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ABSTRACT
ABSTRACT
A restoration and conservation project for a building with heritage values requires an increasingly efficient and sustainable methodology. Based on a collaborative ‘Teamwork’ HBIM (Historic Building Information Modelling) project, this paper aims to describe the technical processes applied to a 16th-century historic building to support an open and interoperable workflow between the participating agents. The process is transparent and controllable by operators and disciplines, ensuring direct and continuous access to project data. The study focuses on implementing effective procedures for the identification and classification of heritage architecture.
The first stage comprises the analysis of the geometry and materiality of the existing architecture, using data acquisition technologies such as Terrestrial Laser Scanning (TLS) and Structure-from-Motion (SfM) photogrammetry. The information modelling of the historic building begins with a medium level of knowledge, based on the metric survey and enriched by the materiality of the textures deriving from the point cloud. This enables a modelling approach that fits building components to the real geometry of the historic building, considering the deformations and irregularities that occur over time.
In the next phase, the BIM project is developed through the analysis of the construction characteristics, materials, and architectural structuring in the historical evolution of the building. The difference between intervening in architectural heritage and new construction lies in the search for the transposition of construction techniques in walls with a long history, thus requiring classification and sectorisation of the various systems used. It is then required to segment the construction systems based on a semantic study of the walls that make up the envelope of the historic architecture. Programming objects in Python within the BIM platform enables the automated identification processes.
The method is applied in the identification of the integrating elements of a larger construction entity, such as the stone ashlars of the masonry wall, and the classification by their construction-temporal dating. The main novelty of this research is the use of the object-oriented programming language (OOP), which automates operations based on an open-source structure and allows the operability of cataloguing, classification, and reuse characteristics.
1. Introduction
In the field of Historical Heritage, there is a need for an effective analysis of these construction systems and objects when they are subjected to a restoration process. However, modelling procedures for architectural elements and objects from art history are complex given the combination of flat and organic-shape geometry. In this sense, the BIM (Building Information Modelling) methodology applied to Heritage (hereinafter, HBIM) constitutes a graphic and semantic information management system that allows the integration of data from scientific analyses. It is a 3D digital data operator, which greatly benefits intervention projects since it effectively incorporates the entire Heritage conservation cycle; from the design phase, through work planning, and physical data recording, to maintenance and monitoring of future deterioration. At the level of the geometric record, the massive data capture systems (MDCSs) configure an exhaustive architectural morphology for the enhancement of the digital document. The sustainability of the system is also an important aspect since it increases the performance optimisation of the building analysis; it can be considered connected with energy efficiency, improving the comfort and quality of the works of art that are kept inside (Khodeir, Aly, and Tarek 2016). Besides, the synchronisation of the operators takes place in the same BIM platform as a server; for the different work processes conducted, restrictions and openings are established (García Valldecabres, López Gonzalez, and Jordán Palomar 2016). Therefore, the HBIM platform allows the integration of various areas of knowledge and the applicability of the system in architectural and archaeological restoration.
This research aims to organise an HBIM project for the classification of elements and construction systems of the heritage model. This is carried out through evolutionary and historical channels that have been decisive for the creation of its current architecture. Starting from reality capture through metric surveys using Laser Scanning Techniques (TLS) and Structure-from-Motion (SfM) photogrammetry studies, the building has been subjected to a systematic study of the construction systems of its architecture, highlighting the singularities of the materials and the different techniques used. Semantic segmentation of walls, floors, and roofs has been carried out based on these studies. Based on automation through object programming in Python, this work delves into an effective methodology to identify and classify the building components: parts of masonry walls, frame beams, floor structures, and roof skirts.
2. Related work
The current BIM methodology, as expected, is providing great benefits to the AECO (Architecture, Engineering, Construction & Operations) sector. The objective is to develop an integrated project of the building or infrastructure, including the construction systems and all associated information. This information facilitates the promotion of the different processes in a coordinated, systematic, and productive way by all the participating agents. In a sector as standardised as construction, the new methodology makes it possible to advance in the definition of the architectural project, avoiding unforeseen events, contradictions, and interference between facilities, which would result in a reduction of unnecessary costs. This issue of sustainability has to be applied to the process of building the Historical Heritage, facilitating collaborative work between different disciplines. The HBIM concept arises from the need to incorporate efficiency and benefits in the heritage environment (Murphy, McGovern, and Pavia 2009). This line of research and implementation of the BIM methodology in Historical Heritage continues to advance and obtain great achievements; with exploration and improvement in BIM technology and components (Logothetis, Delinasiou, and Stylianidis 2015), in modelling using BIM software (Pocobelli et al. 2018), in studies focused on platform tools and methodologies (López et al. 2018), in the uses and their protocols (Jordan-Palomar et al. 2018), as well as the levels of maturity (Merchán et al. 2018). Currently, maintenance and preventive conservation in new buildings are focused on the use of digital twins (DT) (Jouan and Hallot 2020). There are specific studies that reflect on the need to adequately incorporate the specific characteristics and values of historical architecture or Archaeology of Architecture in the HBIM project (Nieto Julián and Moyano Campos 2014), (Angulo-Fornos and Castellano-Román 2020), (Talaverano, Fragero, and De Los Ángeles Utrero Agudo 2021). In this specific area, some studies are based on a BIM project based on a process of surveying and architectural analysis of the historic building, whose typologies evolve according to the level of knowledge (Rua and Gil 2014). Another challenge presented by the Scan-to-BIM methodology is the description of the surface to be modelled. Importing massive point data via TLS and SfM/MVS eases the 3D modelling by transferring 3D data to parametric objects. These recorded data provide great advantages (Remondino 2011) and can be extracted at different levels (Manferdini et al. 2008). Modelling is especially focused on complex elements (Dore and Murphy 2017) and the generation of three-dimensional NURBS surfaces that provide the geometric constraints of the surfaces (Barazzetti et al. 2015) and (Oreni, Brumana, and Banfi 2014). Architectural heritage has the intrinsic peculiarity of historical evolution, which substantially differentiates it from new construction. In this context, two features can be managed by an HBIM project: i) the transposition of the different construction techniques and materials throughout the building’s life cycle; and ii) the effects of natural agents such as erosion, human action, and seismic movements. With the added value that most of the construction elements have an artistic nature, old construction systems mostly consist of masonry walls or stone cladding, which are techniques with systems different from those used today. The tools required are also different, and the skills of the operators arise from knowledge inherited from their ancestors. For this reason, an intervention or conservation project of built heritage must consider the temporal evolution of the building with a view to define a set of construction actions, which have been transposed over the centuries. It could be concluded that the great difference between a recent construction and a historic work is that the former lacks that altering time sequence, as it is the result of an exclusive and exceptional project. The field of knowledge that studies the stratigraphy of architectural heritage is called Archaeology of Architecture. Although originally referred to the geological and archaeological layers, it had its beginnings with the researcher Roberto Parenti in 1985 (Tabales Rodríguez 1997), who conducted the first systematic study of a building from the paramental point of view. Subsequently, from the second decade of the 21st century onwards, the so-called Archaeology of Architecture took shape, in which other influential researchers such as Doglioni (1988) and Brogiolo and Cagnana (2012) participated. Paramental studies are intrinsically linked to the so-called stratigraphic units, essentially based on the structure of a correlative numerical matrix, called the Harris matrix (Harris 2014). It resembles the configuration of a tree, with its branches configuring a temporary classification diagram for the graphical representation of the interfaces (layers) arranged in chronological order.
The 21st century has brought a vertiginous revolution in digitisation. Nowadays, everyday life is shaped by the integration of multiple technologies (Gray and Rumpe 2015) that improve the functionality and productivity of our activities. The Architectural Heritage knowledge area has the opportunity to participate in these technological advances so that the next institutional plans for preservation are closer to sustainable and efficient management. The BIM methodology enables effective applications and specific tools for its applicability, thus benefiting the workflow of the multidisciplinary team involved in the conservation project. In this way, the interoperability of agents such as archaeologists, architects, historians, engineers, and restorers, is reinforced.
The BIM methodology is increasingly being applied in the field of Cultural Heritage, although the main approach varies according to the specific line taken by researchers and academics. There is a large number of researchers who focus their efforts on capturing and accurately representing the geometry of the historic building (Antón et al. 2018), (Tang et al. 2010) and (Thomson and Boehm 2015) or on the parametric modelling of the complexity of architecture without losing artistic quality (Castellano-Román and Pinto-Puerto 2019). Other research has focused on the use of BIM to generate semantic knowledge of heritage, with the management of other data associated with graphic representation for the maintenance and conservation of built heritage (Bruno and Roncella 2019). In the 16th-century heritage building selected in this research, the aim is to create an efficient and sustainable process to address its architectural and artistic values. This intervention project is based on the BIM methodology (HBIM Project) to constitute a record and an interdisciplinary management system of all the data associated with the subsequent stages of the conservation of the selected building.
3. Methodology
This research focuses on the structuring of a restoration and conservation HBIM project, for which a three-dimensional model is developed. All the documentation compiled and adaptations to subsequent studies or new findings will be incorporated into the collaborative project. The specific information is to be managed and entered into a common ‘3D database’ by the agents of the different disciplines involved.
3.1. Case study
The project, still under development, aims to complete the restoration of the 16th-century Hermitage or Chapel of St. Anthony of Padua (known as San Brais), dated 1528., a small and simple Christian construction. However, its main façade presents an outstanding architecture, with an arched doorway decorated with stripped pilasters and crowned with semi-pinnacles. A moulded cornice finishes off a split pediment in the centre, where there is a bell tower (Figure 1).
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03 June 2022Figure 1. Exteriors of the San Brais Chapel. 360° exploration from the Leica JetStream viewer. Source: Enrique Nieto.
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Figure 1. Exteriors of the San Brais Chapel. 360° exploration from the Leica JetStream viewer. Source: Enrique Nieto.
The building requires urgent intervention to address structural problems and water seepage, both in the roof of the building and by capillarity in the walls, as it lacks perimeter drainage.
3.2. The ‘Teamwork’ HBIM project
The restoration project is based on continuous interdisciplinary research to strengthen technical decisions to provide concrete and effective solutions to the problems defined and located in the architectural heritage of the Chapel of San Brais.
The Teamwork HBIM project is fully supported by the Open-BIM Methodology, where participants and collaborators, in their different roles, share and transfer information about the building to be rehabilitated, in its architectural, construction, and historical facets, in a coordinated manner. Emphasis has been placed on the use of the most effective technical means to facilitate the channeling of the specific data by each discipline involved in the project, thus reinforcing a collaborative workflow of specialists that benefits the orderly structuring of information and its consensus. The data will always be available to all the actors in a 3D database, which may be updated in subsequent interventions or due to new findings.
The structure of the project can be synthesised as follows:
The ‘Teamwork’ collaborative restoration project is managed in the BIM platform (in this case, ArchiCAD). The project is shared by the agents involved: the principal architect, execution engineer, BIM manager, and moderators of the drafting team.
The project is uploaded to the BIMcloud (Graphisoft 2020) to be accessible to all participants, thus facilitating data interoperability. In this way, depending on their assigned role, each member of the team can provide specific information. In the flow of information between disciplines, the architect-archaeologist is aided by the exchange of data from predefined schemes; for this case, the import/export interoperability data table is applied based on the xlsx format (Moyano et al. 2021), (Nieto-Julián, Cavada, and Campos 2021).
