# Dynamic Semi-Quantitative Risk Research in Chemical Plants

^{1}

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## Abstract

**:**

## 1. Introduction

^{−6}per year, and some companies in the United Kingdom, the United States, and Denmark use this risk standard. According to the risk assessment methods of major hazards and different occasions, the Dutch government has also established reference values for personal and social risks relating to chemical plants [26,27]. A risk index was devised to allow the assessment of the risk level originating from a given installation or site over the affected zone, and a Bayesian network methodology was developed to estimate the total probability of a major accident in a chemical plant [28,29,30,31,32]. The current research detailed above, which is mainly used for chemical industry park planning and analysis, cannot be easily used for the dynamic safety management of existing chemical industry parks; in addition, only the main hazards themselves were considered in these studies, and other major factors that affect safety accidents, such as human, machine, material, method, and environment, were not considered.

## 2. Using the Analytical Hierarchy Process to Establish a Dynamic Semi-Quantitative Evaluation Model

#### 2.1. Establishing a Dynamic Semi-Quantitative Risk Calculation Model for Chemical Hazards

#### 2.2. Dynamic Semi-Quantitative Calculation and Analysis of Hazards

#### 2.2.1. Dynamic and Quantitative Calculation of Risk Values for Hazards

- (1)
- The classification index uses the actual (stored) amounts of various dangerous chemicals in the unit and their critical amount ratios specified in “Identification of Major Hazard of Dangerous Chemicals” (GB18218); the sum of the ratios of the corrected coefficients is the classification index.
- (2)
- R value calculation

#### 2.2.2. Analysis of Dynamic Semi-Quantitative Hazard Calculation Methods

#### Hazards in the Pipeline

#### Domino Effects in Chemical Industry Parks

#### Operator, Equipment, Process, and Environment

#### Safety Management

#### 2.3. Analysis of Influencing Factors in the Dynamic Quantitative Evaluation

#### 2.3.1. Increased Risk of Quantities in the Pipeline

#### 2.3.2. Domino Effect

_{blast}) and the probability of thermal radiation domino effect (P

_{heat}). The calculation of the domino effect probability was obtained using a simulation evaluation of accident consequences. By selecting the explosion and fire models as the accident consequence models, we can get the shockwave domino effect probability and the thermal radiation domino effect probability; while there are several accident consequence models for a chemical industry park, the more common are explosion and fire.

- (1)
- Explosion—blast shockwave overpressure

- (2)
- Fire—thermal radiation

- (3)
- The accident domino effect threshold

- Thermal radiation domino effect threshold

^{2}, and the threshold for thermal radiation for pressure vessels over more than 10 min is 50 kW/m

^{2}; these were given by Valerio Cozzani et al. [37]. The setting of these thresholds has been approved by other international scholars, and this article also adopts these thresholds.

- b.
- Shock wave domino effect threshold

- (4)
- Domino effect probability

- (5)
- Domino effect coefficientThe value of the domino coefficient γ considers three aspects:
- (1)
- Domino effect forms, including thermal radiation and shock wave overpressure;
- (2)
- The probability of a domino effect;
- (3)
- The number of units that may have a secondary accident affected by the domino effect.

#### 2.3.3. Operator

- (1)
- Personnel eligibility

_{1}= 1; for those not licensed, H

_{1}= NA (empty value).

- (2)
- Personnel proficiency

- (3)
- Personnel stability

- (4)
- Personnel workload

_{0}-many personnel working but in fact has only N

_{0}people, withM

_{0}>N

_{0}, the working hours should be converted. Therefore, the personnel workload was calculated as shown in Equation (15).

- (5)
- Reliability of individual operators

- (6)
- The quality of the operator assigned to the post

- (7)
- The reliability of the quality of a single post

- (8)
- Unit operator quality of reliability

#### 2.3.4. Process/Equipment Rating Scale

#### 2.3.5. Building Environment Rating Scale

#### 2.3.6. Safety Management Rating Scale

#### 2.4. Constructing a Dynamic Semi-Quantitative Calculation Model for Chemical Hazards

## 3. Index Value Calculations via an Analytical Hierarchy Model

#### 3.1. Risk Value Factor of a Hazard, Denoted a (Also R_{3})

_{i}as shown in Equation (24).

