## 6 Conclusions  
This study employs triaxial photogrammetry to assess undisturbed soft soil and utilizes finite element software for numerical simulations. It compares and analyzes the results from conventional triaxial testing, finite element analysis, and photogrammetry. The results of this study lead to the following conclusions:  
1. The MCC (modified Cam-Clay) parameters of undisturbed soft soil were obtained through the test as the critical state slope equal to 0.5810, the consolidation slope equal to 0.150, and the rebound slope equal to 0.022.
2. In the case of low confining pressure, i.e.,\(\sigma_{3}\) less than or equal to 100 kPa, numerical simulation is used to directly obtain a more accurate shear strength index by combining the soil conventional parameters; when \(\sigma_{3}\) greater than 100 kPa, a more accurate shear strength index can be obtained by using triaxial photogrammetry.
3. The shear strength index obtained by triaxial photogrammetry was closest to the true value and superior to numerical simulation, with conventional triaxial tests being the relatively weakest.
4. ABAQUS simulation can substitute traditional tests to acquire stress-strain curves. It achieves an average absolute error of only 0.45 kPa and a relative error of merely 0.21%. Moreover, it can accurately predict the pore water pressure curve and the peak value of deviator stress. These results indicate that the modified Cam-Clay model within the ABAQUS finite element program is reliable.
* Future research should focus on the following two areas: **BP neural network method**: The BP neural network can validate and supplement numerical simulation results. It is trained with experimental data from triaxial tests and photogrammetry, learning patterns, and relationships in the data. The network is then used to check the reliability of the numerical simulation results. Applying the BP neural network can improve deformation measurement accuracy in photogrammetry. The BP neural network can build more complex and accurate soil models in numerical simulations. **More laboratory tests:** Conducting more laboratory tests is necessary to determine the reasons for the deviations, especially for radial deformation. It will consider factors such as the material properties of the soil samples, the experimental setup (including the influence of the confining pressure system and the camera's position in the photogrammetry), and the assumptions in the numerical simulation model.  
Y.Z.: writing and revision, and data analysis; J.L.: methodology and conceptualization; C.M.: writing--original draft, formal analysis, and result interpretation; Z.Q.: data collection and experiment execution; M.F.: data curation, data analysis, and result interpretation; C.L.: computational simulation studies. All authors have read and agreed to the published version of the manuscript.  
This paper is supported by Guangxi Science and Technology Program (Project No. AD25069101); Hubei Provincial Department of Housing and Construction (202341); Research Program of Hubei Polytechnic University (Grant Nos. 23 xiz01A, KY2024-139); the General Projects of Hubei Provincial Natural Science Foundation (Grant Nos. 2025 AFB935); Hubei Talent Project of Chutian Scholars, Hubei Key Talent Plan \"Hundred People Plan\".  
Not applicable.  
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. All data, models, and code generated or used during the study appear in the submitted article.  
The authors declare no conflicts of interest.