are in turn used for the estimation and simulation of cycle times and production rates of ongoing earthwork. This approach is implemented into a digital platform enabling real-time data collection and simulation, particularly in a 2D (e.g., maps) or 3D (e.g., point clouds) virtual environment where the spatial and temporal flows of trucks are visualized. In the case study, the digital platform is applied for an earthmoving operation at the site development work of commercial factories. The results demonstrate that the production rates of various equipment usage scenarios (e.g., the different numbers of trucks) can be estimated through simulation, and then, the optimal number of tucks for the equipment fleet can be determined, thus supporting the practical potential of real-time sensing and simulation for onsite equipment management.

• Nuclear Engineering and Technology
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• 제54권5호
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• pp.1825-1834
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• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• Steel and Composite Structures
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• 제44권2호
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• pp.241-254
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• 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.

• Smart Structures and Systems
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• 제29권3호
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• pp.445-455
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• 2022

Steel anchor bolts are installed in concrete using a variety of methods. One of the most common methods of anchor bolt installation is using epoxy resin as an infill material injected into the drilled hole to act as a bonding material between the steel bolt and the surrounding concrete. Typical design standards assume uniform stress distribution along the length of the anchor bolt accompanied with single crack leading to pull-out failure. Experimental evidence has shown that the steel anchor bolts fail owing to the multiple failure patterns, hence these design assumptions are not realistic. In this regard, the presented research work details the analytical model that takes into consideration multiple micro cracks in the infill material induced via impact loading. The impact loading from the Schmidt hammer is used to evaluate the bond condition bond condition of anchor bolt and the epoxy material. The added advantage of the presented analytical model is that it is able to take into account the various type of end conditions of the anchor bolts such as bent or U-shaped anchors. Through sensitivity analysis the optimum stiffness and shear strength properties of the epoxy infill material is achieved, which have shown to achieve lower displacement coupled with reduced damage to the surrounding concrete. The accuracy of the presented model is confirmed by comparing the simulated deformational responses with the experimental evidence. From the comparison it was found that the model was successful in simulating the experimental results. The proposed model can be adopted by professionals interested in predicting and controlling the deformational response of anchor bolts.

• Current Optics and Photonics
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• 제6권2호
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• pp.202-211
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• 2022

In the pasteurization of escalator handrails using ultraviolet (UV) sterilizers, a combination of light distribution and escalator speed has priority over other important factors. Furthermore, since part of the escalator handrail has a curved structure, proper design is needed to improve the sterilization rate on the surfaces touched by users. In this paper, two types of sterilizers satisfying these conditions are manufactured with 275-nm UV-C LEDs, after modeling the three-dimensional (3D) structure of an escalator handrail and simulating optical distributions of UV-C irradiation on the handrail's surface according to light-emitting diode (LED) positions and reflector variations in the sterilizers. Pasteurization experiments with the UV-C LED sterilizers are conducted on six types of gram-positive and gram-negative bacteria, with exposure times of 0.2, 5, and 15 s at an actual installation distance of 20 mm. The sterilization rates for the gram-positive bacteria are 10.63% to 27.94% at 0.2 s, 89.44% to 96.30% at 5 s, and 99.64% to 99.88% at 15 s. Those for the gram-negative bacteria are 57.70% to 77.63% at 0.2 s, 98.90% to 99.49% at 5 s, and 99.88% to 99.99% at 15 s. The power consumption of the UV-C LED sterilizer is about 8 W, which can be supplied by a self-generation module instead of an external power supply.

• 한국컴퓨터그래픽스학회논문지
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• 제29권1호
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• pp.13-22
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• 2023

본 논문은 특정 자세를 취하고 있는 인간형 캐릭터의 단순한 실루엣 그림 등을 입력으로 받아 이로부터 3차원 신체 외형 정보를 복원하는 기술을 다룬다. 기하학적인 방법 만으로 실루엣에 담기지 않은 내부 형체를 추출하는 것은 매우 어려운 일이기에 본 논문은 대규모 신체 3차원 형체 데이터베이스 및 이의 통계적 분석 데이터를 활용하여 인간형 템플릿 모델을 실루엣에 맞도록 정합 하는 것을 주된 아이디어로 한다. 본 기술은 다음의 세 단계로 이뤄진다. 먼저 주어진 실루엣 이미지로부터 이미지 분석을 통해 윤곽선 및 법선 벡터를 추출한다. 둘째로, 실루엣 이미지와 3차원 모델 간의 점 대 점 대응관계를 수립한다. 마지막으로 수치적 최적화를 통해 실루엣과 모델이 최대한 일치하도록 파라메터들을 정한다. 본 논문은 실루엣 정보로부터 3차원 신체 형태를 최적화하는 실용적 방법론을 제시한 것이 주된 기여이며, 기술의 유효성을 실험을 통해 검증하였다.

