# An Integral Fuzzy Model to Evaluate Slab and Beam Bridges with a Preventive Approach
## 1 Introduction  
Maintaining an adequate road infrastructure is essential to promote the country's socioeconomic development [1]. Road infrastructure encompasses several fundamental elements, including pavement, structures (e.g., bridges, tunnels, drainage systems, and slopes), and devices (e.g., signage, lighting, and toll booths), among others [2]. Bridges stand out as essential assets, as their primary purpose is to connect inaccessible points within the road network. These assets are vulnerable elements in roadways, and they represent the mostsignificant individual investment in the entire transportation system [1]. Therefore, it is necessary to assess their condition based on their functional and operational state, as well as their level of safety. However, in the case of highway bridges in Mexico, their evaluation is limited due to their complexity. International governments use inspection manuals to assess the condition of bridge elements manually, both primary (structural) and secondary (functional), assigning maintenance tasks that restore their functionality. For instance, the American Association of State Highway and Transportation Officials (AASHTO) manual [3], the Ontario Structural Inspection Manual [4], the Peruvian Bridge Inspection Guide [5], and the Manual for the Visual Evaluation of Highway Structures [6]. However, despite the existence of manuals that provide criteria for inspection and assessment, one of the main problems is that the processes used to determine a bridge's condition are not transparent. This means that the connections between different types of deterioration and the affected elements are not explicitly identified, which limits the understanding of the bridge's actual condition. As a result, even when information about the overall condition of a bridge is available, selecting appropriate maintenance actions to restore the functionality of all its components remains a challenge. Furthermore, although conservation measures may be implemented for explicitly evaluated elements, those that have not been considered continue to deteriorate, increasing long-term maintenance costs. Several methods have been proposed to encourage the evaluation of bridges based on traditional and emerging technologies. For instance, [PERSON] et al. in [7] employed a numerical model based on finite elements (FEs), enabling the simulation of a bridge's behavior under various loading and deterioration conditions. [PERSON] et al. in [8] used a mathematical formulation called the sectional constitutive relationship to calculate the ultimate bearing capacity of reinforced concrete arch bridges in operation. Alternatively, the use of artificial intelligence methods, which has become increasingly important, facilitates the management of uncertainty in asset evaluation processes, as seen in [9; 10]. An area of artificial intelligence that has been studied for the assessment of bridge elements is soft computing with a fuzzy logic approach, such as described in [11; 12; 13; 14; 15]. However, a significant limitation remains open; there is a lack of integral catalogs of recommendations for periodic, preventive, and corrective maintenance that cover all possible deterioration scenarios. In response to these challenges, this study presents an integrated fuzzy logic-based model to evaluate the progression of deterioration in slab-and-girder bridge components, incorporating a preventive approach. Additionally, a hierarchical taxonomy is proposed to determine the level of granularity at which bridge evaluation will be performed. Finally, a catalog of maintenance treatments is proposed for all primary and secondary bridge elements. The contributions of the article are summarized below:  
* A hierarchical taxonomy that defines granularity levels for bridge condition evaluation, enabling a diagnosis of the structure's state based on an analysis of individual element properties.