Similitude theory provides an approach to studying collision behavior of the full-scale high-speed train prototype through scaled models. However, the thickness of thin-walled structures in high-speed train body cannot satisfy complete similitude conditions due to manufacturing restrictions, resulting in distorted similitude. The prediction accuracy of distorted models needs to be enhanced. This paper proposes a distortion compensation method to reduce thickness distortion model predicted error. First, the scaling law considering thickness distortion was deduced based on Buckingham Theory. Subsequently, the parameter sensitivity analysis was conducted to determine compensation parameters. Then, the distortion compensation method, including material density compensation (MDC) and initial impact velocity compensation (IVC), was presented. The MDC method and IVC method were developed based on mass consistency and multi-objective optimization method, respectively. Finally, two case studies were analyzed by numerical simulations to validate accuracy and effectiveness of the proposed method. Results have shown that the thickness distortion models compensated by the MDC method and IVC method can reflect dynamic characteristic of full-scale prototype with good accuracy.
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