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The maintenance of port infrastructures presents difficulties due to their location: an aggressive environment or the variability of the waves can cause progressive deterioration. Maritime condi-tions make inspections difficult and, added to the lack of use of efficient tools for the management of assets, planning maintenance, important to ensure operability throughout the life cycle of port in-frastructures, is generally not a priority. In view of these challenges, this research proposes a methodology for the creation of a port infrastructure asset management tool, generated based on the Design Science Research Method (DSRM), in line with Building Information Modeling (BIM) and digitization trends in the infrastructure sector. The proposal provides workflows and recommen-dations for the survey of port infrastructures from UAVs, the reconstruction of digital models by photogrammetry (due to scarce technical documentation), and the reconstruction of BIM models. Along with this, the bidirectional linking of traditional asset management spreadsheets with BIM models is proposed, by visual programming, allowing easy visualization of the status and maintenance requirements. This methodology was applied to a port infrastructure, where the methodology demonstrated the correct functionality of the asset management tool, which allows a constant up-dating of information regarding the structural state of the elements and the necessary maintenance activities.
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sensors
Article
Implementation of Facility Management for Port Infrastructure
through the Use of UAVs, Photogrammetry and BIM
Constanza Jofré-Briceño 1, Felipe Muñoz-La Rivera 1,2,3,* , Edison Atencio 1and Rodrigo F. Herrera 1


Citation: Jofré-Briceño, C.;
Muñoz-La Rivera, F.; Atencio, E.;
Herrera, R.F. Implementation of
Facility Management for Port
Infrastructure through the Use of
UAVs, Photogrammetry and BIM.
Sensors 2021,21, 6686. https://
doi.org/10.3390/s21196686
Academic Editor: Sisi Zlatanova
Received: 18 August 2021
Accepted: 6 October 2021
Published: 8 October 2021
Publisher’s Note: MDPI stays neutral
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Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1School of Civil Engineering, Pontificia Universidad Católica de Valparaíso, Valparaíso 2340000, Chile;
constanza.jofre.b@mail.pucv.cl (C.J.-B.); edison.atencio@pucv.cl (E.A.); rodrigo.herrera@pucv.cl (R.F.H.)
2School of Civil Engineering, Universitat Politecnica de Catalunya, 08034 Barcelona, Spain
3International Center for Numerical Methods in Engineering (CIMNE), 08034 Barcelona, Spain
*Correspondence: felipe.munoz@pucv.cl
Abstract:
The maintenance of port infrastructures presents difficulties due to their location: an ag-
gressive environment or the variability of the waves can cause progressive deterioration. Maritime
conditions make inspections difficult and, added to the lack of use of efficient tools for the man-
agement of assets, planning maintenance, important to ensure operability throughout the life cycle
of port infrastructures, is generally not a priority. In view of these challenges, this research pro-
poses a methodology for the creation of a port infrastructure asset management tool, generated
based on the Design Science Research Method (DSRM), in line with Building Information Modeling
(BIM) and digitization trends in the infrastructure sector. The proposal provides workflows and
recommendations for the survey of port infrastructures from UAVs, the reconstruction of digital
models by photogrammetry (due to scarce technical documentation), and the reconstruction of BIM
models. Along with this, the bidirectional linking of traditional asset management spreadsheets
with BIM models is proposed, by visual programming, allowing easy visualization of the status
and maintenance requirements. This methodology was applied to a port infrastructure, where the
methodology demonstrated the correct functionality of the asset management tool, which allows a
constant up-dating of information regarding the structural state of the elements and the necessary
maintenance activities.
Keywords:
port infrastructures; facility management; building information modelling (BIM);
unmanned aerial vehicles (UAVS); photogrammetry; visual programming
1. Introduction
Port infrastructures (PI) are large-scale facilities with certain particularities that dif-
ferentiate them from others designed in less aggressive environments [
1
]. They exist in a
highly aggressive environment, and materiality, the presence of salt water, and the impact
of coastal dynamics affect infrastructures, accelerating the progressive deterioration of
the elements that compose them. Additionally, environmental conditions make it difficult
to inspect and maintain and/or repair this type of infrastructure [
2
]. The importance of
maintaining port infrastructure lies in its strategic role in the development of economic
activity or connectivity, which could change over time and convert to recreational activities,
although the operability and safety of the infrastructure must be guaranteed throughout
its life cycle [3].
Currently, maintenance activities for this type of infrastructure are affected by the
difficulty of access, the lack of existing documentation (since many of these structures
are old), and the materiality of the elements that compose it (usually reinforced concrete),
problems compounded by the marine environment [
4
], increasing the likelihood of devel-
oping anomalies that may cause progressive damage to the infrastructure [
2
,
5
]. However,
traditional methods for the maintenance of port infrastructure generally follow a corrective
Sensors 2021,21, 6686. https://doi.org/10.3390/s21196686 https://www.mdpi.com/journal/sensors
Sensors 2021,21, 6686 2 of 27
maintenance approach with the clear identification of a deterioration, which is also often
inefficient due to poor information management [6].
Currently, the new methodologies that have been incorporated into the AECO (Ar-
chitecture, Engineering, Construction, and Operations) industry encourage and allow the
development of preventive infrastructure maintenance [
7
]. Among the new management
trends, facility management (FM) is a discipline that seeks to manage the proper function-
ing of buildings and/or infrastructures through the integration of people, space, processes,
and technologies [
8
], which translates into optimal service management, operational man-
agement, and maintenance management, among others [9,10].
The use of building information modelling (BIM) allows the visualization of a project
and the integration of all agents and assets for the successful development of the facilities,
addressing their entire life cycle. The use of parametric 3D models allows for identification
of the typologies of elements that make up the infrastructures, and having full control of
the infrastructures as far as the information of materiality, cost planning, time, and environ-
mental considerations that allow greater control and efficiency in the design, construction,
and operation processes of the products of this industry [7].
However, the use of technologies such as unmanned aerial vehicles (UAVs) allows
for the surveying of environments, reaching areas with difficult access, and their 3D
digital reconstruction by photogrammetry [
11
]. From the photographs captured with
UAVs and the processing of images in software based on structure from motion (SfM)
and multiview stereo (MVS) techniques, it is possible to reconstruct real scenarios and
three-dimensional models.
Faced with the difficulties and problems presented by port infrastructures and the
new methodologies and technologies that have become widespread in the industry, this
investigation proposes a workflow for the integration of the FM activities into harbour
infrastructures. We propose to survey existing infrastructure by using UAVs, with recon-
struction by image processing based on computer vision algorithms SfM-MVS to generate
a point cloud which, together with existing map documentation (generally scarce in old
infrastructures), allows for rebuilding parametric 3D models of port infrastructure in BIM
modelling software, and facilitates visual and interactive management. The proposed flow
also allows for the bidirectional linkage of the information flows, generating an automatic
asset management tool based on 3D models and user-friendly maintenance sheets that can
be used in the field for port asset maintenance inspection.
The methodology developed was applied to a case study of a port penetration infras-
tructure, in which the feasibility of implementation was evaluated, the flow of bidirec-
tionality between the tools created was studied, and the main anomalies of infrastructure
elements according to typology and materiality were studied to develop an effective asset
management tool for the infrastructure in question.
2. Research Methodology
This research studies and proposes the use of technologies and new methodologies
to optimize the asset management of existing port infrastructure. Figure 1details the
activities needed to carry out this research, together with the tools and methodologies
used in its development. The methodology of research in Design Sciences (Design Science
Research Methodology—DSRM) has been used to represent the research process practically,
organized in 5 stages: (1) identification of observed problems; (2) definition of objectives
for a potential solution; (3) design and development; (4) demonstration; (5) evaluation [
12
].
Sensors 2021,21, 6686 3 of 27
Sensors 2021, 21, 6686 3 of 29
STAGE ACTIVITY TOOL
(1)
Identification of
problems
observed and
motivations
Study of use of UAVs and Photogrammetry
for surveying infrastructure.
Identification of BIM and FM usage
advantages applied to PI.
(2)
Defini tion of
objectiv es for a
potential solution
Review of l iterature
Understand the challenges of
traditional PI maintenance, the
use of UAVs and
Photogrammetry for the survey
of existing PI, along with the
advantages of using BIM and
FM in asse t manage ment.
The use of UAVs and
Photogra mmetry all ows the
surve y of IP ex isting in the
absence of technical
documentation, which added to
the use of BIM and FM would
improve IP asset management
(3)
Design and
development
UAV,
Photogrammetry
Software
Flows and criteria for UAV flight and
photometric reconstruction of IP existing and
point cloud gene ration.
Automated
spreadshee t, BIM
software, v isual
programmi ng
Creati on of criteria for the maintenanc e and
generation of asset management tools.
Design and development of a
workflow for the generation of
asset ma nage ment tools for port
infra structure.
(4)
Demonstration
[Caso Study]
(5)
Evaluation
Asset managemen t
tool
Verification of t he integration of spre adsheets
with BIM model an d operation of
manage ment tool developed
Validation of the asset
management tool
Iteration
Critical identifi cation of traditi onal methods
for PI maintenance.
Flows and criteria for recon struct ion of BIM
modeling from the use of point cloud . BIM software
UAV,
Photogrammetry
Software
Photogra mmetri c PI survey a nd
reconstruction, and point cloud generation.
Creati on of criteria for the maintenanc e and
generation of PI asset mana gement for ms.
Creati on of asset man agement tools:
Automatic integration of spreadsheets with
BIM parametric model.
BIM parametric modeling reconstruction
from the use of point cloud. BIM software
Automated form
Case select ion a nd background coll ection. Documentation
BIM software, visual
programmi ng
Use of asset ma nagement tool
applied in case of study
Figure 1. Methodology of research.
In the first stage, a literature review was carried out based on Web of Science and
Scopus repositories, along with the revision of manuals, guides, and technical reports, to
identify deficiencies and particularities of the traditional methods of maintenance of port
infrastructures and to define the challenges that exist in the management of their mainte-
nance. Along with this literature review, the potentialities of emerging technologies and
methodologies that have been incorporated into the AECO industry were studied: use of
UAVs for the collection of information, photogrammetry for the reconstruction of existing
infrastructure, and the use of BIM and FM system for information management applied
to coastal infrastructure. Based on the background gathered, in the second stage, the ob-
jective of a potential solution to the identified problems has been defined: the use of UAVs
and photogrammetry allow for the lifting of existing infrastructure, in the absence of doc-
umentation regarding its structuring, which, combined with the use of BIM and FM tools,
would improve asset management, filling in the gaps in the traditional port infrastructure
maintenance methods.
