Investigation on propagation mechanism of large scale mine gas explosions

2017 ◽  
Vol 49 ◽  
pp. 342-347 ◽  
Author(s):  
Cheng Wang ◽  
Yongyao Zhao ◽  
Emmanuel Kwasi Addai
Keyword(s):  
Large Scale ◽  
Propagation Mechanism ◽  
Gas Explosions ◽  
Mine Gas

Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network

2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Large Scale ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Propagation Mechanism ◽  
Urban Road ◽  
The Road ◽  
Traffic Flow Forecasting ◽  
Gating Mechanism

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.

scholarly journals The Large Scale Machine Learning in an Artificial Society: Prediction of the Ebola Outbreak in Beijing

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Zhang ◽  
Bin Chen ◽  
Liang Ma ◽  
Zhen Li ◽  
Zhichao Song ◽  
...  
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Ebola Virus ◽  
Virus Disease ◽  
Propagation Model ◽  
Propagation Mechanism ◽  
Chinese Government ◽  
Emergency Plans ◽  
Artificial Society ◽  
The City

Ebola virus disease (EVD) distinguishes its feature as high infectivity and mortality. Thus, it is urgent for governments to draw up emergency plans against Ebola. However, it is hard to predict the possible epidemic situations in practice. Luckily, in recent years, computational experiments based on artificial society appeared, providing a new approach to study the propagation of EVD and analyze the corresponding interventions. Therefore, the rationality of artificial society is the key to the accuracy and reliability of experiment results. Individuals’ behaviors along with travel mode directly affect the propagation among individuals. Firstly, artificial Beijing is reconstructed based on geodemographics and machine learning is involved to optimize individuals’ behaviors. Meanwhile, Ebola course model and propagation model are built, according to the parameters in West Africa. Subsequently, propagation mechanism of EVD is analyzed, epidemic scenario is predicted, and corresponding interventions are presented. Finally, by simulating the emergency responses of Chinese government, the conclusion is finally drawn that Ebola is impossible to outbreak in large scale in the city of Beijing.

Gas explosions of methane-air mixtures in a large-scale tube

Fuel ◽  
2021 ◽  
Vol 285 ◽  
pp. 119239 ◽  
Author(s):  
Zhan Li ◽  
Li Chen ◽  
Haichun Yan ◽  
Qin Fang ◽  
Yadong Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Gas Explosions

scholarly journals Suppressive Effects of Silicon Dioxide and Diatomite Powder Aerosols on Coal Mine Gas Explosions in Highlands

2016 ◽  
Vol 16 (9) ◽  
pp. 2119-2128 ◽  
Author(s):  
Zhen-Min Luo ◽  
Fang-Ming Cheng ◽  
Tao Wang ◽  
Jun Deng ◽  
Chi-Min Shu
Keyword(s):  
Silicon Dioxide ◽  
Coal Mine ◽  
Coal Mine Gas ◽  
Gas Explosions ◽  
Mine Gas ◽  
Powder Aerosols

scholarly journals Disentangling shock diffusion on complex networks: identification through graph planarity

2020 ◽  
Vol 8 (3) ◽  
Author(s):  
Sudarshan Kumar ◽  
Tiziana Di Matteo ◽  
Anindya S Chakrabarti
Keyword(s):  
Large Scale ◽  
Developed Countries ◽  
Shock Propagation ◽  
Propagation Mechanism ◽  
Dynamical Process ◽  
Economic Networks ◽  
Closed Loops ◽  
The Usa ◽  
Large Scale Networks ◽  
The Impact

