Industry Foundation Classes Research Articles

Leveraging railway topology to automatically generate track geometric information models from airborne LiDAR data

Geometric information modelling from point cloud data (PCD) is a fundamental step of the digital twinning process for rail infrastructure. Currently, this onerous procedure outweighs the anticipated benefits of the resulting model and expends 74% of the modellers' effort on converting PCD to a model. The cost of the resulting geometric information models (GIM) can be reduced by automating the modelling process. State-of-the-art methods cannot offer large-scale GIM generation required over kilometres without forfeiting precision and manual cost. This paper addresses the challenge of achieving such automation by leveraging the highly standardised topology of railways to automatically generate GIMs of rail track structures.The method first automatically segments rails and track beds, delivering labelled point clusters of track structure elements. Next, it converges the segmented rails with pre-defined parametric assemblies of different rail profiles and uses a mesh-based approach to reconstruct the geometry of the track bed, delivering industry foundation classes (IFC) files of railway track structure elements. Experiments on 18.5 km railway PCDs yielded an average segmentation of 98.1% and 94.9% F1 scores and overall modelling accuracy of 3.5 cm and 2.8 cm root mean square error (RMSE)s for rails and track beds. The proposed method can realise an estimated time savings of 88.9% without needing any manual inputs.

BIM/IFC-based 3D spatial model for condominium ownership: A case study of China

ABSTRACT As the number of high-density buildings has increased, the management of property with complex condominium ownership has become an ongoing challenge in property registration and management. The three-dimensional (3D) modeling of condominium ownership has emerged as an effective means of meeting this challenge and has attracted great attention from fields such as geographical information science, urban planning and management, and property administration. Much progress has been made in building 3D models of condominium ownership; however, existing studies are all on a case-by-case basis and have left some critical issues unsolved, such as vague ownership boundaries, spatial rights without physical counterparts, and the unfixed spatial extent. The purpose of this study is to construct a 3D building ownership model with multiple levels of detail in the context of Chinese law to overcome the defects of 3D models above. This 3D model is presented in a case study of China by subdividing ownership boundaries based on clarifying the internal structure of condominium ownership, embedding the apportionment mechanism, and integrating the semantics, attributes, and geometry associated with the physical and legal entity of the condominium. The proposed 3D model is implemented by extending Building Information Modeling (BIM) based on the Industry Foundation Classes (IFC) and inheriting legal information from Land Administration Domain Model (LADM). In this study, examples of condominium ownership from three real legal dispute cases in China are analyzed and tested. The study clearly demonstrates that the proposed model can provide a better cognitive understanding of the legal space of property by rendering unambiguous ownership boundaries and presenting the spatial internal structure of ownership, which offers solid technical support for dealing with property registration and many legal dispute cases about condominium ownership.

A tool based on the industry foundation classes standard for dynamic data collection and automatic generation of building automation control networks

The use of Building Automation and Control Networks (BACN) is becoming increasingly widespread, largely due to the benefits to end-users and energy management companies of controlling the systems installed in buildings. At the same time, the digitalisation of buildings is increasing every day with the adoption of technologies such as Building Information Modelling (BIM), allowing a high level of digital control in all phases of the building life cycle. However, although the use of BIM is spreading to obtain a digital model of the building, it is not very common to include the existing control systems in BIM models. The integration of BACN-to-BIM seems to be the most appropriate process to have all the information of a building, as it would allow to digitalise and connect both the geometric and the logical part, but it is a challenge to be faced in terms of interoperability. This paper shows the BACN2BIM tool, a tool to make it easier for technical users the creation of monitoring networks linked to BIM models of a building, based on Industry Foundation Classes (IFC) standard. The BACN2BIM tool will allow owners and technical users to easily download dynamic monitoring data, real-time data of the measurements obtained from devices installed in their buildings (temperature, humidity, energy consumption, CO2 concentration, etc.) The tool has been tested in a case study and in a real demo case located in Spain, showing a time reduction in updating a BIM model with the devices of an existing monitoring system and in the download of existing monitoring data.