Figure 1. Methodology of research.
In the first stage, a literature review was carried out based on Web of Science and
Scopus repositories, along with the revision of manuals, guides, and technical reports,
to identify deficiencies and particularities of the traditional methods of maintenance of
port infrastructures and to define the challenges that exist in the management of their
maintenance. Along with this literature review, the potentialities of emerging technologies
and methodologies that have been incorporated into the AECO industry were studied:
use of UAVs for the collection of information, photogrammetry for the reconstruction of
existing infrastructure, and the use of BIM and FM system for information management
applied to coastal infrastructure. Based on the background gathered, in the second stage,
the objective of a potential solution to the identified problems has been defined: the use of
UAVs and photogrammetry allow for the lifting of existing infrastructure, in the absence
of documentation regarding its structuring, which, combined with the use of BIM and
FM tools, would improve asset management, filling in the gaps in the traditional port
infrastructure maintenance methods.
Sensors 2021,21, 6686 4 of 27
In the third stage, the design and development of a set of tools for maintenance man-
agement based on the use of UAVs, photogrammetry, visual programming tools, and BIM
software, for the reconstruction of a digital parametric 3D model of port infrastructure
interconnected with management worksheets, identifying control elements, and defin-
ing conservation activities, make it possible to develop an efficient and practical asset
management tool for users.
In the fourth stage, the tools designed and developed in the previous stage are applied
to a case study of a port infrastructure that has had little maintenance and has a lack of
information about its state and structure. Here, background and documentation of the
infrastructure are collected, which provide information of interest for the reconstruction
of the BIM parametric model. The parametric BIM model is made from a point cloud
obtained from photogrammetry with UAV, thanks to the use of structural from motion
(SfM)-multiview stereo (MVS) algorithms of the image processing software. However,
maintenance criteria are created associated with the types of the element identified from
the parametric BIM model created (in Autodesk
®
Revit), existing documentation, and field
inspections, for which automated forms are developed (in MS Excel) that allow the struc-
tural evaluation of the elements and their corresponding maintenance activities. These
spreadsheets are integrated into the parametric BIM model using visual programming tools
(Dynamo), which allow for the automatic flow of information between both platforms,
thus generating an asset management tool that addresses the need to carry out repair
activities in a systematic manner to prevent significant deterioration of facilities and that,
in turn, ensures an improvement in the management of maintenance processes.
Finally, in the fifth stage, the tools developed are validated, confirming the correct
integration of the parametric BIM model with the automated spreadsheets and their
usability, thus validating the functioning of the asset management tool.
3. Literature Review
Port infrastructures are maritime engineering structures intended for cargo and/or
passenger transfer operations due to their function of connectivity between the maritime
and land sectors. Within these sectors, there are different typologies according to their
orientation or impact on coastal dynamics [
2
]. These structures are constantly exposed
to a marine environment; therefore, they have specific properties that differentiate them
from infrastructures designed in less aggressive environments [
1
,
13
]. Major damage
to port infrastructure results in costs for the repair of the structure itself and economic
losses associated with loss of its economic activity due to inoperability while the repair
work is being carried out [
14
]. Early detection of the potential structural pathologies of
the infrastructure elements and early performance of the maintenance activities avoids
a progressive deterioration, ensures its functionality, and ensures users’ safety. Early
maintenance avoids incurring the high costs incurred in financing complex repair work
in the event of collapse or large-scale breakage [
1
,
2
], reducing the risk of collapse in more
complex situations, such as large seismic events and/or maritime phenomena such as
tsunamis [15].
3.1. Problems and Challenges for Port Infrastructure Maintenance
The complexity of the marine environment has prompted expert entities to develop
technical guides that establish a series of standards for port infrastructures [
2
,
5
]. These
strategies are associated with the material of the elements (usually concrete and steel),
the use of anticorrosion elements and the technical characteristics of the materials used in
the design, construction practices, and maintenance considerations, among others.
Structural concrete, commonly used for PI due to its strength and versatility, is vulner-
able to high concentrations of chlorides and sulfates in coastal waters [
16
,
17
], leading to
the corrosion of armour and loss of concrete strength [
18
,
19
], and, as a result, cracks and
breakdowns of concrete occur and, in more extreme cases, could lead to the collapse of
the structure [
5
,
11
]. The level of corrosion of the armour is relative to the aggressiveness
Sensors 2021,21, 6686 5 of 27
of the environment in the maritime exposure zones. Depending on the different levels
of aggressiveness, different pathologies will develop that affect to different degrees the
elements that make up the infrastructure [20,21].
In this sense, the importance of detecting PI pathologies promptly lies in the prevention
of major deterioration that could affect the functioning of PI. However, PI inspection and
monitoring studies are not simple. The presence of water hinders access to inspect the
infrastructure in detail throughout its length and depth, which, added to the aggressive
environment and high humidity, requires specialized equipment and tools to be used in
inspection or repair activities to enable them to be carried out smoothly [22].
3.2. Traditional Methods of Port Infrastructure Maintenance
Traditionally, to carry out a maintenance strategy for port infrastructure, there are four
main phases: (I) analysis of existing documentation; (II) inventory; (III) overall evaluation;
(IV) record of actions [
1
]. Phase I consists of the analysis of all existing information (plans,
photographic records, repair history, among others). In phase II, through visual field
inspection, all elements are identified, and the geometrical and technical characteristics
of each of the elements are recorded in inventory sheets. In phase III, information is
obtained on the status of the PI assets, and the anomalies of each of them are recorded to
subsequently define the repair techniques and the urgency of intervention required. Finally,
in phase IV, the repair actions carried out for the updating of the state of the infrastructure
are recorded [2,18].
These traditional methods are based on the collection and documentation of infor-
mation on assets on the ground; however, the large size of port infrastructures makes
these processes time-consuming [
2
]. The information collected is recorded in cadastres or
inventory sheets, which generally include graphic references or indications associated with
existing plans to reference the location of the elements and to facilitate the location of the
damage [
23
]. In many cases, this information is digitized, which facilitates access to existing
documentation; however, in this process, digitalization of the cards induces errors [
24
]. This
delay accounts for the shortcomings of traditional methods based on physical or digital
records that merely have an orderly record, missing the potential of new methodologies and
technologies to manage and visualize the information and documentation collected [
25
].
In addition to visual inspection, on-site or laboratory tests are often carried out to define
the structural state of the infrastructural elements. Based on the results of these tests, it is
possible to avoid errors of arbitrary assessment that could be generated in maintenance
procedures based solely on visual inspection because, for example, pathologies such as
corrosion of the internal reinforcement system of the concrete are not visible [15].
In particular, carrying out inspections, testing, and, in general, gathering information
to develop conservation strategies becomes complex with regard to infrastructure at sea.
Sometimes, underwater inspections are required, which are carried out by professional
divers using specialized tools and equipment to measure damage and anomalies in sub-
merged elements [1]. In addition, if the infrastructures are categorized under patrimonial
safeguards, there is an increase in restrictions and care with the elements that make up the
structure, which, added to the scarce existing documentation, which is generally obsolete,
hinders actions to establish maintenance plans under traditional criteria. The damage is
therefore not detected in time [
26
]. Added to these problems due to the nature of PI, there
are economic and human resources, recruitment, and use of technologies, which make it
difficult to develop efficient conservation management [1].
3.3. New Technologies for the AECO Industry
The new methodologies and technologies that have been incorporated into the AECO
industry have made it possible to optimize workflows through tools that allow for collabo-
ration and the integration of information, thus evolving the traditional methods [27].
The BIM allows for integration and collaboration between stakeholders in a project
through parametric models at different levels of detail and can be used throughout the
Sensors 2021,21, 6686 6 of 27
life cycle of a project [
9
]. In addition to three-dimensional visualization, with potential
access to information, the BIM methodology facilitates the updating of the model, either
of parameters or plans of the different specialties without loss of information [
28
]. In this
way, once the model has been developed, it is possible to modify parameters as well as add
and/or remove elements as required to have a completely updated and reliable model that
can be accessed by all project agents, rendering the traditional systems obsolete in which the
projects are worked from the design until the O&M phase, including the manual registry
of records of cadastres or conservation, the fragmented documentation of each element of
the infrastructure, and the recording and updating of maintenance activities [7,29,30].
In line with the new methodologies, facility management allows for the management
of the correct functioning of buildings or infrastructures. The International Association
of Facility Management defines “FM” as a discipline that encompasses various areas to
ensure and manage the operation of buildings and/or infrastructures and their associated
services through the integration of people, spaces, processes, and technologies specific to
such buildings or infrastructures [
31
]. In this sense, correct and reliable information man-
agement facilitates decision-making in the operation and maintenance (O&M) phase [
32
];
however, traditional FM activities methods are performed based on planes or fragmented
or dispersed information, which requires more time to be spent collecting information due
to the lack of integration of information [
33
]. Thus, the integration and use of BIM in FM is
becoming increasingly common. Currently, it has been used for the maintenance of build-
ing assets or large infrastructures, facilitating access to information from the digitisation
of the BIM model, which improves the levels of efficiency and productivity of the sector
by optimising information flows through existing interoperability formats [
8
], optimising
and significantly reducing costs in the O&M phase [
34
] so that such integration becomes a
potential for efficient asset management [35].
Moreover, new technologies have emerged in the AECO industry to solve the prob-
lems of access, information gathering, and digital reconstruction of existing infrastruc-
tures [
26
,
36
]. Among these technologies, terrestrial laser scanners (TLSs) are mass point
acquisition tools which are very useful for the reconstruction of digital models from point
clouds [
37
39
]. While this tool allows for massive, fast, and accurate data capture, gen-
erating a cloud of high-resolution points, these types of tools are high-cost equipment
and require highly trained professionals for their operation, therefore their massive use is
restrictive. On the other hand, unmanned aerial vehicles (UAVs) are remotely operated
aerial vehicles that have become a common method for mapping and digital reconstruction
of infrastructures that, due to their economy and practicality, are preferred over the use
of TLSs [
40
]. Unlike the traditional visual inspection of maintenance plans, the use of
UAVs allows for inspections in much shorter times, in turn allowing for more frequent
inspections, increasing the recurrence of the structural status updates of the elements of
the inspected infrastructure, and thus providing the information for the digital model [
11
].
