Stair wear simulation prediction method based on Monte Carlo simulation

The issue of stairwear in historical buildings has attracted significant attention from archaeologists. Understanding how stairs wear over time can provide valuable insights into human activity patterns and the age of structures. This paper identifies material properties, pedestrian traffic frequency, environmental conditions, and construction techniques as the main factors influencing stair degradation. Surface scanning technology and statistical methods are employed to assess the depth and distribution of wear. Regression analysis and stochastic processes are then used to estimate the historical usage of the stairs. Furthermore, our model is extended to analyze traffic patterns on the stairs. We consider bidirectional movement and assess whether certain directions are more favorable. Pressure distribution and step curvature data infer movement trends over time. Finally, our model is validated through the analysis of stairs from known historical sites. The results show that stairs with uniform wear patterns indicate consistent long-term use, while irregular patterns may suggest abandonment after heavy traffic. Additionally, the wear patterns align closely with existing historical usage records, providing confidence in the accuracy of our model.