Menyunting Bridge Management System

[[File:Drone view of a bridge during an inspection.jpg|thumb|[[Unmanned aerial vehicle|Drone]] view of a bridge during a visual inspection for structural health assessment.]]
A '''bridge management system''' ('''BMS''') is a set of methodologies and procedures for managing information about [[bridge]]s. Such system is capable of document and process data along the entire life cycle of the structure steps: project [[design]], [[construction]], monitoring, [[maintenance]] and end of operation.<ref name=":0" /><ref name=":4">{{Cite journal |last1=Hawk |first1=Hugh |last2=Small |first2=Edgar P. |date=1998 |title=The BRIDGIT Bridge Management System |url=https://www.tandfonline.com/doi/full/10.2749/101686698780488712 |journal=Structural Engineering International |language=en |volume=8 |issue=4 |pages=309–314 |doi=10.2749/101686698780488712 |issn=1016-8664}}</ref>

First used in literature in 1987, the acronym BMS is commonly used in [[structural engineering]] to refer to a single or a combination of digital tools and software that support the documentation of every practice related to the single structure.<ref>{{Cite journal |last1=Hudson |first1=S. W. |last2=Carmichael III |first2=R. F. |last3=Moser |first3=L. O. |last4=Hudson |first4=W. R. |last5=Wilkes |first5=W. J. |date=1987 |title=BRIDGE MANAGEMENT SYSTEMS |url=https://trid.trb.org/view/278332 |journal=NCHRP Report |issue=300 |issn=0077-5614}}</ref> Such [[software architecture]] has to meet the needs of road asset managers interested on tracking the serviceability status of bridges through a workflow mainly based on 4 components: data inventory, cost and construction management, structural analysis and assessment and maintenance planning.<ref name=":0" /> The implementation of BMS usually is built on top of [[Relational database|relational databases]], [[Geographic information system|geographic information systems]] (GIS) and [[building information modeling]] platform (BIM) also named ''bridge information modeling'' (BrIM)<ref name=":3" /> with photogrammetric and laser scanning processing software used for the management of data collected during targeted inspections. The output of the whole procedure, as stated also in some national guidelines of different countries, usually consists of a prioritization of intervention on bridges classified in different risk level according to information collected and processed.<ref name=":2" /><ref name=":3" />

== History ==
Since the late 1980s the structural health assessment and monitoring of bridges represented a critical topic in the field of [[Infrastructure|civil infrastructure]] management.<ref name=":5">{{Cite journal |last1=Thompson |first1=Paul D. |last2=Small |first2=Edgar P. |last3=Johnson |first3=Michael |last4=Marshall |first4=Allen R. |date=1998 |title=The Pontis Bridge Management System |url=https://www.tandfonline.com/doi/full/10.2749/101686698780488758 |journal=Structural Engineering International |language=en |volume=8 |issue=4 |pages=303–308 |doi=10.2749/101686698780488758 |issn=1016-8664}}</ref> In the 1990s, the [[Federal Highway Administration]] (FHWA) of the United States promoted and sponsored PONTIS and BRIDGEIT, two computerized platforms for viaduct inventory and monitoring named BMSs.<ref name=":4" /><ref name=":5" /> In the following years, also outside the U.S., the growing need of an organized and digitized road asset management has led responsible national agencies to adopt increasingly complex solutions able to meet their objectives, such as building inventories and inspection [[Database|databases]], planning for maintenance, repair and rehabilitation interventions in a systematic way, optimizing the allocation of financial resources, and increasing the safety of bridge users.<ref name=":0" /> Moreover, as of 2020s, the occurrence of some significant bridge collapse events and an increased sensitivity to the [[Environmental impact assessment|environmental impact]] of large structure management operations has led some national authorities such as [[France]] and [[Italy]] to the designation of national guidelines with detailed guidance for the development and adoption of multilevel BMS to optimize bridge management.<ref name=":1" /><ref name=":6" /><ref name=":2" /> 