#### 3.2. Domino Effect Factor, Denoted b

#### 3.2.1. Overpressure Explosion Model and Vapor Explosion Model Calculation

_{1}is defined as shown in Equation (28).

- (1)
- Overpressure explosion model

- (2)
- Vapor explosion modell

_{ji}(r) and t

_{i}from Equations (8) to (10), and (27), as shown in Equations (31) and (32).

#### 3.2.2. Overpressure Explosion and Vapor Explosion Model Probability Calculations

_{3i}data set and the vapor explosion probability as the b’

_{3i}data set; the explosion probability matrix can then be constructed as shown in Equations (34) to (36).

#### 3.2.3. Domino Effect Coefficient

#### 3.3. Operator Factor, Denoted c

_{1}), working age (t

_{2}), accident-free time (t

_{3}), and working time (t

_{4}).We set the input matrix as shown in Equation (39).

_{0}= N

_{0}.When g

_{k}= g

_{j}(k ≠ j, k = 1,2,…,n, j = 1,2,…,n), from Equations (13)–(15), H

_{pi}is as shown in Equation (40).

_{1},g

_{2},…,g

_{n}}

_{i}can make up H

_{p}, so the operator risk is as shown in Equation (41).

_{u}has a maximum close to 1. Taking into account the limited impact of personnel factors, when the value is 0.8, the coefficient c is specified as 1. The worse the indicator, the greater the coefficient c. The highest value of H

_{u}is 1 and the lowest value is specified as 0.6, so when the value is lower than 0.6, it is calculated using 0.6 instead. Therefore, the range of c values is 0.8 to 1.33.

_{ui}≤ 0.6, we let H

_{ui}= 0.6, and c

_{i}is calculated as shown in Equation (42).

#### 3.4. Process/Equipment Factor, Denoted d

_{i}, where

_{i}= [X

_{11}X

_{12}X

_{21}X

_{22}X

_{31}X

_{32}X

_{41}X

_{42}X

_{5}X

_{6}X

_{7}X

_{8}X

_{9}X

_{A}X

_{B1}X

_{B2}X

_{C1}X

_{C2}X

_{C3}X

_{C4}X

_{C5}X

_{D1}X

_{D2}X

_{D3}X

_{D4}X

_{D5}]

^{T}

- (1)
- The original input data are only 0 or 1, that is, X
_{11}, X_{12}, …, X_{D5}∈ {0,1}; - (2)
- X
_{11}+ X_{12}≤ 1; - (3)
- X
_{31}+ X_{32}≤ 1; - (4)
- X
_{41}+ X_{42}≤ 1; - (5)
- X
_{5}= X_{51}+ X_{52}≤ 1; - (6)
- X
_{6}= X_{61}+ X_{62}+ X_{63}+ X_{64}+ X_{65}+ X_{66}+ X_{67}+ X_{68}+ X_{69}≤ 1; - (7)
- X
_{7}= X_{71}+ X_{72}+ X_{73}+ X_{74}+ X_{75}≤ 1; - (8)
- X
_{8}= X_{81}+ X_{82}+ X_{83}+ X_{84}+ X_{85}; - (9)
- X
_{9}= X_{91}+ X_{92}+ X_{93}; - (10)
- X
_{A}= X_{A1}+ X_{A2}+ X_{A3}≤ 1; - (11)
- X
_{B1}+ X_{B2}≤ 1.

_{i}, where x

_{i}is the multiplication of matrix D and matrix X

_{i}, as shown in Equation (44).

_{i}= DX

_{i}

_{i}≥ 186, the definition of value d is as shown in Equation (45).

_{i}< 186, the definition of value d is ${d}_{i}=1.33$.

#### 3.5. Building Environmental Factor, Denoted e

_{i}such that Y

_{i}= [Y

_{11}Y

_{21}Y

_{22}Y

_{23}Y

_{31}Y

_{32}Y

_{33}Y

_{41}Y

_{42}Y

_{43}Y

_{44}Y

_{45}Y

_{51}Y

_{52}]

^{T}and with restrictions as follows:

- (1)
- The original input data are only 0 or 1, that is, Y
_{11}, Y_{21},…, Y_{52}∈ {0,1}; - (2)
- Y
_{21}+ Y_{22}+ Y_{23}≤ 1.

