• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권5호
• /
• pp.1666-1689
• /
• 2021

The red line of Permanent Basic Farmland is the most important part in the "three-line" demarcation of China's national territorial development plan. The scientific and reasonable delineation of the red line is a major strategic measure being taken by China to improve its ability to safeguard the practical interests of farmers and guarantee national food security. The delineation of Permanent Basic Farmland zoning (DPBFZ) is essentially a multi-objective optimization problem. However, the traditional method of demarcation does not take into account the synergistic development goals of conservation of cultivated land utilization, ecological conservation, or urban expansion. Therefore, this research introduces the idea of artificial immune optimization and proposes a multi-objective model of DPBFZ red line delineation based on a clone selection algorithm. This research proposes an objective functional system consisting of these three sub-objectives: optimal quality of cropland, spatially concentrated distribution, and stability of cropland. It also takes into consideration constraints such as the red line of ecological protection, topography, and space for major development projects. The mathematical formal expressions for the objectives and constraints are given in the paper, and a multi-objective optimal decision model with multiple constraints for the DPBFZ problem is constructed based on the clone selection algorithm. An antibody coding scheme was designed according to the spatial pattern of DPBFZ zoning. In addition, the antibody-antigen affinity function, the clone mechanism, and mutation strategy were constructed and improved to solve the DPBFZ problem with a spatial optimization feature. Finally, Tongxu County in Henan province was selected as the study area, and a controlled experiment was set up according to different target preferences. The results show that the model proposed in this paper is operational in the work of delineating DPBFZ. It not only avoids the adverse effects of subjective factors in the delineation process but also provides multiple scenarios DPBFZ layouts for decision makers by adjusting the weighting of the objective function.

• 항공우주정책ㆍ법학회지
• /
• 제34권1호
• /
• pp.39-77
• /
• 2019

국제항공운송에 종사하는 승무원은 업무의 성격상 여러 나라에서 근로를 제공하게 된다. 국제사법에 의하면 일상적 노무제공지는 국제근로계약의 준거법 결정(제28조 제2항), 국제재판관할의 결정(제28조 제3항, 제4항)에서 중요한 역할을 수행한다. 일상적 노무제공지는 국제재판관할과 준거법의 결정을 위하여 EU에서 제창된 개념으로, 국제항공법에서 항공안전을 확보할 목적으로 승무원의 피로관리를 위해 도입된 개념인 모기지(母基地)와 입법목적이 서로 달라, 일상적 노무제공지와 모기지는 같은 개념이라고 볼 수 없다. 승무원의 일상적 노무제공지를 결정하기 위해서는 (i) 승무원이 근무를 시작하고 종료하는 곳, (ii) 승무원이 업무를 수행하는 항공기가 주로 주기(駐機)된 곳, (iii) 사용자가 전달한 지시사항을 알게 되고 근무활동을 조직하는 곳, (iv) 근로계약상 승무원이 거주할 의무가 있는 곳, (v) 사용자가 제공하고 승무원이 사용할 수 있는 사무실이 있는 곳, (vi) 승무원이 업무에 부적합하거나 징계사유가 발생할 때 참석할 의무가 있는 곳 등을 종합적으로 고려하여야 한다. 그런데 위에서 열거한 사항은 모두 모기지 소재지와 동일하므로, 승무원의 일상적 노무제공지를 결정할 때 모기지를 가장 중요한 요소로 고려하는 것이 타당하다. 이와 달리 기적국을 일상적 노무제공지로 보아서는 안 된다. 대상사안에서 CJEU는 국제항공운송에 종사하는 객실승무원의 일상적 노무제공지에 관하여 최초로 판단기준을 제시하였는바, 이는 우리나라 국제사법의 모범이 되었던 브뤼셀 규정의 해석이므로, 국제항공운송 승무원에 관하여 국제사법상 일상적 노무제공지의 개념을 이해하는데 많은 도움이 될 것으로 보인다.

