Carbon fiber reinforced polymer (CFRP) thin-walled structures are widely used as core materials for lightweight energy-absorbing components in the aerospace and automotive industries owing to their exceptionally high specific stiffness, specific strength, and specific energy absorption (SEA). However, CFRP tubes face limitations in engineering applications, including high manufacturing costs and a tendency toward sudden brittle failure during crushing. To address these shortcomings, combining highly ductile metals with CFRP to form multi-material hybrid tubes has become an active area of research. Because traditional methods and costly physical experiments cannot readily quantify internal damage mechanisms, this study aimed to develop a high-precision finite element simulation platform. The platform overcomes technical barriers such as three-dimensional progressive damage modeling, thereby strengthening students’ ability to analyze crushing failure mechanisms and multi-material composite effects.

This study adopted a combined experimental and numerical approach. First, quasi-static axial crushing experiments were performed on CFRP square tubes prepared through a vacuum bag hot-pressing process. The tubes, consisting of five alternating layers of 0° and 90° carbon fiber prepreg, provided real force–displacement responses and macroscopic deformation modes for baseline verification. Second, the finite element simulation platform was built using the ABAQUS/Explicit solver. To accurately characterize intralaminar damage in composite materials, a VUMAT user-defined material subroutine was developed through Fortran programming to implement the updated three-dimensional Hashin progressive failure criterion. This mathematical model evaluates fiber tension/compression and matrix tension/compression damage in real time, executing stiffness degradation and element deletion once the ultimate failure thresholds are reached. In addition, cohesive elements governed by a traction–separation law and a quadratic nominal stress damage criterion were inserted between composite plies to simulate interlaminar delamination. Finally, using the verified platform, an extended study on aluminum/carbon fiber (Al/CFRP) hybrid tubes was conducted. Two distinct configurations were designed based on the stacking sequence: the C-A tube (an aluminum outer tube with a CFRP inner layer) and the A-C tube (a CFRP outer tube with an aluminum inner layer). The dynamic evolution processes and interfacial coupling mechanisms of these structures under identical axial crushing conditions were systematically analyzed and compared.

The experimental and simulation results indicated the following: 1) The platform accurately replicated the macroscopic progressive instability and microscopic brittle fracture of CFRP tubes, with the errors in core energy absorption indicators held within 5%; 2) As the lamination sequence changed, the failure modes exhibited entirely opposite composite effects; 3) The A-C configuration experienced early outward tearing, leading to premature loss of lateral constraint and rapid disappearance of the composite effect; 4) Conversely, the C-A configuration effectively suppressed the peeling and chaotic delamination of the internal CFRP layer through the strong hoop constraint provided by the external aluminum tube. Compared with the CFRP tube, the energy absorption (EA), mean crushing force (MCF), and SEA of the C-A configuration increased by 269.42%, 269.61%, and 37.47%, respectively.

The platform proves to be a highly reliable tool for analyzing the complex failure mechanisms of anisotropic materials. The study demonstrates that introducing metal into composite structures fundamentally mitigates sudden brittle failure, achieving deep interfacial synergy. Furthermore, the teaching cases developed through this platform enable students to systematically master crushing experimental methods, finite element modeling, and comparative analysis strategies within a limited timeframe. This approach overcomes the observational limitations of physical experiments and considerably deepens students’ understanding of synergistic failure mechanisms in complex engineering structures.

Aiming at the problem of the identification of whether the bicycle controller is riding or pushing in urban road traffic, it is convenient for the smart car to identify the bicycle controller’s intention to cross the street accurately and prevent possible collisions in advance due to the bicycle crossing the street too fast. Concurrently, to meet the needs of local college students for measuring bicycle riding/pushing posture at a low cost, a bicycle controller riding/pushing posture parameter measurement experiment was completed.

This study is based on bicycle controller riding/pushing physical experiments. Three representative experimental volunteers (a small-statured female, a medium-statured male, and a large-statured male) were selected according to the Chinese adult body dimensions. Three types of bicycles were selected based on appearance and their daily use (commuter, mountain, and road bikes). Reflective stickers were attached to some joints of the controller to facilitate subsequent measurements of posture parameters. This study proposes two measurement methods, manual and software-assisted. Manual measurement involves marking the position of the reflective sticker, connecting the associated marked points, and, subsequently, using a protractor to measure the required angle. Software-assisted measurement relies on the Simi Motion software. The recorded video was imported into the software to automatically read the controller’s posture angle. Seven posture parameters of the bicycle controller were obtained through the measurement methods: back angle, upper arm elevation angle, elbow bending angle, left/right thigh elevation angle, and knee bending angle.

The statistical analysis using the Mann-Whitney U test method showed that the back and thigh elevation angles are the main characteristic parameters that distinguish the riding/pushing postures. When the back angle α>12° and the thigh elevation angle θ≤60°, riding was considered. When the back angle of the controller α≤12° and the thigh elevation angle θ>60°, pushing was considered. On this basis, a method for determining the riding/pushing posture is proposed. The results of 464 real photos showed that 90.3% of the riding/pushing posture could be accurately identified using a single image, showcasing the effectiveness of the proposed method.

This study proposes two methods that can measure seven angle parameters: back angle, upper arm elevation angle, elbow bending angle, left/right thigh elevation angle, and left/right knee bending angle, thus making it easier for school students to use simple materials. It can complete the measurement of posture parameters of riding/pushing bicycles. A riding/pushing posture experiment was performed to analyze the significant differences between the angle parameters. Evidently, the back angle, upper arm elevation angle, thigh elevation angle, and knee bending angle of the riding/pushing controller were significantly different, and the back and upper arm angles were significantly different. A significant correlation exists among the elevation angle, thigh elevation angle, and knee bending angle; thus, the riding/pushing posture can be identified based on the controller’s back angle and thigh elevation angle. A posture recognition method is proposed, and the accuracy of identifying riding/pushing posture based on a picture reaches 90.3%. The posture parameter measurement method proposed in this study primarily serves scientific research and teaching and can provide a low-cost solution for measuring bicycle control and riding postures.