OpenBIM-based assessment for social cost of carbon through building life cycle

Buildings produce many carbon emissions in their life cycle, which leads to global warming, human disease, ecosystem destruction, and food shortages. These harms are translated and revealed into the social cost of carbon (SCC), but assessing the building SCC considering protection objects is still difficult due to the lack of adequate and rapid tools. Therefore, this paper proposes a method based on OpenBIM to calculate the SCC through the building life cycle. This method reflects the cause-effect chains of carbon emissions on human health, ecosystem quality, and social assets under LIME, EPS, and ReCiPe approaches. An original tool, NMBIM, is developed based on this proposed method, which calculates the SCC of a case building by directly importing industry foundation classes (IFC) files. The case results show that the maximum life cycle SCC reaches 5872.4 RMB/m2, which exceeds the construction cost. Although SCC results obtained by different LCIA models vary widely, the ones of human health are the most concerned protection objects. This paper provides an effective method for standardly storing and optimizing SCC at the project design stage, which contributes to construction industry planning, construction company decision-making, and public regulation.

Multi-level assessment for embodied carbon of buildings using multi-source industry foundation classes

Multi-level assessment for embodied carbon of buildings using multi-source industry foundation classes

Solutions on Establishing and Utilizing BIM for General Contractors in Key Scenarios of Digital Construction

Nowadays, digital construction has become popular when bringing convenience and efficiency to the traditional building construction industry. The primary tool of digital construction is the building information model (BIM). However, from the perspective of general contractors, unresolved puzzles still hinder obtaining the benefits of digital construction. When establishing a unified BIM from submodels provided by subcontractors, there will possibly be incomplete or inconsistent data during model merging. But extracting submodels from unified BIM often includes redundant data, thus making models less usable for subcontractors. It is also difficult for general contractors to effectively and accurately utilize resource information and submodel changes. This paper proposed solutions that depend on the widely adopted industry foundation classes standard to ensure the universality of our methods. First, a model merging algorithm is proposed to support the continuous merge of submodels created by different subcontractors. Second, an instance-level model extraction method based on strongly related entities is proposed, which extracts model instances to the minimum submodel and meets the subcontractor requirements at the same time. Third, the new model storage and indexing method are designed to reduce the complexity of model data and support rapid data retrieval, and a new BIM change detection method based on object metadata is provided. The proposed methods were applied by the general contractor of a large airport project during the construction stage. The application results proved that the proposed methods could ensure the quality of established deepening design models and extracted submodels and significantly reduce human labor by improving efficiency when utilizing BIM, which in turn supported key scenarios throughout the digital construction workflow.

Integrating as-built BIM model from point cloud data in construction projects

PurposeAs laser scanning technology becomes readily available and affordable, there is an increasing demand of using point cloud data collected from a laser scanner to create as-built building information modeling (BIM) models for quality assessment, schedule control and energy performance within construction projects. To enhance the as-built modeling efficiency, this study explores an integrated system, called Auto-Scan-To-BIM (ASTB), with an aim to automatically generate a complete Industry Foundation Classes (IFC) model consisted of the 3D building elements for the given building based on its point cloud without requiring additional modeling tools.Design/methodology/approachASTB has been developed with three function modules. Taking the scanned point data as input, Module 1 is built on the basis of the widely used region segmentation methodology and expanded with enhanced plane boundary line detection methods and corner recalibration algorithms. Then, Module 2 is developed with a domain knowledge-based heuristic method to analyze the features of the recognized planes, to associate them with corresponding building elements and to create BIM models. Based on the spatial relationships between these building elements, Module 3 generates a complete IFC model for the entire project compatible with any BIM software.FindingsA case study validated the ASTB with an application with five common types of building elements (e.g. wall, floor, ceiling, window and door).Originality/valueFirst, an integrated system, ASTB, is developed to generate a BIM model from scanned point cloud data without using additional modeling tools. Second, an enhanced plane boundary line detection method and a corner recalibration algorithm are developed in ASTB with high accuracy in obtaining the true surface planes. At last, the research contributes to develop a module, which can automatically convert the identified building elements into an IFC format based on the geometry and spatial relationships of each plan.