_{i}where y

_{i}is the multiplication of matrix E and matrix Y

_{i}, as shown in Equation (47).

_{i}= EY

_{i}

_{i}≥ 53, the definition of e is as shown in Equation (48).

_{i}< 53, the definition of e is ${e}_{i}=1.33$.

#### 3.6. Safety Management Factor, Denoted f

_{i}, where Z

_{i}= [Z

_{1}Z

_{2}Z

_{3}Z

_{4}Z

_{5}Z

_{6}Z

_{7}Z

_{8}Z

_{9}Z

_{A}]

^{T}, with restrictions as follows:

- (1)
- The original input data are only 0 or 1, that is, Z
_{11}, Z_{12},…, Z_{AA}∈ {0,1}; - (2)
- Z
_{1}= Z_{11}+ Z_{12}+ Z_{13}+ Z_{14}+ Z_{15}+ Z_{16}+ Z_{17}+ Z_{18}+ Z_{19}; - (3)
- Z
_{2}= Z_{21}+ Z_{22}+ Z_{23}+ Z_{24}+ Z_{25}+ Z_{26}+ Z_{27}+ Z_{28}; - (4)
- Z
_{3}= Z_{31}+ Z_{32}+ Z_{33}+ Z_{34}; - (5)
- Z
_{4}= Z_{41}+ Z_{42}+ Z_{43}+ Z_{44}+ Z_{45}+ Z_{46}+ Z_{47}; - (6)
- Z
_{5}= Z_{51}+ Z_{52}+ Z_{53}+ Z_{54}+ Z_{55}+ Z_{56}+ Z_{57}+ Z_{58}+ Z_{59}+ Z_{5A}+ Z_{5B}+ Z_{5C}+ Z_{5D}; - (7)
- Z
_{6}= Z_{61}+ Z_{62}+ Z_{63}+ Z_{64}+ Z_{65}; - (8)
- Z
_{7}= Z_{71}+ Z_{72}+ Z_{73}; - (9)
- Z
_{8}= Z_{81}+ Z_{82}+ Z_{83}+ Z_{84}+ Z_{85}+ Z_{86}+ Z_{87}+ Z_{88}+ Z_{89}; - (10)
- Z
_{9}= Z_{91}+ Z_{92}+ Z_{93}+ Z_{94}+ Z_{95}+ Z_{96}+ Z_{97}+ Z_{98}+ Z_{99}; - (11)
- Z
_{A}= Z_{A1}+ Z_{A2}+ Z_{A3}+ Z_{A4}+ Z_{A5}+ Z_{A6}+ Z_{A7}+ Z_{A8}+ Z_{A9}+Z_{AA}.

_{i}, where z

_{i}is the multiplication of matrix F and matrix Z

_{i}as shown in Equation (50).

_{i}= FZ

_{i}

_{i}≥ 60, the definition of f is as shown in Equation (51).

_{i}< 60, the definition of f is ${f}_{i}=1.33$.

#### 3.7. Calculation Results

## 4. Case Analysis

#### 4.1. Major Hazards Factory Fact Sheet

#### 4.2. Dynamic Quantitative Calculation of Hazards

#### 4.2.1. Risk Value Factor of Hazards, Denoted a

#### 4.2.2. Domino Effect Factor, Denoted b

- (1)
- Overpressure explosion

_{c}= 22,675 kJ/kg, ethanol’s heat of combustion Q

_{c}= 29,640 kJ/kg, p

_{0}= 101,325 pa, and L = 70 m is given in the example; from Equation (29), $\Delta p$ can be obtained as shown in Equation (60).

_{2}can be obtained according to Equation (30) and Table 9, and it is as shown in Equation (61).

- (2)
- Vapor explosion

_{0}= 200 kw/m

^{2}, and L = 70 m is given in the example, so q(r) and t can be obtained from Equations (31) and(32) as shown in Equations(63) and (64).