== System components ==
Researchers in the field of structural engineering have identified 4 main components for the implementation of a functional BMS:<ref name=":0">{{Cite journal |last1=Dayan |first1=Vandad |last2=Chileshe |first2=Nicholas |last3=Hassanli |first3=Reza |date=2022 |title=A Scoping Review of Information-Modeling Development in Bridge Management Systems |url=https://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0002340 |journal=Journal of Construction Engineering and Management |language=en |volume=148 |issue=9 |doi=10.1061/(ASCE)CO.1943-7862.0002340 |s2cid=250152261 |issn=0733-9364}}</ref> 

* 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.<ref name=":0" /> Indeed, the inventory usually includes [[Technical drawing|technical drawings]] of the original project design, written reports from periodical in-situ [[Inspection|inspections]], numerical observation series of measurements recorded by installed [[Sensor|sensors]] but also [[Geographic data and information|geo-referenced data]] about the structure site as well as [[:Category:3D graphics file formats|3D scaled model]] that document the actual state of the bridge.<ref>{{Cite journal |last1=Shim |first1=Chang-Su |last2=Dang |first2=Ngoc-Son |last3=Lon |first3=Sokanya |last4=Jeon |first4=Chi-Ho |date=2019 |title=Development of a bridge maintenance system for prestressed concrete bridges using 3D digital twin model |url=https://www.tandfonline.com/doi/full/10.1080/15732479.2019.1620789 |journal=Structure and Infrastructure Engineering |language=en |volume=15 |issue=10 |pages=1319–1332 |doi=10.1080/15732479.2019.1620789 |s2cid=191152354 |issn=1573-2479}}</ref>

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 [[Topography|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 [[Satellite navigation|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, [[Building information modeling|BIM]] and [[computer-aided design]] software, manipulating both 2D and 3D geo-referenced data. Resulting products include [[Point cloud|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.<ref name=":0" />

In addition to visual geomatic inspections, other [[Nondestructive testing|nondestructive evaluation]] techniques are commonly adopted, allowing to collect data not limited to the accurate geometric reconstruction of the structure but also to the material conditions. In this case, the adoption of [[Ground-penetrating radar|ground penetrating radar]] for detection of deterioration of the reinforcement in decks and [[Thermography|infrared thermography]] for identification of delamination and degradation of bridge components is well documented in academic research and considered a complementary step to traditional visual inspection approaches.<ref>{{Cite journal |last1=Abdallah |first1=Abdelrahman M. |last2=Atadero |first2=Rebecca A. |last3=Ozbek |first3=Mehmet E. |date=2022 |title=A State-of-the-Art Review of Bridge Inspection Planning: Current Situation and Future Needs |url=https://ascelibrary.org/doi/10.1061/%28ASCE%29BE.1943-5592.0001812 |journal=Journal of Bridge Engineering |language=en |volume=27 |issue=2 |doi=10.1061/(ASCE)BE.1943-5592.0001812 |s2cid=244515687 |issn=1084-0702}}</ref>

{{Gallery
|title=Technical equipment adopted for visual inspections of bridges.
|width=120 |height=100
|align=center
|File:Topographic survey of a bridge.jpg
 |[[Total station]] Leica MS60 measuring bridge elements
 |alt1=Total station facing a bridge pile for survey
 |File:Prism reflector.jpg
 |[[Retroreflector]] prism used for the measurement of distances and angles with total station
 |alt3=Retroreflector prism on top of a bridge deck
|File:Terrestrial Laser Scanning of a bridge.jpg
 |[[Point cloud]] acquisition with a laser scanner FARO.
 |alt2=Laser scanner tripode operating in front of a bridge
}}