Trade-offs between accuracy and efficiency in BIM-LCA integration

PurposeIn the last decades, various building information modeling–life cycle assessment (BIM-LCA) integration approaches have been developed to assess the environmental impact of the built asset. However, there is a lack of consensus on the optimal BIM-LCA integration approach that provides the most accurate and efficient assessment outcomes. To compare and determine their accuracy and efficiency, this study aimed to investigate four typical BIM-LCA integration solutions, namely, conventional, parametric modeling, plug-in and industry foundation classes (IFC)-based integration.Design/methodology/approachThe four integration approaches were developed and applied using the same building project. A quantitative technique for evaluating the accuracy and efficiency of BIM-LCA integration solutions was used. Four indicators for assessing the performance of BIM-LCA integration were (1) validity of LCA results, (2) accuracy of bill-of-quantity (BOQ) extraction, (3) time for developing life cycle inventories (i.e. developing time) and (4) time for calculating LCA results (i.e. calculation time).FindingsThe results show that the plug-in-based approach outperforms others in developing and calculation time, while the conventional one could derive the most accuracy in BOQ extraction and result validity. The parametric modeling approach outperforms the IFC-based method regarding BOQ extraction, developing time and calculation time. Despite this, the IFC-based approach produces LCA outcomes with approximately 1% error, proving its validity.Originality/valueThis paper forms one of the first studies that employ a quantitative and objective method to determine the performance of four typical BIM-LCA integration solutions and reveal the trade-offs between the accuracy and efficiency of the integration approaches. The findings provide practical references for LCA practitioners to select appropriate BIM-LCA integration approaches for evaluating the environmental impact of the built asset during the design phase.

Smart camera placement for building surveillance using OpenBIM and an efficient Bi-level optimization approach

Cameras have been widely used in buildings for safety and efficiency surveillance. Especially with the integration of artificial intelligence and building information modeling (BIM), many intelligent applications have emerged. However, optimizing the camera plan in buildings with various geometric and semantic properties remains challenging. This study proposes a smart camera placement framework that can be generally applied in different building scenarios to solve this problem. Firstly, a camera-integrated BIM is constructed based on a systematic literature review (SLR) and Industry Foundation Classes (IFC) schema, followed by a sample-based voxelization method to convert BIM models to semantic voxels. Secondly, a realistic camera coverage analysis method is developed to consider the object's properties, based on which a bi-level formulation is proposed. Finally, an efficient bi-level genetic algorithm (EBGA) is proposed to ensure both optimization accuracy and efficiency. The performance of the proposed placement framework is validated in a study of a multi-purpose laboratory and office floor. The validation demonstrated that EBGA obtained full coverage of essential objects and 21.4% more coverage values over the experience-based method. Compared with two benchmark GAs, EBGA saved 65.2% and 49.7% of computation time correspondingly in the experiment.

ENABLING SCAN-TO-BIM WORKFLOW FOR HERITAGE CONSERVATION AND MANAGEMENT PROCESS

Abstract. The paper stresses the potential of digital technology in the field of Cultural Heritage (CH), focusing on Architectural Heritage (AH) conservation and management process. It presents a workflow based on non-parametric automatic 3D modeling and Industry Foundation Classes (IFC) authoring to combine geometry and semantic information. The goal of such a methodology is to overcome time-consuming manual tasks that still limit the Historical Building Information Modelling (HBIM), which nevertheless proves to be one of the most effective digital tools for the conservation and management of AH in the medium to long term. The proposed workflow consists of five steps: the 3D survey campaign and raw data processing, the semantic annotation of images according to different information layers, the annotation transfer from images to the point cloud representing the studied architecture, the obtained Point Cloud Information Model (PCIM) automatic segmentation and 3D mesh wrapping, and finally the IFC generation for the HBIM representation. This unconventional digital chain was tested to support the knowledge representation of Villa Leonardi, an historical house in the Marche Region (Italy). The final output is a 3D model of the building, automatically processed from digital survey data, and semantically enriched thanks to the material consistency and decay analysis carried out and annotated on spherical panoramas. The effectiveness of this approach was proven in the conservation project for the façades of the house: enriched data on materials and decay supported an action plan of restoration works, which was then recorded in the HBIM model, thus permitting time and cost control.