- (3)
- Domino effect coefficient

#### 4.2.3. Operator Factor, Denoted c

_{p}can be obtained as shown in Equation (67).

_{p}and Equation (41), H

_{u}can be obtained as shown in Equation (68).

_{ui}≤ 0.6, we let H

_{ui}= 0.6; the H’

_{u}values obtained after adjustment are as shown in Equation (69).

#### 4.2.4. Process/Equipment Factor, Denoted d

_{i}, a preliminary summary of available data is given in Table 13.

_{i}=DX

_{i}, x

_{i}can be obtained as shown in Equation (71).

#### 4.2.5. Building Environmental Factor, Denoted e

_{i}, a preliminary summary of available data is given in Table 14.

_{i}= DY

_{i}, we can calculate y, and it is as shown in Equation (73).

#### 4.2.6. Safety Management Factor, Denoted f

_{i}, a preliminary summary of available data is given in Table 15.

_{i}= FZ

_{i}, we can calculate z as shown in Equation (75).

#### 4.3. The Final Optimized Hazard Risk Value

#### 4.4. Comparison WITH the Traditional Method of Calculating Hazard Risk Values

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

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**Figure 1.**Flowchart for establishing a dynamic semi-quantitative risk calculation model for chemical hazards.

**Figure 2.**Fishbone diagram analysis of the main factors that affect the risk values of chemical hazards.

Time | Accident Location | Accident Type | Death Toll | Direct Property Loss |
---|---|---|---|---|

1974.6.1 | Flixborough | Chemical explosion | 28 | unknown |

1984.12.2 | Bhopal | Chemical poisoning | 25,000 | $470 million |

1988.7.6 | Piper Alpha | Chemical explosion | 167 | $7500 million |

2013.4.17 | State of Texas | Chemical explosion | 35 | unknown |

2015.8.12 | Binhai, Tianjin | Chemical explosion | 165 | $1098 million |

Parameters: |
---|

(1) Hazards calculation parameter |

R risk value |

q_{1},q_{2}, …, q_{n} The actual quantity (in storage) of each dangerous chemical (tons) |

Q_{1},Q_{2}, …, Q_{n} Corresponding critical mass (ton) |

β_{1},β_{2} …, β_{n} The corresponding correction coefficient |

α Correction factor for number of exposed personnel |

R_{3} R value after optimization |

R_{1} Hazards in the production process |

R_{2} Hazards of the storage tank |

q_{1}’,q_{2}’, …, q_{n}’ Quantity of each dangerous chemical online (ton) |

Q_{1}’,Q_{2}’, …, Q_{n}’ Corresponding critical mass (ton) |

(2) The domino effect calculation parameter |

Δp Blast overpressure (Pa) |

p_{0} Atmospheric pressure (101,325 Pa) |

Z Dimensionless distance |

L The horizontal distance from the target to the source of the blast (m) |

E The total explosive energy source (J) |

α’ Equivalent coefficient for vapor cloud, generally 0.04 |

W_{1} The mass of fuel in the vapor cloud that actually contributes to the blast shockwave (Kg) |

Q_{C} Heat of combustion of the fuel (J/Kg) |

q (r) Radiation flux to the target (W/m^{2)} |

q_{0} Radiation flux on the surface of the fireball, cylindrical tank to take 270 kW/m^{2}, spherical tank to take 200 kW/m^{2} |

R_{0} Fireball radius (m) |

r The horizontal distance from the target to the center of the fireball (m) |

W_{2} Fireball consumption of combustible material (kg) |

t Fireball duration (s) |

P Domino effect probability |

Y Domino effect probability unit |

t’ No-fault time |

I Radiation intensity on the target (KW/m^{2}) |

V Equipment volume (m^{3}) |

P_{blast} The domino effect probability of shockwave |

P_{heat} The domino effect probability of heat radiation |

γ Domino coefficient |

(3) The operator calculation parameter |

H_{1} Personnel qualifying value |

H_{2} Personnel proficiency value |

t_{2} Staff working time at a post |

K_{2} Skilled scale factor |

T_{2} The time required to reach a certain level of proficiency |

H_{3} Personnel stability value |

t_{3} Working hours at the post |

K_{3} Stability ratio coefficient |

T_{3} The time it takes for a person to reach a certain level of operational stability after an accident |

