Yong Dan

The coal gasifier is the core unit of the coal gasification system. Due to its exposure to high temperatures, high pressures, and aggressive media, it is highly susceptible to serious accidents in the event of failure. Therefore, it is important for the gasifier to perform failure-risk assessment to understand its safety status and provide safety measures. Bayesian networks (BNs) for risk analysis of process systems has received a lot of attention due to its powerful inference capability and its ability to reflect complex relationships between risk factors. However, the acquisition of basic probability data in a Bayesian network is always a great challenge. In this study, an improved Bayesian network integrated with a trapezoidal intuitionistic fuzzy number-based similarity aggregation method (TpIFN-SAM) is proposed for the failure-risk assessment of process systems. This approach used the TpIFN-SAM to collect and aggregate experts’ opinions for obtaining the prior probabilities of the root events in the BN. In the TpIFN-SAM, the intuitionistic fuzzy analytic-hierarchy-process method (IF-AHP) was adopted to assign the expert weights for reducing subjectivity or the bias caused by individual differences. To clarify the suitability of the proposed method, a case study of a coal gasifier was demonstrated, and both prediction and diagnosis analyses of the BN were performed; finally, the weak links of the gasifier were identified.

The corrosion behavior of X80 steel in a near-neutral soil-simulated solution under various DC stray currents and applied strains was investigated using electrochemical measurements (open circuit potential, linear polarization, and electrochemical impedance spectroscopy) and surface analysis techniques. Our results show that a DC stray current has a substantially greater effect on steel corrosion compared to applied strain. However, strain could slow down the corrosion rate in specific conditions by affecting the composition of corrosion products and the structure of the corrosion scale on the surface of the steel. Although the porosity of the corrosion scale of steel without an applied strain will increase with increasing DC currents, once strain is applied, the corrosion scale will become denser. Furthermore, both DC currents and strain can promote steel pitting, and the number and size of pitting holes will increase significantly with an increase in current densities.

An investigation into the electrochemical corrosion behavior of X80 pipeline steel under different elastic and plastic tensile stress in a CO₂-saturated NaCl solution has been carried out by using open-circuit potential, potentiodynamic polarization, electrochemical impedance spectroscopy, and surface analysis techniques. The results show that the corrosion rate of X80 steel first increases and then slightly decreases with the increase of elastic tensile stress, whereas the corrosion rate sharply increases with the increase of plastic tensile stress. Both elastic and plastic tensile stress can enhance steel corrosion by improving the electrochemical activity of both anodic and cathodic reactions. Moreover, compared with elastic tensile stress, plastic tensile stress has a more significant effect. Furthermore, electrochemical reactions for CO₂ corrosion and mechanoelectrochemical effect are used to reasonably explain the corrosion behavior of stressed X80 steel in CO₂ environment.