Next, to reinforce the interoperability of Open BIM with external agents or consultants, the HBIM project will be managed in IFC (Industry Foundation Classes) format, making the flow of information more flexible with the created 3D database.
The generated IFC model will be approved in each established time phase to be uploaded to the server that supports the Database, marked with a revision ID, and accessible by all team members and the owners. This open system allows the BIM model data to be synchronised with other digital platforms for data management, processing, and analysis.
The phases developed of the restoration and conservation project for San Brais Chapel will be presented, explaining the methodology carried out in each one, from the beginning to date.
3.3. Previous work. Accurate reality capture
The 3D survey of the building and its surroundings (Figure 2) allows the geometry of the architecture and topography to be captured. Figure 3 shows an orthogonal view of the point cloud from the HBIM project. In this way, before undertaking the modelling process, the structural problems of the building due to subsidence of its granite stone masonry walls were located; the wooden framework of the roof skirts was also marked, which needs urgent intervention, mainly in the choir area and in the porch attached to the right side (Figure 9).
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03 June 2022Figure 2. Visualisation and exploration of the global point cloud, with measurements (JetStream viewer Leica). Source: Enrique Nieto.
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Figure 2. Visualisation and exploration of the global point cloud, with measurements (JetStream viewer Leica). Source: Enrique Nieto.
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03 June 2022Figure 3. Front view of the point cloud, from the left side of the Chapel of San Brias. HBIM ArchiCAD project.
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Figure 3. Front view of the point cloud, from the left side of the Chapel of San Brias. HBIM ArchiCAD project.
3.4. Definition of the HBIM project
The Level of Accuracy or precision (LOA) and its specifications is a reference standard that enables AECO professionals to specify the accuracy and means by which to represent and document the existing conditions (USIBD) (Magazine 2019). Having a clearly defined LOA eases the definition of the intended use of the documentation and allows downstream users to better understand the usability and limitations of that documentation they are receiving. The different levels of precision are stated in terms of standard deviation to document existing building systems and subsystems. In a BIM project of an existing building, the modelling process refers to the data provided by the processed geometric dataset, with the Level of Development (LOD) being significant. In the case of a heritage building and its peculiarities, it is essential to properly select these measurement procedures and equipment. The studies carried out in the Capela de San Brais obtained a very acceptable level of processing precision (Nieto-Julián, Cavada, and Campos 2021a) and are suitable for the validation process. These LOD are progressively enriched in the different phases of the project (Brumana et al. 2018) and the different phases of execution. These levels have been defined in recent literature and as the origin of the work by Fai and Rafeiro (2014). The studies carried out in this phase of the research circumvent the influence of the data acquisition and processing methods. Instead, the focus is on the validation criteria of the point cloud so that they are efficient in semantic segmentation within the BIM environment. Research has addressed the precision analysis of point cloud data (Lehtola et al. 2017), although there are other works related to a more complete validation in which quality criteria of the cloud data are established, such as point cloud data for Scan-to-BIM (Rebolj et al. 2017) and Scan-vs-BIM (Wang et al. 2019). In addition to accuracy analysis, those authors determined parameters for point cloud integrity and density that are required to model various building elements. For precision, researchers report deviations in reference data sets directly or refer to international specifications such as LOA (Magazine 2019), LOD (Forum 2020), or Level of Detail (DOcPlayer 2022).
The USIBD LOA is structured in five levels and two digits, from a low-level LOA10 to exceeding the high-level LOA50 (). Hence, this classification differs from the LOD series by the BIM Forum, which uses three digits. The LOA framework is structured primarily on the measured precision, which represents the range of standard deviation that must be achieved from the final measurements taken, regardless of the measurement method used; and a second precision is represented, understood as the range of standard deviation that must be achieved when the model is completed. Therefore, in addition to specifying the measured precision, it must be established whether the precision specified in terms of standard deviation must be absolute or relative (Figure 4).
Table 1. USIBD LOA Classification
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03 June 2022Figure 4. The LOA framework is further structured into two parts: Measured Accuracy against Represented Accuracy. USIBD.
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Figure 4. The LOA framework is further structured into two parts: Measured Accuracy against Represented Accuracy. USIBD.
The BIM methodology is an efficient standard system for the AECO industry and as such requires language standards. There are currently several references to establish standards in 3D modelling: BIMFORUM, the British Standards Institution (BSI), CanBIM, and the US Construction Documentation Institute (USIBD). They all establish graded levels of geometric details and associated information for different phases of a project. For the most part, these standards are created for new construction but do not ease transfer to BIM for existing buildings. Studies such as the one by Graham, Chow, and Fai (2018) aim at the implementation of the Level of Detail, information, and precision in the construction information modelling of existing and heritage buildings. As a case study, the authors selected the heritage Parliament Hill in Ottawa, Canada. They applied the LODIA Level (detail/information/precision) developed by Carleton Immersive Media Studio (CIMS) and established a guide to identify and evaluate the LOD, LOI, and LOA of BIM and HBIM projects.
The LO(D) describes the graphical representation of the model and follows existing standards, from the symbolic placeholder to the detailed model (LOD 0-1-2-3-4). The choice is determined by the available reference material and the purpose of the model. The LO(I) is the embedded information contained in the BIM elements. This may include information on the materials, manufacturer, and source data. Unlike in new construction, HBIM relies on existing plans, specification documents, and on-site observations to determine the structure, material, and more. The type of embedded information is not limited to traditional categories such as materiality or size of structural components but may contain comments from the specialists (architect/archaeologist/historian/restorer) of the element analysed or if additional verification is needed.
