scholarly journals An Efficient Model for Train-Track-Bridge-Coupled System under Seismic Excitation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Lizhong Jiang ◽  
Tuo Zhou ◽  
Xiang Liu ◽  
Ping Xiang ◽  
Yuntai Zhang
Keyword(s):  
Coupled System ◽  
Seismic Excitation ◽  
Loop Model ◽  
Train Track ◽  
Wheel Load ◽  
Long Distance ◽  
Earthquake Excitation ◽  
Operation Speed ◽  
Proposed Model ◽  
Track Bridge

When an earthquake occurs, due to the high operation speed of the train group, there is still a long distance from braking to stopping, so it needs a large number of bridge spans to calculate the integrated dynamic response, which leads to a large amount of calculation of the train-track-bridge (TTB) system under a seismic event. In order to reduce the amount of calculation, this paper proposed an efficient model called closed-loop model for simply supported railway bridge. The proposed model is realized by coupling the head and end of the rail-slab-bridge system through the utilization of pseudo-element. Simulation comparison of TTB response with and without seismic excitation between conventional TTB model and efficient model indicates that, under the premise of ensuring calculation accuracy, the efficient model shows the advantage of fewer degrees of freedom (DOF) of model and higher computational efficiency. For instance, under El Centro earthquake excitation, the time cost of proposed model is only 6% of conventional model. Meanwhile, six seismic events with different acceleration amplitudes are imposed on the efficient model, and the results of car-body acceleration, wheel-rail force, and wheel load reduction ratio are gathered and discussed; it can be concluded that, except Trinidad earthquake, for other earthquake samples investigated in this paper, with acceleration amplitude larger than 0.8 g, the train operation is at the risk of derailment.

Influences of Wind Barriers on the Train Running Safety on a Highway-Railway One-Story Bridge

2021 ◽  
pp. 2140009
Author(s):  
Ye Liu ◽  
Yan Han ◽  
Peng Hu ◽  
C. S. Cai ◽  
Xuhui He
Keyword(s):  
Dynamic Responses ◽  
Response Analysis ◽  
Train Track ◽  
Wheel Load ◽  
Wind Barrier ◽  
The Mean ◽  
Wind Pressures ◽  
Track Bridge ◽  
Fluctuating Wind ◽  
Bridge System

In this study, the influences of wind barriers on the aerodynamic characteristics of trains (e.g. a CRH2 train) on a highway-railway one-story bridge were investigated by using wind pressure measurement tests, and a reduction factor of overturning moment coefficients was analyzed for trains under wind barriers. Subsequently, based on a joint simulation employing SIMPACK and ANSYS, a wind–train–track–bridge system coupled vibration model was established, and the safety and comfort indexes of trains on the bridge were studied under different wind barrier parameters. The results show that the mean wind pressures and fluctuating wind pressures on the trains’ surface decrease generally if wind barriers are used. As a result, the dynamic responses of the trains also decrease in the whole process of crossing the bridge. Of particular note, the rate of the wheel load reductions and lateral wheel-axle forces can change from unsafe states to relative safe states due to the wind barriers. The influence of the porosity of the wind barriers on the mean wind pressures and fluctuating wind pressures on the windward sides and near the top corner surfaces of the trains are significantly greater than the influence from the height of the wind barriers. Within a certain range, decreasing the wind barrier porosities and increasing the wind barrier heights will significantly reduce the safety and comfort index values of trains on the bridge. It is found that when the porosity of the wind barrier is 40%, the optimal height of the wind barrier is determined as approximately 3.5[Formula: see text]m. At this height, the trains on the bridges are safer and run more smoothly and comfortably. Besides, through the dynamic response analysis of the wind–train–track–bridge system, it is found that the installation of wind barriers in cases with high wind speeds (30[Formula: see text]m/s) may have an adverse effect on the vertical vibration of the train–track–bridge system.

scholarly journals Hamiltonian Monte Carlo with application to train-track-bridge coupled interactions subjected to seismic excitation with uncertainties

2021 ◽  
Author(s):  
Wandji Zoumb Patrick Arnaud
Keyword(s):  
Monte Carlo ◽  
Numerical Models ◽  
Coupled System ◽  
Random Excitation ◽  
Stochastic Gradient Descent ◽  
Fe Model ◽  
Train Track ◽  
Hamiltonian Monte Carlo ◽  
Probability Density Evolution Method ◽  
Track Bridge