The reconstruction of digital models from photogrammetry is based on the SfM
technique, which allows for the generation of digital reconstructions from photographs.
SfM generates a point cloud, which is improved by densifying its resolution through
MV. This technique depends on the quantity and quality of the captured images and the
conditions of the environment at the time of capture. Light conditions, projected shadows
of objects, and areas of homogeneous surfaces can alter the 3D reconstruction, from which
it is possible to generate digital models of the infrastructure [41].
4. Methodology Developed
Figure 2shows the proposed methodology for generating an asset management
tool for port infrastructure, consisting of six stages: (I) UAV flight strategy definition;
(II) image acquisition; (III) data processing; (IV) BIM model reconstruction; (V) definition of
maintenance actions and automated template creation; (VI) creation of asset management
tools. This section shows the conceptual aspects of the proposal. The tools used and
Sensors 2021,21, 6686 7 of 27
integrated into the workflow and the codes developed are shown in detail in the application
case section.
Sensors 2021, 21, 6686 7 of 29
Flying start
Unsafe
cond ition s
during the
flight?
Disrupt mission and
land
Com plete the traj ecto ries an d land
Para meter s etting a nd key point
detection
SfM
Will
checkp oints
be used?
Int roduce contr ol
points
No
Scaling and georeferencing
Multiview stereo
Dense poin t cloud
Impo rt point cloud to B IM Softw are ,
adjustment and orientation
Obtain images according to parameters
Flight speed Time between catches
No
Yes
Yes
Verify atmospheric
facto rs
Moisture
Wind spe ed
No
Yes
[I]
Definition of
UAV flight
strategy
[II]
Image acquisition
[III]
Data processing
[IV]
Reconstruction
model BIM
Iden tify the area o f interes t
Surrounding elements - sea
Area
Faces to capture
Iden tify s afe fli ght
space
Defin ir parámetr os
de regi stro
Design flight paths
Await appropriate
conditions
Are there
any
conditions
for t he flight?
STAGE FLOW
Request permission to fly
maritime authority
CAD d rawi ngs
Previous models
Various background
Recons truction of BIM ge ometric
model
[V]
Defini tion of
maintenance
actions and
automated
worksheet creation
Inv ento ry of PI eleme nt s
Defin ition o f status criteri a acc ording
to th e typo logy of P I elem ents
Development of automated
worksheet for structural state
assessment
Automated bidirectional template
integration with BIM model
[VI]
Creation of
tool asset
management
Main tenance Action Defini tions b y
State and Type of PI Elements
Crea tion an d
assignment of
para mete rs to the BIM
model
Asset management tool enabled for
use
Existing d ocumentatio n
Set of captured images
Figure 2. Flow for the creation of an asset management tool.
Figure 2. Flow for the creation of an asset management tool.
Sensors 2021,21, 6686 8 of 27
4.1. Definition of Flight Strategy
UAV flight strategy for PI uplift must be defined. Because PIs are considered strategic
infrastructures (private or public, as appropriate), it is necessary to request the correspond-
ing permits to conduct the flight of the UAV, according to the general flight rules of these
devices, and according to maritime space registry records established in each country,
as appropriate (usually coastal infrastructure is under naval security). In Chile, UAV flight
is regulated by the Directorate General of Civil Aeronautics (DGAC), which currently
has two regulations that establish certain requirements and limitations for aerial activity:
DAN 151: Remotely Piloted Aircraft Operations (RPAS), used in matters of public interest,
which take place over populated areas; DAN 91: Rules of the Air, which, unlike the former,
applies to non-populated areas.
It is worth mentioning that those UAVs whose weight exceeds 750 g must comply
with DAN 151, which indicates the maximum weight, establishes who can pilot them,
the conditions under which they must be operated, the obligation to register with the
DGAC, and the documents required for their use.
On the other hand, there are two cases of UAVs weighing less than 750 g. When used
in populated places at an altitude of fewer than 50 m, they are not subject to DAN 151 in
terms of registration, credentials, and authorization; however, the operator is responsible
for any damage to third parties. However, those used in non-populated areas must only
have the corresponding authorization from the DGAC, in accordance with the provisions
of DAN 91 [42,43]
Then, the area of interest must be identified. This methodology has been developed
for the port infrastructure of piers of penetration, that is, when the PI is projected from
the coastal edge towards the sea (being able to adapt to other topologies according to the
requirements of the user). In these cases, it is relevant:
To identify all surfaces and faces of interest that are necessary to rebuild; therefore,
it is recommended that the set of photographs cover the entire surface of the infras-
tructure and its perimeter area, covering the greatest possible visibility of the elements
undercover;
For a correct reconstruction, it is necessary to correctly define the registry parameters
that the UAV will use. In practical terms, it is important to consider an overlap
between photographs by over 75%;
To consider the surrounding or PI-specific elements that might interfere with the flight
and the difficulties of the near-sea flight (especially when capturing items that are
under or near the water line at the time the logs will be taken);
Atmospheric factors should be considered in the planning of the day of the flight (low
humidity and wind speed).
Under these considerations and given the characteristics of the penetration springs,
as shown schematically in Figure 3, it is recommended that the flight path of the UAV
covers the surface of the infrastructure with vertical photogrammetry, that is, the axis of
the camera positioned vertically with a flight parallel to the surface, which, for a better
reconstruction, can be complemented with oblique photogrammetry (especially if there
are many elements of complementary infrastructure on the dock). However, oblique
photogrammetry is recommended for the entire perimeter of the infrastructure, trying to
secure three different directions, to achieve greater coverage of the elements.
It is important to consider that the homogeneity of the sea surface and the recurrence
of similar elements in the PI can generate problems in later photogrammetric reconstruction;
therefore, it is recommended to define milestones in the PI that allow for the identification
of different points to make potential corrections in the reconstruction.
Sensors 2021,21, 6686 9 of 27
Sensors 2021, 21, 6686 9 of 29
Figure 3. UAV flight path and photogrammetry used.
It is important to consider that the homogeneity of the sea surface and the recurrence
of similar elements in the PI can generate problems in later photogrammetric reconstruc-
tion; therefore, it is recommended to define milestones in the PI that allow for the identi-
fication of different points to make potential corrections in the reconstruction.
4.2. Data Acquisition
The acquisition of images in the field with the UAV must be done. Atmospheric fac-
tors must first be verified. Flights should not be made on rainy days with high humidity
and/or strong winds, as these conditions affect the functionality of the equipment or de-
stabilize its position, preventing the acquisition of photographs with the required quality
(in capture and positioning). A good photogrammetric reconstruction requires a scenario
with few shadows; therefore, schedules must be found where these conditions exist. A
mid-day capture is ideal, as the position of the sun is practically perpendicular to the sur-
face, and, therefore, the projected shadow of the elements will be minimal, avoiding errors
due to shadows. Similar conditions are achieved on days with high clouds, where soft
shadows are generated and do not significantly harm the captured information. It is rec-
ommended that the flight be conducted as long as the weather conditions allow; other-
wise, you must interrupt the process, and wait for the right conditions or cancel the flight
session and reschedule.
To achieve reconstructions where PI geopositioning is required with a high level of
accuracy, control points can be incorporated into the measurement, referring to the de-
marcation of milestones in the infrastructure, for which it is necessary to measure their
GPS position with a specialized instrument. These points will then be incorporated into
the photogrammetric process.
4.3. Data Processing
With the set of obtained images, we proceed to the processing of images. Using the
structure from motion (SfM) method, it is possible to perform a photogrammetric recon-
struction of the PI, obtaining digital three-dimensional models from the superimposition
of images. SfM is based on machine vision algorithms that automatically correlate the
camera orientation and positioning coordinates between the captured photographs, iden-
tifying points of interest and characteristic coincidences between the photographs. At this
stage, if the control points are used, the control points must be introduced to improve the
quality of the reconstruction and obtain high-precision geopositioning. The point cloud
generated from SfM is densified using MultiView Stereo (MVS), which generates a dense,
higher-resolution point cloud.
Figure 3. UAV flight path and photogrammetry used.
4.2. Data Acquisition
The acquisition of images in the field with the UAV must be done. Atmospheric
factors must first be verified. Flights should not be made on rainy days with high hu-
midity and/or strong winds, as these conditions affect the functionality of the equipment
or destabilize its position, preventing the acquisition of photographs with the required
quality (in capture and positioning). A good photogrammetric reconstruction requires a
scenario with few shadows; therefore, schedules must be found where these conditions
exist. A mid-day capture is ideal, as the position of the sun is practically perpendicular to
the surface, and, therefore, the projected shadow of the elements will be minimal, avoiding
errors due to shadows. Similar conditions are achieved on days with high clouds, where
soft shadows are generated and do not significantly harm the captured information. It is
recommended that the flight be conducted as long as the weather conditions allow; other-
wise, you must interrupt the process, and wait for the right conditions or cancel the flight
session and reschedule.
To achieve reconstructions where PI geopositioning is required with a high level
of accuracy, control points can be incorporated into the measurement, referring to the
demarcation of milestones in the infrastructure, for which it is necessary to measure their
GPS position with a specialized instrument. These points will then be incorporated into
the photogrammetric process.
4.3. Data Processing
With the set of obtained images, we proceed to the processing of images. Using the
structure from motion (SfM) method, it is possible to perform a photogrammetric recon-
struction of the PI, obtaining digital three-dimensional models from the superimposition
of images. SfM is based on machine vision algorithms that automatically correlate the
camera orientation and positioning coordinates between the captured photographs, identi-
fying points of interest and characteristic coincidences between the photographs. At this
stage, if the control points are used, the control points must be introduced to improve the
quality of the reconstruction and obtain high-precision geopositioning. The point cloud
generated from SfM is densified using MultiView Stereo (MVS), which generates a dense,
higher-resolution point cloud.
4.4. Reconstruction BIM Model
It is possible to perform the geometric reconstruction of a BIM model of the PI.
The point cloud generated in the previous stage, together with the background of the
infrastructure under study (CAD drawings, previous models, various antecedents of its
structuring and materiality, etc.), will serve as the basis for the geometric reconstruction of
Sensors 2021,21, 6686 10 of 27
the 3D model on BIM platforms. Independent of the chosen BIM software, it is important
to generate a parametric model, with types of elements corresponding to the nature of the
actual infrastructure and following the general guidelines of the existing documentation.