Regarding the LO(A) category, it accounts for the level at which the deflection and deviation of the building elements are modelled in the BIM. It is worth highlighting that, in this research, the LODIA acts as a compendium of three levels and five classification categories, thus making HBIM based on diverse and inconclusive information. Also, the areas or elements of greater heritage value should be modelled with a higher LODIA compared to the rest of the less significant components of the ‘container’ building.
In the current development phase of the Capela de San Brais HBIM project, the starting point is a simple LOD2 model based on the TLS and SfM survey and enriched by the materiality of the textures from the point clouds. Although the geometry of construction entities such as walls, beams, and pilasters was adjusted to the irregularities of the building, it was important to consider the deformations and tilt of walls caused by the course of time, which are typical of historic buildings. To achieve a viable HBIM project for this building, these transformations must incorporate the construction singularities of its historical architecture and a definition of the materials and techniques used. In this research, a high LOA (LOA2) was achieved, considering the deviation of the element in the modelling in length sections of up to 3000 mm, between corners, or changes due to construction systems. This is the case of the deviation in the structural walls, which do not maintain the orthogonal positioning in the corners, as well as the turning of beams and cornices caused by the isolated subsidence of the structural system. For this LOA2 level, the section was maintained constant. Concerning the walls forming the envelope, an LOA3 level was achieved since they were represented by their variable thicknesses. The tilt per face (interior and exterior) was represented from the TLS data. The lateral walls of the central nave presented large dimensional changes, so it was necessary to divide them into lower sections to consider the deviation of the parametric element (1000–1500 mm).
In relation to the information embedded in the elements, the starting model reached an LOI1 information level. Here, the entities were classified only by generic typologies (e.g., walls, pillars, and floors) with no reference to their location.
On the other hand, given the need to adapt the geometry of the entities to the peculiarities of the building with heritage values, different ‘heritage’ modelling strategies were assumed as standard, integrated into an HBIM project, and presented in different Degrees or Levels of Knowledge applied to modelling (LOK). In the process of creating and enriching the BIM in the field of architectural heritage, the LOK is an adaptation of the LOD and its branches DOd Level of Detail and DOi Information Level. The LOK100 is associated with the identification of the architectural/artistic asset and the generation of knowledge in research on it. The LOK200 allows a characterisation of the graphic information necessary for the development of actions related to the protection of the property and its strategic planning. The LOK300 is further present in the characterisation of 3D elements to facilitate interoperability with disciplines involved in the studies, allowing the results of specialised research to be shared among the agents (e.g., the architect, archaeologist, historian, engineer, and the restorer); and thus, agreeing on specific diagnosis. The LOK400 is a higher level focused on conservation and intervention on the building components, so it is interrelated with the lower level LOK300 as both are combined in many conservation actions. Finally, the LOK500 level is reached in the HBIM projects containing valid information for comprehensive and efficient management of heritage protection (Castellano-Román and Pinto-Puerto 2019).
4. Results
Modelling from TLS data allows for adapting the geometry to the irregularities of the heritage asset. Fitting their faces, base, and intrados results in a model with structural walls of variable thicknesses. An advanced level of detail is then reached in a restoration project—knowledge level 2 (LOK200)—by allowing a parametric representation of the structures with the real singularities of their faces. However, the difference between interventions in architectural heritage and new construction is finding a transposition of construction techniques in the walls with a long history. To do this, the identification and sectorisation of the different systems used become necessary. An intervention project in architectural heritage needs to be enriched with semantic information derived from a high level of segmentation to approach a higher LOK of its systems (LOK300) and incorporate the construction-material configuration based on its historical evolution — time component.
This research develops a methodology to identify the integrating elements of a larger construction entity, such as the ashlars of a masonry wall, and the transformations that occurred in the Chapel of San Brais. From the beginning, CAD contouring of the stratigraphy of the ashlars was avoided, although this approach is still frequently adopted in archaeological projects. Applicability in 2D works requires significantly more effort and time, and that is the reason this research aims at getting the most out of the orthogonal views of the exterior parts, which show the texture of the material and provide precise and sufficient information to segment the wall. In addition, the creation of 3D meshes was not necessary either, thus saving considerable time in the use of other specific software related to reverse engineering. Consequently, this research work is considered unprecedented for two reasons. Firstly, based on a BIM workflow, manual procedures widely used in the cataloging of stratigraphic structures are avoided; this process is automatic in this research. Secondly, using a BIM platform, all the structures can be produced in diverse software and identified to form semantic models, an essential issue in heritage.
4.1. Semantic segmentation procedure
The segmentation procedure presented here is based on the semantic study of the construction systems of San Brais Chapel. The building was almost completely rebuilt in 1738, so the global stratigraphy reveals that the types of stone and masonry were contemporary. In turn, this indicates that there is no transposition of different techniques in the arrangement of the exterior masonry ashlars. For this research, it is necessary to discriminate those masonry walls that cover wall openings such as the one on the left side.
In the field of Cultural Heritage conservation, most of the works on semantic segmentation, such as that by Musicco et al. (2021), are based on colour information of photogrammetric data to support diagnosis and monitoring, which enables discrimination of different types of visible alterations on the masonry surface. The procedure is aided by machine learning methods to automate point cloud segmentation and highlight surface pathologies on stone and plaster walls. Other authors (Angulo-Fornos and Castellano-Román 2020), using SfM to capture high-precision surface data, classified it to produce BIM volumetric entities.
In the San Brais HBIM project (Figure 6), the aim was to adopt an efficient process to reduce the use of specific programmes. Therefore, the segmentation of the walls was carried out within the BIM platform itself (ArchiCAD software). In this case study, TLS and SfM data were used to produce a three-dimensional model structured by its lower units (Figure 5).