BIM Search Engine: Effects of Object Relationships and Information Standards

As Building Information Modeling (BIM) models are getting bigger, with more information linked to geometrical 3D models, a dedicated BIM search engine is important. A BIM search engine was developed to examine the value of exploiting a 3D object’s topological relationships to other 3D objects when assessing that object’s relevance to a query. The impacts of two information standards, the Industry Foundation Classes (IFC) and Uniclass-2015, on information retrieval (IR) performance were also measured. The 3DIR Autodesk Revit toolset was used on a structural model of a 16-story building from an industry partner. The retrieval performance measures of Precision and Recall did not clearly highlight the benefit, although the increased relevance values of those objects deemed by experts to be relevant demonstrates the promise of such contextual measures. The effect of shifting from the native Revit file format to various standards was tested: IR performance was poor with the Uniclass-2015 dataset and was comparable to the Revit native model with the IFC model. Although not shown conclusively to improve retrieval performance, the contextual relevance measures presented in this paper are promising and constitute a significant original contribution. Future research is needed to fine-tune these measures and fully realize their potential.

An ontology-aided, natural language-based approach for multi-constraint BIM model querying

Construction project stakeholders often have to retrieve the required information in Building Information Models (BIMs) to support their design, engineering, and management activities. Natural language interface (NLI) systems are emerging as a time- and cost-effective way to query complex BIM models. However, the existing attempts cannot logically combine different constraints to perform fine-grained queries, dampening the usability of BIM-oriented NLIs. This paper presents a novel ontology-aided semantic parser to automatically map natural language queries (NLQs) that contain different attribute and relational constraints into computer-readable codes for BIM model retrieval in the context of building project development. A modular ontology was first developed to represent natural language expressions of Industry Foundation Classes (IFC) concepts, relationships, and reasoning rules; it was then populated with entities from target BIM models to assimilate project-specific information. After that, the ontology-aided semantic parser progressively extracts concepts, relationships, and value restrictions from NLQs to identify multi-level constraint conditions, resulting in standard SPARQL queries to successfully retrieve IFC-based BIM models. The approach was evaluated based on 225 NLQs collected from BIM users, with a 91% accuracy rate. Finally, a case study about the design-checking of a real-world residential building demonstrates the practicability of the proposed method in the construction industry.

Building Information Modelling for Application in Geotechnical Engineering

BIM (Building Information Modelling) is used to create and manage data during design, construction, and operation. It helps to effectively manage resources and optimize processes in the construction industry. Geotechnical engineering is one of the complex disciplines that may require BIM integration. Various data types must be provided in a timely manner and require real-time feedback, fast processing, and construction guidance. The first problem presented in the paper is the use of the traditional 2D-based method used by engineers for a particular task. It seems to be impractical when some adjustments are included. Another issue is the lack of communication between the workers. It poses the problem of information exchange and misunderstanding during the interpretation of technical data. This paper aims to find different integration techniques and steps for integrating geotechnical data into the BIM process. Methods used to examine the topic are qualitative research, literature review, and case studies. These methods were useful for studying the problems and introducing the soil information into the BIM application. Firstly, a case study with I-BIM was considered, and the BIM–FEM–BIM interaction was applied to introduce geotechnical information with Plaxis 3D. The results have shown that further development of BIM in infrastructure is needed. Another case study explored the present state of the geotechnical design in BIM and potential solutions. The new frameworks were recreated: many boreholes were imported to the BIM, and a 3D geometric model of the entire hill was created for the hill fortification structure with soil clogging. The last two studies in Malaysia modeled a 3D subsurface and used two geotechnical formats, AGS and CVS. The first includes more information than the second; however, the second can be used for a more generalized model. Overall, BIM–FEM interaction can be used as a geometric model for data transfer. However, the open data format of the Industry Foundation Class (IFC) or geotechnical data format of the AGS and CVS were suggested to be used for greater flexibility. It was also found that excessive information makes the model loaded and complex. Therefore, it was recommended that big data be summarized properly with minimal loss of necessary data. Further research is needed to understand data transmission schemes of geotechnical information better. Moreover, it is recommended to put all the strategies directly into practice to create a geotechnical design.

