# Performance Evaluation of a Long-Span Cable-Slayed Bridge Using Non-Destructive Field Loading Tests
## 1 Introduction  
With the rapid development of China's national economy, the demand for transportation infrastructure is increasing [1, 2]. As an important part of transportation networks, the reliability of bridge structures is of great significance to people's personal safety, as well as to the national economy [3, 4, 5]. Mechanical properties are complicated for bridge structures with large spans or complex structural systems throughout their whole life cycle [6]. In order to evaluate the performance of complex bridge structures, mechanical behavior and fundamental characteristics need to be studied. During recent decades, the concept of structural health monitoring (SHM) has been introduced into bridge engineering [7, 8]. The rapid development of modern technologies--such as communication networks, signal processing, and artificial intelligence--has accelerated the advancement of bridge structural health monitoring [9, 10]. Research has been devoted to structural response assessment, load effects monitoring, and reliability evaluation basedon the collected SHM information [11; 12]. [PERSON] et al. [13] proposed a method for assessing the in-service condition of bridge decks based on monitored strain data, and a wavelet decomposition method was applied to extract live load effects from the original SHM data. [PERSON] et al. [14] took a suspension bridge in Hong Kong as an example, and illustrated how SHM systems are used to investigate various load effects, as well as in structural damage evaluation. [PERSON] et al. [15] established a comprehensive data-based monitoring framework to measure, reproduce, and evaluate the structural behavior during and after a failure event, and illustrated the applicability of the proposed framework using a cable-stayed bridge case study. [PERSON] et al. [16] used SHM data to evaluate the main components' reliability and system reliability of a long-span bridge, and incorporated temperature-induced responses into the analysis. The development of SHM technology has evolved from monitoring-based evaluation to monitoring-based prediction. [PERSON] et al. [17] proposed a model for predicting structural extreme stress and reliability indices using SHM data, and verified the effectiveness and feasibility of the proposed model through monitored extreme stress data. [PERSON] et al. [18] proposed a comprehensive framework for performance assessment of suspension bridges based on the analytical hierarchy process, and the analytic hierarchy model was constructed by integrating SHM data. [PERSON] et al. [19] proposed a probabilistic prediction method of structural stress responses based on a Bayesian modeling approach with the help of SHM data. [PERSON] et al. [20] summarized the recent advancements in non-destructive testing techniques--namely, sweep frequency approach, ground-penetrating radar, infrared techniques, fiber-optic sensors, camera-based methods, laser scanner techniques, acoustic emission, and ultrasonic techniques--by applying artificial intelligence. Although the SHM data on these mechanical parameters can update the prediction results of structural safety status, there are still uncertainties arising from errors in modelling and measuring [21]. Meanwhile, large-scale application of SHM in engineering structures would bring significant investments [22]. Considering the disadvantages of SHM systems, and the fact that not all bridges are equipped with them, field load testing is still an effective way to investigate the structural behavior of structurally complex bridges, and their performance can be evaluated with the aid of finite element models [23]. [PERSON] et al. [24] used static field loading tests to investigate the static behavior of a long-span cable-stayed bridge in Taiwan; the results showed that the bridge had linear characteristics, and the analytical results were in good agreement with the test results. [PERSON] et al. [25] discussed experimental and numerical studies on deformation-induced surface roughening in a commercial-purity aluminum alloy. [PERSON] et al.