Abstract Numerical models of train running over the bridge are prone to errors and random excitation sources, which inevitably influence the capacity of such models to accurately predict the observed behaviour. Finite element (FE) updating method can be employed to fit the numerical models through the observed model. This paper proposes a new method to predict the random vibration of train-track-bridge system under earthquakes based on Hamiltonian Monte Carlo (HMC) method. The system identification is performed based on data recorded in situ. FE model is calibrated by minimizing the difference between the FE results and the natural frequencies of a real train-bridge coupled system. Naïve stochastic gradient descent is introduced to optimize the fitting process, avoiding over fitting and under fitting performance. The correlation matrix is built to calculate the correlation score between the measured and the HMC models. Based on above framework, results show that the HMC method has great effectiveness and accuracy with comparisons to the Monte Carlo method (MCM) and the popular probability density evolution method (PDEM). Moreover, the roles of bridge random parameters, track irregularities, and the seismic actions on the random responses are comprehensively investigated. Finally, the updating coefficients reduce the errors to less than 10%.

An efficient hybrid method for dynamic interaction of train–track–bridge coupled system

2020 ◽  
Vol 47 (9) ◽  
pp. 1084-1093 ◽  
Author(s):  
Zhihui Zhu ◽  
Lei Zhang ◽  
Wei Gong ◽  
Lidong Wang ◽  
Yu Bai ◽  
...  
Keyword(s):  
Hybrid Method ◽  
Equations Of Motion ◽  
Coupled System ◽  
Superposition Method ◽  
Train Track ◽  
Mode Superposition Method ◽  
Body Dynamics ◽  
Direct Stiffness ◽  
Track Bridge ◽  
Multi Body

An efficient hybrid method (HM) is proposed by combining the direct stiffness method (DSM) and the mode superposition method (MSM) for analyzing the train–track–bridge coupled system (TTBS). The train and the track are modeled by applying the multi-body dynamics and the DSM, respectively. The bridge is modeled by applying the MSM that is efficient in capturing the dynamic behavior with a small number of modes. The train–track subsystem and the bridge subsystem are coupled by the interaction forces between them. The computational efficiency is significantly improved because of the considerably reduced number of equations of motion of the TTBS. Numerical simulations of a train traversing an arch railway bridge are performed and the results are compared with the field test data and the data from other methods, demonstrating the efficiency and accuracy of the proposed method.

Hierarchical Concept-Driven Language Model

2021 ◽  
Vol 15 (6) ◽  
pp. 1-22
Author(s):  
Yashen Wang ◽  
Huanhuan Zhang ◽  
Zhirun Liu ◽  
Qiang Zhou
Keyword(s):  
Language Model ◽  
Generation Process ◽  
Data Generation ◽  
Modeling Framework ◽  
Long Distance ◽  
Short Text ◽  
Proposed Model ◽  
Scalable Inference ◽  
End To End ◽  
Hidden Layer

For guiding natural language generation, many semantic-driven methods have been proposed. While clearly improving the performance of the end-to-end training task, these existing semantic-driven methods still have clear limitations: for example, (i) they only utilize shallow semantic signals (e.g., from topic models) with only a single stochastic hidden layer in their data generation process, which suffer easily from noise (especially adapted for short-text etc.) and lack of interpretation; (ii) they ignore the sentence order and document context, as they treat each document as a bag of sentences, and fail to capture the long-distance dependencies and global semantic meaning of a document. To overcome these problems, we propose a novel semantic-driven language modeling framework, which is a method to learn a Hierarchical Language Model and a Recurrent Conceptualization-enhanced Gamma Belief Network, simultaneously. For scalable inference, we develop the auto-encoding Variational Recurrent Inference, allowing efficient end-to-end training and simultaneously capturing global semantics from a text corpus. Especially, this article introduces concept information derived from high-quality lexical knowledge graph Probase, which leverages strong interpretability and anti-nose capability for the proposed model. Moreover, the proposed model captures not only intra-sentence word dependencies, but also temporal transitions between sentences and inter-sentence concept dependence. Experiments conducted on several NLP tasks validate the superiority of the proposed approach, which could effectively infer meaningful hierarchical concept structure of document and hierarchical multi-scale structures of sequences, even compared with latest state-of-the-art Transformer-based models.

scholarly journals Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area

2021 ◽  
Vol 13 (3) ◽  
pp. 1190
Author(s):  
Gang Ren ◽  
Xiaohan Wang ◽  
Jiaxin Cai ◽  
Shujuan Guo
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Simultaneous Optimization ◽  
Mixed Integer ◽  
Gantry Crane ◽  
Optimization Scheme ◽  
Long Distance ◽  
Proposed Model ◽  
Hybrid Heuristic Algorithm ◽  
Searching Ability

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.

scholarly journals Stop Plan of Express and Local Train for Regional Rail Transit Line

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Programming Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Long Distance ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.

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