Digital Twinning for 20th Century Concrete Heritage: HBIM Cognitive Model for Torino Esposizioni Halls

In the wide scenario of heritage documentation and conservation, the multi-scale nature of digital models is able to twin the real object, as well as to store information and record investigation results, in order to detect and analyse deformation and materials deterioration, especially from a structural point of view. The contribution proposes an integrated approach for the generation of an n-D enriched model, also called a digital twin, able to support the interdisciplinary investigation process conducted on the site and following the processing of the collected data. Particularly for 20th Century concrete heritage, an integrated approach is required in order to adapt the more consolidated approaches to a new conception of the spaces, where structure and architecture are often coincident. The research plans to present the documentation process for the halls of Torino Esposizioni (Turin, Italy), built in the mid-twentieth century and designed by Pier Luigi Nervi. The HBIM paradigm is explored and expanded in order to fulfil the multi-source data requirements and adapt the consolidated reverse modelling processes based on scan-to-BIM solutions. The most relevant contributions of the research reside in the study of the chances of using and adapting the characteristics of the IFC (Industry Foundation Classes) standard to the archiving needs of the diagnostic investigations results so that the digital twin model can meet the requirements of replicability in the context of the architectural heritage and interoperability with respect to the subsequent intervention phases envisaged by the conservation plan. Another crucial innovation is a proposal of a scan-to-BIM process improved by an automated approach performed by VPL (Visual Programming Languages) contribution. Finally, an online visualisation tool enables the HBIM cognitive system to be accessible and shareable by stakeholders involved in the general conservation process.

Recovering building information model from 2D drawings for mechanical, electrical and plumbing systems of ageing buildings

Ageing buildings have become a significant concern for many cities, exacerbated by inadequate management and maintenance of Mechanical, Electrical, and Plumbing (MEP) systems. Building Information Modelling (BIM) enables efficient MEP Operation and Maintenance (O&M) through the digital representation of system information; however, many ageing buildings were constructed without BIM, and manual reconstruction is costly and inefficient due to the sheer number of such structures. Although some studies have proposed methods for automatically recovering BIM from 2D drawings, few are suitable for MEP systems due to the multiscale and irregular shapes of MEP components. To fill this gap, an automatic approach is proposed for recovering MEP model from 2D drawings with three modules: 1) semantic extraction by combining image cropping with Cascade Mask R-CNN to detect and segment multiscale, irregular MEP components; 2) geometric extraction by semantic-assisted image processing to extract contours and skeletons of irregular parts; and 3) Industry Foundation Class (IFC)-based BIM reconstruction via the open-source pythonOCC and IfcOpenShell. The performance was tested on two MEP systems with 335 and 282 multiscale and irregular elements, and the results show that the method recovered BIMs for the two MEP systems in 2.85 s and 0.79 s, with semantic extraction accuracy exceeding 0.9 and geometric error below 5%. This paper contributes to the existing body of knowledge by providing a semantic and geometric-based approach for recovering multiscale and irregular components from 2D drawings. Future studies could further improve the approach by integrating elevation drawings, reconstructing abstract symbols, and aligning text-geometry.

3D crowdsourced parametric cadastral mapping: Pathways integrating BIM/IFC, crowdsourced data and LADM