The relevant modelling ordered and coded all the elements of the model, therefore a set of
these elements must be ordered and detailed for the inventory.
4.5. Definition of Maintenance Actions and Automated Worksheet Creation
Based on the generated BIM model, it is possible to obtain and visualize the inventory
of all the elements that compose the PI, according to their typology, materiality, and/or
other variables of interest. To obtain and manage the data associated with the inventory
in an orderly manner, it is necessary to order this information in spreadsheets (type MS
Excel), defining and indicating the status criteria and maintenance actions for each type of
PI element. For this type of evaluation, it is necessary to define standardized categories to
facilitate the processes of evaluation and prioritization of maintenance actions. Numerical
scales are recommended; for example, categorizations of values 1 to 5, where values 1 and
2 are assigned to those elements that do not require conservation, 3 and 4 to those that
require conservation to be programmed, and 5 for those that need urgent conservation.
The goal is to achieve the most automated form possible.
4.6. Definition of Maintenance Actions and Automated Worksheet Creation
The stated criteria according to the typology of the elements must be incorporated
as parameters to the BIM model. It will then be necessary to adapt or create parameters
for the specific elements, along with actions for the graphical display to be obtained
on the BIM platform (associated, for example, with display in colour scale according to
a category, actions, and/or maintenance priorities, as required). To finish the process,
the parametric BIM model is linked to the automated worksheet to obtain automatic
bidirectional data updates. The use of visual programming tools allows for the automatic
interconnection of BIM platforms with datasheets, using algorithms based on bidirectional
workflows, thus obtaining an asset management tool for port infrastructures, particularly
penetration springs. A code that allows for the bidirectional exchange of information
between spreadsheets and the BIM environment was developed. A simplified schematic of
the code created is shown in Figure 4.
Sensors 2021, 21, 6686 10 of 29
4.4. Reconstruction BIM Model
It is possible to perform the geometric reconstruction of a BIM model of the PI. The
point cloud generated in the previous stage, together with the background of the infra-
structure under study (CAD drawings, previous models, various antecedents of its struc-
turing and materiality, etc.), will serve as the basis for the geometric reconstruction of the
3D model on BIM platforms. Independent of the chosen BIM software, it is important to
generate a parametric model, with types of elements corresponding to the nature of the
actual infrastructure and following the general guidelines of the existing documentation.
The relevant modelling ordered and coded all the elements of the model, therefore a set
of these elements must be ordered and detailed for the inventory.
4.5. Definition of Maintenance Actions and Automated Worksheet Creation
Based on the generated BIM model, it is possible to obtain and visualize the inventory
of all the elements that compose the PI, according to their typology, materiality, and/or
other variables of interest. To obtain and manage the data associated with the inventory
in an orderly manner, it is necessary to order this information in spreadsheets (type MS
Excel), defining and indicating the status criteria and maintenance actions for each type
of PI element. For this type of evaluation, it is necessary to define standardized categories
to facilitate the processes of evaluation and prioritization of maintenance actions. Numer-
ical scales are recommended; for example, categorizations of values 1 to 5, where values
1 and 2 are assigned to those elements that do not require conservation, 3 and 4 to those
that require conservation to be programmed, and 5 for those that need urgent conserva-
tion. The goal is to achieve the most automated form possible.
4.6. Definition of Maintenance Actions and Automated Worksheet Creation
The stated criteria according to the typology of the elements must be incorporated as
parameters to the BIM model. It will then be necessary to adapt or create parameters for
the specific elements, along with actions for the graphical display to be obtained on the
BIM platform (associated, for example, with display in colour scale according to a cate-
gory, actions, and/or maintenance priorities, as required). To finish the process, the para-
metric BIM model is linked to the automated worksheet to obtain automatic bidirectional
data updates. The use of visual programming tools allows for the automatic interconnec-
tion of BIM platforms with datasheets, using algorithms based on bidirectional work-
flows, thus obtaining an asset management tool for port infrastructures, particularly pen-
etration springs. A code that allows for the bidirectional exchange of information between
spreadsheets and the BIM environment was developed. A simplified schematic of the
code created is shown in Figure 4.
Spreadsheets
with IP elements
(IP data)
SPREAD SHEET S
BIM MO DEL
IP BIM model
(3D parametric
model and IP data)
Element
Selec tion
1
Param etric
reading
2
Expor t to MS
Exce l
3
Param ete rs
CODE SCHEME
(Bidirectional exchange of information)
Data i mport
to the
param etr ic
model
3
Information
selection
2
MS Exce l
Information
1
ID element
Stru ctur al state
Frecuency of
inspection
Recomendation
Element anomalies
Anomal ies and
criteria according
to th e ty pes of
mater ial of the
elements
Visibility and
graphics filters
Qualif icat ion
acord ing to
anomal y
Structural state
Recomendation
Data e xport flo w f rom to spre adshee ts
Data import flow to 3D parametric model
Figure 4. Proposed code scheme.
Figure 4. Proposed code scheme.
5. Case of Application
The proposed methodology has been implemented in port infrastructure, correspond-
ing to a penetration dock built in 1912. The reinforced concrete structure was repaired in
1990, and no major repair work has been carried out since then. This dock is located in a
seismic geographical area with the potential occurrence of tsunamis, and it is also exposed
Sensors 2021,21, 6686 11 of 27
to tidal waves and strong waves, which, in winter season, force its closure. Figure 5shows
the location of the dock and the elements that make it up.
Sensors 2021, 21, 6686 11 of 29
5. Case of Application
The proposed methodology has been implemented in port infrastructure, corre-
sponding to a penetration dock built in 1912. The reinforced concrete structure was repaired
in 1990, and no major repair work has been carried out since then. This dock is located in a
seismic geographical area with the potential occurrence of tsunamis, and it is also exposed
to tidal waves and strong waves, which, in winter season, force its closure. Figure 5 shows
the location of the dock and the elements that make it up.
Figure 5. General description of port infrastructure case study (photographs by the authors. Central
picture from Google Maps).
At present, the infrastructure is not in operation and is intended for recreational and
sporting activities, therefore, there is a need to ensure its functionality for such activities
to be carried out safely, as no maintenance is currently being performed on it.
It is important to maintain infrastructure in a highly aggressive environment where
materiality is affected by the different pathologies described above. To meet this need, the
implementation of a maintenance management tool is proposed based on an integrated
BIM model with a maintenance proposal, facilitating the visualization of the elements and
their structural state, categorized according to the type of items and repair activities re-
quired. Figure 6 details the tools and software used to meet the objective of this applica-
tion, following the proposed workflow.
Photo processing and
point cloud
gener ations
Point cloud
Change cloud format
from dots to file. RCS
Creation of
parametric model,
parameters, and
structural evaluation
criteria
Context Ca pture Autodesk® ReCap Autodesk® Revit®
Obtaining data
from the
infrastructure
Modelo BIM
paramétrico integrado
Review of existing
infras tructure p lans
Autodesk®
AutoCAD®
Export/Import of dat a
Dynamo Microsoft® Excel®
Automated
maintenance
worksheet creation
BIM model
integration with
automated
maintenance
spreadsheets
Review of existing
document ation
Status report and
maintenance a ctions
Asset management tools
Autodesk® Inventor
Identification of
specialized elements
Modeling of
specialized elements
Figure 6. Flow for the generation of asset management tool.
Figure 5.
General description of port infrastructure case study (photographs by the authors. Central
picture from Google Maps).
At present, the infrastructure is not in operation and is intended for recreational and
sporting activities, therefore, there is a need to ensure its functionality for such activities to
be carried out safely, as no maintenance is currently being performed on it.
It is important to maintain infrastructure in a highly aggressive environment where
materiality is affected by the different pathologies described above. To meet this need,
the implementation of a maintenance management tool is proposed based on an integrated
BIM model with a maintenance proposal, facilitating the visualization of the elements and
their structural state, categorized according to the type of items and repair activities re-
quired. Figure 6details the tools and software used to meet the objective of this application,
following the proposed workflow.
Figure 6. Flow for the generation of asset management tool.
5.1. Photogrammetric Reconstruction and Development of the BIM Model
The IP is protected by a naval military zone, therefore, according to the regulations
established at the national level, it must have a special authorization from the institution to
Sensors 2021,21, 6686 12 of 27
which it belongs. In this case, the flight authorization was requested to the Port Captaincy
of Valparaiso.
A UAV DJI Phantom 4 Pro was used to take photographs, the characteristics of which
are shown in Table 1.
Table 1. Technical characteristics UAV DJI Phantom 4 Pro.
Resolution [MP] Opening Range Focal Length [mm] Sensor [mm]
20 (5672 ×3648) f/2.8–11 8.8 12.83 ×7.22-CMOS
Photographs are taken covering the entire surface and perimeter area of the pier with
oblique and vertical photogrammetry, as described in the proposed methodology, obtaining
a total of 148 photographs with an overlap of 80%. The registration was made at noon
(between 12:00 h and 12:45 h) on a day with high cloudiness (ideal conditions to avoid
shade in the structure). The UAV pilot toured the structure, maintaining the visibility
of the UAV, to avoid risks associated with the management of the equipment very close
to the seawater surface. The team did not record photographs under the infrastructure
because, after reviewing the background, it was identified that the elements undercover
are repetitive elements of the same geometry as the exteriors (as captured by the UAV),
therefore the photographs taken would be sufficient for the generation of the 3D model.
Table 2presents the setting parameters.
Table 2. Setting model parameters.
Parameter Value
Number of photos uploaded 148
Number of photos used 115
Percentage of photos used 78
Processing time 2 h 99 min
GSD 6.45 mm/px
Model scale 1:19
Image dimensións 5472 ×3078 px
Total Tie Points 28,242
Average Tie Points per image 1193
Average RMS error 0.47 px
Minimun RMS error 0.01 px
Maximum RMS error 1.77 px
For the application of photogrammetry and 3D scene reconstruction algorithms (SfM-
VSM algorithms), ContextCapture (Bentley) software was used, allowing for generation of
a digital 3D model from a set of imported photographs, the detection of camera parameters,
and the pose of each image entered. Through aerotriangulation, the program detects key
points and identifies similar points in different images. With this information, it is possible
to triangulate the positions of each of the key points using the pose delivered by the UAV
sensors, obtaining a cloud of scattered points with the location and corrected orientation of
each photograph obtained by the UAV. Figure 7presents part of the structure reconstructed
using ContextCapture software.