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03 June 2022Figure 5. Chapel of San Brais. Modelo Textured model with the point cloud (TLS). Exploration in the HBIM project environment (ArchiCAD).
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Figure 5. Chapel of San Brais. Modelo Textured model with the point cloud (TLS). Exploration in the HBIM project environment (ArchiCAD).
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03 June 2022Figure 6. Model with adapted parametric walls; a. with cover coating, b. with the system of beams and rafters in skirts.
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Figure 6. Model with adapted parametric walls; a. with cover coating, b. with the system of beams and rafters in skirts.
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03 June 2022Figure 7. Structural model with override. The elements in red are classified within the Load-Bearing Element Category.
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Figure 7. Structural model with override. The elements in red are classified within the Load-Bearing Element Category.
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03 June 2022Figure 8. Model with the segmentation of stone blocks walls, with beams marked for Restoration review. The note of the ‘Issue Organiser‘ indicates the ‘Replacement of rafters in Porch Cover‘.
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Figure 8. Model with the segmentation of stone blocks walls, with beams marked for Restoration review. The note of the ‘Issue Organiser‘ indicates the ‘Replacement of rafters in Porch Cover‘.
To carry out a semantic identification of the element in its historical context, the masonry walls were segmented into their basic units, the ashlars. Using ArchiCAD’s ‘morph‘ tool, the pieces were outlined and individual surfaces were subtracted based on the real face of the wall, containing its tilt. Next, the depth of the sectorised unit was determined perpendicular to the face to obtain a three-dimensional solid object. Working with the global point cloud of the building envelope makes it unnecessary to map the textures onto each piece. In previous studies (Nieto Julián and Moyano Campos 2014), a stratigraphic analysis and image sectorisation were carried out on orthoimages that showed the alterations because of the course of time: alterations on masonry walls, covering of holes and creation of new openings, replacement of original pieces, and imposition of usual construction techniques in later stages of its history.
In the new case study, point cloud data are valid and sufficient for the specialists to apply their knowledge and differentiate zones (Z) in the model, establish activities (A), and discriminate stratigraphic units in the analysed canvas (EU) following the methodology of the Archaeology of Architecture (Azkarate Garai-Olaun 2010). It will be a matter of managing the layers and creating appropriate combinations of them to establish orthogonal, axonometric or perspective views that show the proper monitoring of the sector depending on the level of detail determined.
The thickness of the envelope is estimated by analogy with other contemporary buildings, since the relevant tests have not yet been carried out, and thus determines a more precise structural system of the building. The new data provided in subsequent stages will update the HBIM project in a flexible, fast and precise way, simply by accessing the table or interactive diagram of the parametric elements and changing the variable in question. This is where the level of information or historical knowledge (LOK) of the element within the HBIM model comes into action; the level of detail of the object will increase both in its geometric appearance and in the semantics of the entity itself. The following figures display the building through different LOK. Firstly, with the global point cloud being the maximum exponent of accurate representation, the model was filtered based on its architectural characteristics such as walls and pieces of the envelope (Figure 5). The parametric model has finally been adapted to wall tilt and deformations due to subsidence (Figure 6). To differentiate the essential construction category of the building, the Structural Model is displayed, where the elements in red are classified within the Load-Bearing Element Category (Figure 7).
The model must also be subdivided into elements classified by other architectural and construction subcategories, derived from the monitoring process applied to the point cloud. In this way, marking and classification of elements to be restored took place: beams, rafters, roof skirting boards, among other elements. For the right-side porch, all rafters and beams have been flagged for Restoration review. The note in the ‘Issue Organiser‘ indicates ‘Replacement of rafters on the Porch Cover‘ (Figure 8).
On the other hand, other global units coexist that usually contain sub elements to be classified or different construction systems spaced out over time, as is the case of the envelope masonry walls. Therefore, a subdivision is applied in semantic units that can contain the data of a stratigraphic study. The process ended in a typological classification and quantification applied to unique parametric 3D elements, the stone ashlar. Figure (9) shows a perspective of the filtered model showing all the ashlars. Access to the analytical views of the model, such as those shown in the figures, is direct from the HBIM project browser (Graphisoft ArchiCAD), which will be automatically updated as the model is enriched with the data of new hypotheses provided for investigations, or it is definitively readjusted to the contributions demonstrated in the interventions.
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03 June 2022![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/uarc20/0/uarc20.ahead-of-print/15583058.2022.2073294/20220603/images/medium/uarc_a_2073294_f0009_oc.jpg"})
Figure 9. Filtered model perspective with all stone blocks.
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03 June 2022![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/uarc20/0/uarc20.ahead-of-print/15583058.2022.2073294/20220603/images/medium/uarc_a_2073294_f0010_oc.jpg"})
Figure 10. Vector drawing of the left side: Wall with stone blocks.
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03 June 2022Figure 11. Export of data diagrams for interoperability with external collaborators to the project.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/uarc20/0/uarc20.ahead-of-print/15583058.2022.2073294/20220603/images/medium/uarc_a_2073294_f0011_oc.jpg"})
Figure 11. Export of data diagrams for interoperability with external collaborators to the project.
4.2. Semantic classification of the HBIM model
To raise the LOK, it has first been necessary to classify the pieces by their location, depending on the orientation of the retaining wall. Interactive schemes have been developed that incorporate some pre-established items to facilitate the classification of the ashlars: Facade Orientation (Front, Right, Back, Left, Cover), Location (opening, bell tower, door brow, buttress, cornice, lintel, masonry, niche, pilaster, stone bench, sacristy, drum without cover), Structural Function (Bearing element, Non-bearing Element), Construction Material, Characteristics of the Surface or Finishing, Classification according to standards of the area, region or country (BCCA, GuBIMclass, CYPE), area, volume, and quantity. A total of 842 ashlars distributed by orientation in the building shell were obtained. The following figure shows the Scheme of elements classified according to the established fields or items ().
