A MATLAB GUI‐Based Calculation Platform for Soil Arching Effect to Assist Teaching and Learning in Soil Mechanics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT The soil arching effect is a key concept in soil mechanics education. It is widely recognized as an important principle in geotechnical engineering, characterized by stress redistribution due to relative soil displacement, which impacts the safety and stability of geotechnical structures. Despite advances in classical theories and numerical methods, the complexity of models and formulas still presents significant challenges for students and engineers in understanding and application. To address this challenge, this study introduces a practical and educational solution by developing a computer‐aided calculation platform for the soil arching effect, designed by Hunan Provincial Engineering Research Center of Advanced Technology and Intelligent Equipment for Underground Space Development in Hunan University, aimed at enhancing soil mechanics education through an intuitive MATLAB graphical user interface. The primary contribution of this study is the development of a platform that integrates seven theoretical models, enabling users to calculate key parameters, such as the soil arching ratio, by inputting soil properties and unloading width. The platform features real‐time data visualization and interactivity, allowing users to easily select models, input parameters, and obtain results quickly, thereby facilitating comparative analysis across different theoretical frameworks. Compared to conventional teaching methods, the platform simplifies complex calculations and deepens students’ understanding of the soil arching effect. Results from student surveys indicate a remarkable improvement in comprehension and analytical skills, with high satisfaction regarding the platform's usability and educational value.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it