scholarly journals Risk Control Technology for Water Inrush during the Construction of Deep, Long Tunnels

2019 ◽  
Vol 2019 ◽  
pp. 1-21
Author(s):  
Yiming Liu ◽  
Yuanpu Xia ◽  
Hao Lu ◽  
Ziming Xiong
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Effective Means ◽  
Water Inrush ◽  
Risk Control ◽  
Risk Information ◽  
Economic Losses ◽  
Analysis Model ◽  
Control Scheme ◽  
Changes In Risk

Water inrush is one of the main disasters occurring during tunnel construction in complex geological areas: once it happens, it can cause economic losses, casualties, and delay. Based on risk analysis and management, a risk control scheme is proposed as an effective means to control the risk of such a disaster; however, there are some deficiencies in existing research because the impacts of human factors on the risk of water inrush, dynamic changes in risk information during construction, and the diversity of types of water inrush are neglected. To enrich the research results of water inrush risk control and improve the effect of water inrush risk control, we first use the advantages of Bayesian network to analyse risk events, construct a Bayesian network structure chart of water inrush risk during construction, and propose a fuzzy probability risk analysis model for water inrush. The model can quickly track changes in risk information and diagnose the cause of water inrush disasters while providing an early warning thereof. In addition, considering that the diversity of water inrush types leads to differences in water inrush mechanisms, we believe that the formulation of any water inrush risk control scheme must be combined with water inrush mechanism analysis; therefore, we take a nondefect generated water inrush in front of the tunnel as a representative case and analyse the possible mechanism of water inrush through the stability analysis of the water-resisting strata. Then, based on the results of risk analysis and an analysis of the water inrush mechanism, a reasonable risk control scheme for water inrush is derived.

scholarly journals STUDY ON RISK CONTROL OF WATER INRUSH IN TUNNEL CONSTRUCTION PERIOD CONSIDERING UNCERTAINTY

2019 ◽  
Vol 25 (8) ◽  
pp. 757-772
Author(s):  
Zhu Wen ◽  
Yuanpu Xia ◽  
Yuguo Ji ◽  
Yiming Liu ◽  
Ziming Xiong ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Inrush ◽  
Risk Control ◽  
Tunnel Construction ◽  
Analysis Model ◽  
Factors Affecting ◽  
Construction Period ◽  
Control Scheme ◽  
Definition Of ◽  
Decision Making Model

Water inrush risk is a bottleneck problem affecting the safety and smooth construction of tunnel engineering works, so the risk control of water inrush is important, however, geological uncertainty and artificial uncertainty always accompany tunnel construction. Uncertainty will not only affect the accuracy of water inrush risk assessment results, but also affect the reliability of water inrush risk decision-making results. How to control the influence of uncertainty on water inrush risk is key to solving the problem of water inrush risk control. Based on the definition of improved risk, a risk analysis model of water inrush based on a fuzzy Bayesian network is constructed. The main factors affecting the risk of water inrush are determined by sensitivity analysis, and possible schemes in risk control of water inrush are proposed. Based on the characteristics of risk control of water inrush in a tunnel, a multi-attribute group decision-making model is constructed to determine the optimal water inrush risk control scheme, so that the optimal scheme for reducing uncertainty in risk control of water inrush is determined. Finally, this system is applied to Shiziyuan Tunnel. The results show that the proposed risk control system for reducing uncertainty of water inrush is efficacious.

A Development of Hydrologic Dam Risk Analysis Model Using Bayesian Network(BN)

2015 ◽  
Vol 48 (10) ◽  
pp. 781-791 ◽  
Author(s):  
Jin-Young Kim ◽  
◽  
Jin-Guk Kim ◽  
Byoung-Han Choi ◽  
Hyun-Han Kwon
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Analysis Model ◽  
Dam Risk

Risk Analysis Model of Water Inrush Through the Seam Floor Based on Set Pair Analysis

2017 ◽  
Vol 37 (2) ◽  
pp. 281-287 ◽  
Author(s):  
Li Bo ◽  
Wu Qiang ◽  
Duan xian-qian ◽  
Chen Meng-yu
Keyword(s):  
Risk Analysis ◽  
Water Inrush ◽  
Set Pair Analysis ◽  
Analysis Model ◽  
Pair Analysis

scholarly journals RNAseq Reveals Differential Gene Expression Contributing to Phytophthora nicotianae Adaptation to Partial Resistance in Tobacco