• 대한토목학회논문집
• /
• 제33권6호
• /
• pp.2483-2491
• /
• 2013

교통사고를 감소시키고 안전성을 향상시키기 위해, 사고에 영향을 미치는 요인들을 분석하여 교통사고를 예측하는 모형은 지속적으로 개발되어 왔다. 교통사고 감소와 사고 사망자 감소에 대한 문제는 선진국과 후진국 모두 중요한 문제로서, 우리나라에서는 매해 교통사고 감소를 위한 정책 및 방안을 제시하고 있다. 주 5일제 시행과 여가활동에 대한 관심의 증가로 주중과 주말의 통행패턴은 다른 형태를 지니고 있으며, 교통사고의 특성도 마찬가지로 다르게 나타난다. 본 연구에서는 주중과 주말의 사고 심각도에 미치는 요인이 다름에 대하여 분석하였으며, 이는 고속도로에서 발생한 5년 동안의 사고자료를 구조방정식 모형을 이용하여 분석하였다. 모형의 추정결과 주중 사고 심각도 모형은 도로 요인이 사고 심각도에 가장 큰 영향을 미치는 것으로 나타났으며, 주말 사고 심각도 모형은 운전자 요인이 사고 심각도에 가장 큰 영향을 미치는 것으로 나타나 주중과 주말 사고의 원인 차이를 나타냈다.

• 한국항해항만학회지
• /
• 제42권3호
• /
• pp.187-194
• /
• 2018

항로표지는 해상교통의 안전을 도모하는 선박운항의 능률성을 향상시키기 위한 해양교통안전시설로서 국제적으로 IALA에서 관련 규정 및 권고사항에 따라 적용하고 있다. 우리나라는 항로표지 이용자에게 안정적인 서비스를 제공하기 위해 항로표지를 관리하고 있지만 항로 표지사고는 연평균 141건이 발생하고 있다. 항로표지사고는 관리자에게 기능을 복구시켜야 비계획 업무를 강요하고, 이용자에게는 심리적 불안감을 유발하여 경제적인 손실이 발생한다. 본 연구에서는 항로표지사고로 인해 기능정지에서 복구까지 소요되는 관리자의 경제활동과 이용자의 불편함을 비용으로 정량화하기 위한 항로표지사고의 사회적비용(Social Cost) 평가모델을 개발하였다. 항로표지사고의 사회적비용 평가모델은 생산손실비용, 행정비용, 위험비용의 합으로 제안하였다.

• Nuclear Engineering and Technology
• /
• 제48권4호
• /
• pp.941-951
• /
• 2016

The aim of this work is to simulate the thermohydraulic consequences of a main steam line break and to compare the obtained results with Rossendorf Coolant Mixing Model (ROCOM) 1.1 experimental results. The objective is to utilize data from steady-state mixing experiments and computational fluid dynamics (CFD) calculations to determine the flow distribution and the effect of thermal mixing phenomena in the primary loops for the improvement of normal operation conditions and structural integrity assessment of pressurized water reactors. The numerical model of ROCOM was developed using the FLUENT code. The positions of the inlet and outlet boundary conditions and the distribution of detailed velocity/turbulence parameters were determined by preliminary calculations. The temperature fields of transient calculation were averaged in time and compared with time-averaged experimental data. The perforated barrel under the core inlet homogenizes the flow, and therefore, a uniform temperature distribution is formed in the pressure vessel bottom. The calculated and measured values of lowest temperature were equal. The inlet temperature is an essential parameter for safety assessment. The calculation predicts precisely the experimental results at the core inlet central region. CFD results showed a good agreement (both qualitatively and quantitatively) with experimental results.

• Advances in Computational Design
• /
• 제4권2호
• /
• pp.119-139
• /
• 2019

Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. Better on-site management allows for substantial productivity improvements and cost savings. The procurement system should be able to manage a wider variety of materials and products of the required quality in order to have less stock, in less time, using less space, with less investment and avoiding multiple storage stations. The objective of this paper is to demonstrate the advantages of using the Chronographic modeling, by combining spatiotemporal technical scheduling with the 4D simulations, the Last Planner System and the Takt-time when modeling the construction of building projects. This paper work toward the aforementioned goal by examining the impact that material flow has on site occupancy. The proposed spatiotemporal model promotes efficient site use, defines optimal site-occupancy and workforce-rotation rates, minimizes intermediate stocks, and ensures a suitable procurement process. This paper study the material flow on the site and consider horizontal and vertical paths, traffic flows and appropriate means of transportation to ensure fluidity and safety. This paper contributes to the existing body of knowledge by linking execution and supply to the spatial and temporal aspects. The methodology compare the performance and procurement processes for the proposed Chronographic model with the Gantt-Precedence diagram. Two examples are presented to demonstrate the benefits of the proposed model and to validate the related concepts. This validation is designed to test the model's graphical ability to simulate construction and procurement.