=== 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.<ref>{{Cite journal |last1=Orcesi |first1=André D. |last2=Frangopol |first2=Dan M. |date=2010 |title=Optimization of Bridge Management under Budget Constraints: Role of Structural Health Monitoring |url=http://journals.sagepub.com/doi/10.3141/2202-18 |journal=Transportation Research Record: Journal of the Transportation Research Board |language=en |volume=2202 |issue=1 |pages=148–158 |doi=10.3141/2202-18 |s2cid=109515237 |issn=0361-1981}}</ref> 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.<ref>{{Cite journal |last1=Zou |first1=Yang |last2=Kiviniemi |first2=Arto |last3=Jones |first3=Stephen W. |last4=Walsh |first4=James |date=2019-02-01 |title=Risk Information Management for Bridges by Integrating Risk Breakdown Structure into 3D/4D BIM |url=https://doi.org/10.1007/s12205-018-1924-3 |journal=KSCE Journal of Civil Engineering |language=en |volume=23 |issue=2 |pages=467–480 |doi=10.1007/s12205-018-1924-3 |s2cid=255540775 |issn=1976-3808}}</ref> In recent BMS applications, [[Sustainability measurement|sustainability]] also plays a crucial role in the definition of procedures for cost optimization adopting dedicated approaches such as [[Life-cycle assessment|Life Cycle Assessment]], calculation of [[Carbon footprint|carbon-footprint]] and energy consumption along the different phase of the bridge life cycle.<ref name=":6">{{Cite journal |last1=Kaewunruen |first1=Sakdirat |last2=Sresakoolchai |first2=Jessada |last3=Zhou |first3=Zhihao |date=2020 |title=Sustainability-Based Lifecycle Management for Bridge Infrastructure Using 6D BIM |journal=Sustainability |language=en |volume=12 |issue=6 |pages=2436 |doi=10.3390/su12062436 |issn=2071-1050 |doi-access=free }}</ref>

=== Structural analysis and assessment ===
[[File:Puente atirantado CivilFEM.png|alt=Example of FEM analysis on a bridge.|thumb|Example of a structural analysis of a bridge in a FEM environment.]]
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|Computer Vision]] techniques taking advantage of [[Artificial intelligence|Artificial Intelligence]] and [[Machine learning|Machine Learning]] semi-automatize the extraction of meaningful information from pictures taken during inspections.<ref>{{Cite journal |last1=Chen |first1=Jieh-Haur |last2=Su |first2=Mu-Chun |last3=Cao |first3=Ruijun |last4=Hsu |first4=Shu-Chien |last5=Lu |first5=Jin-Chun |date=2017-01-01 |title=A self organizing map optimization based image recognition and processing model for bridge crack inspection |url=https://www.sciencedirect.com/science/article/pii/S092658051630187X |journal=Automation in Construction |language=en |volume=73 |pages=58–66 |doi=10.1016/j.autcon.2016.08.033 |issn=0926-5805}}</ref> For example, recent applications of semantic segmentation allows the identification of elements affected by corrosion or other degradation phenomena,<ref>{{Cite book |last1=Ahuja |first1=Sanjay Kumar |last2=Shukla |first2=Manoj Kumar |title=Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2 |chapter=A Survey of Computer Vision Based Corrosion Detection Approaches |date=2018 |editor-last=Satapathy |editor-first=Suresh Chandra |editor2-last=Joshi |editor2-first=Amit |chapter-url=https://link.springer.com/chapter/10.1007/978-3-319-63645-0_6 |series=Smart Innovation, Systems and Technologies |volume=84 |language=en |location=Cham |publisher=Springer International Publishing |pages=55–63 |doi=10.1007/978-3-319-63645-0_6 |isbn=978-3-319-63645-0}}</ref> enabling experts to assign a grade of severity for the damage.<ref name=":0" /> Additional insights on the structure conditions are given by numerical simulations on fatigue behavior with [[finite element method]] modeling. This case is particularly valuable when data from in-depth detailed inspections or load tests are available, providing a rich information inventory also for computing simulations on stress behaviors and mechanics.<ref>{{Cite journal |last1=Zhu |first1=Zhiwen |last2=Xiang |first2=Ze |last3=Li |first3=Jianpeng |last4=Huang |first4=Yan |last5=Ruan |first5=Shipeng |date=2020-04-15 |title=Fatigue behavior of orthotropic bridge decks with two types of cutout geometry based on field monitoring and FEM analysis |url=https://www.sciencedirect.com/science/article/pii/S0141029619310363 |journal=Engineering Structures |language=en |volume=209 |pages=109926 |doi=10.1016/j.engstruct.2019.109926 |s2cid=214390583 |issn=0141-0296}}</ref><ref name=":0" /> 