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 656
Author(s):  
Jing Jin ◽  
Rui Shi ◽  
Ramsey Steven Lewis ◽  
Howard David Shew
Keyword(s):  
Partial Resistance ◽  
Molecular Mechanisms ◽  
Biological Activities ◽  
Effective Means ◽  
Phytophthora Nicotianae ◽  
Economic Losses ◽  
Black Shank ◽  
Differential Gene ◽  
Go Terms

Phytophthora nicotianae is a devastating oomycete plant pathogen with a wide host range. On tobacco, it causes black shank, a disease that can result in severe economic losses. Deployment of host resistance is one of the most effective means of controlling tobacco black shank, but adaptation to complete and partial resistance by P. nicotianae can limit the long-term effectiveness of the resistance. The molecular basis of adaptation to partial resistance is largely unknown. RNAseq was performed on two isolates of P. nicotianae (adapted to either the susceptible tobacco genotype Hicks or the partially resistant genotype K 326 Wz/Wz) to identify differentially expressed genes (DEGs) during their pathogenic interactions with K 326 Wz/Wz and Hicks. Approximately 69% of the up-regulated DEGs were associated with pathogenicity in the K 326 Wz/Wz-adapted isolate when sampled following infection of its adapted host K 326 Wz/Wz. Thirty-one percent of the up-regulated DEGs were associated with pathogenicity in the Hicks-adapted isolate on K 326 Wz/Wz. A broad spectrum of over-represented gene ontology (GO) terms were assigned to down-regulated genes in the Hicks-adapted isolate. In the host, a series of GO terms involved in nuclear biosynthesis processes were assigned to the down-regulated genes in K 326 Wz/Wz inoculated with K 326 Wz/Wz-adapted isolate. This study enhances our understanding of the molecular mechanisms of P. nicotianae adaptation to partial resistance in tobacco by elucidating how the pathogen recruits pathogenicity-associated genes that impact host biological activities.

A Bayesian-Network-based Approach to Risk Analysis in Runway Excursions

2019 ◽  
Vol 72 (5) ◽  
pp. 1121-1139 ◽  
Author(s):  
Fernando Calle-Alonso ◽  
Carlos J. Pérez ◽  
Eduardo S. Ayra
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Exploratory Analysis ◽  
Hypothesis Tests ◽  
Aircraft Accidents ◽  
Risk Scenarios ◽  
Key Variables ◽  
Expert Recommendations

Aircraft accidents are extremely rare in the aviation sector. However, their consequences can be very dramatic. One of the most important problems is runway excursions, when an aircraft exceeds the end (overrun) or the side (veer-off) of the runway. After performing exploratory analysis and hypothesis tests, a Bayesian-network-based approach was considered to provide information from risk scenarios involving landing procedures. The method was applied to a real database containing key variables related to landing operations on three runways. The objective was to analyse the effects over runway overrun excursions of failing to fulfil expert recommendations upon landing. For this purpose, the most influential variables were analysed statistically, and several scenarios were built, leading to a runway ranking based on the risk assessed.

Research on Combat Effectiveness Evaluation of Radar EW System Based on Bayesian Network

2011 ◽  
Vol 204-210 ◽  
pp. 1697-1700 ◽  
Author(s):  
Yu Jie Zheng
Keyword(s):  
Bayesian Network ◽  
Evaluation Model ◽  
Effectiveness Evaluation ◽  
Analysis Model ◽  
Key Factors ◽  
Bayesian Network Model ◽  
Simulation Data ◽  
Factors Analysis ◽  
Combat Effectiveness ◽  
Hidden Knowledge

Radar EW system combat effectiveness evaluation is a essential link to Radar system Demonstration, mainly give service to selection, optimization and key factors analysis of Weapon equipment scheme. In this paper, we introduce the Bayesian network model into the area of Radar EW system combat effectiveness evaluation and put forward the concept of combat effectiveness evaluation model based on Bayesian network. The ability to express complex relationship, the ability to express the uncertainty of probability, and the reasoning functions. By learning from Expertise and Simulation data, excavating the hidden knowledge included in both of them, we can build the combat efficiency Analysis model, and then carry out efficient analysis.

Scenario based evaluation of a cost risk model through sensitivity analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Önder Ökmen ◽  
Ahmet Öztaş
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Practical Method ◽  
Cost Evaluation ◽  
Sensitivity Analyses ◽  
Analysis Model ◽  
Content Type ◽  
Detailed Evaluation ◽  
Cost Risk

Purpose – Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses. Design/methodology/approach – The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results. Findings – The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies. Originality/value – Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.

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