## 1 Introduction
[PERSON] et al. [20] proposed a new type of active-passive integrated cutting energy-absorbing structure, which can effectively improve the deformation stroke of the energy-absorbing tube. The effect of different cutting depths and energy-absorbing tube materials on their performance is also investigated under quasi-static tests. [PERSON] et al. [21] divided the chip deformation mode in the cutting energy absorption process into three fracture modes and applied different failure models in cutting and non-cutting areas for numerical simulation. [PERSON] [22] proposes changing the tool of the cutting-type energy-absorbing structure to a metal ball to reduce its stress concentration. However, the poor cutting properties of the metal ball lead to easy damage to the support tool in the area of contact with the ball. Structural parameter optimization is the primary technical tool to improve the crashworthiness of energy-absorbing structures. As in most real-life engineering applications, crashworthiness optimization can usually be characterized by many design criteria [23]. These design objectives often conflict with each other, so multi-objective optimization methods are widely used in crashworthiness optimization [24]. Energy absorption, average impact force, and peak force are used primarily as optimization objectives of cutting-type energy-absorbing structures. [PERSON] [17] used orthogonal polynomial regression analysis and a genetic algorithm to optimize the cutting force per unit area and the energy absorption per unit volume. [PERSON] et al. [21] performed a multi-objective optimization based on the response surface method and non-dominated sorting genetic algorithm II (NSGA-II) to maximize the energy absorption and minimize the peak force of the energy-absorbing structure under quasi-static loading. [PERSON] et al. [25] compared the accuracy of the polynomial response surface method (RSM) and radial basis function (RBF) surrogate model. Then, the model with fewer errors was applied to optimize the energy absorption and minimize the peak force by the multi-objective particle swarm optimization (MOPSO) algorithm. [PERSON] et al. [26] propose a hybrid optimization approach that combines the theories of multi-objective optimization and multiple-criteria decision making with the consideration of engineering practitioners' preferences, which can be effectively employed to optimize cutting types' energy-absorbing structures. In optimization for machiningprocess conditions, many studies have set various optimization objectives to obtain optimal cutting conditions, including tool temperature, wear, breakage, roughness, etc. ([27; 28; 29]). However, most research on the existing cutting energy-absorbing structure crashworthiness pays less attention to the tool failure in the energy-absorbing cutting process. Take the subway collision speed (6.94 m/s) specified in the EN15227 standard [30] as an example. It is several times higher than the cutting speed of the normal turning process (about 1 m/s). Therefore, the cutting energy-absorption process can be considered a high-speed cutting process at a large feed, which means the effect of cutting temperature and thermal stress on tool wear and breakage becomes more significant than low-speed cutting [11]. It is essential to study the tool failure in the energy-absorption process to improve the reliability and crashworthiness of the cutting energy-absorption structure. This paper investigates the tool failure mode of the energy-absorbing cutting structure under axial impact using experimental and numerical methods, and then its reliability and crashworthiness are optimized. Axial impact tests are implemented to obtain the collision response, including force-displacement curves, chip deformation patterns, and tool failure forms. A tool-tube finite element model is developed for coupled thermal-structural analysis, and each collision response is verified by comparing it with experimental results.