H_{4} Personnel workload value |

t_{4} Personnel work time from work start to work end |

K_{4} Workload ratio factor |

T_{4} Job normal working-class work time, generally taken to be 8 h |

M_{0} Jobs required for the number of workers |

N_{0} The actual number of jobs at the post, and N_{0} < M_{0} |

H_{5} The reliability value of a single person |

H_{s} The reliability of the designated post |

H_{p} The reliability of a single staff member |

H_{u} The reliability of unit personnel quality |

(4) The process/equipment, building environment, and safety management calculation parameter |

D Process/equipment basic score |

X_{i} The result of process/equipment judgment, yes is 1, no 0 |

E Building environment basic score |

Y_{i} The result of building environmental judgment, yes is 1 and no is 0 |

F Safety management basic score |

Z_{i} The result of safety management judgment, yes is 1 and no is 0 |

Chemical Hazard Significance Level | R Value |
---|---|

Level 1 | R ≥ 100 |

Level 2 | 100 > R ≥ 50 |

Level 3 | 50 > R ≥ 10 |

Level 4 | R < 10 |

Physical Factors | Container Type | Threshold | Probability Calculation Equations |
---|---|---|---|

Overpressure | Atmospheric pressure | 22 kPa | Y = −18.96 + 2.44lnP_{s} |

Pressure | 16 kPa | Y = −42.44 + 4.33lnP_{s} | |

Long type | 31 kPa | Y = −28.07 + 3.16lnP_{s} | |

Small type | 37 kPa | Y = −17.79 + 2.18lnP_{s} | |

Heat radiation | Atmospheric pressure | More than 10 m,15 W/m^{2} | Y=12.54 − 1.847lnt’ |

lnt’ = −1.128lnI − 2.667 × 10^{−5}V + 9.877 | |||

Pressure | More than 10 m, 50 W/m^{2} | Y=12.54−1.847lnt’ | |

lnt’ = −0.947lnI + 8.835V^{0.032} |

Number | Item | Content(Keywords) | Score (D) | X_{i} |
---|---|---|---|---|

1 | Equipment maintenance (or) | 1. Strict, 2. Basic | 8, 6 | X_{11}, X_{12} |

2 | Explosion-proof device (and) | 1. Explosive itself, 2. Explosion-proof membrane | 24, 11 | X_{21}, X_{22} |

3 | Inert gas protection(or) | 1. Continuous, 2. Sufficient | 13, 15 | X_{31}, X_{32} |

4 | Emergency cooling (or) | 1. More than 10 min, 2. About 10 min | 10, 12 | X_{41}, X_{42} |

5 | Emergency Power Supply (or) | 1. Multi-channel power supply, 2. Generator set | 12 | X_{51}, X_{52} |

6 | Electrical explosion-proof(or) | 1. Flameproof, 2. Increased safety, 3. Intrinsically safe, 4. Positive pressure, 5. Oil-filled, 6. Sand-filled, 7. No spark, 8. Explosion-proof, 9. Dust Explosion-proof | 7 | X_{61}, X_{62}, X_{63}, X_{64}, X_{65},X _{66}, X_{67}, X_{68}, X_{69} |

7 | Anti-static (and) | 1. Less production, 2. Leakage, 3. Neutralization, 4. Shielding, 5. Smooth surface | 7 | X_{71}, X_{72}, X_{73}, X_{74}, X_{75} |

8 | Lightning protection (and) | 1. Less production, 2. Leakage, 3. Neutralization, 4. Shielding, 5. Smooth surface | 7 | X_{81}, X_{82}, X_{83}, X_{84}, X_{85} |

9 | Device for preventing fire (and) | 1. Flame arrester, 2. Fluid seal, 3. Others | 12 | X_{91}, X_{92}, X_{93} |

10 | Process parameter control (or) | 1. A set, 2. Parallel and manual, 3. Parallel and automatic | 11 | X_{A1}, X_{A2}, X_{A3} |

11 | Leak detection device and response(or) | 1. Alarm and confirmation, 2. Alarm and protection | 11, 15 | X_{B1}, X_{B2} |

