## 1 Introduction  
Reinforced concrete (RC) structures are essential structures in today's society. Most strategic RC infrastructures around the world (e.g., bridges, nuclear, or hydroelectric powerhouses) were built before the 1950s and are now reaching the end of their lifespan. It is estimated that the repair and rebuilding costs of concrete infrastructures, just in the United States, will be in the trillions of dollars, which will be paid by future generations [1]. As cement serves as the primary binding agent in concrete construction and contributes significantly to carbon dioxide emissions during the manufacturing process, concrete is recognized as a major contributor to the overall carbon footprint. The environmental costs of rebuilding will consequently have serious repercussions for the planet. Therefore, it is more profitable to extend the lifespan of existing critical RC structures using _innovative and robust assessment tools_, as well as targeted repair technologies. Although the designs of old RC structures were based on rather simplified models (e.g., 2D models versus 3D, no or limited redistribution of stresses, etc.) and conservative design approaches (e.g., the sectional design method), at present, more sophisticated numerical tools, such as advanced nonlinear finite element analysis, or ANFEA, are increasingly used. ANFEA, using constitutive concrete models, is a state-of-the-art analytic tool in the field of the numerical simulation of concrete structures [2]. It is based on a 3D discretization of structures using 3D elements, and it uses a smeared crack or discrete crack (e.g., XFEM) approach to represent the cracking process that takes place using initiation and propagation criteria. ANFEA is suitable for designing complex concrete structures [3], assessing reinforced and non-reinforced concrete structures with initial damage conditions, or structures that are subjected to extreme loads (e.g., [4; 5; 6; 7]). This work focuses on the assessment of the specific case of _large reinforced concrete structures_ which are known to have complex structural behavior. An example of such a structure is illustrated in Figure 1, which showcases a typical powerhouse unit in a hydroelectric facility that will be considered in the application section of this study. These constructions, employing mass concrete with large aggregates (more than 40 mm in diameter), are commonly utilized in hydroelectric facilities to address stability concerns, necessitating larger concrete volumes. Compared with conventional concrete structures such as buildings and bridges, they exhibit more complex behavior due to factors such as early age thermal effects, the complexity of the geometry influenced by the waterway (3D complex geometry), and size effects with light reinforcement usage. Notably, these structures fall outside the scope of standard concrete design codes. In the authors' experience, the application of ANFEA to assess large reinforced concrete structures may present limitations. This is mainly due to the substantial influence of concrete's tensile behavior (both peak and post-peak) on structural response, compounded by challenges in characterizing this behavior for existing facilities. Additionally, ANFEA is known for its high sensitivity to various input parameters, typically demanded by the concrete constitutive model. Even if the computational framework of ANFEA has undergone a rigorous verification and validation (V&V) process that is suitable for the target assessed structure [3; 8], it is still dependent on the quality of at least _measurable_ concrete/reinforcement parameters that can be assessed from existing structures (e.g., using characterization tests on extracted cores).