Abstract Large scale networks delineating collective dynamics often exhibit cascading failures across nodes leading to a system-wide collapse. Prominent examples of such phenomena would include collapse on financial and economic networks. Intertwined nature of the dynamics of nodes in such network makes it difficult to disentangle the source and destination of a shock that percolates through the network, a property known as reflexivity. In this article, we propose a novel methodology by combining vector autoregression with an unique identification restrictions obtained from the topological structure of the network to uniquely characterize cascades. In particular, we show that planarity of the network allows us to statistically estimate a dynamical process consistent with the observed network and thereby uniquely identify a path for shock propagation from any chosen epicentre to all other nodes in the network. We analyse the distress propagation mechanism in closed loops giving rise to a detailed picture of the effect of feedback loops in transmitting shocks. We show usefulness and applications of the algorithm in two networks with dynamics at different time-scales: worldwide GDP growth network and stock network. In both cases, we observe that the model predicts the impact of the shocks emanating from the USA would be concentrated within the cluster of developed countries and the developing countries show very muted response, which is consistent with empirical observations over the past decade.

Numerical study of external explosion characteristics induced by indoor natural gas vented explosion

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lei Pang ◽  
Qianran Hu ◽  
Kai Yang
Keyword(s):  
Natural Gas ◽  
Design Methodology ◽  
Large Scale ◽  
Numerical Study ◽  
Outdoor Environment ◽  
Gas Explosion ◽  
Content Type ◽  
Gas Explosions ◽  
Explosion Overpressure ◽  
Vented Explosion

Purpose The purpose of this paper is to ascertain the harm to personnel and equipment caused by an external explosion during natural gas explosion venting. The external explosion characteristics induced by the indoor natural gas explosion are the focal points of the investigation. Design/methodology/approach Computational fluid dynamics technology was used to investigate the large-scale explosion venting process of natural gas in a 6 × 3 × 2.5 m room, and the characteristics of external explosion under different scaled vent size (Kv = Av/V2/3, 0.05, 0.08, 0.13, 0.18) were numerically analyzed. Findings When Kv = 0.08, the length and duration of the explosion fireball are 13.39 and 450 ms, respectively, which significantly expands the degree and range of high-temperature hazards. The suitable flow-field structure causes the external explosion overpressure to be more than twice that indoors, i.e. the natural gas explosion venting overpressure may be considerably more hazardous in an outdoor environment than inside a room. A specific range for the Kv can promote the superposition of outdoor rupture waves and explosion shock waves, thereby creating a new overpressure hazard. Originality/value Little attention has been devoted to investigating systematically the external explosion hazards. Based on the numerical simulation and the analysis, the external explosion characteristics induced by the indoor large-scale gas explosion were obtained. The research results are theoretically significant for mitigating the effects of external gas explosions on personnel and equipment.

A label propagation approach based on local optimization

2018 ◽  
Vol 29 (06) ◽  
pp. 1850047
Author(s):  
Xiaohong Zhang ◽  
Yulin Jiang ◽  
Jianji Ren ◽  
Chaosheng Tang
Keyword(s):  
Social Network ◽  
Community Detection ◽  
Large Scale ◽  
Local Optimization ◽  
Label Propagation ◽  
Propagation Mechanism ◽  
Propagation Algorithm ◽  
Large Scale Networks ◽  
Special Factors

Community detection offers an important way to understand the structures and functions of social network. The label propagation algorithm has attracted vast attention since it is very suitable for discovering communities from large-scale networks. However, the algorithm suffers from the instability and inefficiency problem caused by the random policies it adopted. In this paper, we propose a novel label propagation approach based on local optimization to deal with the problem. The approach introduces a pre-propagation mechanism to optimize randomly initialized labels according to special factors, for example, node compactness. After that, it traverses and relabels nodes in the descending order of aggregate influence. The experiment results demonstrate the usefulness and effectiveness of our approach.

Analysis of results from large scale hydrocarbon gas explosions

2000 ◽  
Vol 13 (2) ◽  
pp. 167-173 ◽  
Author(s):  
Murray J Shearer ◽  
Vincent H.Y Tam ◽  
Brian Corr
Keyword(s):  
Large Scale ◽  
Gas Explosions ◽  
Analysis Of Results ◽  
Hydrocarbon Gas
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