# Low-Cost Assessment Method for Existing Adjacent Beam Bridges
## 1 Introduction  
Adjacent precast concrete girder bridge systems are a common form for short-to-medium-span highway bridges, with adjacent box beam bridges (ABBB) and adjacent hollow-core slab bridges (AVSB) being two prevalent types [1]. Such bridges can be described as structures composed of precast box beams or hollow-core slabs that abutting one another with keyways reserved, linked laterally by longitudinal shear keys filled with grouting, and overlaid with concrete or asphalt pavement. The design procedure of transverse connections varies from country to country. As shown in Figure 1[2], in some cases of the United States, Japan, and South Korea, end and intermediate diaphragms with transverse ties that consist of post-tensioning strands/tie-bars are installed in the box beams and hollow-core slabs to strengthen transverse stiffness and improve the load transfer mechanism [3, 4]. In China, instead of diaphragms and transverse post-tensioning, adjacent beams are connected by overlapping loop reinforcements that are extended from girders into shear keys and arranged closely along the longitudinal direction of the bridge [2]. Therefore, in order to avoid confusion and for the convenience of expression, adjacent box beam bridges (ABBB) and adjacent void slab bridges (AVSB) will be represented by adjacent rectangular hollow-beam (ARHB) bridges in this paper. The condition of transverse connections greatly affects the performance of in-service precast ARHB bridges [5]. However, a recurring issue occurring in this type of bridge is cracking in the grouted joints (shear keys and interface between shear keys and beams) between adjacent beams, which will result in reflective cracks forming in pavements and leakage of chloride-laden water, which will penetrate into shear keys and the girders, causing corrosion of the reinforcement (prestressed and non-prestressed) [4]. These will cause the loss of load transfer in the lateral direction, eventually leading individual girders to endure live loads larger than the design live loads and then fail. Timely maintenance and repair are the keys to ensuring the in-service performance of ARHB bridges and preventing collapse accidents, while the maintenance and repair arrangements are based on bridge performance assessment results. The procedure of bridge performance assessment is to gain the bridge damage information first, and then evaluate the bridge performance by corresponding measurement indicators, which can be categorized into two groups: one is index values calculated from a defined formula using input data, and the other is whether bridges meet defined criteria or not [6]. At present, the acquisition methods of bridge-damage information include routine visual inspection, static and/or dynamic load testing methods, finite-element (FE)-model-based methods, and data-driven methods. Visual inspection has become the default methodology of routine inspection [7] due to its advantages of economic, convenient operation, and no interference with traffic [8]. In addition, bridge condition assessment results based on visual inspections also serve as the basis for determining whether more advanced and detailed inspections are required. Data-driven methods, including statistical analysis or pattern recognition, machine learning, and deep learning methods, have attracted the attention of scholars and obtained some achievements [9; 10; 11], while no research results on grouted joints of adjacent beam bridges have been found. As more mature technologies than data-driven methods, static and/or dynamic load testing methods and finite-element (FE)-model-based methods can provide more accurate and objective information than visual inspection on damage detection, quantification, and localization, so it is the research field most concerned by scholars. [PERSON] et al.