12 | Fault alarm and control device (and) | 1. Cut off, 2. Control valve, 3. Vibration and alarm, 4. Vibration and protection, 5. Others | 11, 11, 10, 13, 10 | X_{C1}, X_{C2}, X_{C3}, X_{C4}, X_{C5} |

13 | Accident emissions and treatment (and) | 1. Safety, 2. Outside the unit, 3. Emergency ventilation duct, 4. Double jacket, 5. Protective dike | 11, 13, 13, 14, 11 | X_{D1}, X_{D2}, X_{D3}, X_{D4}, X_{D5} |

Number | Item | Content(Keywords) | Score (E) | Y_{i} |
---|---|---|---|---|

1 | Ventilation plant | Full ventilation | 6 | Y_{11} |

2 | Pressure relief (or) | 1. Auto window, 2. Safety hole, 3. Other | 8 | Y_{21}, Y_{22}, Y_{23} |

3 | Monitoring device (and) | 1. Control room, 2. Surveillance, 3. Troubleshooting | 10, 12, 18 | Y_{31}, Y_{32}, Y_{33} |

4 | Plant structure (and) | 1. Reasonable classification, 2. Fire resistance, 3. Fire prevention distance, 4. Explosion protection, 5. Escape port | 5 | Y_{41}, Y_{42}, Y_{43},Y _{44}, Y_{45} |

5 | Industrial sewer (and) | 1. Industrial sewer, 2. Oil trap | 5 | Y_{51}, Y_{52} |

Number | Item | Content(Keywords) | Score (F) | Z_{i} |
---|---|---|---|---|

1 | Safety production responsibility system | 1. Director, 2. Deputy director, 3. Other deputy director, 4. Chief engineer, 5. Head of department, 6. Director of the workshop, 7. Team leader, 8. Operator, 9. Union leader | 1.11 | Z_{11}~Z_{19} |

2 | Safety education | 1. New workers, 2. Special workers, 3. New technologies, 4. Returning workers, 5. New jobs, 6. Middle-level cadres, 7. Team leaders, 8. All staff | 1.25 | Z_{21}~Z_{28} |

3 | Safety technical measures plan | 1. Plan, 2. Specific funds, 3. Responsible person, 4. Target value | 2.50 | Z_{31}~Z_{34} |

4 | Safety inspection | 1. Regular, 2. Frequent, 3. Dedicated, 4. Professional, 5. Seasonal, 6. Holidays, 7. Focus | 1.43 | Z_{41}~Z_{47} |

5 | Safety rules and regulations | 1. Rewards, 2. On-duty, 3. Operational procedures, 4. Management, 5. Approval, 6. Hazard, 7. Protection, 8. Electricity, 9. Overtime, 10. Ignition, 11. Inspection, 12. Leakage prevention, 13. Signs | 0.77 | Z_{51}~Z_{5D} |

6 | Safety management agencies and personnel | 1. Committee, 2. Agency, 3. Part-time management, 4. Part-time employee insurance, 5. Supervisor | 2.00 | Z_{61}~Z_{65} |

7 | Statistical analysis of accidents | 1. Record, 2. Analyze 3. Statistics | 3.33 | Z_{71}~Z_{73} |

8 | Hazard assessment and rectification | 1. Safety evaluation, 2. Hierarchical management, 3. Restructuring, 4. Important management | 2.50 | Z_{81}~Z_{84} |

9 | Emergency plans and measures | 1. Command, 2. Procedure, 3. Plan, 4. Device, 5. Safety exit, 6. Emergency equipment, 7. Communication, 8. Service organization, 9. Exercise | 1.11 | Z_{91}~Z_{99} |

10 | Fire safety management | 1. Committee, 2. Responsibility, 3. Inspection, 4. Account, 5. Mark, 6. Plane paper, 7. Fire protection, 8. Fire suppression, 9. Communication, 10. Exercise | 1.00 | Z_{A1}~Z_{AA} |