At a larger territorial scale, a similar grading approach is also applied to the evaluation of the whole [[Street network|road network]] context in which the single structure analyzed is located. Such quantitative analysis are usually connected to the evaluation of road surface deformations with [[Interferometric synthetic-aperture radar|InSAR]] technologies or to calculation and prediction of the average daily traffic flow in GIS environments.<ref>{{Cite journal |last1=Macchiarulo |first1=Valentina |last2=Milillo |first2=Pietro |last3=Blenkinsopp |first3=Chris |last4=Giardina |first4=Giorgia |date=2022 |title=Monitoring deformations of infrastructure networks: A fully automated GIS integration and analysis of InSAR time-series |url=http://journals.sagepub.com/doi/10.1177/14759217211045912 |journal=Structural Health Monitoring |language=en |volume=21 |issue=4 |pages=1849–1878 |doi=10.1177/14759217211045912 |s2cid=245807673 |issn=1475-9217}}</ref><ref>{{Cite journal |last1=Jiang |first1=B. |last2=Liu |first2=C. |date=2009 |title=Street‐based topological representations and analyses for predicting traffic flow in GIS |url=https://www.tandfonline.com/doi/full/10.1080/13658810701690448 |journal=International Journal of Geographical Information Science |language=en |volume=23 |issue=9 |pages=1119–1137 |doi=10.1080/13658810701690448 |arxiv=0709.1981 |s2cid=32772999 |issn=1365-8816}}</ref> 

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.<ref name=":3" /><ref name=":0" />

=== Maintenance planning ===
[[File:Bridge Inspection - geograph.org.uk - 1602903.jpg|alt=Bridge deck special inspection|thumb|Targeted special inspection of a bridge deck.]]
The definition of operation schedule and more detailed inspection is a key function in the [[Decision-making|decision making process]] of a BMS. Based on quantitative and qualitative data acquired during routine inspections and along the processing of information in the structural analyze phase, BMS users need to identify priority interventions through a dedicated maintenance plan. This goal is achieved with the implementation of platforms and tools that enable stakeholders to explore data, results and observations and link them to detailed [[Fact sheet|fact sheets]] reporting the health conditions of each [[Glossary of structural engineering|structural elements of the bridge]].<ref name=":3">{{Cite journal |last1=Mohammadi |first1=Masoud |last2=Rashidi |first2=Maria |last3=Mousavi |first3=Vahid |last4=Yu |first4=Yang |last5=Samali |first5=Bijan |date=2022 |title=Application of TLS Method in Digitization of Bridge Infrastructures: A Path to BrIM Development |journal=Remote Sensing |language=en |volume=14 |issue=5 |pages=1148 |doi=10.3390/rs14051148 |issn=2072-4292 |doi-access=free }}</ref>

[[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. <ref name=":1">{{Cite journal |last1=Natali |first1=Agnese |last2=Cosentino |first2=Antonella |last3=Morelli |first3=Francesco |last4=Salvatore |first4=Walter |date=2023 |title=Multilevel Approach for Management of Existing Bridges: Critical Analysis and Application of the Italian Guidelines with the New Operating Instructions |journal=Infrastructures |language=en |volume=8 |issue=4 |pages=70 |doi=10.3390/infrastructures8040070 |issn=2412-3811 |doi-access=free }}</ref> 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 (structure)|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 testing|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.<ref name=":1" /> 

== National guidelines ==
In order to assess and quantify the health condition of the bridges located in their national territory, many countries have formulated a series of general indications and guidelines for the implementation of dedicated bridge management systems.

