Fire-driven flow analysis in the underground subway station has been performed with various main tunnel ventilations. Shin-gum-ho station （depth： 46 m） in Seoul is selected as a simulation model. The ventilation mo...Fire-driven flow analysis in the underground subway station has been performed with various main tunnel ventilations. Shin-gum-ho station （depth： 46 m） in Seoul is selected as a simulation model. The ventilation mode is assumed to be emergency state. Various main tunnel ventilations are applied to operate in a proper way for helping of smoke exhaustion in platform. The entire station is covered for simulation. Ventilation diffusers are modeled as 95 square shapes of 0.6 m × 0.6 m in the lobby and as 222 square shapes of 0.6 m × 0.6 m and four rectangular shapes of 1.2 m × 0.8 m in the platform. The total of 7.5 million grids is generated and whole domain is divided to 22 blocks for MPI （massage passing interface） efficiency of calculation. LES （large eddy simulation） is applied to solve the momentum equation. Smagorinsky model （Cs = 0.2） is used as SGS （subgrid scale） model. The distribution of CO （carbon monoxide） is calculated for various capacity of main tunnel ventilation and compared with each other.展开更多
In order to meet key requirements imposed by transitioning to a 5G network, new network management techniques must be employed in order to increase network reliability and efficiency. Most notably, it is important tha...In order to meet key requirements imposed by transitioning to a 5G network, new network management techniques must be employed in order to increase network reliability and efficiency. Most notably, it is important that a Self-Organizing Network (SON) is able to recover autonomously from network failure or congestion through Self-Healing procedures (<i>i.e.</i> autonomous detection, diagnosis, and correction). This paper aims to develop a self-healing algorithm that can effectively “heal” a 5G network by testing a proposed self-healing algorithm within a network simulator that adheres to current 5G standards. The simulator developed in this paper aims to model a network of small cells that can inherit one of multiple states (healthy, congested, and failing) to validate the effectiveness of a programmed self-healing algorithm in recovering a simulated network. Results show that the application of a self-healing in a network is able to resolve issues related to Quality of Service (QoS) and reduced network data rates in portions of a network that are in a partially congested or failing state.展开更多
Effect of different fire strengths on the smoke distribution in the subway station is investigated. Shin-Gum-Ho station （line #5） in Seoui is selected as a case study for variation of CO （carbon monoxide） distribu...Effect of different fire strengths on the smoke distribution in the subway station is investigated. Shin-Gum-Ho station （line #5） in Seoui is selected as a case study for variation of CO （carbon monoxide） distribution caused by the fire in the platform. The ventilation in the station is set to be an air supply mod in the lobby and an air exhaustion mod in the platform. One-side main tunnel ventilation （7,000 m3/min） is applied to operate in the tunnel. The fire is assumed to break out in the middle of train parked in the platform tunnel. Two kinds of fire strength are used. One is 10 MW and the other is 20 MW. Ventilation diffusers in the station are modeled as 317 square shapes ＆ four rectangular shapes in the lobby and platform. The total of 7.5 million grids is generated and whole domain is divided to 22 blocks for parallel computation. Large eddy simulation method is applied to solve the momentum equation. The behavior of CO is calculated according to different fire strengths and compared with each other.展开更多
Owing to potential regulation capacities from flexible resources in energy coupling,storage,and consumption links,central energy stations(CESs)can provide additional support to power distribution network(PDN)in case o...Owing to potential regulation capacities from flexible resources in energy coupling,storage,and consumption links,central energy stations(CESs)can provide additional support to power distribution network(PDN)in case of power disruption.However,existing research has not explicitly revealed the emergency response of PDN with leveraging multiple CESs.This paper proposes a decentralized self-healing strategy of PDN to minimize the entire load loss,in which multi-area CESs’potentials including thermal storage and building thermal inertia,as well as the flexible topology of PDN,are reasonably exploited for service recovery.For sake of privacy preservation,the co-optimization of PDN and CESs is realized in a decentralized manner using adaptive alternating direction method of multipliers(ADMM).Furtherly,bilateral risk management with conditional value-at-risk(CVaR)for PDN and risk constraints for CESs is integrated to deal with uncertainties from outage duration.Case studies are conducted on a modified IEEE 33-bus PDN with multiple CESs.Numerical results illustrate that the proposed strategy can fully utilize the potentials of multi-area CESs for coordinated load restoration.The effectiveness of the performance and behaviors’adaptation against random risks is also validated.展开更多