**Table 8.**Chemical hazard dynamic quantitative calculation model parameters used in the calculation of parameters.

Parameters: |
---|

q Chemical hazards storage mass(ton); |

q’ Chemical hazards production site mass (ton); |

Q Chemical hazards storage critical mass (ton); |

Q’ Chemical hazards production site critical mass (ton); |

i The ith monitoring point |

m Read m monitoring point data |

N n kinds of chemical substances. |

b_{2} Domino effect probability unit |

b_{3} Domino effect probability |

R’ The final optimized risk value |

Number | x Value | Condition | Result |
---|---|---|---|

1 | x_{1} = 1 | Δp ≥ 22 kpa | b_{2} = Y=−18.96 + 2.44lnP_{s} |

Δp < 22 kpa | b3 = 0 | ||

2 | x_{2} = 1 | Δp ≥ 16 kpa | b_{2} = Y=−42.44 + 4.33lnP_{s} |

Δp < 16 kpa | b3 = 0 | ||

3 | x_{3} = 1 | Δp ≥ 31 kpa | b_{2} = Y=−28.07 + 3.16lnP_{s} |

Δp < 31 kpa | b3 = 0 | ||

4 | x_{4}= 1 | Δp ≥ 37 kpa | b_{2} = Y=−17.79 + 2.18lnP_{s} |

Δp < 37 kpa | b3 = 0 |

Number | y Value | Condition | Result |
---|---|---|---|

1 | y_{1} = 1 | q_{ji}(r) ≥ 15 kpa and t ≥ 10 min | b_{2} = Y = 12.54 − 1.847(−1.128lnI − 2.667 × 10^{−5}V + 9.877) |

q_{ji}(r) < 15 kpa or t < 10 min | b_{3} = 0 | ||

2 | y_{2} = 1 | q_{ji}(r) ≥ 50 kpa and t ≥ 10 min | b_{2} = Y = 12.54−1.847(−0.947lnI + 8.835V^{0.032}) |

q_{ji}(r) < 50 kpa or t < 10 min | b_{3} = 0 |

Evaluation Items | One-to-One Comparison Result | Points Accumulated | Weight (ω_{j}) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|

Domino effect | 1 | 1 | 1 | 1 | 4 | 0.4 | ||||||

Operator | 0 | 1 | 1 | 0 | 2 | 0.2 | ||||||

Process/equipment | 0 | 0 | 1 | 0 | 1 | 0.1 | ||||||

Building environment | 0 | 0 | 0 | 1 | 1 | 0.1 | ||||||

Safety management | 0 | 1 | 1 | 0 | 2 | 0.2 | ||||||

Total | 10 | 1.0 |

Monitoring Point | Name | Post | Certificate | Working Age (Years) | Accident-Free Time (Years) | Working Time (Hours/Day) |
---|---|---|---|---|---|---|

1 | Tom | Storage | Yes | 1 | 1 | 8 |

2 | Tom | Storage | Yes | 1 | 1 | 9 |

3 | Tom | Storage | Yes | 1 | 1 | 10 |

4 | Tom | Storage | Yes | 1 | 1 | 8 |

5 | Tom | Storage | Yes | 2 | 2 | 8 |

6 | Tom | Storage | Yes | 2 | 0 | 8 |

7 | Tom | Storage | Yes | 2 | 0 | 10 |

8 | Tom | Storage | Yes | 2 | 1 | 8 |

9 | Jack | Storage | Yes | 5 | 5 | 8 |

10 | Jack | Storage | Yes | 5 | 5 | 10 |

11 | Mark | Storage | Yes | 2 | 0 | 8 |

12 | Mark | Storage | Yes | 2 | 0 | 8 |

13 | Mark | Storage | Yes | 2 | 0 | 8 |

14 | Jose | Storage | Yes | 1 | 1 | 8 |

15 | Joe | Storage | Yes | 4 | 4 | 10 |

X_{i} | Monitoring Points | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | |

X_{11} | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |

X_{12} | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 |

X_{21} | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 |

X_{22} | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 |

X_{31} | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 |

X_{32} | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 |

X_{41} | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 |

X_{42} | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |

X_{5} | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 |

X_{6} | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 |

X_{7} | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 1 |

X_{8} | 2 | 3 | 5 | 4 | 1 | 3 | 4 | 5 | 2 | 3 | 5 | 5 | 2 | 4 | 3 |

X_{9} | 3 | 2 | 1 | 1 | 2 | 2 | 2 | 2 | 3 | 3 | 3 | 2 | 2 | 1 | 1 |

X_{A} | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 |

X_{B1} | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 |

X_{B2} | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |

X_{C1} | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 |

X_{C2} | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |

X_{C3} | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 |

X_{C4} | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 1 |

X_{C5} | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 |

X_{D1} | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 |

X_{D2} | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |

X_{D3} | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 |

X_{D4} | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 |

X_{D5} | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 1 |

Y_{i} | Monitoring Points | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | |

Y_{11} | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 |

Y_{21} | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 |

Y_{22} | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 |

Y_{23} | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 |

Y_{31} | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 |

Y_{32} | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 |

Y_{33} | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |

Y_{41} | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 |

Y_{42} | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 |

Y_{43} | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 |

Y_{44} | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 |

Y_{45} | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 |

Y_{51} | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 |

Y_{52} | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 |

Z_{i} | Monitoring Points | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | |

Z_{1} | 10 | 10 | 10 | 7.7 | 6.6 | 10 | 3 | 10 | 8.8 | 7.7 | 10 | 8.8 | 7.7 | 10 | 10 |

Z_{2} | 10 | 8.8 | 8.8 | 7.5 | 7.5 | 8.8 | 8.8 | 7.5 | 7.5 | 10 | 10 | 10 | 7.5 | 7.5 | 10 |

Z_{3} | 10 | 7.5 | 7.5 | 5.0 | 5.0 | 5.0 | 7.5 | 10 | 10 | 10 | 7.5 | 7.5 | 10 | 10 | 7.5 |

Z_{4} | 10 | 8.6 | 8.6 | 7.1 | 7.1 | 5.7 | 7.1 | 7.1 | 8.6 | 8.6 | 8.6 | 10 | 10 | 10 | 8.6 |

Z_{5} | 10 | 9.2 | 9.2 | 8.5 | 8.5 | 6.9 | 6.9 | 10 | 10 | 10 | 6.9 | 6.9 | 8.5 | 9.2 | 10 |

Z_{6} | 10 | 8.0 | 10 | 10 | 8.0 | 6.0 | 8.0 | 6.0 | 10 | 10 | 10 | 6.0 | 6.0 | 10 | 8.0 |

Z_{7} | 10 | 10 | 6.6 | 6.6 | 6.6 | 6.6 | 3.3 | 10 | 10 | 10 | 10 | 6.6 | 6.6 | 10 | 10 |

Z_{8} | 10 | 10 | 7.5 | 5.0 | 5.0 | 5.0 | 2.5 | 7.5 | 7.5 | 7.5 | 10 | 10 | 10 | 10 | 10 |

Z_{9} | 10 | 10 | 10 | 6.6 | 7.7 | 8.8 | 5.5 | 10 | 10 | 8.8 | 7.7 | 7.7 | 8.8 | 6.6 | 10 |

Z_{A} | 8 | 9.0 | 9.0 | 10 | 8.0 | 9.0 | 5.0 | 9.0 | 9.0 | 7.0 | 7.0 | 8.0 | 10 | 10 | 9.0 |

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**MDPI and ACS Style**

Song, Q.; Jiang, P.; Zheng, S.; Kong, Y.; Zhao, Y.; Shen, G.
Dynamic Semi-Quantitative Risk Research in Chemical Plants. *Processes* **2019**, *7*, 849.
https://doi.org/10.3390/pr7110849

**AMA Style**

Song Q, Jiang P, Zheng S, Kong Y, Zhao Y, Shen G.
Dynamic Semi-Quantitative Risk Research in Chemical Plants. *Processes*. 2019; 7(11):849.
https://doi.org/10.3390/pr7110849

**Chicago/Turabian Style**

Song, Qiusheng, Peng Jiang, Song Zheng, Yaguang Kong, Ye Zhao, and Gang Shen.
2019. "Dynamic Semi-Quantitative Risk Research in Chemical Plants" *Processes* 7, no. 11: 849.
https://doi.org/10.3390/pr7110849