=== France ===
In 2019, the French Centre for Studies on Risks, the Environment, Mobility and Urban Planning (CEREMA) in collaboration with the [[IFSTTAR|French Institute of Science and Technology for Transport]], Development and Networks issued the national guidelines, proposing a multilevel methodology for the assessment and management of the risk of failure due to scour for bridges with foundations in water. The current version of the French guidelines only refers to bridge scour and hydraulic risk.The proposed methodology runs on 4 levels:<ref name=":2">{{Citation |last1=Giordano |first1=P.F. |title=Risk-based scour assessment of bridges: Italian VS French guidelines |date=2022-06-27 |url=https://www.taylorfrancis.com/books/9781003322641/chapters/10.1201/9781003322641-169 |work=Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability |pages=1393–1399 |access-date=2023-07-05 |edition=1 |place=London |publisher=CRC Press |language=en |doi=10.1201/9781003322641-169 |isbn=978-1-003-32264-1 |last2=Turksezer |first2=Z.I. |last3=Limongelli |first3=M.P.}}</ref>

# Summary analysis: [[qualitative risk analysis]] on a large scale and classification of the structure into three risk classes: low, medium, and high;
# Simplified analysis: semi-quantitative analysis on bridges previously classified in the medium and high level of risk;
# Detailed analysis: in-depth studies on high-risk structures with numerical modeling approaches
# [[Risk management]]: identification of actions to improve the conditions and/or reduce the sensitivity of critical bridges.

=== Italy ===
[[File:Il Ponte Morandi dopo il crollo, visto da Est, panoramica (cropped).jpg|alt=View of the collapsed Morandi Bridge in Genova|thumb|Collapsed Morandi Bridge in August 2018 in Genova (Italy).]]
Ensuring the safety and well-being of these road infrastructures has become an urgent matter in Italy, especially after the evidence of [[bridge collapses]] occurred in the last decade.<ref>{{Cite journal |last1=Calvi |first1=Gian Michele |last2=Moratti |first2=Matteo |last3=O'Reilly |first3=Gerard J. |last4=Scattarreggia |first4=Nicola |last5=Monteiro |first5=Ricardo |last6=Malomo |first6=Daniele |last7=Calvi |first7=Paolo Martino |last8=Pinho |first8=Rui |date=2019-04-03 |title=Once upon a Time in Italy: The Tale of the Morandi Bridge |url=https://www.tandfonline.com/doi/full/10.1080/10168664.2018.1558033 |journal=Structural Engineering International |language=en |volume=29 |issue=2 |pages=198–217 |doi=10.1080/10168664.2018.1558033 |s2cid=116753139 |issn=1016-8664}}</ref> In response to the need for reliable and up-to-date information regarding bridge conditions, in 2020 the [[Ministry of Infrastructure and Transport (Italy)|Italian Superior Council of Public Works]] has developed the Guidelines on Risk Classification and Management.<ref>{{Cite web |last=Consiglio Superiore dei Lavori Pubblici |date=2020 |title=Linee Guida per la classificazione e gestione del rischio, la valutazione della sicurezza ed il monitoraggio dei ponti esistenti |url=https://www.mit.gov.it/normativa/decreto-ministeriale-numero-204-del-1-luglio-2022 |access-date=2023-07-05 |website=Ministero delle infrastrutture e dei trasporti}}</ref> These guidelines establish a multi-level approach for documenting bridge characteristics, assessing their health through [[visual inspection]] and damage identification, and determining their risk classification based on hazard, exposure and vulnerability derived from the previous steps.<ref name=":2" /> Subsequently, depending on the assigned class, the number of investigation levels required to evaluate the structure's safety is determined. Road asset managers are then asked to establish and maintain a management system able to track in time interventions, documenting defects assessed on different portion of the bridge as well as environmental site conditions ([[hydraulics]], [[geology]], [[seismology]]). The guidelines identifies six levels:<ref name=":1" />

