# Simulation of Test Arch Based on Concrete Damage Plasticity Model and Damage Evolution Analysis
## 1 Introduction  
With the advancement of new design theories, construction technologies, and high-performance materials, reinforced concrete arch bridges have consistently achieved new span records both domestically and internationally, with their prevalence increasing [1; 2; 3]. Yet, the construction management of these large-span arch bridges presents amplified challenges [4; 5]. Coupled with environmental degradation and the deterioration of structural materials over time, there emerges a heightened risk of subsequent damage in the later phases of these arch bridges.  
[PERSON] et al. [6] employed the tensor damage theory, drawing from tests on 28-year-old RC arches, to model arch rib damage and delve into its failure mechanisms. Using on-site monitoring data from operational RC arch bridges, [PERSON] et al. [7] constructed experimental arch models mirroring actual damage scenarios. Their research highlighted the impacts of varying damage locations and magnitudes on the arch structure. [PERSON] et al. [8] compared the kinematic method with the finite element method to simulate the material loss, degradation, and longitudinal cracking in arch structures, investigating the ramifications of distinct damages on load-bearing capacities. Focusing on masonry arch bridges from the early 20 th century, [PERSON] et al. [9] identified pronounced cracks at the 1/4 span andwithin the vault, underscoring the arch's quadrants as points of vulnerability. [PERSON] et al. [10] formulated a pragmatic rehabilitation strategy for the Lipen Bridge--a concrete arch structure erected in the early 1900s. Over its extended operational life, this bridge exhibited material detachment and weakening on approximately 20-25% of its arch ring surface, averaging a depth between 10 and 30 mm. [PERSON] et al. [11] assessed geometric and design parameters, analyzing the vulnerability of arch bridges. Their findings emphasized the connection modality and sagittal span ratio as influential factors in failure probability. The damage mechanisms of RC arches, particularly those influenced by the rusting and expansion of steel bars, currently stand as prominent research subjects. In this vein, [PERSON] et al. [12] explored the influence of rusting and expansion on the load-bearing capabilities and failure patterns of RC arches post-rust-loading. [PERSON] et al. [13] chose the RC arch as their focal point, designed an RC bare arch test, and studied the damage evolution of arch ribs under rust-induced expansion.  
While the load-bearing damage mechanism of concrete arches has been elucidated [14] and advancements have been made in damage identification technology with in-depth research into the rusting and swelling of reinforcing steel, a notable gap exists. Most current studies target post-construction bridge damages, often overlooking latent damages incurred during construction. In the above studies, there are fewer cases of finite element simulation of damage to arch ribs, and there is no simulation method for damage inside the structure. During the erection of suspension arch bridges, the tower-cable-arch combined system is influenced by various elements like thermal disparities, cable tensioning, and subpar construction quality [15], leading to varying damage extents. In order to understand the force and damage mechanisms during this phase, there is a need for new approaches to damage modelling for related research.  
This study contrasts stress calculation outcomes from constructing three suspension arches with existing experimental data. Utilizing the CDP model, a simulation model of downscaled reinforced concrete arches was constructed. In this paper, a new simulation method (stochastic porosity method) is proposed to simulate local material damage in arch ribs. This method is implemented by programming a command stream in Python. The current analysis focuses on displacement trend shifts across these conditions, inferring localized damage progression and their overarching spatial distribution.