Bridge Management System Research Articles

Implementation of High-Precision Life Cycle Cost Analysis (HP-LCCA) on Indonesian Bridge Management System

Life Cycle Cost Analysis (LCCA) is a method used to determine the preservation costs required for an object, in this case, a bridge, throughout its service life. This method has been implemented in several advanced countries, including Japan. The LCCA calculation concept in Japan differs from those in other countries, as it involves a detailed segmentation of structural elements of bridges, making the model unique and highly detailed. This model is known as High-Precision Life Cycle Cost Analysis (HP-LCCA) and will be tested for application in Bridge Management Systems (BMS) in Indonesia. Implementing this model requires several adjustments, including aligning perceptions of visual inspection results and adapting the assessment concepts for each element based on research interpretations. Additionally, the difference between non-physical and physical condition assessment models presents a challenge for adopting this calculation model. The research shows a similar pattern and positive correlation between non-physical and physical assessment models. Furthermore, factors influencing LCC calculations include bridge age and the number of segments in structural elements. This research aims to provide optimal LCC calculations and facilitate their application in BMS in Indonesia.

Hyperparameter Tuning Technique to Improve the Accuracy of Bridge Damage Identification Model

In recent years, active research has been conducted using deep learning to evaluate damage to aging bridges. However, this method is inappropriate for practical use because its performance deteriorates owing to numerous classifications, and it does not use photos of actual sites. To this end, this study used image data from an actual bridge management system as training data and employed a combined learning model for each member among various instance segmentation models, including YOLO, Mask R-CNN, and BlendMask. Meanwhile, techniques such as hyperparameter tuning are widely used to improve the accuracy of deep learning, and this study aimed to improve the accuracy of the existing model through this. The hyperparameters optimized in this study are DEPTH, learning rate (LR), and iterations (ITER) of the neural network. This technique can improve the accuracy by tuning only the hyperparameters while using the existing model for bridge damage identification as it is. As a result of the experiment, when DEPTH, LR, and ITER were set to the optimal values, mAP was improved by approximately 2.9% compared to the existing model.

Technologies and Platforms for Remote and Autonomous Bridge Inspection – Review

Recent scientific and technological advancements have enabled a more efficient structural condition assessment of bridges, mainly through the implementation of intelligent inspection strategies. These intelligent strategies can provide early identification of critically damaged components before failure, and will therefore play a key role in extending the life of infrastructure. The latest inspection technologies can provide inspection plans with damage conditions, create a damage report as well as provide statistics and comparisons to the previous inspection findings. The new and existing inspection technologies are directed to help with the digitalization of the Bridge Management System (BMS). The complexity of maintenance/inspection requires organized, automated, open and transparent digital processes, which should consider both—structure and asset management data. Further, the inspection/monitoring findings serve as a source for decision-making models. The digitalized aspects of autonomous inspection provide better performance prediction models and guarantee safety for the users. This paper presents the latest findings in the field of remote inspection of bridges. In particular, the main technologies for inspection and geometrical assessment are depicted, especially those based on computer vision systems installed in UAVs and robots, LiDAR, radar, satellites and other non-contact systems including on-board monitoring. The accompanying article entitled: “Methodologies for remote bridge inspection” deals with the methodologies used for data processing based on Artificial Intelligence (AI).

Bridge Assessment Analysis using Sufficiency Rating Method (Case Study of The Mungkung Overpass)