• Geomechanics and Engineering
• /
• 제29권3호
• /
• pp.321-329
• /
• 2022

Tunnel site where high water pressure is applied, such as subsea tunnel, generally selects the shield TBM (Tunnel Boring Machine) to maintain the tunnel excavation face. The shield TBM has cutters installed, and the cutters wear out during the process of excavation, so it should be checked and replaced regularly. This is called CHI (Cutterhead Intervention). The conventional CHI under high water pressure is very disadvantageous in terms of safety and economics because humans perform work in response to high water pressure and huge water inflow in the chamber. To overcome this disadvantage, this study proposes a new method to dramatically reduce water pressure and water ingress by injecting an appropriate grout solution into the front of the tunnel face through the shield TBM chamber, called New Face Grouting Method (NFGM). The tunnel model tests were performed to determine the characteristics, injection volume, and curing time of grout solution to be applied to the NFGM. Model test apparatus was composed of a pressure soil tank, a model shield TBM, a grout tank, and an air compressor to measure the amount of water inflow into the chamber. The model tests were conducted by changing the injection amount of the grout solution, the curing time after the grout injection, and the water/cement ratio of grout solution. From an economic point of view, the results showed that the injection volume of 1.0 L, curing time of 6 hours, and water/cement ratio of the grout solution between 1.5 and 2.0 are the most economical. It can be concluded that this study has presented a method to economically perform the CHI under the high water pressure.

• Geomechanics and Engineering
• /
• 제31권6호
• /
• pp.545-556
• /
• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• Nuclear Engineering and Technology
• /
• 제55권9호
• /
• pp.3423-3440
• /
• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• Nuclear Engineering and Technology
• /
• 제55권5호
• /
• pp.1802-1813
• /
• 2023

Conjugate heat transfer between liquid metal and solid is a common phenomenon in a liquid-metal-cooled fast reactor's fuel assembly and heat exchanger, dramatically affecting the reactor's safety and economy. Therefore, comprehensively studying the sophisticated conjugate heat transfer in a liquid-metal-cooled fast reactor is profound. However, it has been evidenced that the traditional Simple Gradient Diffusion Hypothesis (SGDH), assuming a constant turbulent Prandtl number (Pr_t,, usually 0.85 - 1.0), is inappropriate in the Computational Fluid Dynamics (CFD) simulations of liquid metal. In recent decades, numerous studies have been performed on the four-equation model, which is expected to improve the precision of liquid metal's CFD simulations but has not been introduced into the conjugate heat transfer calculation between liquid metal and solid. Consequently, a four-equation model, consisting of the Abe k - ε turbulence model and the Manservisi k_𝜃 - ε_𝜃 heat transfer model, is applied to study the conjugate heat transfer concerning liquid metal in the present work. To verify the numerical validity of the four-equation model used in the conjugate heat transfer simulations, we reproduce Johnson's experiments of the liquid lead-bismuth-cooled turbulent pipe flow using the four-equation model and the traditional SGDH model. The simulation results obtained with different models are compared with the available experimental data, revealing that the relative errors of the local Nusselt number and mean heat transfer coefficient obtained with the four-equation model are considerably reduced compared with the SGDH model. Then, the thermal-hydraulic characteristics of liquid metal turbulent pipe flow obtained with the four-equation model are analyzed. Moreover, the impact of the turbulence model used in the four-equation model on overall simulation performance is investigated. At last, the effectiveness of the four-equation model in the CFD simulations of liquid sodium conjugate heat transfer is assessed. This paper mainly proves that it is feasible to use the four-equation model in the study of liquid metal conjugate heat transfer and provides a reference for the research of conjugate heat transfer in a liquid-metal-cooled fast reactor.