Sensors 2021,21, 6686 13 of 27
Sensors 2021, 21, 6686 13 of 29
Figure 7. Point Cloud Context Capture.
BIM structural modelling software is required for the reconstruction of the 3D model.
In this application case, we used Revit® (Autodesk®, Mill Valley, CA, USA), which stands
out for the modelling of elements from custom families and user-defined parameters, al-
lowing for a precise reconstruction, which, added to its massive use, interoperability, and
data export properties, make it an attractive asset management software [37]. Before 3D
modelling, Autodesk® ReCap was used to convert the point cloud format to a file RCS-
compatible with Autodesk® Revit. Infrastructure documentation (general CAD drawings,
reports, and sheets, with outdated information) was reviewed to identify parameters and
technical considerations. The elements of the infrastructure were modelled on Autodesk®
Revit based on the point cloud (RCS) and imported CAD drawings.
The process of modelling based on the cloud of points and CAD planes starts with
the creation of axes and reference planes, which will serve as a guide to locate the ele-
ments. Customized families were created for the creation of reinforced concrete elements
(slabs, beams, piles, slab protection), railings, and crinoline staircases. To create a generic
model for the berths (elements for boat moorings), we used the software Inventor® (Au-
todesk®, Mill Valley, CA, USA), which allows us to create custom models exportable to
Autodesk® Revit with more complex geometries (since Revit has a traditional construction
element approach). Figure 8 shows the reconstruction of the 3D model, from the import
of the point cloud and CAD drawings to the final model.
Figure 7. Point Cloud Context Capture.
BIM structural modelling software is required for the reconstruction of the 3D model.
In this application case, we used Revit
®
(Autodesk
®
, Mill Valley, CA, USA), which stands
out for the modelling of elements from custom families and user-defined parameters,
allowing for a precise reconstruction, which, added to its massive use, interoperability,
and data export properties, make it an attractive asset management software [
37
]. Before
3D modelling, Autodesk
®
ReCap was used to convert the point cloud format to a file RCS-
compatible with Autodesk
®
Revit. Infrastructure documentation (general CAD drawings,
reports, and sheets, with outdated information) was reviewed to identify parameters and
technical considerations. The elements of the infrastructure were modelled on Autodesk
®
Revit based on the point cloud (RCS) and imported CAD drawings.
The process of modelling based on the cloud of points and CAD planes starts with the
creation of axes and reference planes, which will serve as a guide to locate the elements.
Customized families were created for the creation of reinforced concrete elements (slabs,
beams, piles, slab protection), railings, and crinoline staircases. To create a generic model
for the berths (elements for boat moorings), we used the software Inventor
®
(Autodesk
®
,
Mill Valley, CA, USA), which allows us to create custom models exportable to Autodesk
®
Revit with more complex geometries (since Revit has a traditional construction element
approach). Figure 8shows the reconstruction of the 3D model, from the import of the point
cloud and CAD drawings to the final model.
Figure 9shows the generated BIM 3D model and its main elements: longitudinal
beams and crossbeams, slabs, batteries and protection batteries, metal elements such as
railings, crinoline staircases, and specialized elements such as bitts.
5.2. Definition of Anomalies and Maintenance Activities According to the Type of Elements
To carry out a structural evaluation of the elements that make up the infrastructure,
evaluation and categorization criteria were defined, together with maintenance activities.
The Design, Construction, Operation and Maintenance Guide of the Port Works Directorate
of Chile defines the main anomalies according to the types of material of the elements.
Tables 3and 4present the anomalies and degrees of deterioration of the main materials,
reinforced concrete, and metal elements.
Sensors 2021,21, 6686 14 of 27
Sensors 2021, 21, 6686 14 of 29
Figure 8. Reconstruction of the parametric IP BIM model in Autodesk. Revit, based on cloud of points and CAD planes.
(a) IP Point cloud; (b) Initial reconstruction of IP BIM model based on point cloud; (c) Development of IP BIM model; (d)
Reconstructed IP BIM model; and (e) Overview of reconstructed IP BIM model in environment.
Figure 8.
Reconstruction of the parametric IP BIM model in Autodesk. Revit, based on cloud of points and CAD planes.
(
a
) IP Point cloud; (
b
) Initial reconstruction of IP BIM model based on point cloud; (
c
) Development of IP BIM model;
(d) Reconstructed IP BIM model; and (e) Overview of reconstructed IP BIM model in environment.
Sensors 2021,21, 6686 15 of 27
Sensors 2021, 21, 6686 15 of 29
Figure 9 shows the generated BIM 3D model and its main elements: longitudinal
beams and crossbeams, slabs, batteries and protection batteries, metal elements such as
railings, crinoline staircases, and specialized elements such as bitts.
Figure 9. Elements of port infrastructure.
5.2. Definition of Anomalies and Maintenance Activities According to the Type of Elements
To carry out a structural evaluation of the elements that make up the infrastructure,
evaluation and categorization criteria were defined, together with maintenance activities.
The Design, Construction, Operation and Maintenance Guide of the Port Works Direc-
torate of Chile defines the main anomalies according to the types of material of the ele-
ments. Tables 3 and 4 present the anomalies and degrees of deterioration of the main ma-
terials, reinforced concrete, and metal elements.
Figure 9. Elements of port infrastructure.
Each degree of deterioration is evaluated with a rating ranging from 1 to 5 for each
anomaly, which was assigned to visually facilitate the degree of deterioration according to
the type of element (Table 5).
The criterion for determining whether the element requires maintenance will be
conditioned by the maximum note obtained between anomalies, where 1 and 2 do not
require, 3 requires but can wait, and 4 and 5 require urgent intervention considering that
the element is bad or very bad (Table 6).
In addition, maintenance activities are defined for the elements in question. For re-
inforced concrete elements, there is the repair of cracks (surface or deep fissure sealing),
steel replacement-concrete, structural repair, cleaning joint expansion in slabs, cleaning,
and painting for railings and bites.
Sensors 2021,21, 6686 16 of 27
Table 3. Anomalies and criteria elements of reinforced concrete.
Anomalies State Description
(I)
Cracking
Very good There is no indication
Good 0–10% presence of fissures
Regular 10–40% cracks without armour in sight
Bad
0–10% cracks with armour in sight or through the element
Very bad >10% cracks with armour in sight or through the element
(II)
Surface wear
Very good There is no indication
Good Surface wear areas
Regular Significant loss of surface grout
Very bad >20% loss of visible coating/armour
(III)
Armour corrosion
Very good There is no indication
Good 0–10% of the visible area with signs of corrosion
Regular 10–40% of visible area with signs of corrosion
Bad >40% of visible area with signs of corrosion
Very bad Section loss
(IV)
Break
Very good There is no indication
Good 0–10% coating detachment, no armour in sight
Regular Coating detachment, without visible armour
Bad >20% detachment of sections with visible armour
Very bad >10% element break or failure
Table 4. Anomalies and criteria metal elements.
Anomalies State Description
(I)
Deformation
Very good There is no indication
Good 0–10% dents without damage to corrosion protection
Regular 10–40% dents with damage to corrosion protection
Bad >20% loss of element symmetry axes
Very bad >10% section loss/element break
(II)
Corrosion
Very Good There is no indication
Good 0–10% of visible area with signs of corrosion
Regular 10–40% of the visible area with signs of corrosion
Very bad >40% of visible area with signs of corrosion
(III)
Loss of corrosion
protection
Very good There are no indications
Good 0–10% of the area visible without protection
Regular 10–40% of the area visible without protection
Bad >40% of the area visible without protection
Table 5. Criteria note elements.
Criteria Note Elements Rating
Very good 1
Good 2
Regular 3
Bad 4
Very bad 5
Table 6. The criteria for determining whether the item requires maintenance.
Maintenance Rating
Does not require 1
Does not require 2
Requires scheduled conservation 3
Urgent conservation 4
Urgent conservation 5
Sensors 2021,21, 6686 17 of 27
5.3. Creation of an Asset Management Tool
The anomalies presented, the evaluation criteria, and the maintenance activities de-
scribed were linked and automated in an MS Excel
®
spreadsheet; therefore, when modify-
ing the criteria of the anomalies, the structural condition of the element was automatically
updated, determining the urgency of maintenance. Figure 10 shows an extract from the
automated worksheet, where, from the created drop-down lists, it is possible to modify
the state of the item concerning an anomaly, its anomaly rating, and, in turn, the structural
state of the element corresponding to the maximum note of each of them.
Sensors 2021, 21, 6686 17 of 29
The criterion for determining whether the element requires maintenance will be con-
ditioned by the maximum note obtained between anomalies, where 1 and 2 do not require,
3 requires but can wait, and 4 and 5 require urgent intervention considering that the ele-
ment is bad or very bad (Table 6).
Table 6. The criteria for determining whether the item requires maintenance.
Maintenance Rating
Does not require 1
Does not require 2
Requires scheduled conservation 3
Urgent conservation 4
Urgent conservation 5
In addition, maintenance activities are defined for the elements in question. For rein-
forced concrete elements, there is the repair of cracks (surface or deep fissure sealing),
steel replacement-concrete, structural repair, cleaning joint expansion in slabs, cleaning,
and painting for railings and bites.
5.3. Creation of an Asset Management Tool
The anomalies presented, the evaluation criteria, and the maintenance activities de-
scribed were linked and automated in an MS Excel
®
spreadsheet; therefore, when modi-
fying the criteria of the anomalies, the structural condition of the element was automati-
cally updated, determining the urgency of maintenance. Figure 10 shows an extract from
the automated worksheet, where, from the created drop-down lists, it is possible to mod-
ify the state of the item concerning an anomaly, its anomaly rating, and, in turn, the struc-
tural state of the element corresponding to the maximum note of each of them.
Figure 10. Automated MS Excel
®
form.
The infrastructure asset management tool is based on the integration of the paramet-
ric BIM model with the automated spreadsheets in MS Excel
®
, so that each element repre-
sented in the model contains updated information regarding its anomalies, structural con-
dition, and recommended remedial activities. To achieve this goal, a reliable information
flow between Autodesk
®
Revit
®
and MS Excel
®
is required. For this information flow, Dy-
namo was used, an extension of Autodesk
®
Revit
®
based on visual programming, which,
Figure 10. Automated MS Excel®form.