Table 2. Diagram of ‘stone blocks‘ classified according to the established elements. ArchiCAD 25
4.3. Stratigraphic identification of units in the HBIM model
The table of elements () shows the grouping of ashlars on each wall, depending on their location. It is necessary to carry out the identification for each unit, with a unique ID, valid to establish their position and relationship with the others in a time stratigraphic sequence typical of a paramental reading (Figure 10).
The BIM platform used allows to associate the elements with categories of usual properties related to the construction material, identification, and manufacturing; the incorporation of other specific functions is also conducted. Taking advantage of this functionality, the ArchiCAD Property Manager has been used to create and manage the property set of an HBIM project. For this case, the characteristic elements have been determined in a stratigraphic study. Own values have been defined per type and the availability of Properties has been customised for various classifications. As a result, when editing a parametric object in the HBIM project, an editing subwindow is available for the new category ‘Stratigraphic Study‘. From it, the ‘diachronic and synchronous‘ properties of the selected element (e.g., Wall, Slab, Roof, Beam, Column, Stair, Morph, Object), or portion of it, will be specified, for which identification and subdivision will be necessary. An ‘Option Set‘ Type that facilitates multiple marking was also programmed to define the variables to be applied. In this way, a stratigraphic unit will be identified by: ID element, Position, Dimensions of the piece (perimeter, area, volume), Classification, Structural Function, Phase, State of Restoration, ID of the Cata or matrix element, Material, Construction System, Interface (dimensions, layout), Chronology (dating).
These fields are established in some data schemes, which can be shared with the specialist who performs the stratigraphic study of the faces and enters new information. Access to the ‘Teamwork’ HBIM project is direct to perform the assigned tasks based on the role of the stakeholder within the collaborative team. In the case of being external to the project, the schemes will be exported in Excel files (xlsx, xls) so that specific data can be entered. Subsequently, the updated information will be fed back into the HBIM project using the Interoperability > Classifications and Properties > Import Property Values into Elements path (Figure 11).
4.4. Programmed stratigraphic identification
As an innovative work, experiments have been carried out with the use of the object-oriented programming language (OOP), which automates operations based on a code structure. Thus, these operations are effectively established and reused, making it easier for them and the data to be executed and grouped into logical units or objects. ArchiCAD’s connection with Python allows for running scripts to automate processes in the same environment as the BIM project. These programming scripts can be adapted to specific common tasks in the field of architecture and engineering, providing efficiency as routine processes are automated, which leads to great time savings and increased productivity.
The case study was developed in the HBIM project through the ArchiCAD-Python connection, using the ARCHICAD JSON interface. The ArchiCAD-Python API helps establish the connection, staying embedded and always on, using JSON messages, a language-independent data format, over HTTP. In its application to the case study, a script for classifying parametric elements by ID was restructured and adapted to apply to the identification of the masonry wall ashlars that enclose the Chapel of San Brais (2).
4.4.1. Script structure
For the creation of the Python script, it is necessary to structure the information of the BIM model objects. To do this, the following phases have been followed:
Firstly, the identification of the object is performed. In the API interface, all objects (type elements, properties, classifications) are uniquely identified by ID objects; the identifier ‘ElementId’ is used for the element, ‘PropertyId’ for properties, and ‘ClassificationItemId’ for classification elements.
Secondly, recognition of identifications (ID). IDs have their own named object diagram, and this name matches the word ‘ID‘. The respective field names will refer to this diagram as their types. Element types are enumerated in the ‘ElementType‘ diagram as string, Wall, Column, Beam, Window, Door, Object, Lamp, Slab, Roof, Mesh, Zone, CurtainWall, Shell, Skylight, Morph, Stair, Railing, Opening.
Finally, Properties are set. There are two different types of properties in ArchiCAD; a) user-defined properties, which are displayed in the Property Manager box. The user can modify the name of these Properties and call that name to locate it. Their format can be found in the ‘UserDefinedPropertyUserId‘ schema; and b) the ‘integrated‘ properties, defined by the BIM software itself. In this case, they cannot be modified by the user and can only be accessed by their internal name. Their format is in ‘BuiltInPropertyUserId‘. In the case of the stone blocks of the masonry wall, an appropriate element classification was introduced for each piece based on its nature, collected in the ArchiCAD database: Materials > Stone > Stone Masonry > Stones — Masonry > Stone Blocks, and identified in the script. Although other classifications were also used according to national and international standards (e.g., BCCA, and GuBIMclass). In this way, the ‘Stone Blocks’ ID is collected in the script for the large blocks of the wall.
In the case of the left lateral wall, an opening covered with a different type of masonry and its materiality were located. To differentiate the ‘ashlar’ elements of that covered opening and establish their interface, a different classification (‘Stone Bricks’) was used to differentiate them from the rest of the ashlars of the façade plane. Thus, these pieces were characterised in their diachronic facet—in their historical evolution—since it is assumed that the covering of the opening was after the building of the sidewall of the Chapel. This classification is the basis to start the synchronous analysis of the wall, where the specialist will carry out an internal cross-sectional interpretation of the spatial structure in each period.