文摘Fire-driven flow analysis in the underground subway station has been performed with various main tunnel ventilations. Shin-gum-ho station （depth： 46 m） in Seoul is selected as a simulation model. The ventilation mode is assumed to be emergency state. Various main tunnel ventilations are applied to operate in a proper way for helping of smoke exhaustion in platform. The entire station is covered for simulation. Ventilation diffusers are modeled as 95 square shapes of 0.6 m × 0.6 m in the lobby and as 222 square shapes of 0.6 m × 0.6 m and four rectangular shapes of 1.2 m × 0.8 m in the platform. The total of 7.5 million grids is generated and whole domain is divided to 22 blocks for MPI （massage passing interface） efficiency of calculation. LES （large eddy simulation） is applied to solve the momentum equation. Smagorinsky model （Cs = 0.2） is used as SGS （subgrid scale） model. The distribution of CO （carbon monoxide） is calculated for various capacity of main tunnel ventilation and compared with each other.
文摘In order to meet key requirements imposed by transitioning to a 5G network, new network management techniques must be employed in order to increase network reliability and efficiency. Most notably, it is important that a Self-Organizing Network (SON) is able to recover autonomously from network failure or congestion through Self-Healing procedures (<i>i.e.</i> autonomous detection, diagnosis, and correction). This paper aims to develop a self-healing algorithm that can effectively “heal” a 5G network by testing a proposed self-healing algorithm within a network simulator that adheres to current 5G standards. The simulator developed in this paper aims to model a network of small cells that can inherit one of multiple states (healthy, congested, and failing) to validate the effectiveness of a programmed self-healing algorithm in recovering a simulated network. Results show that the application of a self-healing in a network is able to resolve issues related to Quality of Service (QoS) and reduced network data rates in portions of a network that are in a partially congested or failing state.
文摘Effect of different fire strengths on the smoke distribution in the subway station is investigated. Shin-Gum-Ho station （line #5） in Seoui is selected as a case study for variation of CO （carbon monoxide） distribution caused by the fire in the platform. The ventilation in the station is set to be an air supply mod in the lobby and an air exhaustion mod in the platform. One-side main tunnel ventilation （7,000 m3/min） is applied to operate in the tunnel. The fire is assumed to break out in the middle of train parked in the platform tunnel. Two kinds of fire strength are used. One is 10 MW and the other is 20 MW. Ventilation diffusers in the station are modeled as 317 square shapes ＆ four rectangular shapes in the lobby and platform. The total of 7.5 million grids is generated and whole domain is divided to 22 blocks for parallel computation. Large eddy simulation method is applied to solve the momentum equation. The behavior of CO is calculated according to different fire strengths and compared with each other.
基金financially supported by the Fundamental Research Funds for the Central Universities(No.2021QN1066)。
文摘Owing to potential regulation capacities from flexible resources in energy coupling,storage,and consumption links,central energy stations(CESs)can provide additional support to power distribution network(PDN)in case of power disruption.However,existing research has not explicitly revealed the emergency response of PDN with leveraging multiple CESs.This paper proposes a decentralized self-healing strategy of PDN to minimize the entire load loss,in which multi-area CESs’potentials including thermal storage and building thermal inertia,as well as the flexible topology of PDN,are reasonably exploited for service recovery.For sake of privacy preservation,the co-optimization of PDN and CESs is realized in a decentralized manner using adaptive alternating direction method of multipliers(ADMM).Furtherly,bilateral risk management with conditional value-at-risk(CVaR)for PDN and risk constraints for CESs is integrated to deal with uncertainties from outage duration.Case studies are conducted on a modified IEEE 33-bus PDN with multiple CESs.Numerical results illustrate that the proposed strategy can fully utilize the potentials of multi-area CESs for coordinated load restoration.The effectiveness of the performance and behaviors’adaptation against random risks is also validated.