Bridges play a crucial role in connecting various routes and water bodies, necessitating regular monitoring to prevent potential hazards and losses due to deterioration. In Indonesia employs the Bridge Management System (BMS) for decision-making regarding maintenance, repair, and replacement activities, its reliance on a limited set of criteria may lead to uncertainties in bridge condition assessmsents. This study explores the Sufficiency Rating (SR) method as an alternative for assessing bridge feasibility. By considering multiple factors, including structural adequacy, serviceability, functionality, and public interest, the SR method offers a comprehensive approach to bridge evaluation. An analysis of the Mungkung Overpass on the Ngawi Kertasono toll road was conducted to evaluate the effectiveness of the SR method. The findings classified the bridge as excellent, indicating no immediate need for treatment. However, the SR method has limitations, particularly in visually assessing damage to superstructure and substructure elements, which may introduce subjectivity. Overall, this research contributes to the ongoing development of bridge assessment methodologies in Indonesia, aiming to enhance decision-making processes and ensure the safety and longevity of bridge infrastructure. After analyzing the data obtained through the implementation of the SR method, it was revealed that S1 achieved a value of 45%, S2 achieved 23%, S3 achieved 12.7%, and S4 achieved 6%. The total actual value of the four parameters calculated based on the SR method was 74.7%, with a difference of 25.3% from the maximum value. These findings clearly illustrated that the bridge satisfied the criteria for deficiency, thereby necessitating comprehensive rehabilitation measures to be undertaken.

СТАН МОСТОВОГО ГОСПОДАРСТВА УКРАЇНИ НА ДОРОГАХ ЗАГАЛЬНОГО КОРИСТУВАННЯ ДЕРЖАВНОГО ЗНАЧЕННЯ НА ПІДКОНТРОЛЬНИХ ТЕРИТОРІЯХ ЗА 2023 РІК

Introduction. Bridges are important critical infrastructure facilities; they play a key role in economic development and ensure the security of regions and the state as a whole. During the period of martial law, bridges became an important element of the country's defense capability, as well as routes for humanitarian evacuation and export logistics. To make effective management decisions at the level of the State Agency for the Restoration and Development of Infrastructure of Ukraine in the field of bridge management, the Analytical Expert Bridge Management System (AESUM) software package is being implemented. Problem statement. In connection with the introduction of martial law in Ukraine, ensuring the proper functioning of the bridge sector has become of great social importance, since the availability of sustainable transport links allows to ensure the vital activity of the population and the functioning of the state under martial law. It is also important to improve the strategy of operation of transport facilities, taking into account the scientific and analytical apparatus of the AESUM software package. Objective. Implementation of an effective strategy for the operation of bridges on highways in order to plan financial resources for their repair and maintenance. Providing the general public with up-to-date statistical information on bridges from AESUM will be useful for scientific and practical purposes, and identifying certain analytical trends will allow to improve AESUM in terms of forming a strategy for the operation of transport facilities. Materials and methods. Analytical, statistical, system analysis. Results. The paper presents analytical and statistical information on transport facilities on public roads of national importance in the controlled territories of Ukraine as of the end of 2023. Certain trends have been identified and the technical condition of transport facilities has been focused on.

Impact of Environmental Conditions on Predicting Condition Rating of Concrete Bridge Decks

Highway agencies prioritize maintaining bridge infrastructure through bridge management systems amid budget constraints. The premature deterioration of reinforced concrete (RC) bridge decks caused by more frequent and increasingly heavy truck load spectra coupled with aggressive environmental conditions has become a critical concern. Despite the prevalence of conventional models and the emerging popularity of machine learning (ML) models in bridge deterioration predictions, they fall short in feature selection and handling of climate conditions, leading to suboptimal accuracy. To address these gaps, this study presents a data-driven framework utilizing ML-based techniques to predict the condition rating of RC bridge decks with a focus on identifying the influencing factors that affect the deck condition. The framework employs the XGBoost algorithm for model development, encompassing comprehensive datasets that include structural, geographical, and climate variables from across the U.S. Furthermore, the Shapley additive explanations approach is applied to identify the explanatory variables with the most impact. Age emerged as the most crucial factor, followed by freeze-thaw cycles and truck traffic, as indicated by the average daily truck traffic. Rainfall also plays a substantial role in deck deterioration. Based on feature importance and monotonicity, this study recommends a series of bridge classifications for transportation agencies to incorporate into their deterioration models. Overall, this research enhances understanding of the primary causes of bridge deck deterioration, enabling more informed decisions about funding allocation and bolstering bridge performance against environmental challenges.