The infrastructure asset management tool is based on the integration of the parametric
BIM model with the automated spreadsheets in MS Excel
®
, so that each element represented
in the model contains updated information regarding its anomalies, structural condition,
and recommended remedial activities. To achieve this goal, a reliable information flow
between Autodesk
®
Revit
®
and MS Excel
®
is required. For this information flow, Dynamo
was used, an extension of Autodesk
®
Revit
®
based on visual programming, which, from
visual elements knows as “nodes”, allows for the creation of custom algorithms to process
data or create complex geometries.
Before this step, it was necessary to develop a BIM model in Autodesk
®
Revit and
create parameters that would allow for storing the information of the automated work-
sheets. Therefore, parameters associated with the anomalies of the elements were created
according to their material and degree of deterioration. Figure 11 shows, as an example,
the parameters created for the infrastructure slabs, elements on which the explanation of
data import/export flows will be based.
To facilitate the visualization of the elements in the automated spreadsheets, it is
required that the information be entered in an organized way, without altering its previous
configurations, therefore additional parameters associated with the location of the elements
were created. For example, concrete slabs 1 to 6 have been listed using the parameter
created called Module. Figure 12 shows the export flow of these six elements, which has
been organized into three groups. Group 1 selects and organizes the model information
to be exported. Dynamo has a series of nodes that allow selecting the elements, by family
and by type, among others. In this case, since there are only six elements, the Select Models
Elements node was used to select the elements directly in the model. The SortByKey node
allows you to sort lists according to a specific parameter, for which use can be made of
the created location parameters. Therefore, this node has as its input the list of elements
to classify and the parameter for their classification; the parameter is specified using the
Sensors 2021,21, 6686 18 of 27
GetParameterValueByName, which obtains the information from the specified parameter of
the elements; however, these are disordered. In this way, the SortByKey code allows the
output of group 1 to be two lists ordered according to the indicated parameter, and list
0 contains the six elements of the slab ordered correlatively according to its “Module”,
a parameter contained in list 1.
Sensors 2021, 21, 6686 18 of 29
from visual elements knows as “nodes”, allows for the creation of custom algorithms to
process data or create complex geometries.
Before this step, it was necessary to develop a BIM model in Autodesk
®
Revit and
create parameters that would allow for storing the information of the automated work-
sheets. Therefore, parameters associated with the anomalies of the elements were created
according to their material and degree of deterioration. Figure 11 shows, as an example,
the parameters created for the infrastructure slabs, elements on which the explanation of
data import/export flows will be based.
Figure 11. Parameters created for reinforced concrete elements.
To facilitate the visualization of the elements in the automated spreadsheets, it is re-
quired that the information be entered in an organized way, without altering its previous
configurations, therefore additional parameters associated with the location of the ele-
ments were created. For example, concrete slabs 1 to 6 have been listed using the param-
eter created called Module. Figure 12 shows the export flow of these six elements, which
has been organized into three groups. Group 1 selects and organizes the model infor-
mation to be exported. Dynamo has a series of nodes that allow selecting the elements, by
family and by type, among others. In this case, since there are only six elements, the Select
Models Elements node was used to select the elements directly in the model. The SortByKey
node allows you to sort lists according to a specific parameter, for which use can be made
of the created location parameters. Therefore, this node has as its input the list of elements
to classify and the parameter for their classification; the parameter is specified using the
GetParameterValueByName, which obtains the information from the specified parameter of
the elements; however, these are disordered. In this way, the SortByKey code allows the
output of group 1 to be two lists ordered according to the indicated parameter, and list 0
contains the six elements of the slab ordered correlatively according to its “Module”, a
parameter contained in list 1.
Figure 11. Parameters created for reinforced concrete elements.
Sensors 2021, 21, 6686 19 of 29
Figure 12. Data export flow from Autodesk
®
Revit
®
and MS to Excel–Slabs.
Group 2 reads the parameter information you want to export to the automated
spreadsheets. Therefore, from the output of group 1, the list of ordered items is used (list
0), which is connected as an input to the GetParameterValueByName nodes specifying the
different parameters of the elements and, additionally, reads the UniqueId, which obtains
a list with the unique ID of the elements (which is generated by the default software). The
information obtained from each of the parameters is stored in lists through the ListCreate,
node; since this node returns the information in lists organized in rows, it is necessary to
use the Transpose node to transfer the data, so that, when exporting parametric data to
spreadsheets, each parameter is organized by columns.
In group 3, the Data, the ExportExcel node is used for data export; this node indicates
the path of the target file (FilePath node), the sheet on which the data will be written
(SheetName node), and the row and column from which the data will start to be filled
(StartRow and StarCol nodes, respectively). The numbering of rows and columns starts
from (0,0), that is, row 0 corresponds to row 1 of MS Excel, column 0 to column A, etc. The
described flow allows for sending all the information of the parameters associated with
the location and anomalies of the elements to the automated worksheets in an organized
manner, which is also modifiable from the drop-down lists created, as shown in Figure
13.
Figure 12. Data export flow from Autodesk®Revit®and MS to Excel–Slabs.
Group 2 reads the parameter information you want to export to the automated spread-
sheets. Therefore, from the output of group 1, the list of ordered items is used (list 0), which
Sensors 2021,21, 6686 19 of 27
is connected as an input to the GetParameterValueByName nodes specifying the different
parameters of the elements and, additionally, reads the UniqueId, which obtains a list with
the unique ID of the elements (which is generated by the default software). The information
obtained from each of the parameters is stored in lists through the ListCreate, node; since
this node returns the information in lists organized in rows, it is necessary to use the
Transpose node to transfer the data, so that, when exporting parametric data to spreadsheets,
each parameter is organized by columns.
In group 3, the Data, the ExportExcel node is used for data export; this node indicates
the path of the target file (FilePath node), the sheet on which the data will be written
(SheetName node), and the row and column from which the data will start to be filled
(StartRow and StarCol nodes, respectively). The numbering of rows and columns starts
from (0,0), that is, row 0 corresponds to row 1 of MS Excel, column 0 to column A, etc.
The described flow allows for sending all the information of the parameters associated with
the location and anomalies of the elements to the automated worksheets in an organized
manner, which is also modifiable from the drop-down lists created, as shown in Figure 13.
Sensors 2021, 21, 6686 20 of 29
Figure 13. Automated inspection form—Elements: Slabs.
Similarly, the flow was performed for the other elements, where in group 1 the infor-
mation is selected, in group 2 the UniqueID is specified, as well as the parameters of location
and anomalies of the elements, and, in group 3, the export of the elements themselves is
carried out. Figure 14 shows an example where the flow of group 1 is more extensive. This
case corresponds to the battery protections (modelled as a wall), where the number of
elements is greater, so other nodes are used to sort the information according to how you
want to visualize it in the forms. Prior to this, two parameters were created that will allow
organizing the elements in the forms: one corresponds to the “Side”, which can be East or
West, and the other corresponds to the “Transversal axis”, which goes from A–1 to A–19.
Figure 14. Data export flow from Autodesk
®
Revit
®
and MS to Excel–Protection RC Piles Group 1.
In this case, the selection of elements is made according to their typology through the
node Categories and AllElementOfType; in this way, all the walls created in the model are
selected. To filter only those that correspond to the battery protections, the node is ob-
tained. Parameter ByName was used to indicate the parameter “Side”, followed by a se-
quence of nodes that reaches FilterByBoolMask, which gives a list of Boolean (True/False)
values that allows for the generation of two separate lists of those elements on the east
and west sides. However, these lists are also ordered correlatively according to the trans-
verse axis; therefore, the nodes GetparameterValueByName and ListSortByKey are used
again, now obtaining two separate lists that are exported to the automated forms, where
the elements are grouped according to the “Side” and sorted according to the “Transverse
Axis”, as shown in Figure 15.
Figure 13. Automated inspection form—Elements: Slabs.
Similarly, the flow was performed for the other elements, where in group 1 the
information is selected, in group 2 the UniqueID is specified, as well as the parameters
of location and anomalies of the elements, and, in group 3, the export of the elements
themselves is carried out. Figure 14 shows an example where the flow of group 1 is more
extensive. This case corresponds to the battery protections (modelled as a wall), where the
number of elements is greater, so other nodes are used to sort the information according to
how you want to visualize it in the forms. Prior to this, two parameters were created that
will allow organizing the elements in the forms: one corresponds to the “Side”, which can
be East or West, and the other corresponds to the “Transversal axis”, which goes from A–1
to A–19.
Sensors 2021, 21, 6686 20 of 29
Figure 13. Automated inspection form—Elements: Slabs.
Similarly, the flow was performed for the other elements, where in group 1 the infor-
mation is selected, in group 2 the UniqueID is specified, as well as the parameters of location
and anomalies of the elements, and, in group 3, the export of the elements themselves is
carried out. Figure 14 shows an example where the flow of group 1 is more extensive. This
case corresponds to the battery protections (modelled as a wall), where the number of
elements is greater, so other nodes are used to sort the information according to how you
want to visualize it in the forms. Prior to this, two parameters were created that will allow
organizing the elements in the forms: one corresponds to the “Side”, which can be East or
West, and the other corresponds to the “Transversal axis”, which goes from A–1 to A–19.
Figure 14. Data export flow from Autodesk
®
Revit
®
and MS to Excel–Protection RC Piles Group 1.
In this case, the selection of elements is made according to their typology through the
node Categories and AllElementOfType; in this way, all the walls created in the model are
selected. To filter only those that correspond to the battery protections, the node is ob-
tained. Parameter ByName was used to indicate the parameter “Side”, followed by a se-
quence of nodes that reaches FilterByBoolMask, which gives a list of Boolean (True/False)
values that allows for the generation of two separate lists of those elements on the east
and west sides. However, these lists are also ordered correlatively according to the trans-
verse axis; therefore, the nodes GetparameterValueByName and ListSortByKey are used
again, now obtaining two separate lists that are exported to the automated forms, where
the elements are grouped according to the “Side” and sorted according to the “Transverse
Axis”, as shown in Figure 15.