When the scripts are executed, the stone blocks are numbered in a row and column path, in a ziz-zag from right to left and upwards (3.a). A specific Prefix ‘SP’ was applied to identify the elements of the covered opening and differentiate it from the general Prefix ‘S’ for the ashlars of the envelope. Three-digit numbering was automatically assigned to the element, where the first digit establishes the element’s position in height relative to the reference level. The script has the variable ‘STORY_GROUPING_LIMIT‘ to establish the limit of the Z coordinate of the ID elements concerning the same floor (storey). Figure 12 and Figure 13 show the script execution process and subsequent automatic numbering. Figure 14, Figure 15 shows a filtered axonometric view of the model incorporating the identification label of each stone block. The initial Scheme of elements identified as ‘ashlar’ will be automatically updated to collect the new unique ID of each piece (5).
Published online:
03 June 2022Figure 12. Elements of the wall identified with ID ‘stone block‘ before being classified as ‘Stone Blocks or Stone Bricks‘.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/uarc20/0/uarc20.ahead-of-print/15583058.2022.2073294/20220603/images/medium/uarc_a_2073294_f0012_oc.jpg"})
Figure 12. Elements of the wall identified with ID ‘stone block‘ before being classified as ‘Stone Blocks or Stone Bricks‘.
Published online:
03 June 2022Figure 13. a) Identification of stone blocks., b) Covered opening in the wall, with the stone blocks identified as Stone Bricks (a) and numbered with their own ID (SPnnn) when executing the Python script (b).
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/uarc20/0/uarc20.ahead-of-print/15583058.2022.2073294/20220603/images/medium/uarc_a_2073294_f0013_oc.jpg"})
Figure 13. a) Identification of stone blocks., b) Covered opening in the wall, with the stone blocks identified as Stone Bricks (a) and numbered with their own ID (SPnnn) when executing the Python script (b).
Published online:
03 June 2022Figure 14. Perspective of the filtered wall with stone blocks classified and numbered with their own ID after executing the Python scripts.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/uarc20/0/uarc20.ahead-of-print/15583058.2022.2073294/20220603/images/medium/uarc_a_2073294_f0014_oc.jpg"})
Figure 14. Perspective of the filtered wall with stone blocks classified and numbered with their own ID after executing the Python scripts.
Published online:
03 June 2022Figure 15. Final scheme of elements identified with the new unique ID for each piece.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/uarc20/0/uarc20.ahead-of-print/15583058.2022.2073294/20220603/images/medium/uarc_a_2073294_f0015_oc.jpg"})
Figure 15. Final scheme of elements identified with the new unique ID for each piece.
5. Discussion
A collaborative workflow in an HBIM project for the restoration and conservation of cultural heritage was developed to establish a methodology for the conservation cycle of the historic building. The small dimensions of the San Brais Chapel allow a complete segmentation of all the walls of its envelope. This research develops a model of parametric elements adapted to the real geometric peculiarities of the historic building and its paramental structure. The results obtained show that it is possible to implement routine ashlar segmentation tasks in architectural archaeology on BIM platforms and included them in a Heritage Project. The process of automatic identification of parametric elements gives satisfactory results when applied to stone masonry walls, with a single typology in size of the piece and uniform arrangement by rows. In the case presented, the stone masonry shows a random arrangement depending on the size of the piece, revealing a great disparity of dimensions that causes the breaking of the horizontal (row) and vertical (column) non-linearity. Therefore, in the initial phases of the procedure, the investigation showed certain problems with the correlative numbering of the units. To achieve better results, script programming was adequately restructured with a unique and orderly identification. The proposed method entails an original systematic process to facilitate a segmented identification that classifies construction techniques, units, and interfaces within the same element (wall). In turn, it satisfied efficiency by automating the process of establishing its units. In this way, the analysis of each sector by the specialist or archaeologist is facilitated to be related in the Harris Matrix. Work with small buildings facilitated the application of a complete segmentation of the walls of their envelope, essential to measure the human effort and performance of the computer equipment used in the methodology. A model of parametric elements is developed and adapted to the real geometric peculiarities of the historic building and its paramental structure. For this, flexible and precise tools provided by the BIM platform itself are used, as is the case of the ‘Morph’ tool, which allows semantic subdivision into parametric objects. These pieces were prepared to be fed with specific information in a collaborative HBIM process. Here, a working session of about a day’s work by the operator (advanced user in ArchiCAD), who represented all the ashlars of the building, taking as a reference the geometry of the joints from the point cloud of the envelope. Initially, there was no information on the interior geometry of the wall, so an average thickness was estimated for all the pieces by applying an extrusion operation on the external face. These data can be modified in later work of ashlar extraction or through testing if they are not considered in the restoration project.
To reach a greater precision of the model, it is necessary to take advantage of the real geometry in the TLS data. In previous work (Santoni et al. 2021) and (Fabrizio Banfi et al. 2022) transformation processes from point cloud to mesh and/or the use of rational B-spline surfaces (NURBS) were developed. However, using the workflow based on the GOG 9 and GOG 10 generation grades (F. Banfi, Fai, and Brumana 2017) would imply an extra and unsustainable effort due to what it entails, such as the use of different additional software to the BIM platform. The cost would be higher due to i) software licences, ii) user training to handle the data, iii) the coordination between specialists and the planning of the interoperability between applications. In the case study developed in this research, the methodology aimed to achieve the automation of work routines, avoiding inaccurate human tasks in the identification and cataloguing of elements arranged without a current construction logic, typical of stone masonry that has transformed over time.
For a cost-benefit analysis of the complete method, considering that the main purpose of the research is to approach an interoperable and efficient workflow, the authors of this paper believe that the applied modelling strategy has benefited the process by considerably reducing the duration of the stages. This workflow automates processes, allows data management associated with elements, and classifies them according to its historical-construction taxonomy. Thus, this Collaborative workflow in an HBIM project for the restoration and conservation of cultural heritage establishes an appropriate and efficient methodology for the entire conservation cycle of the historic building.
