# Performance Simulation of the Transportation Process Risk of Bauxite Carriers Based on the Markov Chain and Cloud Model

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Literature Review

^{3}affects the stability safety of the carrier during transportation [13].

## 3. Methods

#### 3.1. Transportation Risk Assessment

#### 3.2. Markov Chain

#### 3.3. Cloud Model

_{x}(Expectation) is the core of all cloud-drops in the number field, reflecting the best projection of the qualitative concept in the number field. E

_{n}(Entropy) is the variable that expresses the qualitative concept as well as others, reflecting the extent of the linguistic values accepted in the number field, which is fuzziness. It also reflects the probability of the linguistic value represented in the number field. H

_{e}(Hyper) is the dispersion degree of entropy, standing for the cohesiveness of each value representing the certainty of linguistic values and reflecting the degree of condensation of cloud-drops.

_{x}, E

_{n}and H

_{e}, respectively, in Table 1.

#### 3.4. Markov Chain Cloud Simulation

## 4. Results

#### 4.1. Data Collection

#### 4.2. Markov Property Judgment

#### 4.3. Cloud Simulation

#### 4.4. Status Transfer of Process Risk

## 5. Analysis and Discussion

#### 5.1. Tendency of Risk

#### 5.2. Characteristics of Process Risk

- The initial moisture content of the cargo, the conformity of the stowage plan, the weather condition during the cargo loading process, the safety status of the ship, the competence and preparation of the seafarers contribute to the initial risks of the whole transportation process. As a result, the loading stage of the bauxite transportation is at a relatively higher risk status. The special property of the bauxite determines the basic value for the overall risk of the carrier, which is consistent with the practice of shipping. According to the interviews and questionnaires, some risks are hidden in the stages of pre-loading and loading. A total of 65% of seafarers put more emphasis on the inspection of the suitability of the ship prior to loading. A total of 47% of seafarers stated that there is a certain amount of false information provided by shippers prior to loading. A total of 50% of seafarers said that the ship detected water content occasionally in accordance with the IMSBC code. A total of 47% of the seafarers thought good cooperation and communication was lacking between the ship and shore during the process of loading and unloading the bauxite.
- Once loading is completed, the engine trial and the irregular rotation of propeller lead to the vibration of the whole ship, which has negative effects on the status of the bauxite and results in the formation of volatility risk. During unberthing, the risk imposed on the carrier has due to the great fluctuation. The overall risk was low due to the assistance of tugboats and the pilot on board at the wharf apron and harbor waters. However, because of the frequent change of the course and speed, the external interference on the bauxite carrier fluctuates. Therefore, the risk of this phrase is referred to as volatility risk.
- After passing the approach channel offshore, the bauxite carrier encounters a greater disturbance from the complexity of the navigation environment, due to such things as the wind, current and waves [49]. Due to great hull vibrations and wave swings of the ship in the coastal sea, a huge influence on the liquefaction characteristics of bauxite occurred. The risk of the transverse inclination was aggravated on the basis of the small angle heel produced by cargo shifts and compaction. That is the derivative risk in the ocean navigation stage during the transportation process. The risk status in the stages of departure and sea-voyages gradually increase.
- As the bauxite carrier sails farther away from the land and the risk of bauxite liquefaction greatly increases, this is referred to as the derivative risk of the transportation process.

#### 5.3. Discussion

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 6.**The space-time expression of risk during the prophase of the transportation of bauxite carrier.

Risk Grade | Very Low | Low | Medium | High | Very High |
---|---|---|---|---|---|

Risk value | [0, 1] | [1, 2] | [2, 3] | [3, 4] | [4, 5] |

E_{x} | 0 | 1.5 | 2.5 | 3.5 | 5 |

E_{n} | 1/3 | 1/6 | 1/6 | 1/6 | 1/3 |

H_{e} | 1/25 | 1/30 | 1/30 | 1/30 | 1/25 |

**Table 2.**The sampling risk value matrix during the prophase of the transportation process of the bauxite carrier.

Sampling Site | Wharf (t1) | Wharf Apron (t2) | Harbor Basin (t3) | Inner Channel (t4) | Outer Channel (t5) | Coastal Sea (t6) |
---|---|---|---|---|---|---|

No.1 | 1.6 | 1.5 | 1.5 | 2.0 | 3.0 | 4.2 |

No.2 | 3.0 | 1.0 | 2.0 | 2.0 | 2.5 | 4.0 |

No.3 | 2.8 | 2.0 | 1.3 | 2.4 | 3.2 | 4.5 |

No.4 | 3.0 | 1.6 | 1.0 | 1.8 | 2.1 | 3.8 |

No.5 | 2.7 | 2.1 | 1.5 | 2.5 | 3.5 | 4.2 |

No.6 | 1.8 | 1.5 | 1.3 | 1.6 | 2.5 | 3.5 |

No.7 | 3.1 | 1.8 | 2.1 | 2.5 | 3.0 | 4.0 |

No.8 | 2.3 | 1.9 | 1.5 | 2.0 | 3.5 | 4.2 |

Position | Wharf | Wharf Apron | Harbor Basin | Inner Channel | Outer Channel | Coastal Sea |
---|---|---|---|---|---|---|

E_{x} | 2.5375 | 1.6750 | 1.5250 | 2.1000 | 2.9125 | 4.0500 |

E_{n} | 0.5992 | 0.3447 | 0.3290 | 0.3447 | 0.1097 | 0.1097 |

H_{e} | 0.1669 | 0.0788 | 0.1592 | 0.0858 | 0.4935 | 0.1091 |

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**MDPI and ACS Style**

Wu, J.; Hu, S.; Jin, Y.; Fei, J.; Fu, S.
Performance Simulation of the Transportation Process Risk of Bauxite Carriers Based on the Markov Chain and Cloud Model. *J. Mar. Sci. Eng.* **2019**, *7*, 108.
https://doi.org/10.3390/jmse7040108

**AMA Style**

Wu J, Hu S, Jin Y, Fei J, Fu S.
Performance Simulation of the Transportation Process Risk of Bauxite Carriers Based on the Markov Chain and Cloud Model. *Journal of Marine Science and Engineering*. 2019; 7(4):108.
https://doi.org/10.3390/jmse7040108

**Chicago/Turabian Style**

Wu, Jianjun, Shenping Hu, Yongxing Jin, Jiangang Fei, and Shanshan Fu.
2019. "Performance Simulation of the Transportation Process Risk of Bauxite Carriers Based on the Markov Chain and Cloud Model" *Journal of Marine Science and Engineering* 7, no. 4: 108.
https://doi.org/10.3390/jmse7040108