## 6 Conclusions  
This study proposes a dynamic iterative method with segmented adjustment of incremental step sizes to improve the efficiency of parameter inversion for the CSUH model. Through theoretical analysis and experimental validation, the following key conclusions are obtained:  
1. The elastoplastic flexibility matrix of the elastoplastic constitutive model and the incremental stress-strain relationships under different boundary conditions are derived. This eliminates the need to solve equation systems when calculating theoretical model curves, thereby accelerating computation speed. 2. Based on the variation characteristics of the stress-strain curve slope, the iterative step size is distributed using an arithmetic sequence over 30% of the total axial strain range, while a uniform distribution is applied over the remaining 70%. This effectively balances computational accuracy and efficiency. The study shows that this method reduces the number of iterations from the traditional 3000 steps to just 50 steps, decreasing computation time by approximately 47 times while maintaining accuracy comparable to the fourth-order Runge-Kutta method. 3. The CSUH model accurately describes the stress-strain characteristics of different soil types (such as clay, sand, and rockfill) under various stress paths, including isotropic compression, constant \(p\) drained conditions with different intermediate principal stress ratios, CD, and CU tests. The dynamic iterative method proposed in this study significantly enhances the efficiency of parameter inversion for elasto-plastic models, creating favorable conditions for the practical engineering application of the CSUH model. However, the CSUH model exhibits limitations in characterizing stress-strain behaviors of structured soils, anisotropic formations, and environments influenced by variable water content, prolonged creep processes, or thermal variations. Specialized constitutive formulations are required for these complex scenarios, necessitating tailored parameter recalibration and iterative scheme redevelopment. In addition, it should be noted that the current validation is primarily performed on datasets used for model calibration and has not yet been extended to independent datasets or new, unseen stress paths. Although the dynamic iterative method demonstrates clear advantages in computational efficiency and accuracy in the present cases, further  
Figure 15: Comparisons between the CU test measured results of the rockfill from the Changhe dam and the CSUH predictions [23]: (**a**) Axial Strain vs. Deviatoric Stress; (**b**) Axial Strain vs. Excess Pore Pressure. comprehensive cross-validation and testing on independent datasets and more complex loading conditions are needed in future research to fully establish the generalizability and robustness of the proposed approach. Conceptualization, B.Z. and H.Y. ; methodology, B.Z. ; software, B.Z. and J.Y. ; validation, D.C., H.Y. and B.Z. ; formal analysis, B.Z. ; investigation, Z.B. ; resources, D.C.; data curation, M.O. ; writing--original draft preparation, B.Z. ; writing--review and editing, B.Z. and Z.B. ; visualization, B.Z. ; supervision, D.C.; project administration, H.Y. ; funding acquisition, D.C. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China (Grant No. U2268216); the Science and Technology Research and Development Program of China State Railway Group Co., Ltd. (Grant No. L2023G009); research projects of China Academy of Railway Sciences Corporation Limited (Grant No. 2023Y384); and the 2022 Tencent XPLORER PRIZE (Research on Prefabricated Railway Subgrade Structure and Fundamental Theory). Not applicable. All data that support the findings of this study are included within the article. We give thanks to [PERSON] for his guidance on the unified hardening constitutive model. All authors were employed by the company China Academy of Railway Sciences Corporation Limited.