Kajian Pemeriksaan Kondisi Jembatan di Ruas Jalan Nasional Provinsi Jambi (Studi kasus: Jembatan Rangka)

Bridge inspection is one of the most important parts in a bridge management information system. Bridge inspection is related to bridge requirements, planning for maintenance or service improvement in the future. This study discusses the framework of bridges on several bridges which are stretched on Jambi provincial roads, specifically the Sei Bridge. Bernai, Lubuk Kuari and Sei Bridge. Trap Expected more than 25 years. The examination in this study only waits for the detailed inspection of the manual issued by the public works department. This study uses the calculation method proposed in the BMS (Bridge Management System) which has been translated into SMJ (Bridge Management System) based on conditions that occur in the field. The results of the bridge situation examination obtained from this study are Sei. Trapping has a condition value of 1, Lubuk Kuari has a condition value of 2, Sei. Bernai has a condition value of 1.

Bridge management systems: an overview and comparison

Bridges are one of the key elements of the transportation infrastructure of each country, and the reliability of the entire transportation network depends on their functioning. Maintaining bridges in proper technical condition is the main task of bridge management, for which more and more countries use bridge management systems (BMS). This study is devoted to comparing different BMS, reviewing the main functions and modules and determining the perspectives of development and implementation of the latest technologies in BMS. The analysed bridge management systems were compared by functions such as storage of bridge passport data, initial information on the bridge condition, assessment of the bridge condition, forecasting of the bridge condition and consideration of different maintenance strategies. Some systems are distinguished by the fact that they can predict future bridge condition, offer optimal maintenance strategies and take into account losses not only for the operation of structures, but also for transportation. Prospects for the development of BMS were also identified: the use of neural networks, the introduction of building information modelling (BIM) and the Internet of Things (IoT).

Configuring Taiwan’s highway bridge performance indicator: a semi-quantitative risk assessment approach

The Taiwan Bridge Management System (TBMS) calculates the condition index (CI) of every highway bridge in its inventory using the latest findings from biennial routine inspections. However, the computational approach for CI can yield skewed results and make a bridge appear healthier than it actually is. To address this issue, a highway bridge performance indicator called the bridge risk index (RI) is presented. The RI is determined by combining the risks associated with the failure of each bridge component, which are evaluated using a semi-quantitative risk assessment approach. This evaluation considers the probability and consequence of a bridge component’s failure as a function of a component's deterioration state and criticality to the bridge’s overall structural safety and serviceability, respectively. To validate the effectiveness of the RI, inspection data from a sample of seven highway bridges were extracted from the TBMS and used to compare the RI with the CI. The results showed that the RI and its associated parameters can mitigate the inherent issues observed with the CI. Hence, the RI has the potential to be a valuable decision-support tool for transport agencies that rely on similar routine inspection processes to enhance their bridge management systems.

State-Based Technical Condition Assessment and Prediction of Concrete Box Girder Bridges

The technical condition of bridges has become a crucial issue for organizing the maintenance and repairs in bridge management systems. It is of great practical engineering significance to construct an effective model for predicting the technical condition degradation of the bridge through the use of the historical inspection data. Based on the semi-Markov random process, this paper proposes a useful deterioration prediction model for bridges in the highway network. From the historical inspection data of the prefabricated concrete box girder bridges, the degradation curves of technical condition rating are obtained. The effect of bridge length on degradation rate of the prefabricated concrete box girder bridges is analyzed. According to the Weibull distribution parameters of different condition grades, the technical state degradation models for a bridge group and an individual bridge are proposed to predict the performance of the overall bridge and superstructure of the bridge. The results show that with the increase in bridge length, the degradation rate of bridge technical condition increases. The degradation rate of the technical condition of the superstructure is faster than that of the overall bridge. The proposed semi-Markov stochastic degradation model for the bridge group can not only predict the different condition ratings of the bridges at any time, but also predict the future deterioration trend of an individual bridge under any ratings.