The innovative aspect of the research is the implementation of object-oriented programming (OOP) in the BIM platform itself to automate operations based on a code structure and facilitate data grouping into logical units. To do this, the application of an appropriate taxonomic process of parametric elements was required. Once the walls were segmented, a script was restructured and adapted to apply it to the identification of the ashlars. Initially, the process of automatic identification of parametric elements with the help of the Python script gave satisfactory results when applied to brick masonry walls, with a single typology in size of the piece and uniform arrangement by rows. In this case, the stone masonry presents a random arrangement depending on the size of the piece, locating a great disparity of dimensions that causes the breaking of the horizontal (row) and vertical (column) non-linearity. It is therefore in the initial phases of the procedure that the experimentation presents certain problems. Through the implementation of the programming of the scripts, it has been adequately restructured to improve the results, with a unique and ordered identification.
Finally, the extra time spent on the adaptability of the OOP to the particularity of masonry, with pieces in a random position, was counterbalanced by obtaining a valid method that supports an original systematic process to facilitate segmented identification and classification techniques, constructions, units, and interfaces within the same element (wall). In turn, it satisfied efficiency by automating the process of establishing its units. In this way, the analysis of each sector by the specialist or archaeologist is facilitated to be related in the Harris Matrix.
6. Conclusions
The HBIM project of the San Brais Chapel has been efficiently enriched to the point that an efficient LOK was achieved for analysis tasks, which has facilitated the characterisation of the envelope of the historic building. The innovative and original process applied to its façades automatically identifies the stone ashlars for analysis and stratigraphic study. To achieve the results obtained, the normal applicability sequences of the data acquisition technologies for the 3D model (TLS) have been followed. The digital reconstruction on the BIM platform (ArchiCAD) reached, at least, a LOK 300. Next, elements were modelled as complete construction units, identified by orientation and location within the architectural complex. In this way, the walls of the envelope were raised as unique units, to later apply the deformations or tilt when comparing them with the TLS data; the latter is subject to further investigation. In view of other works in the HBIM field, the level of representation achieved, based on real geometry, is similar to a LOD. At this point, the parametric elements incorporate data related to the construction system in its set, as it is a masonry wall of irregular granite ashlars; the database will incorporate, in addition to its actual metric proportions, the information parameters related to the system as a whole: type of masonry, materials and dating of the whole. Concerning the implementation, a semantic analysis was carried out by segmenting the construction units through implementing the ‘Teamwork’ HBIM project to support architectural, archaeological and historical analysis, Thus, agreeing on the characterisation of each piece within the construction systems, a LOK400 was achieved. The BIM project is subjected to monitoring the intervention and conservation actions in the historic building. The phases of the process demonstrated the feasibility of an interdisciplinary BIM methodological approach to the digitisation, automation, and data management of cultural heritage, without making use of time-consuming 2D representation techniques.
Future work will address the implementation of these automatic operations in brick/ashlar selection and classification processes in historic buildings, and establish stratification in masonry construction units where the pieces have variable geometry and material differences. As a result, this new interoperability between BIM platforms and classification algorithms using Python programming language allows configuring ad hoc scripts to adapt the geometry of the model to the peculiarities of the envelope of historic buildings. This process entails automating the identification and classification of irregular pieces of masonry walls. In this way, the actions of intervention, registration, cataloguing, and preventive conservation become more effective since the parameter data associated with the elements are easily accessible. The collaborating agents of the ‘Teamwork’ HBIM project have access to this established 3D database, which may be modified or incorporate new data derived from subsequent studies.
| Level | Upper Range | Lower Range |
| LOA10 | User defined | 5 cm * |
| LOA20 | 5 cm * | 15 mm * |
| LOA30 | 15 mm * | 5 mm * |
| LOA40 | 5 mm * | 1 mm * |
| LOA50 | 1 mm * | 0 * |
| TOTAL CLASSIFICATION OF STONE ASHLAR — SILLARES | ||||||||||
| Layer | Facade | Location | Structural Function | Building Material | Surface | ARCHICAD Classification | GuBIMclass ES — 1.2 | BCCA_2017–1.0 | Volume (by Story) | Quantity |
| 01 ARQ_FCH_Sillares (Ashlar) | ||||||||||
| Cover | Drum on Roof | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 0,99 | 20 | |
| Front Facade | Mansory | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 7,69 | 108 | |
| Left Facade | Buttress | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 1,57 | 29 | |
| Left Facade | Closing Door | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Bricks | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 0,49 | 12 | |
| Left Facade | Lintel | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Blocks | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 0,22 | 2 | |
| Left Facade | Mansory | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Blocks | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 4,86 | 101 | |
| Left Facade | Mansory | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 8,41 | 108 | |
| Left Facade | Sacristy | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 3,88 | 37 | |
| Rear Facade | Mansory | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 8,82 | 127 | |
| Right Facade | Buttress | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 1,51 | 29 | |
| Right Facade | Lintel; Mansory | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 0,19 | 3 | |
| Right Facade | Lintel; Sacristy | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 0,09 | 1 | |
| Right Facade | Mansory | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 11,69 | 231 | |
| Right Facade | Pilaster | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 0,61 | 20 | |
| Right Facade | Poyete | Non-Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 0,13 | 4 | |
| Right Facade | Sacristy | Load-Bearing Element | Stone — Structural | Stone — Gray Granite | Stone Masonry | 20.20.10.30 Walls — Structural | 06CSS Sillares -Stone Ashlar | 0,52 | 10 | |
| 842 | ||||||||||
Disclosure statement
No potential conflict of interest was reported by the author(s).
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