A New System Risk Definition and System Risk Analysis Approach Based on Improved Risk Field

Risk is an objective quantity applied to describe the degree of harm to a specific system of many activities and technologies. In order to manage risk successfully and ensure the normal operation of a system, an explicit system risk definition and a system risk analysis approach are essential. After analyzing the system risk change curve, a new definition of system risk is given, which is formulated as the risk energy change in a system. A Gaussian pulse energy function is introduced to calculate the changed risk energy, and a new unit <inline-formula><tex-math notation="LaTeX">$\text{H}$</tex-math></inline-formula> is given to describe the system risk, where <inline-formula><tex-math notation="LaTeX">$\text{H}$</tex-math></inline-formula> formulates each unit energy change in the system or subsystem caused by the risk pulse. Based on the Gaussian pulse energy function, an improved risk field is modeled and described from two perspectives: risk potential and risk field strength. The characteristics of the improved risk field are modeled and simulated, including the superposition law of the risk potential, superposition law of the risk field strength and risk force, the flux and divergence of the risk field, and the ring flux and rotation of the risk field. The risk potential superposition law and the risk field strength superposition law provide a new system risk analysis approach to explain the formation process of system coupling risk and the interaction laws of the risk factors in a system. Finally, a real-world case study is conducted by taking a railway dangerous goods transportation accident in 2001 as a background. The simulation results of risk pulse energy show that the system risk energy value of the risk-accident critical state is between 1.712e−04<inline-formula><tex-math notation="LaTeX">$\text{H}$</tex-math></inline-formula> and 1.922e−04<inline-formula><tex-math notation="LaTeX">$\text{H}$</tex-math></inline-formula>. When the fourth risk pulse appeared, the system risk change curve crossed the risk-accident critical state line, and the accident happened. The simulation results of the risk potential and risk field strength show that risk source 1 has the biggest risk potential value and risk field strength value, followed by risk sources 1, 3, and 4, which means that risk source 1 has the biggest contribution to the accident, and it has the biggest risk impact strength to other matters.

[1]  P. Slovic.  Perception of risk. , 1987, Science.

[2]  Cai Meng-xian.  Region Environmental Risk Assessment of Railway Dangerous Goods Transportation , 2011 .

[3]  B. Cohen,et al.  A catalog of risks. , 1979, Health physics.

[4]  Jian Wang,et al.  A Modified Floor Field Model Combined with Risk Field for Pedestrian Simulation , 2016 .

[5]  Gui Fu,et al.  Relationship Analysis of Causal Factors in Coal and Gas Outburst Accidents Based on the 24Model , 2017 .

[6]  Hai-long Zhu,et al.  Hazard identification and control in the pre-blasting process , 2011 .

[7]  Arnab Majumdar,et al.  A Systemic Modeling of Ground Handling Services Using the Functional Resonance Analysis Method , 2016 .

[8]  Dajun Liu,et al.  The influence of oceanic turbulence on the spectral properties of chirped Gaussian pulsed beam , 2016 .

[9]  S. Kaplan,et al.  On The Quantitative Definition of Risk , 1981 .

[10]  Yang Can.  Network Security Risk Fusion Model Based on Data Field , 2009 .

[11]  Liu Hong-wei.  Three dimensional assessment method for risk , 2010 .

[12]  Yangpeng Wang,et al.  Using catastrophe theory to describe railway system safety and discuss system risk concept , 2017 .

[13]  W. Marsden.  I and J , 2012 .

[14]  Yang Wang,et al.  Using entropy-TOPSIS method to evaluate urban rail transit system operation performance: The China case , 2018 .

[15]  Albert Kuhlmann.  Introduction to Safety Science , 1986 .

[16]  Jicheng Liu,et al.  Risk identification and analysis for new energy power system in China based on D numbers and decision-making trial and evaluation laboratory (DEMATEL) , 2018 .

[17]  Rene D. Zentner,et al.  Hazards in the chemical industry , 1979 .

[18]  Jan Magott,et al.  A System-Theoretic Accident Model and Process with Human Factors Analysis and Classification System taxonomy , 2018, Safety Science.

[19]  Navid Akar,et al.  Risk analysis of geothermal power plants using Failure Modes and Effects Analysis (FMEA) technique , 2013 .

[20]  L. Christophorou.  Science , 2018, Emerging Dynamics: Science, Energy, Society and Values.

[21]  H. Inhaber,et al.  Risk with energy from conventional and nonconventional sources. , 1979, Science.

[22]  K. Lewin.  Field theory in social science , 1951 .

[23]  Wang Lei,et al.  Corrected Entropy Based Operation Performance Evaluation about Urban Rail Transportation Non-networks System , 2016 .

[24]  W. Freudenburg.  Perceived risk, real risk: social science and the art of probabilistic risk assessment. , 1988, Science.

[25]  Wencheng Huang,et al.  A systematic railway dangerous goods transportation system risk analysis approach: The 24 model , 2019, Journal of Loss Prevention in the Process Industries.

[26]  Hong Zhang,et al.  Study on Failure of Third-Party Damage for Urban Gas Pipeline Based on Fuzzy Comprehensive Evaluation , 2016, PloS one.

[27]  C L Comar,et al.  Risk: a pragmatic de minimis approach. , 1979, Science.

[28]  J. Shaoul.  Human Error , 1973, Nature.

[29]  I. Svedung,et al.  Proactive Risk Management in a Dynamic Society , 2000 .

[30]  Jun g Sik Kong,et al.  Quantitative risk evaluation based on event tree analysis technique: Application to the design of shield TBM , 2009 .

[31]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[32]  W. Ruckelshaus.  Science, risk, and public policy. , 1983, Science.

[33]  Cui Naigang.  Method to evaluate operational effectiveness of air-surface missile swarm based on combat simulation , 2009 .

[34]  D Okrent,et al.  Comment on Societal Risk , 1980, Science.