: 1. Collection of available data about bridge construction, accessing existing archives;
: 2. Visual inspection reports about structure geometry and bridge elements conditions;
: 3. Risk classification of the structure in one of the five attention classes, i.e., low, medium-low, medium, medium-high, and high;
: 4. Simplified safety assessment for bridges in medium or medium-high attention class;
: 5. Accurate safety assessment for bridges in the high attention class;
: 6. Resilience analysis at the network level. (Only drafted in the current version of the guidelines).<ref name=":2" />

== Examples ==
The below are examples of commonly used bridge management software: 
* [[Pontis]], now Known as AASHTOWare Bridge Management, a BMS software sponsored by the U.S. [[Federal Highway Administration]] for the management of highway networks;<ref>{{Cite web |title=AASHTOWare Bridge |url=https://www.aashtowarebridge.com/ |access-date=2023-07-06 |language=en-US}}</ref>
* DANBRO+, computer-based BMS commonly used in Denmark;<ref>{{Cite book |url=https://www.taylorfrancis.com/books/edit/10.1201/b18175/advances-bridge-maintenance-safety-management-life-cycle-performance-set-book-cd-rom-luis-canhoto-neves-paulo-da-sousa-cruz-dan-frangopol |title=Advances in Bridge Maintenance, Safety Management, and Life-Cycle Performance, Set of Book & CD-ROM: Proceedings of the Third International Conference on Bridge Maintenance, Safety and Management, 16-19 July 2006, Porto, Portugal - IABMAS '06 |date=2015-03-11 |publisher=CRC Press |isbn=978-0-429-15809-4 |editor-last=Neves |editor-first=Paulo J. da Sousa Cruz, Dan M. Frangopol, Luis C. Canhoto |location=London |doi=10.1201/b18175}}</ref>
* SwissInspect, Swiss digital twin platform specialized in the management of civil infrastructures, mainly bridges;<ref>{{Cite web |title=SwissInspect - Create Digital Twins of Infrastructure |url=https://www.swissinspect.io/ |access-date=2023-07-06 |website=www.swissinspect.io}}</ref>
* INBEE, digital platform and mobile application that implement the Italian guidelines for bridge monitoring.<ref>{{Cite web |title=INBEE |url=https://inbee.it/ |access-date=2023-07-06 |website=Inbee |language=it-IT}}</ref>

== See also ==

* [[Structural health monitoring]]
* [[Management system]]
* [[Digital twin]]
* [[Structural engineering]]
* [[Glossary of structural engineering]]

==References==
{{Reflist}}
[[Category:Bridges]]
[[Category:Construction]]
[[Category:Transportation engineering]]
[[Category:Technology systems]]
[[Category:Information systems]]
[[Category:Management systems]]

== Further reading ==

* {{Cite journal |title=BRIDGE MANAGEMENT SYSTEMS |url=https://trid.trb.org/view/278332 |access-date=2023-07-07 |journal=NCHRP Report |date=December 1987 |issue=300 |language=en |last1=Hudson |first1=S. W. |last2=Carmichael III |first2=R. F. |last3=Moser |first3=L. O. |last4=Hudson |first4=W. R. |last5=Wilkes |first5=W. J. |via=US Transportation Research Board}}
* {{Cite web |title=Linee Guida per la classificazione e gestione del rischio, la valutazione della sicurezza ed il monitoraggio dei ponti esistenti |trans-title=Guidelines for risk classification and management, safety assessment and monitoring of existing bridges |url=https://www.mit.gov.it/comunicazione/news/mit-approvate-le-linee-guida-per-la-sicurezza-dei-ponti |access-date=2023-07-06 |language=it}}
* {{Cite web |date=2019-03-28 |title=Analyse de risque des ponts en site affouillable: un guide du Cerema |trans-title=Risk analysis of bridges on scourable sites: a Cerema guide |url=https://www.cerema.fr/fr/actualites/analyse-risque-ponts-site-affouillable-guide-du-cerema |access-date=2023-07-06 |website=Cerema, climat et territoires de demain. Aménegement et résilience |language=fr}}