<p>This study focuses on numerical simulation and deep learning techniques to investigate in detail the stress distribution characteristics of pipelines under the influence of elastic modulus, wall thickness changes, and corrosion defect characteristics (especially length and depth). The core objective is to provide accurate pipeline stress analysis and residual strength prediction tools to guide material selection, structural design, maintenance strategy formulation in pipeline engineering. It is found that the pipeline with high elastic modulus is prone to stress concentration under internal pressure load, and the increase of the pipeline elastic modulus from 500 to 900&#xa0;MPa leads to a doubling of the maximum equivalent stress, which increases the risk of failure. The pipe with low elastic modulus can better adapt to deformation and reduce stress concentration because of its good flexibility. The pipe wall thickening can significantly improve the bearing capacity. Doubling the pipe wall thickness (from 1 to 2&#xa0;cm) can reduce the maximum equivalent stress by about 33%. When the corrosion depth increases from 25 to 90% of the wall thickness, the maximum equivalent stress increases by 41%. Future studies will further explore model optimization in more complex environments to improve prediction accuracy and comprehensively guide pipeline safety evaluation and maintenance.</p>