Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and proces...Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.展开更多
This paper examines the feasibility and the efficiency of a multiple-relaxation-time lattice Boltzmann model （MRT-LBM） for simulating open channel flows in engineering practice. A MRT-LBM scheme for 2-D shallow wate...This paper examines the feasibility and the efficiency of a multiple-relaxation-time lattice Boltzmann model （MRT-LBM） for simulating open channel flows in engineering practice. A MRT-LBM scheme for 2-D shallow water flows taking into account of the bed slope and the friction is proposed. The scheme＇s reliability is verified by benchmark problems and the simulation capability is improved by implementing the scheme on a graphic processing unit （GPU）. We use the method to analyze the flow characteristics in the connecting open channel of two cascaded hydropower stations. The flow fields and parameters such as the water depth, the flow rate, and the side-weir discharge, under different operating conditions, are analyzed. The factors affecting the accuracy and the effi- ciency are discussed. The results are found to be reasonable and may be used as a guidance in the project design. It is shown that the GPU-implemented MRT-LBM on a fine mesh can efficiently simulate two-dimensional shallow water flows in engineering practice.展开更多
Evacuation systems in buildings are frequently assessed to improve emergency response processes.This paper proposes a method to evaluate the performance of different evacuation modes,and determine a rational mode for ...Evacuation systems in buildings are frequently assessed to improve emergency response processes.This paper proposes a method to evaluate the performance of different evacuation modes,and determine a rational mode for large railway stations.We developed a simulation for the evaluation of fire safety in large buildings based on an analytic hierarchy process(AHP)method.This approach includes AHP-based exploration and simulation-based refinement.We considered a typical railway station for validation,conducted a field survey to collect the data,and calculated the influencing factors based on expert opinion.The influencing factors were further processed based on the principles of a hierarchical model.The relative weights of the influencing factors were calculated through a series of pairwise comparisons using the AHP.Further,we applied factor refinement based on the evacuation simulations to determine the degree and status of influence of each factor.The influence of external factors was generally stronger than that of the internal factors.Among them,the building component characteristics and people's physiological capabilities were the core of the evacuation assessment in large railway stations.Additionally,the exit width,seat layout,visibility,speed,and reaction capabilities were crucial to the evacuation process.The proposed method is practical as it demands limited computations to provide useful information,such as a priority ranking of each influencing factor,for the evaluation process.展开更多
文摘Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.
基金Project support by the National Natural Science Foun-dation of China(Grant Nos.11172219,51579187)the Specia-lized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20130141110013)
文摘This paper examines the feasibility and the efficiency of a multiple-relaxation-time lattice Boltzmann model （MRT-LBM） for simulating open channel flows in engineering practice. A MRT-LBM scheme for 2-D shallow water flows taking into account of the bed slope and the friction is proposed. The scheme＇s reliability is verified by benchmark problems and the simulation capability is improved by implementing the scheme on a graphic processing unit （GPU）. We use the method to analyze the flow characteristics in the connecting open channel of two cascaded hydropower stations. The flow fields and parameters such as the water depth, the flow rate, and the side-weir discharge, under different operating conditions, are analyzed. The factors affecting the accuracy and the effi- ciency are discussed. The results are found to be reasonable and may be used as a guidance in the project design. It is shown that the GPU-implemented MRT-LBM on a fine mesh can efficiently simulate two-dimensional shallow water flows in engineering practice.
基金supported by the National Natural Science Foundation of China(NSFC)(51808160 and 51878210)the Fundamental Research Funds for the Central Universities(HIT.NSRIF.2020035).
文摘Evacuation systems in buildings are frequently assessed to improve emergency response processes.This paper proposes a method to evaluate the performance of different evacuation modes,and determine a rational mode for large railway stations.We developed a simulation for the evaluation of fire safety in large buildings based on an analytic hierarchy process(AHP)method.This approach includes AHP-based exploration and simulation-based refinement.We considered a typical railway station for validation,conducted a field survey to collect the data,and calculated the influencing factors based on expert opinion.The influencing factors were further processed based on the principles of a hierarchical model.The relative weights of the influencing factors were calculated through a series of pairwise comparisons using the AHP.Further,we applied factor refinement based on the evacuation simulations to determine the degree and status of influence of each factor.The influence of external factors was generally stronger than that of the internal factors.Among them,the building component characteristics and people's physiological capabilities were the core of the evacuation assessment in large railway stations.Additionally,the exit width,seat layout,visibility,speed,and reaction capabilities were crucial to the evacuation process.The proposed method is practical as it demands limited computations to provide useful information,such as a priority ranking of each influencing factor,for the evaluation process.