Figure 14. Data export flow from Autodesk®Revit®and MS to Excel–Protection RC Piles Group 1.
In this case, the selection of elements is made according to their typology through
the node Categories and AllElementOfType; in this way, all the walls created in the model
Sensors 2021,21, 6686 20 of 27
are selected. To filter only those that correspond to the battery protections, the node is
obtained. Parameter ByName was used to indicate the parameter “Side”, followed by a
sequence of nodes that reaches FilterByBoolMask, which gives a list of Boolean (True/False)
values that allows for the generation of two separate lists of those elements on the east and
west sides. However, these lists are also ordered correlatively according to the transverse
axis; therefore, the nodes GetparameterValueByName and ListSortByKey are used again,
now obtaining two separate lists that are exported to the automated forms, where the
elements are grouped according to the “Side” and sorted according to the “Transverse
Axis”, as shown in Figure 15.
Sensors 2021, 21, 6686 21 of 29
Figure 15. Automated inspection form—Elements: Protection RC Piles.
In addition, to generate a bidirectional flow between MS Excel
®
to Autodesk
®
Revit
®
,
Dynamo algorithms were created that allow the import of data from MS Excel
®
to Auto-
desk
®
Revit
®
. Therefore, the information that is modified in the automated spreadsheets
will be uploaded to the BIM model, keeping the model updated according to inspections
carried out. Similar to export flows, these flows have been grouped into three parts.
Figure 16 presents an example of the scheduled flow for importing the slab inspection
data. In group 1, the data in the MS Excel
®
spreadsheet are read through the Data Im-
portExcel node, in which the path of the file and the name of the sheet containing the data
to be imported must be specified. The output of this node returns the information in a
series of lists by rows, therefore the List transpose node is very useful to organize the in-
formation as it comes from the original worksheet. In group 2, the information to be read
from the automated spreadsheets is specified and separated, and the GetItemAtIndex node
allows us to indicate the index of the list containing the parameter information, which
allows us to generate separate lists of the parametric information, which will be loaded to
the parameters specified in group 3 via the ParameterByName.
Figure 15. Automated inspection form—Elements: Protection RC Piles.
In addition, to generate a bidirectional flow between MS Excel
®
to Autodesk
®
Revit
®
,
Dynamo algorithms were created that allow the import of data from MS Excel
®
to Autodesk
®
Revit
®
. Therefore, the information that is modified in the automated spreadsheets will be
uploaded to the BIM model, keeping the model updated according to inspections carried
out. Similar to export flows, these flows have been grouped into three parts.
Figure 16 presents an example of the scheduled flow for importing the slab inspection
data. In group 1, the data in the MS Excel
®
spreadsheet are read through the Data Impor-
tExcel node, in which the path of the file and the name of the sheet containing the data to
be imported must be specified. The output of this node returns the information in a series
of lists by rows, therefore the List transpose node is very useful to organize the information
as it comes from the original worksheet. In group 2, the information to be read from the
automated spreadsheets is specified and separated, and the GetItemAtIndex node allows
us to indicate the index of the list containing the parameter information, which allows
us to generate separate lists of the parametric information, which will be loaded to the
parameters specified in group 3 via the ParameterByName.
In this way, when selecting an element in the model, it is possible to see, in the
properties tab, the updated inspection information, its structural condition, the frequency
of inspection, and the recommended activities according to the material of the elements,
information matching the automated spreadsheets (Figure 17).
Sensors 2021,21, 6686 21 of 27
Sensors 2021, 21, 6686 22 of 29
Figure 16. Data import MS Excel
®
to Autodesk
®
Revit
®
.
In this way, when selecting an element in the model, it is possible to see, in the prop-
erties tab, the updated inspection information, its structural condition, the frequency of
inspection, and the recommended activities according to the material of the elements, in-
formation matching the automated spreadsheets (Figure 17).
Figure 16. Data import MS Excel®to Autodesk®Revit®.
Sensors 2021, 21, 6686 23 of 29
Figure 17. Example display data in parametric BIM model.
For the asset management tool to be managed from the model and the MS Excel
worksheet to be updated, copies of elements have been created to which parameter values
created in Autodesk
®
Revit
®
have been assigned, to display in the parameters box a list of
all possible states of each anomaly as shown in Figure 18; the BIM model and the auto-
mated spreadsheets are modifiable, allowing a two-way flow of information from Auto-
desk
®
Revit
®
to MS and Excel.
Figure 18. Criteria for anomalies in Autodesk
®
Revit
®
.
Figure 17. Example display data in parametric BIM model.
Sensors 2021,21, 6686 22 of 27
For the asset management tool to be managed from the model and the MS Excel
worksheet to be updated, copies of elements have been created to which parameter values
created in Autodesk
®
Revit
®
have been assigned, to display in the parameters box a list of
all possible states of each anomaly as shown in Figure 18; the BIM model and the automated
spreadsheets are modifiable, allowing a two-way flow of information from Autodesk
®
Revit®to MS and Excel.
Sensors 2021, 21, 6686 23 of 29
Figure 17. Example display data in parametric BIM model.
For the asset management tool to be managed from the model and the MS Excel
worksheet to be updated, copies of elements have been created to which parameter values
created in Autodesk
®
Revit
®
have been assigned, to display in the parameters box a list of
all possible states of each anomaly as shown in Figure 18; the BIM model and the auto-
mated spreadsheets are modifiable, allowing a two-way flow of information from Auto-
desk
®
Revit
®
to MS and Excel.
Figure 18. Criteria for anomalies in Autodesk
®
Revit
®
.
Figure 18. Criteria for anomalies in Autodesk®Revit®.
5.4. Display of Final BIM Model
To facilitate the visualization of the structural state of the elements of the infrastructure,
graphic visibility filters were created in Autodesk
®
Revit
®
according to the structural state
of the element to determine the need and urgency of maintenance of each element. In this
way, it is possible to visualize the infrastructure with the corresponding colours, which
vary according to the information record after each inspection (Figure 19).
Additionally, two parameters have been created for all elements of the Autodesk
®
Revit
®
, the infrastructure, one of which indicates the frequency of inspection of the element
and, another, the recommended maintenance activities that must be validated and/or
supplemented by the engineer in charge of the inspection. Therefore, the performance of
the recommended maintenance activities will be conditioned by the rating of the particular
item. Figure 20 shows an example of a slab cloth in which, in addition to the structural state
properties, it is possible to visualize that an annual inspection, represented with the letter
A, should be carried out, as well as the recommended maintenance activities. Since this
element has a regular structural state, the indicated maintenance activities do not require
more urgency so that they can be programmed.
In this way, it is possible to visualize, in the model, both the structural state of
the elements, their rating, the location parameters, the inspection frequency, and the
recommended activities aligned to the automated forms that facilitate the inspection of the
port infrastructure, keeping both platforms constantly updated.
Sensors 2021,21, 6686 23 of 27
Sensors 2021, 21, 6686 24 of 29
5.4. Display of Final BIM Model
To facilitate the visualization of the structural state of the elements of the infrastruc-
ture, graphic visibility filters were created in Autodesk
®
Revit
®
according to the structural
state of the element to determine the need and urgency of maintenance of each element.
In this way, it is possible to visualize the infrastructure with the corresponding colours,
which vary according to the information record after each inspection (Figure 19).
Figure 19. Filter Visibility/Graphics created in Autodesk
®
Revit
®
.
Additionally, two parameters have been created for all elements of the Autodesk
®
Revit
®
, the infrastructure, one of which indicates the frequency of inspection of the ele-
ment and, another, the recommended maintenance activities that must be validated
and/or supplemented by the engineer in charge of the inspection. Therefore, the perfor-
mance of the recommended maintenance activities will be conditioned by the rating of the
particular item. Figure 20 shows an example of a slab cloth in which, in addition to the
structural state properties, it is possible to visualize that an annual inspection, represented
with the letter A, should be carried out, as well as the recommended maintenance activi-
ties. Since this element has a regular structural state, the indicated maintenance activities
do not require more urgency so that they can be programmed.
Figure 19. Filter Visibility/Graphics created in Autodesk®Revit®.
Sensors 2021, 21, 6686 25 of 29
Figure 20. Inspection frequency and maintenance activities—Element: Slab.
In this way, it is possible to visualize, in the model, both the structural state of the
elements, their rating, the location parameters, the inspection frequency, and the recom-
mended activities aligned to the automated forms that facilitate the inspection of the port
infrastructure, keeping both platforms constantly updated.
6. Discussion
In the literature, works related to the method proposed in this research, where the
use of UAVs (as well as in combination with scanners), point cloud, and BIM for facility
management is integrated. The applications are focused on knowing, at different levels of
detail, the condition of structures such as bridges [44] and towers [45], as well as uses for
heritage BIM (HBIM) [46,47]. The capture of damage in these works is obtained from non-
invasive methods in contact with the structure and the identification from images ob-
tained with the UAV. Thus, these articles offer different alternatives for capturing damage
and parameters of interest to input into a BIM model. However, no detail of the general
process applied would allow for replication of the process in other situations. Moreover,
no applications to maritime works were found.
This research, along with being applied in a case not seen before in the literature,
offers a generic and replicable method for other structures. In addition, our proposal seeks
to be a management tool, allowing its exploitation both for users who do not use BIM
(using only the structure status registration form) and for BIM users on the parameterized
model. Thus, this is intended to be a methodological work focused on applied research. It
differs from other related papers, generating a generic and replicable methodology for
other structures. Also, we illustrate the application of the method with a detailed applied
case, facilitating understanding and replication for researchers and practitioners.
The proposed recommendations provided an orderly acquisition of photographics
through UAVs for the generation of point clouds. With this, together with the technical
background and drawings of the project, it was possible to reconstruct a parametric BIM
model of the PI. Although a BIM model of all elements of the PI was performed, and the
current conditions of the PI with respect to the outdated plans and technical background
were rectified, limitations in the model’s photogrammetric reconstruction were identified.
Despite the high resolution of the images acquired, the structure’s sea movement and
shadows did not allow for the correct reconstruction of all the exterior pillars. In addition,
Figure 20. Inspection frequency and maintenance activities—Element: Slab.