Analisa Penilaian Kondisi Jembatan Sarolangun Batang Tembesi Dengan Metode Bridge Manajemen System (BMS)

Bridges are an important part of a road network system because they have a significant impact if the bridge collapses or if it does not function properly. A bridge is a structure that crosses a river or other traffic barrier, so the collapse of the bridge will reduce or hold back traffic, which as a result will disrupt the comfort of the public in traffic and disrupt economic relations. A bridge is a structure that crosses a river or other traffic barrier, which as a result disrupts people's comfort in traffic and disrupts economic relations (Bridge Inspection Guidelines 2012). Bridges are built so that pedestrians, vehicle or train drivers can cross these obstacles. However, it turns out that there are many types of bridges which of course vary both in terms of structure, strength and even construction costs. The main components of a bridge are the unity of the road embankment structure approaching the bridge, the sub-bridge structure and the bridge super-structure (BMS, 1993). The main objective of this research is to analyze the condition of the Sarolangun Batang Tembesi Bridge by observing it visually, assessing the technical condition of the bridge, and determining the priority order for bridge maintenance based on its condition value. However, the database results produced in this bridge management system are only limited to screening and ranking results in preparing bridge management programs (Directorate General of Highways, Bridge Management Systems, (1993), "IBMS General Procedure Guide", BMS, Department of Public Works of the Republic of Indonesia.

Digital Twin and Asset Management for Italian highways decision support towards scheduled maintenance, repair and rehab

This paper describes Sina’s current inventory and inspection system (SIOS) development with BIM (Building Information Modelling) applications and BMS (Bridge Management System) strategies towards an Asset Management system implementation. Procedures and data flows using Sina databases SIOS (Sistema Ispettivo Opere Sina inventory and inspection data, seismic vulnerability analysis database, etc.) as inputs supporting BIM modelling are described. Starting from a first project, which is currently being applied to an entire highway agency and which also envisages a later integration of tunnels, a BIM modelling procedure was developed to reach information models for an “inspection” “BIM USE”. Such information models, populated with the information necessary for bridge management system processing, have been connected to Business Intelligence tools to create dashboards supporting decision-making criteria based on management and maintenance approaches (Bridge and Asset Management System). In addition, for Asset Management development, the approach of decision-making tools, integrated with a multi-level approach of Italian Guidelines For The Classification And Management Of Risk, The Assessment Of Safety And The Monitoring Of Existing Bridges, can convey information flows to support criteria planning to choose routine and extraordinary maintenance and restoring interventions. The project illustrated in this paper shows how integrating technologies, methodologies, experience and knowledge must be supported by consistent information management towards companies’ digital transformation and asset management development as a decision-making tool based on enabling technologies.

Management of road bridge networks in Italy by means of integrated SHM systems

Management of stocks with large number of bridges is a relevant issue for the Italian roadway system. In the last years the use of integrated SHM (Structural Health Monitoring) systems is being introduced within the framework of the modern BMS (Bridge Management Systems) with the aim of implementing a continuous damage identification strategy. In this framework, ambient vibration-based SHM has received most attention owing to its minimal intrusiveness, non-destructive character and global damage identification capabilities. A lot of research effort has been devoted in the last years to SHM techniques but ease of use, interpretability and minimal intervention of expert judgement are essential issues for the fruitful application of SHM in real and wide bridge networks. ANAS S.p.A., the main road managing Authority in Italy, is implementing a huge monitoring program on its bridge network with the main purpose of addressing the recent indications of the Italian guidelines for assessing and monitoring of bridges, and the University of Padova, together with the University of Perugia, Politecnico of Milan, University of Pisa and the other Universities of FABRE Consortium are supporting ANAS for the real application of modern SHM techniques. According to these actual needs, a new software suite called P3P has been developed and is being applied to a huge stock of bridges distributed in all the Italian territory.

