Mingnian Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Mingnian Wang has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Anmin Wang
Yunnan Institute of Transportation Planning and Design, Kunming 650011, China
1 shared publication - Changling Han
CCCC First Highway Consultants Co., Ltd., Xi’an 710068, China
1 shared publication - Jingyu Chen
Guangdong Hualu Transport Technology Co., Ltd., Guangzhou 510420, China
1 shared publication - Tao Yan
Key Laboratory of Transportation Tunnel Engineering, Ministry of Education, Southwest Jiaotong University, Chengdu 610031, China
1 shared publication - Yangqin Ni
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
1 shared publication - Yuxuan Guo
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
1 shared publication
Latest Publications
- Open Access
Prediction Method of Tunnel Natural Wind Based on Open-Source Meteorological Parameters
The rational use of natural wind in extra-long tunnels for feedforward operation ventilation control can dramatically reduce tunnel operation costs. However, traditional tunnel natural wind calculation theory lacks a prediction function. This paper proposes a three-stage tunnel natural wind prediction method relying on the Yanglin Tunnel in Yunnan, China based on the massive meteorological parameters provided by the open-source national meteorological stations around the tunnel, which make up for the partial deficiency of the meteorological parameters of the tunnel portal. The multi-layer perceptron model (MLP) was used to predict the real-time meteorological parameters of the tunnel portal using the data from four national meteorological stations. The nonlinear autoregressive network model (NARX) was used to predict the meteorological parameters of the tunnel portal in the next period based on the predicted and measured real-time data. The natural wind speed in the tunnel was obtained by a theoretical calculation method using the predicted meteorological parameters. The final tunnel natural wind prediction results are in good agreement with the field measured data, which indicates that the research results of this paper can play a guiding role in the feedforward regulation of tunnel operation fans.
Open AccessPrediction Method of Tunnel Natural Wind Based on Open-Source Meteorological Parameters
The rational use of natural wind in extra-long tunnels for feedforward operation ventilation control can dramatically reduce tunnel operation costs. However, traditional tunnel natural wind calculation theory lacks a prediction function. This paper proposes a three-stage tunnel natural wind prediction method relying on the Yanglin Tunnel in Yunnan, China based on the massive meteorological parameters provided by the open-source national meteorological stations around the tunnel, which make up for the partial deficiency of the meteorological parameters of the tunnel portal. The multi-layer perceptron model (MLP) was used to predict the real-time meteorological parameters of the tunnel portal using the data from four national meteorological stations. The nonlinear autoregressive network model (NARX) was used to predict the meteorological parameters of the tunnel portal in the next period based on the predicted and measured real-time data. The natural wind speed in the tunnel was obtained by a theoretical calculation method using the predicted meteorological parameters. The final tunnel natural wind prediction results are in good agreement with the field measured data, which indicates that the research results of this paper can play a guiding role in the feedforward regulation of tunnel operation fans.