This paper is part of a doctoral dissertation (PhD) research aligned with global trends aiming to develop practical technical tools for the collection, management and visualization of three-dimensional (3D) property rights in urban areas. Recently, the Building Information Models (BIMs) claim a prominent position in the field of 3D cadastres and the digital twins of the cities. In addition to all other building information, the BIM can also provide data about the exact boundaries of all kind of legal spaces (e.g., property ownership rights as well as land use restrictions), under the support of Industry Foundation Classes (IFCs). However, the utilization of BIMs for 3D cadastral surveys is still accompanied with two main drawbacks. The first refers to BIMs limited availability, as till now they mainly encounter in new large constructions. The second refers to the complexity in defining the exact geometric location of the legal boundaries regarding the exterior/interior partitions of the construction and of the common spaces. The latter parameter is formed on the basis of the current legal legislation in each country. Through in-depth investigation of the current legal framework of each country it may be possible to visualize the various 3D legal spaces within complex constructions and thus to facilitate the integration of existing BIMs in the development of 3D cadasters that will enable a better understanding and communication of all involved parties in the operation of cross-boundary real estate markets. In parallel, crowdsourcing has already been proved to be a powerful data collection method for the initial participatory implementation of fast, reliable and affordable 3D cadastral surveys, utilizing all capabilities provided by the latest low-cost devices, mobile services (m-services), open-source software (OSS) and the international standard of Land Administration Domain Model (LADM ISO 19152). If no precise 3D building models are already available, the currently available 2D architectural plans combined with the additional geometric and descriptive cadastral information may be utilized for a participatory crowdsourced cadastral survey of the 3D property units. In this paper a ‘two-route’ crowdsourced approach is described. This approach suggests both the use of existing BIMs – those available – to proceed with 3D crowdsourced cadastral surveys of those constructions, as well as the use of 2D georeferenced basemaps (e.g., orthophotos for the compilation of 2D crowdsourced cadastral surveys, and all existing architectural floor plans of the constructions) to proceed with 3D crowdsourced cadastral surveys of all other constructions. A database schema describing the linkage between LADM standard, BIM/IFC and 3D crowdsourced geometric and descriptive cadastral information is developed and presented. A hybrid mobile application enabling the manipulation of BIM/IFC descriptive data – if existing; the collection of 3D crowdsourced geometric and descriptive information by property owners/users/non-professionals; the registration of the cadastral data and their relationships within a LADM-based cadastral geodatabase; the automated generation of 3D property unit models as block models (LoD1), using Model-driven approach; and the objects visualization in real-time, are developed. An investigation regarding the legally correct representation of the location of property unit boundaries, focusing mainly in the Greek territory is conducted. A practical experiment for each one of the cases of the ‘two-route’ crowdsourced approach is implemented, for two multi-storey buildings in the city of Athens, Greece. The potentials of the proposed crowdsourced solution as well as the achieved geometric accuracy – in the absence of BIM – are discussed and assessed. The results show that integrating BIM data with cadastral information derived from crowdsourcing, may significantly contribute to the implementation of 3D Cadastres, providing also a better visual understanding of 3D property rights. Nonetheless, even in the absence of a BIM the achieved accuracy seems to satisfy the cadastral specifications of the Greek cadaster enhancing the potential of exploiting crowdsourced data in the initial phases of the cadastral formal procedures.

A deep natural language processing‐based method for ontology learning of project‐specific properties from building information models

AbstractElement property is a crucial aspect of building information modeling (BIM) for almost all BIM‐based engineering tasks. Since there are limited properties predefined in Industry Foundation Classes (IFC) specifications, a vast number of property concepts were customized and stored in BIM models, which lack labor‐intensive data modeling and alignment for effective information management and reuse. To tackle the challenge, this study presents a natural language understanding (NLU)‐based method for the automatic ontological knowledge modeling of project‐specific property concepts from BIM models. A soft pattern matching model was used to acquire contextual definitions of concepts from a domain corpus before applying deep NLU models to transform the concept names and definitions into dense vector representations. These outputs were then fed into two stacking ensemble learning models to carry out two tasks: (a) classifying whether an unseen concept overlaps with the IFC ontology, and (b) aligning the repetitive concepts with the most relevant concepts in the ontology. Finally, all fresh properties were appended to an IFC ontology, either as new objects or new synonyms. The performance was evaluated based on 327 property concepts from real‐life BIM models. The results show that the proposed approach incorporating reading comprehension of definitions outperforms the existing name similarity‐based methods. Finally, a case study on a renovation project demonstrates the effectiveness of this study in automatic ontology modeling of property concepts.

