The analysis of the basic characteristics of various research methods is highly needed to predict the residual life of the pipeline accurately, help managers understand the operational risks, and provide a reference for developing pipeline transportation and maintenance inspection plans and anti-corrosion measures. Based on a comprehensive investigation of the existing research on the residual life of the pipeline, this paper finds that the current mainstream life prediction method, based on historical statistical data, has the shortcomings of inconsistent modeling methods, inconsistent basic data, and a lack of comparative evaluation among methods. Moreover, considering the in-depth study of BP neural network modeling, grey theory modeling, time series modeling, and exponential smoothing modeling, optimal prediction models using different methods based on the same historical data are established. These optimal modeling methods are discussed, and the feasible modeling path for the accurate prediction of the pipeline’s residual life is given by comparing the prediction accuracy of each model. In addition, the findings serve as a guide for developing an anti-corrosion strategy by highlighting the contribution of the prediction results of the residual life to pipeline decision-making. By comparison, it is found that the accuracy of the four prediction models is as follows: the grey theory prediction model, the exponential smoothing prediction model, the BP neural network prediction model, and the time series prediction model, from high to low, respectively.

In recent years, the storage of lithium-ion battery (LIB) containers in general cargo container yards has become an urgent operational requirement for port container terminals. To effectively control the impact range of thermal runaway (TR) incidents in LIB containers and reduce potential economic losses, it is imperative to establish appropriate isolation protocols. This study develops a mathematical–physical model of heat transfer following LIB container TR, incorporating (1) the national regulation limiting stacking height to three layers, (2) the exothermic characteristics of LIB TR, and (3) the fundamental heat transfer theory. Through detailed numerical simulations based on actual engineering scenarios, our analysis demonstrates that when (1) The TR temperature of conventional LIBs remains below 700 °C, (2) the thermal conductivity of goods in adjacent ordinary cargo containers does not exceed 10 W/(m·K). An effective isolation configuration can be achieved by (1) arranging no fewer than four ordinary cargo containers longitudinally and (2) placing no fewer than two ordinary cargo containers transversally. The methodology and conclusions presented in this study provide practical guidance for industrial applications and demonstrate significant engineering value.