A methodology for the preliminary seismic assessment of road bridges within the italian guidelines on the assessment and management of risk conditions of bridges

Following the tragic collapse of the Polcevera Bridge in Genova (Italy), the Italian Ministry of Sustainable Infrastructure and Mobility issued the guidelines for “risk classification and management, safety assessment and monitoring of existing bridges”. This guideline proposes a multi-level procedure with an increasing level of information to be collected in each step. In this context, the MLAZIO project was born with the aim to create a methodology for the construction of an efficient Bridge Management System (BMS) for Lazio Region that takes in account all the levels prescribed in the Italian guidelines. Satellite monitoring, BIM, GIS and methods for risk assessment, both static and seismic, are some of the innovative techniques included in the methodology, validated through the application to several case studies. This paper describes the general structure of MLAZIO project and its state of progress, such as the creation of a relational database (used for cataloging structures and developing optimized GIS and BIM environments), with a special focus on the development of an expeditious procedure for the quantitative evaluation of the static and seismic risk of bridges. In this regard, a specific application has been developed that allows to automatically assess the static and seismic risk index of a bridge starting from the limited information included in the database.

Bridge Data: a cloud-based platform for the assessment of the Class of Attention of existing bridges

The Italian Guidelines for the classification of existing bridges introduced a procedure based on a multi-Level approach. The first three Levels (from 0 to 2) allow identifying a Class of Attention for the infrastructure and require the acquisition and elaboration of a considerable amount of data based on surveys and visual inspections. To facilitate the data entry, a cloud-based software for the automatic management of inspections of existing bridges was implemented. The developed multi-platform management system, named Bridge Data, allows an easy real time access with any device (PC, tablet, phone) to the database via a user-friendly web app interface, allowing the concurrent consultation, data entry and generation of statistics, also considering different privileges for the users. Every bridge is surveyed considering basic data (e.g. coordinates, constructive typology), but also classifying the sub-elements of the super- and sub-structures (piers, abutments, longitudinal beams, slabs and so on), and organizing the documents in categories. A crucial aspect of the inspections lays on the identification of defects in each element of the bridge and requires an appropriate number of pictures (both general of the element and specific for each defect) and the need to fill out convenient forms, then further automatically elaborated to obtain comprehensive structural and seismic Levels of Defectiveness. Geometric, structural, geological, hydraulic, transportation data are also collected in the database, and finally processed to provide an automatic estimation of the Class of Attention consistent with the prescribed rules and logical flows. Bridge Data is not only the core for developing a complete Bridge Management System (BMS) but is also an organized database of pictures and documents. For every bridge it is also possible to generate a photographic survey and defectiveness forms as well as a detailed report describing the logical flow for the determination of the Class of Attention.

Guidelines for the classification and management of risk, for the evaluation of safety and for the monitoring of existing bridges: differential analysis of experimental software applications for level 0,1,2 assessments

This paper investigates the application of the procedure described by the Italian Guideline for existing bridges and its related Operating Instructions for an existing bridge through three different IT (Information Technology) applications in order to evaluate its compliance with the regulation, and its effectiveness and efficiency, also in perspective of product certification. The work initially describes the result obtained applying manually the Guidelines with the aid of a non-commercial software developed at Sapienza for the definition of the level of defectiveness. Thus, the same procedure is repeated using two open - source commercial software, Inspicio and InBee which allow to operate within a Bridge Management System framework. Finally, a differential analysis among the three analyses is performed, highlighting the differences and the main characteristics of the software for the definition of the level of defectiveness, which is crucial for determining the attention class and to properly schedule the maintenance operations. Pros and cons of each individual software are detailed, followed by some suggestions for their potential improvement.