Integration of Building Information Modeling Interoperability into Nonlinear Finite Element Analysis of Bridge Substructures

Acceptance of building information modeling (BIM) throughout the bridge industry is widely recognized as inevitable. However, while adoption of BIM technologies has proliferated throughout the building industry, advances pertaining to BIM for bridges and other structures remain underway. The present study aims to increase the potential for integrating BIM processes into software packages that possess capabilities for nonlinear finite element analysis (FEA) of bridge substructures. Moreover, the present study is intended to galvanize stakeholders within the area of soil–structure interaction (SSI) modeling and analysis to more effectively participate in interoperability workflows as part of bridge design. A proof-of-concept exporter tool was formulated in a modular manner to robustly export finite element model data stored in a selected SSI analysis package into the Industry Foundation Classes (IFC) standard, with the IFC standard chosen as the target schema owing to its widespread usage in the construction industry. The ability of the exporter tool to—with fidelity—convert a model from the selected analysis software to the IFC standard is showcased through an illustrative case study. In carrying out the case study, collections of geotechnical modeling parameters were identified that, while being common to numerous nonlinear SSI analysis packages, are not present in the existing IFC schema. Inclusion of these parameters in the IFC schema is proposed, serving to: 1) lower the barrier for entry of SSI modeling and analysis stakeholders to take part in interoperability processes and 2) encourage adoption of novel BIM processes in the bridge industry.

Improving IFC-Based Interoperability between BIM and BEM Using Invariant Signatures of HVAC Objects

The heating, ventilation, and air conditioning (HVAC) system is one of the most complex parts in a building design, which requires a high level of specialty to interpret and analyze during building energy modeling. From an energy simulation perspective, significant efforts are required in extracting HVAC information from the two-dimensional (2D) mechanical drawings or three-dimensional (3D) design models and manually inputting the data into the energy models. This tedious, error-prone, and time-consuming process has hindered high productivity in energy analysis. Automatically transforming HVAC data already contained in building information modeling (BIM) into building energy modeling (BEM) can significantly accelerate this process and improve efficiency during design iterations. To automate this process, the authors proposed a new algorithmic method by leveraging the state-of-the-art data-driven reverse engineering algorithm development (D-READ) method and the invariant signatures of HVAC objects. Following the proposed method, an algorithm was developed using a 2-story residential building model and a 2-story office building model. It successfully transformed HVAC data from BIM to EnergyPlus input file following the Industry Foundation Classes (IFC) standard. It was tested on two testing models with different HVAC systems [i.e., a 4-story office building model with a boiler radiator system and a 2-story clinic building with a variable air volume (VAV) system], which achieved 97.5% and 98.7% transformation accuracy compared with evaluation models manually created in commercially available software, respectively. Results also showed a satisfactory precision (<9.6% error) in total energy consumption by the algorithmically generated model when compared with the evaluation model. This work provides a new IFC-based approach to address the research gap of HVAC interoperability between BIM and BEM and supports better accessibility compared with a proprietary workflow. It builds a solid step for realizing seamless and fully-automated HVAC information transformation between BIM and BEM, for complete BIM-BEM interoperability.

Conducting smart energy audits of buildings with the use of building information modelling

Energy audits are an integral part of the overall energy savings strategy in the building sector. The significance of energy audits was confirmed both by their adoption by the European Energy Savings Directive (2012/27) as well as by the development and issuance of a large number of European standards (standard series EN16247, EN 15378, EN 16798, EN 16946, EN 16947 etc.), related to the energy audit of buildings and building systems. However, current practices for conducting energy audits in buildings do not adopt the latest developments in the field of Industry 4.0 practices, resulting in the general belief within the engineering community of building physics that energy auditing can be further updated and improved. This work aims to introduce a novel approach for the improvement of existing building energy audit practices with the adaptation of building information models and associated data. The study presents the potential of evaluation process utilizing building information models for constituent energy audit procedure – assessment of building energy consumption related to building envelope. The question of whether there is room for further adoption of digitization practices in carrying out energy audits, as well as the possibilities of developing new tools in this area are addressed. Following this, the main outcome of this study is the overview and analysis of Industry Foundation Classes schema building information model data structure and its interrelationships with the aim of using the extracted information to digitize energy audit procedures. Research approach covers digitization of building energy consumption assessment influenced by building envelope characteristics, as well as evaluation of economic and energy aspects for possible building shell optimization scenarios. The study also presents the results of a case study evaluation carried out with the developed tool using building envelope modification feature for various environment and economic parameters. Additionally, the architecture, and the rationale for the developed tool backed, used to extract necessary information for implementing building energy audits are presented. We finalize with the discussion on upcoming developments in the field and on future work of this study.