Researchers in the field of structural engineering have identified 4 main components for the implementation of a functional BMS: • Data inventory. • Cost and construction management. • Structural analysis and assessment. • Maintenance planning.
Data inventory Data and information referring to each life cycle step of bridges need to be collected and archived through a flexible approach, making possible to efficiently update and access them. In commonly used BMS, such goal is achieved adopting
database solutions that allows the documentation of data in different formats such as texts, images, three-dimensional models and more. While the collection of historical documentation and project design of the structure is represented by analogical and digital archives managed by road asset managers, the geometric data input implies the application of
topographic techniques through dedicated surveys on the field. In particular, bridge inspections for the 3D reconstruction of a
digital twin of the structure usually consists of survey campaigns using
global navigation satellite system measurements, ground and drone-based
photogrammetry and
laser scanning. Data management in this phase implies the use of geographic information systems,
BIM and
computer-aided design software, manipulating both 2D and 3D geo-referenced data. Resulting products include
point clouds and meshes that serves as the basis for building information modeling processes. Bridge surveys can be repeated in different steps of the structure life cycle and their frequency depends on decision making and prioritization of maintenance operation and national guidelines.
Cost and construction management An accurate implementation of a virtual digital twin or a BIM model of a structure is considered the starting point for budget management and optimization since the early stage studies on BMS. For example, it provides the opportunity to calculate the total cost materials and specialized operator needed in the construction step, quantifying in advance the expenses and consequently adopting better economic strategies. Moreover, a multi-temporal management of information referenced to specific portions of the bridge enables the possibility to define efficient time tables for material delivery planning, project progress monitoring and documentation, construction schedule improvement and workers and experts coordination. In recent BMS applications,
sustainability also plays a crucial role in the definition of procedures for cost optimization adopting dedicated approaches such as
Life Cycle Assessment, calculation of
carbon-footprint and energy consumption along the different phase of the bridge life cycle.
Structural analysis and assessment Visual inspection often result in large amounts of data stored in the BMS inventory that serve as input for image-based processes for defect and damage detection. While traditional method for simply relied on human evaluation,
Computer Vision techniques taking advantage of
Artificial Intelligence and
Machine Learning semi-automatize the extraction of meaningful information from pictures taken during inspections. For example, recent applications of semantic segmentation allows the identification of elements affected by corrosion or other degradation phenomena, enabling experts to assign a grade of severity for the damage. All the results coming from analysis, simulations and severity level classifications serve as input for the execution of the intervention prioritization, the core part of the maintenance planning component in a BMS framework.
Prioritization of intervention on single elements or on the whole structure is determined through a multi-criteria approach that consider the risk of defect or collapse. In particular, the process usually implies the computation of indexes for quantifying
hazard,
vulnerability and value exposure and derives from them a warning class. Warning classes then serve as parameters for prioritizing the allocation of funds and operators for further detailed and more frequent monitoring approaches for structures at risk. As a result, bridges whose structural integrity and
serviceability are more affected are classified in higher warning classes, requiring targeted interventions. This operation is essential to determine if special inspections with expert operators and specific tests (e.g.
load tests) are required and if any new or additional sensors (e.g.
extensometer,
accelerometer) for continuous monitoring need to be installed on the structures for targeted monitoring. == National guidelines ==