6. Discussion
In the literature, works related to the method proposed in this research, where the
use of UAVs (as well as in combination with scanners), point cloud, and BIM for facility
management is integrated. The applications are focused on knowing, at different levels
of detail, the condition of structures such as bridges [
44
] and towers [
45
], as well as uses
for heritage BIM (HBIM) [
46
,
47
]. The capture of damage in these works is obtained from
non-invasive methods in contact with the structure and the identification from images
obtained with the UAV. Thus, these articles offer different alternatives for capturing damage
and parameters of interest to input into a BIM model. However, no detail of the general
Sensors 2021,21, 6686 24 of 27
process applied would allow for replication of the process in other situations. Moreover,
no applications to maritime works were found.
This research, along with being applied in a case not seen before in the literature,
offers a generic and replicable method for other structures. In addition, our proposal seeks
to be a management tool, allowing its exploitation both for users who do not use BIM
(using only the structure status registration form) and for BIM users on the parameterized
model. Thus, this is intended to be a methodological work focused on applied research.
It differs from other related papers, generating a generic and replicable methodology for
other structures. Also, we illustrate the application of the method with a detailed applied
case, facilitating understanding and replication for researchers and practitioners.
The proposed recommendations provided an orderly acquisition of photographics
through UAVs for the generation of point clouds. With this, together with the technical
background and drawings of the project, it was possible to reconstruct a parametric BIM
model of the PI. Although a BIM model of all elements of the PI was performed, and the
current conditions of the PI with respect to the outdated plans and technical background
were rectified, limitations in the model’s photogrammetric reconstruction were identified.
Despite the high resolution of the images acquired, the structure’s sea movement and
shadows did not allow for the correct reconstruction of all the exterior pillars. In addition,
it was not possible to access or reconstruct the bottom side of the infrastructure due to
the swell and the absence of light. Taking photographs in these conditions with UAVs
represents a risk for the equipment. In addition, a reconstruction with pictures is not
possible in these conditions (low light and many shadows). Other reconstruction techniques
of existing infrastructure could be used (such as Lidar sensors or 3D scanning). However,
the team did not have this equipment. In addition, the research team aimed to use low-cost
tools to facilitate the use of the methodology; therefore, these other tools were discarded.
An automated Excel spreadsheet was developed, containing information on all the
elements of the PI, their ID coding, structural condition, and maintenance measures. In ad-
dition, the BIM model was able to incorporate all this information, together with the
visualization of the color scales associated with the structural states. The code created
allows for the bidirectional connection of data between both work environments. Thus,
the maintenance manager will perform his inspections from Excel or Revit, and the in-
formation will be updated and synchronized in the other platform. Moreover, if new
elements are created in excel or Revit, the other platform will recognize them and update
the information, maintaining the bidirectional synchronization.
The application of our methodology and the case study involve certain obstacles.
The main difficulty lies in the complete visualization of the structure, where it is not
possible in certain cases. In the case study, it was not possible to access the pier’s piles,
where, in addition, there were not good lighting conditions. This problem could be solved
by accessing old plans of the structure, which are not always available. Another obstacle
is the reconstruction of complex elements to model with photogrammetry. In this case,
the cranes of the pier are elements that, to be well represented in the model, require a
special flight strategy. To make the application of the methodology efficient, it is important
to be clear about the detailed requirement of the elements to be controlled. In cases where
a detail of the component is not required, a geometrically simplified version can be chosen,
as in the case of the dock cranes.
7. Conclusions
This investigation identified the main deficiencies and difficulties of the plans for the
maintenance of port infrastructures that are associated with an inefficient inventory of
elements, with the lack of existing information, erroneous digitization in the transfer of
information, little use of asset management tools, and difficulty of access. Thus, processes
involving a maintenance plan, such as inventory generation or infrastructure inspections,
are time-consuming and unreliable. This information helped to clarify the need to maintain
Sensors 2021,21, 6686 25 of 27
this type of infrastructure to prevent progressive damage over time that would lead to
higher repair costs.
An asset management tool was developed using technologies and methodologies as
potential tools to optimize traditional processes involving maintenance plans. A code was
developed and implemented for bi-directional exchange between the BIM environment
and the traditional IP management spreadsheets. From this point, the advantages of the
proposed methodology are clearly and objectively shown, managing to efficiently capture
the information needed to generate clear, orderly, and dynamic asset management.
The proposed methodology was implemented in port infrastructure, particularly
a penetration dock where a large number of the elements that make up the dock are
immersed in seawater and are affected by salinity and the marine environment, developing
various pathologies which must be controlled to avoid progressive deterioration of the
infrastructure. The structural state of the elements was obtained from visual inspection,
and the categorization of structural damage along with these maintenance activities was
defined according to material, information that can be easily accessed in the digital model
and in the MS Excel spreadsheets. Through visual programming, it was possible to generate
a two-way flow of automatic import and export of information, which allows for the digital
model to be kept up to date and with a clear visualization of the structural state of each
element and its maintenance activities, presenting the possibility of handling this tool from
the MS Excel spreadsheets or from the same model generated in Autodesk Revit. The tool
developed proves to be very useful for optimizing maintenance activities and keeping an
up-to-date record of the activities carried out. To determine the structural condition of the
infrastructure in greater detail, it is advisable to supplement the results obtained in visual
inspection with laboratory or in situ tests, whether destructive or nondestructive. Among
the applicable tests are the compressive strength test, the strength of the reinforcements,
and carbonation, among others. In this way, it will be possible to know the current state of
the elements and define maintenance actions that complement those already established,
generating a complete maintenance plan that addresses the current deficiencies of the
elements of the infrastructure.
The digital reconstruction of a historic infrastructure by photogrammetry with UAVs
allows for the centralization of documentation and dispersed existing information, which,
added to the interoperability properties and an automation tool, allows for the develop-
ment of a management tool for the maintenance of the infrastructure, which concentrates
the characteristics and dimensions of the elements, their current structural state using a
color scale according to the structural evaluation, the urgency of intervention, and the rec-
ommended maintenance activities required according to the anomalies and deterioration
of each element, contributing significantly to FM activities.
As a future line of research, we propose to study the efficiency of the developed
asset management tool and its usability over time in real applications to optimize tra-
ditional maintenance methods. In this sense, the new methodologies and technologies
that accelerate the digital transformation in construction would allow, in the following
years, the planning of predictive maintenance for infrastructures. The use of digital twins
or digital twins in industry 4.0 is based on the identical virtual representation of a real
environment in all its aspects, in which it is possible to simulate scenarios of all kinds
and to know the behaviour that the infrastructures would have without affecting the
behaviour, which would make it possible to define maintenance activities avoiding the
development of progressive damage, speeding up current processes, increasing resource
efficiency, and generally facilitating decision-making associated with different aspects,
opening up possibilities for the development and implementation of predictive mainte-
nance of infrastructures by drawing on the full potential of emerging technologies and
methodologies in the AECO industry.
Sensors 2021,21, 6686 26 of 27
Author Contributions:
This paper represents the results of teamwork. C.J.-B., E.A. and F.M.-L.R. de-
signed the research methodology. C.J.-B. carried out the literature review, methods, and experiments.
All of the authors worked on the results, discussions, and conclusions of the manuscript. Finally,
R.F.H., F.M.-L.R., and E.A. reviewed and edited the manuscript. All authors have read and agreed to
the published version of the manuscript.
Funding:
This research was funded by CONICYT grant number CONICYT-PCHA/International
Doctorate/2019-72200306 for funding the graduate research of Muñoz–La Rivera.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments:
The authors wish to thank all organizations participating in this study as well
as the experts for the insight provided. The authors wish to thank the TIMS space (Technology,
Innovation, Management, and Innovation) of the School of Civil Engineering of the Pontificia
Universidad Católica de Valparaíso (Chile), where part of the research was carried out.
Conflicts of Interest: The authors declare no conflict of interest.
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... Estudos como os deRodrigues et al. (2023),Matos et al. (2023),Tan et al. (2022), Xu e Turkan (2020) eRibeiro et al. (2020) discutem superficialmente as possibilidades e recomendações para essa integração. Em contraste,Jofré-Briceño et al. (2021) desenvolveram um fluxo de trabalho detalhado para a manutenção de infraestrutura portuária, mas sua abordagem apresenta limitações, pois a representação das manifestações patológicas no modelo BIM é feita apenas por alteração das cores dos elementos modelados, o que se torna inadequado quando essas manifestações têm características variadas ao longo de um elemento ou sistema. ...
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The chloride-induced steel corrosion is one of the main causes of deterioration for reinforced concrete structures exposed to marine environments. The chloride ingress into reinforced concrete structures is even more complex since it depends on random parameters linked to transport and chemical properties of materials, which results in variability of corrosion initiation. This variation raises the need of statistical approaches to evaluate the risk of corrosion initiation due to chloride ingress. To address this issue, we use sensitivity analysis to identify the influence of input parameters on critical length of time before corrosion initiation predicted by our chloride diffusion model. Exceedance probabilities of corrosion initiation time given that input parameters exceed certain thresholds were also calculated. Results showed that the corrosion initiation time was most sensitive to: chloride effective diffusion coefficient De in concrete, that is a parameter controllable by relevant stakeholders; surface chloride concentration Cs, a non-controllable parameter depending on surrounding conditions. Reducing the chloride diffusion coefficient enables us to postpone the maintenance of structures. However, the interaction between controllable parameters and non-controllable surrounding conditions was revealed influential on the reliability of results. For instance, the probability that corrosion initiation time exceeds 15 years given an effective diffusion coefficient (De) equal to 0.1 × 10⁻¹² m²⋅s-1 can vary from 19 to 41% according to stochastic variations of chloride concentrations (Cs) values. Postponing the corrosion initiation time was combined with a decreasing probability of its occurrence.
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This paper studied the environmental conditions and corrosion behaviour of mortar samples at two different marine tidal zones and investigated the correlation among the environmental conditions, corrosion rates, and corrosion products. From the experimental results, the concrete structure damage is a function of numerous correlated factors such as the temperature, humidity, and corrosion products. The chloride penetration rate increased by 15% when the humidity increased by 10% and temperature increased 4 °C. Chloride content is the main factor intensifying the reinforcement corrosion. Although the high temperature, humidity, and chloride concentration aggravate the early corrosion of reinforcement, the role of resultant corrosion products shows more important in the developing stage of corrosion damage. The resultant corrosion products affect further corrosion persistence in a complex way, because in some cases, corrosion products-caused cracks will promote corrosion, while in others, corrosion is reduced by sealing the pores with products.