Fatigue vulnerability assessment of a steel arch bridge using the probabilistic weibull model and considering its remaining service life under localized corrosion effects

This study attempts to obtain the approximate fatigue vulnerability of a steel arch bridge from the Colombian national road network. It establishes the interaction between the demand and the available capacity through the Weibull probability equation, and an AASHTO remaining-time equation indicated in (FHWA, 2015). However, the available capacity in terms of the S-N curve obtained from available international references was modified to account for the effects of corrosion present in elements and/or joints in the bridge. The load demand was modeled as the controlled action of the fatigue truck reported in AASHTO, which was systematically located on a structural model represented by Shell and Frame type finite elements, which represented the information available in drawings (in the current Colombian bridge management system), and the one obtained from structural survey activities. The structural model was further calibrated by a parametric study on the modulus of elasticity of steel, which included the minimization of the error difference in the vertical deflections of a bridge load test, keeping the magnitude within the expected ranges established in a protocol. Such reports of actual deflections were achieved using distance meters at important points of the bridge. This model allowed for estimating the magnitude of stresses in the structural elements of the bridge, especially in an area of interest for the study where chemical and physical elements of structural deficiency were determined. The results show an inverse relationship between the probability of failure and remaining service life. The effect of corrosion on the remaining capacity and the probability of failure of the structural elements is clear.

Analysis of the information flux model among all the actors involved in the use of a Bridge Management System according to Italian Guidelines: the BMS as a collaborative workplace

Bridges are critical elements in an infrastructural system for the resilience of the transportation network. It is important to guarantee proper maintenance of these structures since they are strategic for the economic and social welfare and support access to emergency services.The adoption of Italian Guidelines for the classification, risk management, safety and monitoring of existing bridges primarily introduces common instructions in periodic bridge inspections. At the same time, they suggest the use of digital instruments to collect data derived by the application of the guidelines.Bridge Management Systems (BMS) can absolve to this requirement and represent an additional value compared to a mere digital archive. From one hand, they are a tool for bridge owners to manage information to guarantee a proper maintenance while complying with budget and founding limitations defined by the Ministry. On the other hand, technicians can exploit them for data collection during bridge inspections and in-depth structural assessment.Thus, the creation of a collaborative workplace is one of the main requirements in the construction of a valid BMS. However, the information fluxes among the subjects can be complex inside a BMS from a management point of view. For instance, BMS must be a place where technicians can insert and receive information accordingly to their task and expertise. For this reason, it is important to ensure the possibility to differentiate data access levels and associate data property and responsibility.After briefly discussing the roles of each actor - technicians, bridge owners, Ministry - involved in the use of a BMS, this paper describes the interaction among all these figures and provides the flux model that has been implemented in INBEE, a new BMS that applies the latest version of the Italian Guidelines.

A GEO-DATABASE FOR 3D-AIDED MULTI-EPOCH DOCUMENTATION OF BRIDGE INSPECTIONS

Abstract. The recent collapse of bridges in Italy has prompted numerous studies on monitoring and maintenance. Many structures in Italy have been in service for over 50 years, necessitating new approaches to ensure their safety. To address this issue, Italy's Consiglio Superiore dei Lavori Pubblici (Superior Council of Public Works) has developed the Guidelines for Risk Classification and Management, proposing a multi-level approach to bridge management within a complex geomorphological environment. The guidelines outline a multi-level process that includes surveying the structures, conducting detailed inspections, and assigning risk classes based on hazard, exposure, and vulnerability. Current inspection processes are time-consuming and costly. Therefore, alternative monitoring technologies are crucial. Unmanned aerial vehicles equipped with cameras, laser technologies, and GPS systems offer flexible and cost-effective solutions for visual inspection. These technologies enable the collection of both quantitative and qualitative data, such as size, material properties, and overall condition. In this context, efficient data management and exploration systems are necessary to handle the vast amount of geo-referenced information. Multi-epoch databases play a crucial role in documenting the conditions of bridges and supporting a maintenance and structural health monitoring workflow. These databases can be utilized within a Bridge Management System to aid road managers in decision-making processes. Additionally, 3D exploration platforms provide visual analysis and highlight areas of interest within the structure. This work presents a multi-epoch geo-database that adheres to the Italian guidelines, offering optimized data management and queryability for 2D and 3D information. The entire process is designed using open-source and reproducible solutions.

A new bridge management system based on spatial database and open source GIS

A new bridge management system based on spatial database and open source GIS