• Current Optics and Photonics
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• 제7권1호
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• pp.1-14
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• 2023

Wavefront-coding imaging can achieve high-quality imaging along with a wide range of defocus. In this paper, the anti-laser detection and damage performance of wavefront-coding imaging systems using different asymmetric phase masks are studied, through modeling and simulation. Based on FresnelKirchhoff diffraction theory, the laser-propagation model of the wavefront-coding imaging system is established. The model uses defocus distance rather than wave aberration to characterize the degree of defocus of an imaging system. Then, based on a given defocus range, an optimization method based on Fisher information is used to determine the optimal phase-mask parameters. Finally, the anti-laser detection and damage performance of asymmetric phase masks at different defocus distances and propagation distances are simulated and analyzed. When studying the influence of defocus distance, compared to conventional imaging, the maximum single-pixel receiving power and echo-detection receiving power of asymmetric phase masks are reduced by about one and two orders of magnitude respectively. When exploring the influence of propagation distance, the maximum single-pixel receiving power of asymmetric phase masks decreases by about one order of magnitude and remains stable, and the echodetection receiving power gradually decreases with increasing propagation distance, until it approaches zero.

• 한국컴퓨터그래픽스학회논문지
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• 제28권4호
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• pp.1-11
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• 2022

선형 스키닝 기반 3D 인체 생성 모델 SMPL (Skinned Multi-Person Linear Model)은 1990년대 미국 거주 미국인들 3천 8백여명을 대상으로 만들어진 3D 신체 데이터베이스인 CEASAR 로부터 최적화 기법을 통해 만들어진 가장 널리 쓰이는 통계적인 3D 모델이다. 본 연구는 한국인 체형의 통계적 특성을 보다 정확히 표현하는 SMPL기반의 한국인 체형 3D 모델을 제안한다. 이를 위해 우리는 한국인 여성 2천7백여명의 신체 각 부위의 실측 데이터에 기존 3D SMPL 모델을 피팅하는 비선형 최적화 알고리즘을 개발한다. 이를 사용하여 한국인 3D 신체 데이터베이스를 구축하고, 주성분 분석 방법으로 한국인 체형 기반 매개화된 3D 모델을 개발한다. 본 연구를 통해 제안하는 한국인의 체형적 특징을 가진 블렌드쉐입과 새로운 체형 파라미터는 기존 모델이 표현하는 체형에 비해 한국인 체형 데이터 특성을 잘 반영함을 확인하였다. 뿐만 아니라, 우리의 모델은 SMPL에 비해 신체 실측 데이터에 대한 피팅 정확도를 개선함을 확인하였다. 제안된 모델은 향후 아바타 생성이나 인체 형상 측정 등 다양한 용도로 사용될 수 있다.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.75-84
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• 2020

Modular construction is a construction method whereby prefabricated volumetric units are produced in a factory and are installed on site to form a building block. The construction productivity can be substantially improved by the manufacturing and assembly of standardized modular units. 3D printing is a computer-controlled fabrication method first adopted in the manufacturing industry and was utilized for the automated construction of small-scale houses in recent years. Implementing 3D printing in the fabrication of modular units brings huge benefits to modular construction, including increased customization, lower material waste, and reduced labor work. Such implementation also benefits the large-scale and wider adoption of 3D printing in engineering practice. However, a critical issue for 3D printed modules is the loading capacity, particularly in response to horizontal forces like wind load, which requires a deeper understanding of the building structure behavior and the design of load-bearing modules. Therefore, this paper presents the state-of-the-art literature concerning recent achievement in 3D printing for buildings, followed by discussion on the opportunities and challenges for examining 3D printing in modular construction. Promising 3D printing techniques are critically reviewed and discussed with regard to their advantages and limitations in construction. The appropriate structural form needs to be determined at the design stage, taking into consideration the overall building structural behavior, site environmental conditions (e.g., wind), and load-carrying capacity of the 3D printed modules. Detailed finite element modelling of the entire modular buildings needs to be conducted to verify the structural performance, considering the code-stipulated lateral drift, strength criteria, and other design requirements. Moreover, integration of building information modelling (BIM) method is beneficial for generating the material and geometric details of the 3D printed modules, which can then be utilized for the fabrication.

• Smart Structures and Systems
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• 제32권5호
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• pp.281-295
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• 2023

The purpose of this study is to demonstrate and verify the application of phase-control absolute-acceleration-feedback active tuned mass dampers (PCA-ATMD) to multiple-degree-of-freedom (MDOF) building structures. In addition, servo speed control technique has been developed as a replacement for force control in order to mitigate the negative effects caused by friction and inertia. The essence of the proposed PCA-ATMD is to achieve a 90° phase lag for a structure by implementing the desired control force so that the PCA-ATMD can receive the maximum power flow with which to effectively mitigate the structural vibration. An MDOF building structure with a PCA-ATMD and a real-time filter forming a complete system is modeled using a state-space representation and is presented in detail. The feedback measurement for the phase control algorithm of the MDOF structure is compact, with only the absolute acceleration of one structural floor and ATMD's velocity relative to the structure required. A discrete-time direct output-feedback optimization method is introduced to the PCA-ATMD to ensure that the control system is optimized and stable. Numerical simulation and shaking table experiments are conducted on a three-story steel shear building structure to verify the performance of the PCA-ATMD. The results indicate that the absolute acceleration of the structure is well suppressed whether considering peak or root-mean-square responses. The experiment also demonstrates that the control of the PCA-ATMD can be decentralized, so that it is convenient to apply and maintain to real high-rise building structures.